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Merge master to fix merge error.
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CHANGELOG.md
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CHANGELOG.md
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## ClickHouse release 21.2
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### ClickHouse release v21.2.2.8-stable, 2021-02-07
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#### Backward Incompatible Change
|
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* Bitwise functions (`bitAnd`, `bitOr`, etc) are forbidden for floating point arguments. Now you have to do explicit cast to integer. [#19853](https://github.com/ClickHouse/ClickHouse/pull/19853) ([Azat Khuzhin](https://github.com/azat)).
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* Forbid `lcm`/`gcd` for floats. [#19532](https://github.com/ClickHouse/ClickHouse/pull/19532) ([Azat Khuzhin](https://github.com/azat)).
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* Fix memory tracking for `OPTIMIZE TABLE`/merges; account query memory limits and sampling for `OPTIMIZE TABLE`/merges. [#18772](https://github.com/ClickHouse/ClickHouse/pull/18772) ([Azat Khuzhin](https://github.com/azat)).
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* Disallow floating point column as partition key, see [#18421](https://github.com/ClickHouse/ClickHouse/issues/18421#event-4147046255). [#18464](https://github.com/ClickHouse/ClickHouse/pull/18464) ([hexiaoting](https://github.com/hexiaoting)).
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* Excessive parenthesis in type definitions no longer supported, example: `Array((UInt8))`.
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#### New Feature
|
||||
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* Added `PostgreSQL` table engine (both select/insert, with support for multidimensional arrays), also as table function. Added `PostgreSQL` dictionary source. Added `PostgreSQL` database engine. [#18554](https://github.com/ClickHouse/ClickHouse/pull/18554) ([Kseniia Sumarokova](https://github.com/kssenii)).
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* Data type `Nested` now supports arbitrary levels of nesting. Introduced subcolumns of complex types, such as `size0` in `Array`, `null` in `Nullable`, names of `Tuple` elements, which can be read without reading of whole column. [#17310](https://github.com/ClickHouse/ClickHouse/pull/17310) ([Anton Popov](https://github.com/CurtizJ)).
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* Added `Nullable` support for `FlatDictionary`, `HashedDictionary`, `ComplexKeyHashedDictionary`, `DirectDictionary`, `ComplexKeyDirectDictionary`, `RangeHashedDictionary`. [#18236](https://github.com/ClickHouse/ClickHouse/pull/18236) ([Maksim Kita](https://github.com/kitaisreal)).
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* Adds a new table called `system.distributed_ddl_queue` that displays the queries in the DDL worker queue. [#17656](https://github.com/ClickHouse/ClickHouse/pull/17656) ([Bharat Nallan](https://github.com/bharatnc)).
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* Added support of mapping LDAP group names, and attribute values in general, to local roles for users from ldap user directories. [#17211](https://github.com/ClickHouse/ClickHouse/pull/17211) ([Denis Glazachev](https://github.com/traceon)).
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* Support insert into table function `cluster`, and for both table functions `remote` and `cluster`, support distributing data across nodes by specify sharding key. Close [#16752](https://github.com/ClickHouse/ClickHouse/issues/16752). [#18264](https://github.com/ClickHouse/ClickHouse/pull/18264) ([flynn](https://github.com/ucasFL)).
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* Add function `decodeXMLComponent` to decode characters for XML. Example: `SELECT decodeXMLComponent('Hello,"world"!')` [#17659](https://github.com/ClickHouse/ClickHouse/issues/17659). [#18542](https://github.com/ClickHouse/ClickHouse/pull/18542) ([nauta](https://github.com/nautaa)).
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* Added functions `parseDateTimeBestEffortUSOrZero`, `parseDateTimeBestEffortUSOrNull`. [#19712](https://github.com/ClickHouse/ClickHouse/pull/19712) ([Maksim Kita](https://github.com/kitaisreal)).
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* Add `sign` math function. [#19527](https://github.com/ClickHouse/ClickHouse/pull/19527) ([flynn](https://github.com/ucasFL)).
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* Add information about used features (functions, table engines, etc) into system.query_log. [#18495](https://github.com/ClickHouse/ClickHouse/issues/18495). [#19371](https://github.com/ClickHouse/ClickHouse/pull/19371) ([Kseniia Sumarokova](https://github.com/kssenii)).
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* Function `formatDateTime` support the `%Q` modification to format date to quarter. [#19224](https://github.com/ClickHouse/ClickHouse/pull/19224) ([Jianmei Zhang](https://github.com/zhangjmruc)).
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* Support MetaKey+Enter hotkey binding in play UI. [#19012](https://github.com/ClickHouse/ClickHouse/pull/19012) ([sundyli](https://github.com/sundy-li)).
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* Add three functions for map data type: 1. `mapContains(map, key)` to check weather map.keys include the second parameter key. 2. `mapKeys(map)` return all the keys in Array format 3. `mapValues(map)` return all the values in Array format. [#18788](https://github.com/ClickHouse/ClickHouse/pull/18788) ([hexiaoting](https://github.com/hexiaoting)).
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* Add `log_comment` setting related to [#18494](https://github.com/ClickHouse/ClickHouse/issues/18494). [#18549](https://github.com/ClickHouse/ClickHouse/pull/18549) ([Zijie Lu](https://github.com/TszKitLo40)).
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* Add support of tuple argument to `argMin` and `argMax` functions. [#17359](https://github.com/ClickHouse/ClickHouse/pull/17359) ([Ildus Kurbangaliev](https://github.com/ildus)).
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* Support `EXISTS VIEW` syntax. [#18552](https://github.com/ClickHouse/ClickHouse/pull/18552) ([Du Chuan](https://github.com/spongedu)).
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* Add `SELECT ALL` syntax. closes [#18706](https://github.com/ClickHouse/ClickHouse/issues/18706). [#18723](https://github.com/ClickHouse/ClickHouse/pull/18723) ([flynn](https://github.com/ucasFL)).
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#### Performance Improvement
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||||
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* Faster parts removal by lowering the number of `stat` syscalls. This returns the optimization that existed while ago. More safe interface of `IDisk`. This closes [#19065](https://github.com/ClickHouse/ClickHouse/issues/19065). [#19086](https://github.com/ClickHouse/ClickHouse/pull/19086) ([alexey-milovidov](https://github.com/alexey-milovidov)).
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* Aliases declared in `WITH` statement are properly used in index analysis. Queries like `WITH column AS alias SELECT ... WHERE alias = ...` may use index now. [#18896](https://github.com/ClickHouse/ClickHouse/pull/18896) ([Amos Bird](https://github.com/amosbird)).
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* Add `optimize_alias_column_prediction` (on by default), that will: - Respect aliased columns in WHERE during partition pruning and skipping data using secondary indexes; - Respect aliased columns in WHERE for trivial count queries for optimize_trivial_count; - Respect aliased columns in GROUP BY/ORDER BY for optimize_aggregation_in_order/optimize_read_in_order. [#16995](https://github.com/ClickHouse/ClickHouse/pull/16995) ([sundyli](https://github.com/sundy-li)).
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* Speed up aggregate function `sum`. Improvement only visible on synthetic benchmarks and not very practical. [#19216](https://github.com/ClickHouse/ClickHouse/pull/19216) ([alexey-milovidov](https://github.com/alexey-milovidov)).
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* Update libc++ and use another ABI to provide better performance. [#18914](https://github.com/ClickHouse/ClickHouse/pull/18914) ([Danila Kutenin](https://github.com/danlark1)).
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* Rewrite `sumIf()` and `sum(if())` function to `countIf()` function when logically equivalent. [#17041](https://github.com/ClickHouse/ClickHouse/pull/17041) ([flynn](https://github.com/ucasFL)).
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* Use a connection pool for S3 connections, controlled by the `s3_max_connections` settings. [#13405](https://github.com/ClickHouse/ClickHouse/pull/13405) ([Vladimir Chebotarev](https://github.com/excitoon)).
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* Add support for zstd long option for better compression of string columns to save space. [#17184](https://github.com/ClickHouse/ClickHouse/pull/17184) ([ygrek](https://github.com/ygrek)).
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* Slightly improve server latency by removing access to configuration on every connection. [#19863](https://github.com/ClickHouse/ClickHouse/pull/19863) ([alexey-milovidov](https://github.com/alexey-milovidov)).
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* Reduce lock contention for multiple layers of the `Buffer` engine. [#19379](https://github.com/ClickHouse/ClickHouse/pull/19379) ([Azat Khuzhin](https://github.com/azat)).
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* Support splitting `Filter` step of query plan into `Expression + Filter` pair. Together with `Expression + Expression` merging optimization ([#17458](https://github.com/ClickHouse/ClickHouse/issues/17458)) it may delay execution for some expressions after `Filter` step. [#19253](https://github.com/ClickHouse/ClickHouse/pull/19253) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
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#### Improvement
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* `SELECT count() FROM table` now can be executed if only one any column can be selected from the `table`. This PR fixes [#10639](https://github.com/ClickHouse/ClickHouse/issues/10639). [#18233](https://github.com/ClickHouse/ClickHouse/pull/18233) ([Vitaly Baranov](https://github.com/vitlibar)).
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* Set charset to `utf8mb4` when interacting with remote MySQL servers. Fixes [#19795](https://github.com/ClickHouse/ClickHouse/issues/19795). [#19800](https://github.com/ClickHouse/ClickHouse/pull/19800) ([alexey-milovidov](https://github.com/alexey-milovidov)).
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* `S3` table function now supports `auto` compression mode (autodetect). This closes [#18754](https://github.com/ClickHouse/ClickHouse/issues/18754). [#19793](https://github.com/ClickHouse/ClickHouse/pull/19793) ([Vladimir Chebotarev](https://github.com/excitoon)).
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* Correctly output infinite arguments for `formatReadableTimeDelta` function. In previous versions, there was implicit conversion to implementation specific integer value. [#19791](https://github.com/ClickHouse/ClickHouse/pull/19791) ([alexey-milovidov](https://github.com/alexey-milovidov)).
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* Table function `S3` will use global region if the region can't be determined exactly. This closes [#10998](https://github.com/ClickHouse/ClickHouse/issues/10998). [#19750](https://github.com/ClickHouse/ClickHouse/pull/19750) ([Vladimir Chebotarev](https://github.com/excitoon)).
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* In distributed queries if the setting `async_socket_for_remote` is enabled, it was possible to get stack overflow at least in debug build configuration if very deeply nested data type is used in table (e.g. `Array(Array(Array(...more...)))`). This fixes [#19108](https://github.com/ClickHouse/ClickHouse/issues/19108). This change introduces minor backward incompatibility: excessive parenthesis in type definitions no longer supported, example: `Array((UInt8))`. [#19736](https://github.com/ClickHouse/ClickHouse/pull/19736) ([alexey-milovidov](https://github.com/alexey-milovidov)).
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* Add separate pool for message brokers (RabbitMQ and Kafka). [#19722](https://github.com/ClickHouse/ClickHouse/pull/19722) ([Azat Khuzhin](https://github.com/azat)).
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* Fix rare `max_number_of_merges_with_ttl_in_pool` limit overrun (more merges with TTL can be assigned) for non-replicated MergeTree. [#19708](https://github.com/ClickHouse/ClickHouse/pull/19708) ([alesapin](https://github.com/alesapin)).
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* Dictionary: better error message during attribute parsing. [#19678](https://github.com/ClickHouse/ClickHouse/pull/19678) ([Maksim Kita](https://github.com/kitaisreal)).
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* Add an option to disable validation of checksums on reading. Should never be used in production. Please do not expect any benefits in disabling it. It may only be used for experiments and benchmarks. The setting only applicable for tables of MergeTree family. Checksums are always validated for other table engines and when receiving data over network. In my observations there is no performance difference or it is less than 0.5%. [#19588](https://github.com/ClickHouse/ClickHouse/pull/19588) ([alexey-milovidov](https://github.com/alexey-milovidov)).
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* Support constant result in function `multiIf`. [#19533](https://github.com/ClickHouse/ClickHouse/pull/19533) ([Maksim Kita](https://github.com/kitaisreal)).
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* Enable function length/empty/notEmpty for datatype Map, which returns keys number in Map. [#19530](https://github.com/ClickHouse/ClickHouse/pull/19530) ([taiyang-li](https://github.com/taiyang-li)).
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* Add `--reconnect` option to `clickhouse-benchmark`. When this option is specified, it will reconnect before every request. This is needed for testing. [#19872](https://github.com/ClickHouse/ClickHouse/pull/19872) ([alexey-milovidov](https://github.com/alexey-milovidov)).
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* Support using the new location of `.debug` file. This fixes [#19348](https://github.com/ClickHouse/ClickHouse/issues/19348). [#19520](https://github.com/ClickHouse/ClickHouse/pull/19520) ([Amos Bird](https://github.com/amosbird)).
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* `toIPv6` function parses `IPv4` addresses. [#19518](https://github.com/ClickHouse/ClickHouse/pull/19518) ([Bharat Nallan](https://github.com/bharatnc)).
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* Add `http_referer` field to `system.query_log`, `system.processes`, etc. This closes [#19389](https://github.com/ClickHouse/ClickHouse/issues/19389). [#19390](https://github.com/ClickHouse/ClickHouse/pull/19390) ([alexey-milovidov](https://github.com/alexey-milovidov)).
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* Improve MySQL compatibility by making more functions case insensitive and adding aliases. [#19387](https://github.com/ClickHouse/ClickHouse/pull/19387) ([Daniil Kondratyev](https://github.com/dankondr)).
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* Add metrics for MergeTree parts (Wide/Compact/InMemory) types. [#19381](https://github.com/ClickHouse/ClickHouse/pull/19381) ([Azat Khuzhin](https://github.com/azat)).
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* Allow docker to be executed with arbitrary uid. [#19374](https://github.com/ClickHouse/ClickHouse/pull/19374) ([filimonov](https://github.com/filimonov)).
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* Fix wrong alignment of values of `IPv4` data type in Pretty formats. They were aligned to the right, not to the left. This closes [#19184](https://github.com/ClickHouse/ClickHouse/issues/19184). [#19339](https://github.com/ClickHouse/ClickHouse/pull/19339) ([alexey-milovidov](https://github.com/alexey-milovidov)).
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* Allow change `max_server_memory_usage` without restart. This closes [#18154](https://github.com/ClickHouse/ClickHouse/issues/18154). [#19186](https://github.com/ClickHouse/ClickHouse/pull/19186) ([alexey-milovidov](https://github.com/alexey-milovidov)).
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* The exception when function `bar` is called with certain NaN argument may be slightly misleading in previous versions. This fixes [#19088](https://github.com/ClickHouse/ClickHouse/issues/19088). [#19107](https://github.com/ClickHouse/ClickHouse/pull/19107) ([alexey-milovidov](https://github.com/alexey-milovidov)).
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* Explicitly set uid / gid of clickhouse user & group to the fixed values (101) in clickhouse-server images. [#19096](https://github.com/ClickHouse/ClickHouse/pull/19096) ([filimonov](https://github.com/filimonov)).
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* Fixed `PeekableReadBuffer: Memory limit exceed` error when inserting data with huge strings. Fixes [#18690](https://github.com/ClickHouse/ClickHouse/issues/18690). [#18979](https://github.com/ClickHouse/ClickHouse/pull/18979) ([tavplubix](https://github.com/tavplubix)).
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* Docker image: several improvements for clickhouse-server entrypoint. [#18954](https://github.com/ClickHouse/ClickHouse/pull/18954) ([filimonov](https://github.com/filimonov)).
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* Add `normalizeQueryKeepNames` and `normalizedQueryHashKeepNames` to normalize queries without masking long names with `?`. This helps better analyze complex query logs. [#18910](https://github.com/ClickHouse/ClickHouse/pull/18910) ([Amos Bird](https://github.com/amosbird)).
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* Check per-block checksum of the distributed batch on the sender before sending (without reading the file twice, the checksums will be verified while reading), this will avoid stuck of the INSERT on the receiver (on truncated .bin file on the sender). Avoid reading .bin files twice for batched INSERT (it was required to calculate rows/bytes to take squashing into account, now this information included into the header, backward compatible is preserved). [#18853](https://github.com/ClickHouse/ClickHouse/pull/18853) ([Azat Khuzhin](https://github.com/azat)).
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* Fix issues with RIGHT and FULL JOIN of tables with aggregate function states. In previous versions exception about `cloneResized` method was thrown. [#18818](https://github.com/ClickHouse/ClickHouse/pull/18818) ([templarzq](https://github.com/templarzq)).
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* Added prefix-based S3 endpoint settings. [#18812](https://github.com/ClickHouse/ClickHouse/pull/18812) ([Vladimir Chebotarev](https://github.com/excitoon)).
|
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* Add [UInt8, UInt16, UInt32, UInt64] arguments types support for bitmapTransform, bitmapSubsetInRange, bitmapSubsetLimit, bitmapContains functions. This closes [#18713](https://github.com/ClickHouse/ClickHouse/issues/18713). [#18791](https://github.com/ClickHouse/ClickHouse/pull/18791) ([sundyli](https://github.com/sundy-li)).
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* Allow CTE (Common Table Expressions) to be further aliased. Propagate CSE (Common Subexpressions Elimination) to subqueries in the same level when `enable_global_with_statement = 1`. This fixes [#17378](https://github.com/ClickHouse/ClickHouse/issues/17378) . This fixes https://github.com/ClickHouse/ClickHouse/pull/16575#issuecomment-753416235 . [#18684](https://github.com/ClickHouse/ClickHouse/pull/18684) ([Amos Bird](https://github.com/amosbird)).
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* Update librdkafka to v1.6.0-RC2. Fixes [#18668](https://github.com/ClickHouse/ClickHouse/issues/18668). [#18671](https://github.com/ClickHouse/ClickHouse/pull/18671) ([filimonov](https://github.com/filimonov)).
|
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* In case of unexpected exceptions automatically restart background thread which is responsible for execution of distributed DDL queries. Fixes [#17991](https://github.com/ClickHouse/ClickHouse/issues/17991). [#18285](https://github.com/ClickHouse/ClickHouse/pull/18285) ([徐炘](https://github.com/weeds085490)).
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* Updated AWS C++ SDK in order to utilize global regions in S3. [#17870](https://github.com/ClickHouse/ClickHouse/pull/17870) ([Vladimir Chebotarev](https://github.com/excitoon)).
|
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* Added support for `WITH ... [AND] [PERIODIC] REFRESH [interval_in_sec]` clause when creating `LIVE VIEW` tables. [#14822](https://github.com/ClickHouse/ClickHouse/pull/14822) ([vzakaznikov](https://github.com/vzakaznikov)).
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* Restrict `MODIFY TTL` queries for `MergeTree` tables created in old syntax. Previously the query succeeded, but actually it had no effect. [#19064](https://github.com/ClickHouse/ClickHouse/pull/19064) ([Anton Popov](https://github.com/CurtizJ)).
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|
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#### Bug Fix
|
||||
|
||||
* Fix index analysis of binary functions with constant argument which leads to wrong query results. This fixes [#18364](https://github.com/ClickHouse/ClickHouse/issues/18364). [#18373](https://github.com/ClickHouse/ClickHouse/pull/18373) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Fix starting the server with tables having default expressions containing dictGet(). Allow getting return type of dictGet() without loading dictionary. [#19805](https://github.com/ClickHouse/ClickHouse/pull/19805) ([Vitaly Baranov](https://github.com/vitlibar)).
|
||||
* Fix server crash after query with `if` function with `Tuple` type of then/else branches result. `Tuple` type must contain `Array` or another complex type. Fixes [#18356](https://github.com/ClickHouse/ClickHouse/issues/18356). [#20133](https://github.com/ClickHouse/ClickHouse/pull/20133) ([alesapin](https://github.com/alesapin)).
|
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* `MaterializeMySQL` (experimental feature): Fix replication for statements that update several tables. [#20066](https://github.com/ClickHouse/ClickHouse/pull/20066) ([Håvard Kvålen](https://github.com/havardk)).
|
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* Prevent "Connection refused" in docker during initialization script execution. [#20012](https://github.com/ClickHouse/ClickHouse/pull/20012) ([filimonov](https://github.com/filimonov)).
|
||||
* `EmbeddedRocksDB` is an experimental storage. Fix the issue with lack of proper type checking. Simplified code. This closes [#19967](https://github.com/ClickHouse/ClickHouse/issues/19967). [#19972](https://github.com/ClickHouse/ClickHouse/pull/19972) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fix a segfault in function `fromModifiedJulianDay` when the argument type is `Nullable(T)` for any integral types other than Int32. [#19959](https://github.com/ClickHouse/ClickHouse/pull/19959) ([PHO](https://github.com/depressed-pho)).
|
||||
* The function `greatCircleAngle` returned inaccurate results in previous versions. This closes [#19769](https://github.com/ClickHouse/ClickHouse/issues/19769). [#19789](https://github.com/ClickHouse/ClickHouse/pull/19789) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fix rare bug when some replicated operations (like mutation) cannot process some parts after data corruption. Fixes [#19593](https://github.com/ClickHouse/ClickHouse/issues/19593). [#19702](https://github.com/ClickHouse/ClickHouse/pull/19702) ([alesapin](https://github.com/alesapin)).
|
||||
* Background thread which executes `ON CLUSTER` queries might hang waiting for dropped replicated table to do something. It's fixed. [#19684](https://github.com/ClickHouse/ClickHouse/pull/19684) ([yiguolei](https://github.com/yiguolei)).
|
||||
* Fix wrong deserialization of columns description. It makes INSERT into a table with a column named `\` impossible. [#19479](https://github.com/ClickHouse/ClickHouse/pull/19479) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Mark distributed batch as broken in case of empty data block in one of files. [#19449](https://github.com/ClickHouse/ClickHouse/pull/19449) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* Fixed very rare bug that might cause mutation to hang after `DROP/DETACH/REPLACE/MOVE PARTITION`. It was partially fixed by [#15537](https://github.com/ClickHouse/ClickHouse/issues/15537) for the most cases. [#19443](https://github.com/ClickHouse/ClickHouse/pull/19443) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Fix possible error `Extremes transform was already added to pipeline`. Fixes [#14100](https://github.com/ClickHouse/ClickHouse/issues/14100). [#19430](https://github.com/ClickHouse/ClickHouse/pull/19430) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Fix default value in join types with non-zero default (e.g. some Enums). Closes [#18197](https://github.com/ClickHouse/ClickHouse/issues/18197). [#19360](https://github.com/ClickHouse/ClickHouse/pull/19360) ([vdimir](https://github.com/vdimir)).
|
||||
* Do not mark file for distributed send as broken on EOF. [#19290](https://github.com/ClickHouse/ClickHouse/pull/19290) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* Fix leaking of pipe fd for `async_socket_for_remote`. [#19153](https://github.com/ClickHouse/ClickHouse/pull/19153) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* Fix infinite reading from file in `ORC` format (was introduced in [#10580](https://github.com/ClickHouse/ClickHouse/issues/10580)). Fixes [#19095](https://github.com/ClickHouse/ClickHouse/issues/19095). [#19134](https://github.com/ClickHouse/ClickHouse/pull/19134) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Fix issue in merge tree data writer which can lead to marks with bigger size than fixed granularity size. Fixes [#18913](https://github.com/ClickHouse/ClickHouse/issues/18913). [#19123](https://github.com/ClickHouse/ClickHouse/pull/19123) ([alesapin](https://github.com/alesapin)).
|
||||
* Fix startup bug when clickhouse was not able to read compression codec from `LowCardinality(Nullable(...))` and throws exception `Attempt to read after EOF`. Fixes [#18340](https://github.com/ClickHouse/ClickHouse/issues/18340). [#19101](https://github.com/ClickHouse/ClickHouse/pull/19101) ([alesapin](https://github.com/alesapin)).
|
||||
* Simplify the implementation of `tupleHammingDistance`. Support for tuples of any equal length. Fixes [#19029](https://github.com/ClickHouse/ClickHouse/issues/19029). [#19084](https://github.com/ClickHouse/ClickHouse/pull/19084) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Make sure `groupUniqArray` returns correct type for argument of Enum type. This closes [#17875](https://github.com/ClickHouse/ClickHouse/issues/17875). [#19019](https://github.com/ClickHouse/ClickHouse/pull/19019) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fix possible error `Expected single dictionary argument for function` if use function `ignore` with `LowCardinality` argument. Fixes [#14275](https://github.com/ClickHouse/ClickHouse/issues/14275). [#19016](https://github.com/ClickHouse/ClickHouse/pull/19016) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Fix inserting of `LowCardinality` column to table with `TinyLog` engine. Fixes [#18629](https://github.com/ClickHouse/ClickHouse/issues/18629). [#19010](https://github.com/ClickHouse/ClickHouse/pull/19010) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Fix minor issue in JOIN: Join tries to materialize const columns, but our code waits for them in other places. [#18982](https://github.com/ClickHouse/ClickHouse/pull/18982) ([Nikita Mikhaylov](https://github.com/nikitamikhaylov)).
|
||||
* Disable `optimize_move_functions_out_of_any` because optimization is not always correct. This closes [#18051](https://github.com/ClickHouse/ClickHouse/issues/18051). This closes [#18973](https://github.com/ClickHouse/ClickHouse/issues/18973). [#18981](https://github.com/ClickHouse/ClickHouse/pull/18981) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fix possible exception `QueryPipeline stream: different number of columns` caused by merging of query plan's `Expression` steps. Fixes [#18190](https://github.com/ClickHouse/ClickHouse/issues/18190). [#18980](https://github.com/ClickHouse/ClickHouse/pull/18980) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Fixed very rare deadlock at shutdown. [#18977](https://github.com/ClickHouse/ClickHouse/pull/18977) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Fixed rare crashes when server run out of memory. [#18976](https://github.com/ClickHouse/ClickHouse/pull/18976) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Fix incorrect behavior when `ALTER TABLE ... DROP PART 'part_name'` query removes all deduplication blocks for the whole partition. Fixes [#18874](https://github.com/ClickHouse/ClickHouse/issues/18874). [#18969](https://github.com/ClickHouse/ClickHouse/pull/18969) ([alesapin](https://github.com/alesapin)).
|
||||
* Fixed issue [#18894](https://github.com/ClickHouse/ClickHouse/issues/18894) Add a check to avoid exception when long column alias('table.column' style, usually auto-generated by BI tools like Looker) equals to long table name. [#18968](https://github.com/ClickHouse/ClickHouse/pull/18968) ([Daniel Qin](https://github.com/mathfool)).
|
||||
* Fix error `Task was not found in task queue` (possible only for remote queries, with `async_socket_for_remote = 1`). [#18964](https://github.com/ClickHouse/ClickHouse/pull/18964) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Fix bug when mutation with some escaped text (like `ALTER ... UPDATE e = CAST('foo', 'Enum8(\'foo\' = 1')` serialized incorrectly. Fixes [#18878](https://github.com/ClickHouse/ClickHouse/issues/18878). [#18944](https://github.com/ClickHouse/ClickHouse/pull/18944) ([alesapin](https://github.com/alesapin)).
|
||||
* ATTACH PARTITION will reset mutations. [#18804](https://github.com/ClickHouse/ClickHouse/issues/18804). [#18935](https://github.com/ClickHouse/ClickHouse/pull/18935) ([fastio](https://github.com/fastio)).
|
||||
* Fix issue with `bitmapOrCardinality` that may lead to nullptr dereference. This closes [#18911](https://github.com/ClickHouse/ClickHouse/issues/18911). [#18912](https://github.com/ClickHouse/ClickHouse/pull/18912) ([sundyli](https://github.com/sundy-li)).
|
||||
* Fixed `Attempt to read after eof` error when trying to `CAST` `NULL` from `Nullable(String)` to `Nullable(Decimal(P, S))`. Now function `CAST` returns `NULL` when it cannot parse decimal from nullable string. Fixes [#7690](https://github.com/ClickHouse/ClickHouse/issues/7690). [#18718](https://github.com/ClickHouse/ClickHouse/pull/18718) ([Winter Zhang](https://github.com/zhang2014)).
|
||||
* Fix data type convert issue for MySQL engine. [#18124](https://github.com/ClickHouse/ClickHouse/pull/18124) ([bo zeng](https://github.com/mis98zb)).
|
||||
* Fix clickhouse-client abort exception while executing only `select`. [#19790](https://github.com/ClickHouse/ClickHouse/pull/19790) ([taiyang-li](https://github.com/taiyang-li)).
|
||||
|
||||
|
||||
#### Build/Testing/Packaging Improvement
|
||||
|
||||
* Run [SQLancer](https://twitter.com/RiggerManuel/status/1352345625480884228) (logical SQL fuzzer) in CI. [#19006](https://github.com/ClickHouse/ClickHouse/pull/19006) ([Ilya Yatsishin](https://github.com/qoega)).
|
||||
* Query Fuzzer will fuzz newly added tests more extensively. This closes [#18916](https://github.com/ClickHouse/ClickHouse/issues/18916). [#19185](https://github.com/ClickHouse/ClickHouse/pull/19185) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Integrate with [Big List of Naughty Strings](https://github.com/minimaxir/big-list-of-naughty-strings/) for better fuzzing. [#19480](https://github.com/ClickHouse/ClickHouse/pull/19480) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Add integration tests run with MSan. [#18974](https://github.com/ClickHouse/ClickHouse/pull/18974) ([alesapin](https://github.com/alesapin)).
|
||||
* Fixed MemorySanitizer errors in cyrus-sasl and musl. [#19821](https://github.com/ClickHouse/ClickHouse/pull/19821) ([Ilya Yatsishin](https://github.com/qoega)).
|
||||
* Insuffiient arguments check in `positionCaseInsensitiveUTF8` function triggered address sanitizer. [#19720](https://github.com/ClickHouse/ClickHouse/pull/19720) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Remove --project-directory for docker-compose in integration test. Fix logs formatting from docker container. [#19706](https://github.com/ClickHouse/ClickHouse/pull/19706) ([Ilya Yatsishin](https://github.com/qoega)).
|
||||
* Made generation of macros.xml easier for integration tests. No more excessive logging from dicttoxml. dicttoxml project is not active for 5+ years. [#19697](https://github.com/ClickHouse/ClickHouse/pull/19697) ([Ilya Yatsishin](https://github.com/qoega)).
|
||||
* Allow to explicitly enable or disable watchdog via environment variable `CLICKHOUSE_WATCHDOG_ENABLE`. By default it is enabled if server is not attached to terminal. [#19522](https://github.com/ClickHouse/ClickHouse/pull/19522) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Allow building ClickHouse with Kafka support on arm64. [#19369](https://github.com/ClickHouse/ClickHouse/pull/19369) ([filimonov](https://github.com/filimonov)).
|
||||
* Allow building librdkafka without ssl. [#19337](https://github.com/ClickHouse/ClickHouse/pull/19337) ([filimonov](https://github.com/filimonov)).
|
||||
* Restore Kafka input in FreeBSD builds. [#18924](https://github.com/ClickHouse/ClickHouse/pull/18924) ([Alexandre Snarskii](https://github.com/snar)).
|
||||
* Fix potential nullptr dereference in table function `VALUES`. [#19357](https://github.com/ClickHouse/ClickHouse/pull/19357) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Avoid UBSan reports in `arrayElement` function, `substring` and `arraySum`. Fixes [#19305](https://github.com/ClickHouse/ClickHouse/issues/19305). Fixes [#19287](https://github.com/ClickHouse/ClickHouse/issues/19287). This closes [#19336](https://github.com/ClickHouse/ClickHouse/issues/19336). [#19347](https://github.com/ClickHouse/ClickHouse/pull/19347) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
|
||||
|
||||
## ClickHouse release 21.1
|
||||
|
||||
### ClickHouse release v21.1.3.32-stable, 2021-02-03
|
||||
|
||||
#### Bug Fix
|
||||
|
||||
* BloomFilter index crash fix. Fixes [#19757](https://github.com/ClickHouse/ClickHouse/issues/19757). [#19884](https://github.com/ClickHouse/ClickHouse/pull/19884) ([Maksim Kita](https://github.com/kitaisreal)).
|
||||
* Fix crash when pushing down predicates to union distinct subquery. This fixes [#19855](https://github.com/ClickHouse/ClickHouse/issues/19855). [#19861](https://github.com/ClickHouse/ClickHouse/pull/19861) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Fix filtering by UInt8 greater than 127. [#19799](https://github.com/ClickHouse/ClickHouse/pull/19799) ([Anton Popov](https://github.com/CurtizJ)).
|
||||
* In previous versions, unusual arguments for function arrayEnumerateUniq may cause crash or infinite loop. This closes [#19787](https://github.com/ClickHouse/ClickHouse/issues/19787). [#19788](https://github.com/ClickHouse/ClickHouse/pull/19788) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fixed stack overflow when using accurate comparison of arithmetic type with string type. [#19773](https://github.com/ClickHouse/ClickHouse/pull/19773) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Fix crash when nested column name was used in `WHERE` or `PREWHERE`. Fixes [#19755](https://github.com/ClickHouse/ClickHouse/issues/19755). [#19763](https://github.com/ClickHouse/ClickHouse/pull/19763) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Fix a segmentation fault in `bitmapAndnot` function. Fixes [#19668](https://github.com/ClickHouse/ClickHouse/issues/19668). [#19713](https://github.com/ClickHouse/ClickHouse/pull/19713) ([Maksim Kita](https://github.com/kitaisreal)).
|
||||
* Some functions with big integers may cause segfault. Big integers is experimental feature. This closes [#19667](https://github.com/ClickHouse/ClickHouse/issues/19667). [#19672](https://github.com/ClickHouse/ClickHouse/pull/19672) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fix wrong result of function `neighbor` for `LowCardinality` argument. Fixes [#10333](https://github.com/ClickHouse/ClickHouse/issues/10333). [#19617](https://github.com/ClickHouse/ClickHouse/pull/19617) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Fix use-after-free of the CompressedWriteBuffer in Connection after disconnect. [#19599](https://github.com/ClickHouse/ClickHouse/pull/19599) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* `DROP/DETACH TABLE table ON CLUSTER cluster SYNC` query might hang, it's fixed. Fixes [#19568](https://github.com/ClickHouse/ClickHouse/issues/19568). [#19572](https://github.com/ClickHouse/ClickHouse/pull/19572) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Query CREATE DICTIONARY id expression fix. [#19571](https://github.com/ClickHouse/ClickHouse/pull/19571) ([Maksim Kita](https://github.com/kitaisreal)).
|
||||
* Fix SIGSEGV with merge_tree_min_rows_for_concurrent_read/merge_tree_min_bytes_for_concurrent_read=0/UINT64_MAX. [#19528](https://github.com/ClickHouse/ClickHouse/pull/19528) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* Buffer overflow (on memory read) was possible if `addMonth` function was called with specifically crafted arguments. This fixes [#19441](https://github.com/ClickHouse/ClickHouse/issues/19441). This fixes [#19413](https://github.com/ClickHouse/ClickHouse/issues/19413). [#19472](https://github.com/ClickHouse/ClickHouse/pull/19472) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Uninitialized memory read was possible in encrypt/decrypt functions if empty string was passed as IV. This closes [#19391](https://github.com/ClickHouse/ClickHouse/issues/19391). [#19397](https://github.com/ClickHouse/ClickHouse/pull/19397) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fix possible buffer overflow in Uber H3 library. See https://github.com/uber/h3/issues/392. This closes [#19219](https://github.com/ClickHouse/ClickHouse/issues/19219). [#19383](https://github.com/ClickHouse/ClickHouse/pull/19383) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fix system.parts _state column (LOGICAL_ERROR when querying this column, due to incorrect order). [#19346](https://github.com/ClickHouse/ClickHouse/pull/19346) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* Fixed possible wrong result or segfault on aggregation when Materialized View and its target table have different structure. Fixes [#18063](https://github.com/ClickHouse/ClickHouse/issues/18063). [#19322](https://github.com/ClickHouse/ClickHouse/pull/19322) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Fix error `Cannot convert column now64() because it is constant but values of constants are different in source and result`. Continuation of [#7156](https://github.com/ClickHouse/ClickHouse/issues/7156). [#19316](https://github.com/ClickHouse/ClickHouse/pull/19316) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Fix bug when concurrent `ALTER` and `DROP` queries may hang while processing ReplicatedMergeTree table. [#19237](https://github.com/ClickHouse/ClickHouse/pull/19237) ([alesapin](https://github.com/alesapin)).
|
||||
* Fixed `There is no checkpoint` error when inserting data through http interface using `Template` or `CustomSeparated` format. Fixes [#19021](https://github.com/ClickHouse/ClickHouse/issues/19021). [#19072](https://github.com/ClickHouse/ClickHouse/pull/19072) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Disable constant folding for subqueries on the analysis stage, when the result cannot be calculated. [#18446](https://github.com/ClickHouse/ClickHouse/pull/18446) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* Mutation might hang waiting for some non-existent part after `MOVE` or `REPLACE PARTITION` or, in rare cases, after `DETACH` or `DROP PARTITION`. It's fixed. [#15537](https://github.com/ClickHouse/ClickHouse/pull/15537) ([tavplubix](https://github.com/tavplubix)).
|
||||
|
||||
|
||||
|
||||
### ClickHouse release v21.1.2.15-stable 2021-01-18
|
||||
|
||||
#### Backward Incompatible Change
|
||||
|
||||
@ -8,7 +8,7 @@ ClickHouse® is an open-source column-oriented database management system that a
|
||||
* [Tutorial](https://clickhouse.tech/docs/en/getting_started/tutorial/) shows how to set up and query small ClickHouse cluster.
|
||||
* [Documentation](https://clickhouse.tech/docs/en/) provides more in-depth information.
|
||||
* [YouTube channel](https://www.youtube.com/c/ClickHouseDB) has a lot of content about ClickHouse in video format.
|
||||
* [Slack](https://join.slack.com/t/clickhousedb/shared_invite/zt-d2zxkf9e-XyxDa_ucfPxzuH4SJIm~Ng) and [Telegram](https://telegram.me/clickhouse_en) allow to chat with ClickHouse users in real-time.
|
||||
* [Slack](https://join.slack.com/t/clickhousedb/shared_invite/zt-ly9m4w1x-6j7x5Ts_pQZqrctAbRZ3cg) and [Telegram](https://telegram.me/clickhouse_en) allow to chat with ClickHouse users in real-time.
|
||||
* [Blog](https://clickhouse.yandex/blog/en/) contains various ClickHouse-related articles, as well as announcements and reports about events.
|
||||
* [Code Browser](https://clickhouse.tech/codebrowser/html_report/ClickHouse/index.html) with syntax highlight and navigation.
|
||||
* [Yandex.Messenger channel](https://yandex.ru/chat/#/join/20e380d9-c7be-4123-ab06-e95fb946975e) shares announcements and useful links in Russian.
|
||||
|
||||
@ -278,6 +278,31 @@ public:
|
||||
return res / 3600;
|
||||
}
|
||||
|
||||
/** Calculating offset from UTC in seconds.
|
||||
* which means Using the same literal time of "t" to get the corresponding timestamp in UTC,
|
||||
* then subtract the former from the latter to get the offset result.
|
||||
* The boundaries when meets DST(daylight saving time) change should be handled very carefully.
|
||||
*/
|
||||
inline time_t timezoneOffset(time_t t) const
|
||||
{
|
||||
DayNum index = findIndex(t);
|
||||
|
||||
/// Calculate daylight saving offset first.
|
||||
/// Because the "amount_of_offset_change" in LUT entry only exists in the change day, it's costly to scan it from the very begin.
|
||||
/// but we can figure out all the accumulated offsets from 1970-01-01 to that day just by get the whole difference between lut[].date,
|
||||
/// and then, we can directly subtract multiple 86400s to get the real DST offsets for the leap seconds is not considered now.
|
||||
time_t res = (lut[index].date - lut[0].date) % 86400;
|
||||
/// As so far to know, the maximal DST offset couldn't be more than 2 hours, so after the modulo operation the remainder
|
||||
/// will sits between [-offset --> 0 --> offset] which respectively corresponds to moving clock forward or backward.
|
||||
res = res > 43200 ? (86400 - res) : (0 - res);
|
||||
|
||||
/// Check if has a offset change during this day. Add the change when cross the line
|
||||
if (lut[index].amount_of_offset_change != 0 && t >= lut[index].date + lut[index].time_at_offset_change)
|
||||
res += lut[index].amount_of_offset_change;
|
||||
|
||||
return res + offset_at_start_of_epoch;
|
||||
}
|
||||
|
||||
/** Only for time zones with/when offset from UTC is multiple of five minutes.
|
||||
* This is true for all time zones: right now, all time zones have an offset that is multiple of 15 minutes.
|
||||
*
|
||||
|
||||
@ -168,14 +168,6 @@ public:
|
||||
static_assert(sizeof(LocalDate) == 4);
|
||||
|
||||
|
||||
inline std::ostream & operator<< (std::ostream & ostr, const LocalDate & date)
|
||||
{
|
||||
return ostr << date.year()
|
||||
<< '-' << (date.month() / 10) << (date.month() % 10)
|
||||
<< '-' << (date.day() / 10) << (date.day() % 10);
|
||||
}
|
||||
|
||||
|
||||
namespace std
|
||||
{
|
||||
inline string to_string(const LocalDate & date)
|
||||
|
||||
@ -169,20 +169,6 @@ public:
|
||||
static_assert(sizeof(LocalDateTime) == 8);
|
||||
|
||||
|
||||
inline std::ostream & operator<< (std::ostream & ostr, const LocalDateTime & datetime)
|
||||
{
|
||||
ostr << std::setfill('0') << std::setw(4) << datetime.year();
|
||||
|
||||
ostr << '-' << (datetime.month() / 10) << (datetime.month() % 10)
|
||||
<< '-' << (datetime.day() / 10) << (datetime.day() % 10)
|
||||
<< ' ' << (datetime.hour() / 10) << (datetime.hour() % 10)
|
||||
<< ':' << (datetime.minute() / 10) << (datetime.minute() % 10)
|
||||
<< ':' << (datetime.second() / 10) << (datetime.second() % 10);
|
||||
|
||||
return ostr;
|
||||
}
|
||||
|
||||
|
||||
namespace std
|
||||
{
|
||||
inline string to_string(const LocalDateTime & datetime)
|
||||
|
||||
@ -12,6 +12,8 @@
|
||||
#include <dlfcn.h>
|
||||
#include <fcntl.h>
|
||||
#include <fstream>
|
||||
#include <fmt/format.h>
|
||||
|
||||
|
||||
namespace
|
||||
{
|
||||
@ -189,8 +191,8 @@ void ReplxxLineReader::openEditor()
|
||||
return;
|
||||
}
|
||||
|
||||
String editor = std::getenv("EDITOR");
|
||||
if (editor.empty())
|
||||
const char * editor = std::getenv("EDITOR");
|
||||
if (!editor || !*editor)
|
||||
editor = "vim";
|
||||
|
||||
replxx::Replxx::State state(rx.get_state());
|
||||
@ -204,7 +206,7 @@ void ReplxxLineReader::openEditor()
|
||||
if ((-1 == res || 0 == res) && errno != EINTR)
|
||||
{
|
||||
rx.print("Cannot write to temporary query file %s: %s\n", filename, errnoToString(errno).c_str());
|
||||
return;
|
||||
break;
|
||||
}
|
||||
bytes_written += res;
|
||||
}
|
||||
@ -215,7 +217,7 @@ void ReplxxLineReader::openEditor()
|
||||
return;
|
||||
}
|
||||
|
||||
if (0 == execute(editor + " " + filename))
|
||||
if (0 == execute(fmt::format("{} {}", editor, filename)))
|
||||
{
|
||||
try
|
||||
{
|
||||
|
||||
@ -230,10 +230,10 @@ public:
|
||||
}
|
||||
else
|
||||
{
|
||||
siginfo_t info;
|
||||
ucontext_t context;
|
||||
siginfo_t info{};
|
||||
ucontext_t context{};
|
||||
StackTrace stack_trace(NoCapture{});
|
||||
UInt32 thread_num;
|
||||
UInt32 thread_num{};
|
||||
std::string query_id;
|
||||
DB::ThreadStatus * thread_ptr{};
|
||||
|
||||
|
||||
@ -3,7 +3,6 @@ add_library (mysqlxx
|
||||
Exception.cpp
|
||||
Query.cpp
|
||||
ResultBase.cpp
|
||||
StoreQueryResult.cpp
|
||||
UseQueryResult.cpp
|
||||
Row.cpp
|
||||
Value.cpp
|
||||
|
||||
@ -39,7 +39,6 @@ private:
|
||||
/** MySQL connection.
|
||||
* Usage:
|
||||
* mysqlxx::Connection connection("Test", "127.0.0.1", "root", "qwerty", 3306);
|
||||
* std::cout << connection.query("SELECT 'Hello, World!'").store().at(0).at(0).getString() << std::endl;
|
||||
*
|
||||
* Or with Poco library configuration:
|
||||
* mysqlxx::Connection connection("mysql_params");
|
||||
|
||||
@ -71,16 +71,6 @@ UseQueryResult Query::use()
|
||||
return UseQueryResult(res, conn, this);
|
||||
}
|
||||
|
||||
StoreQueryResult Query::store()
|
||||
{
|
||||
executeImpl();
|
||||
MYSQL_RES * res = mysql_store_result(conn->getDriver());
|
||||
if (!res)
|
||||
checkError(conn->getDriver());
|
||||
|
||||
return StoreQueryResult(res, conn, this);
|
||||
}
|
||||
|
||||
void Query::execute()
|
||||
{
|
||||
executeImpl();
|
||||
|
||||
@ -3,7 +3,6 @@
|
||||
#include <sstream>
|
||||
|
||||
#include <mysqlxx/UseQueryResult.h>
|
||||
#include <mysqlxx/StoreQueryResult.h>
|
||||
|
||||
|
||||
namespace mysqlxx
|
||||
@ -46,11 +45,6 @@ public:
|
||||
*/
|
||||
UseQueryResult use();
|
||||
|
||||
/** Выполнить запрос с загрузкой на клиента всех строк.
|
||||
* Требуется оперативка, чтобы вместить весь результат, зато к строкам можно обращаться в произвольном порядке.
|
||||
*/
|
||||
StoreQueryResult store();
|
||||
|
||||
/// Значение auto increment после последнего INSERT-а.
|
||||
UInt64 insertID();
|
||||
|
||||
|
||||
@ -9,7 +9,7 @@ class Connection;
|
||||
class Query;
|
||||
|
||||
|
||||
/** Базовый класс для UseQueryResult и StoreQueryResult.
|
||||
/** Базовый класс для UseQueryResult.
|
||||
* Содержит общую часть реализации,
|
||||
* Ссылается на Connection. Если уничтожить Connection, то пользоваться ResultBase и любым результатом нельзя.
|
||||
* Использовать объект можно только для результата одного запроса!
|
||||
|
||||
@ -35,7 +35,7 @@ public:
|
||||
{
|
||||
}
|
||||
|
||||
/** Для того, чтобы создать Row, используйте соответствующие методы UseQueryResult или StoreQueryResult. */
|
||||
/** Для того, чтобы создать Row, используйте соответствующие методы UseQueryResult. */
|
||||
Row(MYSQL_ROW row_, ResultBase * res_, MYSQL_LENGTHS lengths_)
|
||||
: row(row_), res(res_), lengths(lengths_)
|
||||
{
|
||||
|
||||
@ -1,30 +0,0 @@
|
||||
#if __has_include(<mysql.h>)
|
||||
#include <mysql.h>
|
||||
#else
|
||||
#include <mysql/mysql.h>
|
||||
#endif
|
||||
|
||||
#include <mysqlxx/Connection.h>
|
||||
#include <mysqlxx/StoreQueryResult.h>
|
||||
|
||||
|
||||
namespace mysqlxx
|
||||
{
|
||||
|
||||
StoreQueryResult::StoreQueryResult(MYSQL_RES * res_, Connection * conn_, const Query * query_) : ResultBase(res_, conn_, query_)
|
||||
{
|
||||
UInt64 rows = mysql_num_rows(res);
|
||||
reserve(rows);
|
||||
lengths.resize(rows * num_fields);
|
||||
|
||||
for (UInt64 i = 0; MYSQL_ROW row = mysql_fetch_row(res); ++i)
|
||||
{
|
||||
MYSQL_LENGTHS lengths_for_row = mysql_fetch_lengths(res);
|
||||
memcpy(&lengths[i * num_fields], lengths_for_row, sizeof(lengths[0]) * num_fields);
|
||||
|
||||
push_back(Row(row, this, &lengths[i * num_fields]));
|
||||
}
|
||||
checkError(conn->getDriver());
|
||||
}
|
||||
|
||||
}
|
||||
@ -1,45 +0,0 @@
|
||||
#pragma once
|
||||
|
||||
#include <vector>
|
||||
|
||||
#include <mysqlxx/ResultBase.h>
|
||||
#include <mysqlxx/Row.h>
|
||||
|
||||
|
||||
namespace mysqlxx
|
||||
{
|
||||
|
||||
class Connection;
|
||||
|
||||
|
||||
/** Результат выполнения запроса, загруженный полностью на клиента.
|
||||
* Это требует оперативку, чтобы вместить весь результат,
|
||||
* но зато реализует произвольный доступ к строкам по индексу.
|
||||
* Если размер результата большой - используйте лучше UseQueryResult.
|
||||
* Объект содержит ссылку на Connection.
|
||||
* Если уничтожить Connection, то объект становится некорректным и все строки результата - тоже.
|
||||
* Если задать следующий запрос в соединении, то объект и все строки тоже становятся некорректными.
|
||||
* Использовать объект можно только для результата одного запроса!
|
||||
* (При попытке присвоить объекту результат следующего запроса - UB.)
|
||||
*/
|
||||
class StoreQueryResult : public std::vector<Row>, public ResultBase
|
||||
{
|
||||
public:
|
||||
StoreQueryResult(MYSQL_RES * res_, Connection * conn_, const Query * query_);
|
||||
|
||||
size_t num_rows() const { return size(); }
|
||||
|
||||
private:
|
||||
|
||||
/** Не смотря на то, что весь результат выполнения запроса загружается на клиента,
|
||||
* и все указатели MYSQL_ROW на отдельные строки различные,
|
||||
* при этом функция mysql_fetch_lengths() возвращает длины
|
||||
* для текущей строки по одному и тому же адресу.
|
||||
* То есть, чтобы можно было пользоваться несколькими Row одновременно,
|
||||
* необходимо заранее куда-то сложить все длины.
|
||||
*/
|
||||
using Lengths = std::vector<MYSQL_LENGTH>;
|
||||
Lengths lengths;
|
||||
};
|
||||
|
||||
}
|
||||
@ -12,8 +12,7 @@ class Connection;
|
||||
|
||||
/** Результат выполнения запроса, предназначенный для чтения строк, одна за другой.
|
||||
* В памяти при этом хранится только одна, текущая строка.
|
||||
* В отличие от StoreQueryResult, произвольный доступ к строкам невозможен,
|
||||
* а также, при чтении следующей строки, предыдущая становится некорректной.
|
||||
* При чтении следующей строки, предыдущая становится некорректной.
|
||||
* Вы обязаны прочитать все строки из результата
|
||||
* (вызывать функцию fetch(), пока она не вернёт значение, преобразующееся к false),
|
||||
* иначе при следующем запросе будет выкинуто исключение с текстом "Commands out of sync".
|
||||
|
||||
@ -25,7 +25,7 @@ class ResultBase;
|
||||
|
||||
/** Represents a single value read from MySQL.
|
||||
* It doesn't owns the value. It's just a wrapper of a pair (const char *, size_t).
|
||||
* If the UseQueryResult/StoreQueryResult or Connection is destroyed,
|
||||
* If the UseQueryResult or Connection is destroyed,
|
||||
* or you have read the next Row while using UseQueryResult, then the object is invalidated.
|
||||
* Allows to transform (parse) the value to various data types:
|
||||
* - with getUInt(), getString(), ... (recommended);
|
||||
|
||||
@ -38,15 +38,6 @@ int main(int, char **)
|
||||
}
|
||||
}
|
||||
|
||||
{
|
||||
mysqlxx::Query query = connection.query();
|
||||
query << "SELECT 1234567890 abc, 12345.67890 def UNION ALL SELECT 9876543210, 98765.43210";
|
||||
mysqlxx::StoreQueryResult result = query.store();
|
||||
|
||||
std::cerr << result.at(0)["abc"].getUInt() << ", " << result.at(0)["def"].getDouble() << std::endl
|
||||
<< result.at(1)["abc"].getUInt() << ", " << result.at(1)["def"].getDouble() << std::endl;
|
||||
}
|
||||
|
||||
{
|
||||
mysqlxx::UseQueryResult result = connection.query("SELECT 'abc\\\\def' x").use();
|
||||
mysqlxx::Row row = result.fetch();
|
||||
@ -54,27 +45,6 @@ int main(int, char **)
|
||||
std::cerr << row << std::endl;
|
||||
}
|
||||
|
||||
{
|
||||
mysqlxx::Query query = connection.query("SEL");
|
||||
query << "ECT 1";
|
||||
|
||||
std::cerr << query.store().at(0).at(0) << std::endl;
|
||||
}
|
||||
|
||||
{
|
||||
/// Копирование Query
|
||||
mysqlxx::Query query = connection.query("SELECT 'Ok' x");
|
||||
using Queries = std::vector<mysqlxx::Query>;
|
||||
Queries queries;
|
||||
queries.push_back(query);
|
||||
|
||||
for (auto & q : queries)
|
||||
{
|
||||
std::cerr << q.str() << std::endl;
|
||||
std::cerr << q.store().at(0) << std::endl;
|
||||
}
|
||||
}
|
||||
|
||||
{
|
||||
/// Копирование Query
|
||||
mysqlxx::Query query1 = connection.query("SELECT");
|
||||
@ -84,62 +54,6 @@ int main(int, char **)
|
||||
std::cerr << query1.str() << ", " << query2.str() << std::endl;
|
||||
}
|
||||
|
||||
{
|
||||
/// Копирование Query
|
||||
using Queries = std::list<mysqlxx::Query>;
|
||||
Queries queries;
|
||||
queries.push_back(connection.query("SELECT"));
|
||||
mysqlxx::Query & qref = queries.back();
|
||||
qref << " 1";
|
||||
|
||||
for (auto & query : queries)
|
||||
{
|
||||
std::cerr << query.str() << std::endl;
|
||||
std::cerr << query.store().at(0) << std::endl;
|
||||
}
|
||||
}
|
||||
|
||||
{
|
||||
/// Транзакции
|
||||
connection.query("DROP TABLE IF EXISTS tmp").execute();
|
||||
connection.query("CREATE TABLE tmp (x INT, PRIMARY KEY (x)) ENGINE = InnoDB").execute();
|
||||
|
||||
mysqlxx::Transaction trans(connection);
|
||||
connection.query("INSERT INTO tmp VALUES (1)").execute();
|
||||
|
||||
std::cerr << connection.query("SELECT * FROM tmp").store().size() << std::endl;
|
||||
|
||||
trans.rollback();
|
||||
|
||||
std::cerr << connection.query("SELECT * FROM tmp").store().size() << std::endl;
|
||||
}
|
||||
|
||||
{
|
||||
/// Транзакции
|
||||
connection.query("DROP TABLE IF EXISTS tmp").execute();
|
||||
connection.query("CREATE TABLE tmp (x INT, PRIMARY KEY (x)) ENGINE = InnoDB").execute();
|
||||
|
||||
{
|
||||
mysqlxx::Transaction trans(connection);
|
||||
connection.query("INSERT INTO tmp VALUES (1)").execute();
|
||||
std::cerr << connection.query("SELECT * FROM tmp").store().size() << std::endl;
|
||||
}
|
||||
|
||||
std::cerr << connection.query("SELECT * FROM tmp").store().size() << std::endl;
|
||||
}
|
||||
|
||||
{
|
||||
/// Транзакции
|
||||
mysqlxx::Connection connection2("test", "127.0.0.1", "root", "qwerty", 3306);
|
||||
connection2.query("DROP TABLE IF EXISTS tmp").execute();
|
||||
connection2.query("CREATE TABLE tmp (x INT, PRIMARY KEY (x)) ENGINE = InnoDB").execute();
|
||||
|
||||
mysqlxx::Transaction trans(connection2);
|
||||
connection2.query("INSERT INTO tmp VALUES (1)").execute();
|
||||
std::cerr << connection2.query("SELECT * FROM tmp").store().size() << std::endl;
|
||||
}
|
||||
std::cerr << connection.query("SELECT * FROM tmp").store().size() << std::endl;
|
||||
|
||||
{
|
||||
/// NULL
|
||||
mysqlxx::Null<int> x = mysqlxx::null;
|
||||
@ -152,59 +66,6 @@ int main(int, char **)
|
||||
std::cerr << (x == 1 ? "Ok" : "Fail") << std::endl;
|
||||
std::cerr << (x.isNull() ? "Fail" : "Ok") << std::endl;
|
||||
}
|
||||
|
||||
{
|
||||
/// Исключения при попытке достать значение не того типа
|
||||
try
|
||||
{
|
||||
connection.query("SELECT -1").store().at(0).at(0).getUInt();
|
||||
std::cerr << "Fail" << std::endl;
|
||||
}
|
||||
catch (const mysqlxx::Exception & e)
|
||||
{
|
||||
std::cerr << "Ok, " << e.message() << std::endl;
|
||||
}
|
||||
|
||||
try
|
||||
{
|
||||
connection.query("SELECT 'xxx'").store().at(0).at(0).getInt();
|
||||
std::cerr << "Fail" << std::endl;
|
||||
}
|
||||
catch (const mysqlxx::Exception & e)
|
||||
{
|
||||
std::cerr << "Ok, " << e.message() << std::endl;
|
||||
}
|
||||
|
||||
try
|
||||
{
|
||||
connection.query("SELECT NULL").store().at(0).at(0).getString();
|
||||
std::cerr << "Fail" << std::endl;
|
||||
}
|
||||
catch (const mysqlxx::Exception & e)
|
||||
{
|
||||
std::cerr << "Ok, " << e.message() << std::endl;
|
||||
}
|
||||
|
||||
try
|
||||
{
|
||||
connection.query("SELECT 123").store().at(0).at(0).getDate();
|
||||
std::cerr << "Fail" << std::endl;
|
||||
}
|
||||
catch (const mysqlxx::Exception & e)
|
||||
{
|
||||
std::cerr << "Ok, " << e.message() << std::endl;
|
||||
}
|
||||
|
||||
try
|
||||
{
|
||||
connection.query("SELECT '2011-01-01'").store().at(0).at(0).getDateTime();
|
||||
std::cerr << "Fail" << std::endl;
|
||||
}
|
||||
catch (const mysqlxx::Exception & e)
|
||||
{
|
||||
std::cerr << "Ok, " << e.message() << std::endl;
|
||||
}
|
||||
}
|
||||
}
|
||||
catch (const mysqlxx::Exception & e)
|
||||
{
|
||||
|
||||
@ -11,7 +11,7 @@ endif ()
|
||||
target_compile_options(base64_scalar PRIVATE -falign-loops)
|
||||
|
||||
if (ARCH_AMD64)
|
||||
target_compile_options(base64_ssse3 PRIVATE -mssse3 -falign-loops)
|
||||
target_compile_options(base64_ssse3 PRIVATE -mno-avx -mno-avx2 -mssse3 -falign-loops)
|
||||
target_compile_options(base64_avx PRIVATE -falign-loops -mavx)
|
||||
target_compile_options(base64_avx2 PRIVATE -falign-loops -mavx2)
|
||||
else ()
|
||||
|
||||
@ -252,6 +252,7 @@ if (NOT EXTERNAL_HYPERSCAN_LIBRARY_FOUND)
|
||||
target_compile_definitions (hyperscan PUBLIC USE_HYPERSCAN=1)
|
||||
target_compile_options (hyperscan
|
||||
PRIVATE -g0 # Library has too much debug information
|
||||
-mno-avx -mno-avx2 # The library is using dynamic dispatch and is confused if AVX is enabled globally
|
||||
-march=corei7 -O2 -fno-strict-aliasing -fno-omit-frame-pointer -fvisibility=hidden # The options from original build system
|
||||
-fno-sanitize=undefined # Assume the library takes care of itself
|
||||
)
|
||||
|
||||
2
contrib/poco
vendored
2
contrib/poco
vendored
@ -1 +1 @@
|
||||
Subproject commit e11f3c971570cf6a31006cd21cadf41a259c360a
|
||||
Subproject commit fbaaba4a02e29987b8c584747a496c79528f125f
|
||||
@ -120,7 +120,7 @@ if [ -n "$(ls /docker-entrypoint-initdb.d/)" ] || [ -n "$CLICKHOUSE_DB" ]; then
|
||||
sleep 1
|
||||
done
|
||||
|
||||
clickhouseclient=( clickhouse-client --multiquery -u "$CLICKHOUSE_USER" --password "$CLICKHOUSE_PASSWORD" )
|
||||
clickhouseclient=( clickhouse-client --multiquery --host "127.0.0.1" -u "$CLICKHOUSE_USER" --password "$CLICKHOUSE_PASSWORD" )
|
||||
|
||||
echo
|
||||
|
||||
|
||||
@ -319,6 +319,7 @@ function run_tests
|
||||
|
||||
# In fasttest, ENABLE_LIBRARIES=0, so rocksdb engine is not enabled by default
|
||||
01504_rocksdb
|
||||
01686_rocksdb
|
||||
|
||||
# Look at DistributedFilesToInsert, so cannot run in parallel.
|
||||
01460_DistributedFilesToInsert
|
||||
|
||||
@ -61,7 +61,7 @@ RUN python3 -m pip install \
|
||||
aerospike \
|
||||
avro \
|
||||
cassandra-driver \
|
||||
confluent-kafka \
|
||||
confluent-kafka==1.5.0 \
|
||||
dict2xml \
|
||||
dicttoxml \
|
||||
docker \
|
||||
|
||||
@ -14,7 +14,7 @@ services:
|
||||
ports:
|
||||
- 1006:1006
|
||||
- 50070:50070
|
||||
- 9000:9000
|
||||
- 9010:9010
|
||||
depends_on:
|
||||
- hdfskerberos
|
||||
entrypoint: /etc/bootstrap.sh -d
|
||||
|
||||
@ -12,6 +12,9 @@ List of supported integrations:
|
||||
- [ODBC](../../../engines/table-engines/integrations/odbc.md)
|
||||
- [JDBC](../../../engines/table-engines/integrations/jdbc.md)
|
||||
- [MySQL](../../../engines/table-engines/integrations/mysql.md)
|
||||
- [MongoDB](../../../engines/table-engines/integrations/mongodb.md)
|
||||
- [HDFS](../../../engines/table-engines/integrations/hdfs.md)
|
||||
- [S3](../../../engines/table-engines/integrations/s3.md)
|
||||
- [Kafka](../../../engines/table-engines/integrations/kafka.md)
|
||||
- [EmbeddedRocksDB](../../../engines/table-engines/integrations/embedded-rocksdb.md)
|
||||
- [RabbitMQ](../../../engines/table-engines/integrations/rabbitmq.md)
|
||||
|
||||
57
docs/en/engines/table-engines/integrations/mongodb.md
Normal file
57
docs/en/engines/table-engines/integrations/mongodb.md
Normal file
@ -0,0 +1,57 @@
|
||||
---
|
||||
toc_priority: 7
|
||||
toc_title: MongoDB
|
||||
---
|
||||
|
||||
# MongoDB {#mongodb}
|
||||
|
||||
MongoDB engine is read-only table engine which allows to read data (`SELECT` queries) from remote MongoDB collection. Engine supports only non-nested data types. `INSERT` queries are not supported.
|
||||
|
||||
## Creating a Table {#creating-a-table}
|
||||
|
||||
``` sql
|
||||
CREATE TABLE [IF NOT EXISTS] [db.]table_name
|
||||
(
|
||||
name1 [type1],
|
||||
name2 [type2],
|
||||
...
|
||||
) ENGINE = MongoDB(host:port, database, collection, user, password);
|
||||
```
|
||||
|
||||
**Engine Parameters**
|
||||
|
||||
- `host:port` — MongoDB server address.
|
||||
|
||||
- `database` — Remote database name.
|
||||
|
||||
- `collection` — Remote collection name.
|
||||
|
||||
- `user` — MongoDB user.
|
||||
|
||||
- `password` — User password.
|
||||
|
||||
## Usage Example {#usage-example}
|
||||
|
||||
Table in ClickHouse which allows to read data from MongoDB collection:
|
||||
|
||||
``` text
|
||||
CREATE TABLE mongo_table
|
||||
(
|
||||
key UInt64,
|
||||
data String
|
||||
) ENGINE = MongoDB('mongo1:27017', 'test', 'simple_table', 'testuser', 'clickhouse');
|
||||
```
|
||||
|
||||
Query:
|
||||
|
||||
``` sql
|
||||
SELECT COUNT() FROM mongo_table;
|
||||
```
|
||||
|
||||
``` text
|
||||
┌─count()─┐
|
||||
│ 4 │
|
||||
└─────────┘
|
||||
```
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/integrations/mongodb/) <!--hide-->
|
||||
@ -45,7 +45,10 @@ ORDER BY expr
|
||||
[PARTITION BY expr]
|
||||
[PRIMARY KEY expr]
|
||||
[SAMPLE BY expr]
|
||||
[TTL expr [DELETE|TO DISK 'xxx'|TO VOLUME 'xxx'], ...]
|
||||
[TTL expr
|
||||
[DELETE|TO DISK 'xxx'|TO VOLUME 'xxx' [, ...] ]
|
||||
[WHERE conditions]
|
||||
[GROUP BY key_expr [SET v1 = aggr_func(v1) [, v2 = aggr_func(v2) ...]] ] ]
|
||||
[SETTINGS name=value, ...]
|
||||
```
|
||||
|
||||
@ -80,7 +83,7 @@ For a description of parameters, see the [CREATE query description](../../../sql
|
||||
Expression must have one `Date` or `DateTime` column as a result. Example:
|
||||
`TTL date + INTERVAL 1 DAY`
|
||||
|
||||
Type of the rule `DELETE|TO DISK 'xxx'|TO VOLUME 'xxx'` specifies an action to be done with the part if the expression is satisfied (reaches current time): removal of expired rows, moving a part (if expression is satisfied for all rows in a part) to specified disk (`TO DISK 'xxx'`) or to volume (`TO VOLUME 'xxx'`). Default type of the rule is removal (`DELETE`). List of multiple rules can specified, but there should be no more than one `DELETE` rule.
|
||||
Type of the rule `DELETE|TO DISK 'xxx'|TO VOLUME 'xxx'|GROUP BY` specifies an action to be done with the part if the expression is satisfied (reaches current time): removal of expired rows, moving a part (if expression is satisfied for all rows in a part) to specified disk (`TO DISK 'xxx'`) or to volume (`TO VOLUME 'xxx'`), or aggregating values in expired rows. Default type of the rule is removal (`DELETE`). List of multiple rules can specified, but there should be no more than one `DELETE` rule.
|
||||
|
||||
For more details, see [TTL for columns and tables](#table_engine-mergetree-ttl)
|
||||
|
||||
@ -455,18 +458,28 @@ ALTER TABLE example_table
|
||||
Table can have an expression for removal of expired rows, and multiple expressions for automatic move of parts between [disks or volumes](#table_engine-mergetree-multiple-volumes). When rows in the table expire, ClickHouse deletes all corresponding rows. For parts moving feature, all rows of a part must satisfy the movement expression criteria.
|
||||
|
||||
``` sql
|
||||
TTL expr [DELETE|TO DISK 'aaa'|TO VOLUME 'bbb'], ...
|
||||
TTL expr
|
||||
[DELETE|TO DISK 'xxx'|TO VOLUME 'xxx'][, DELETE|TO DISK 'aaa'|TO VOLUME 'bbb'] ...
|
||||
[WHERE conditions]
|
||||
[GROUP BY key_expr [SET v1 = aggr_func(v1) [, v2 = aggr_func(v2) ...]] ]
|
||||
```
|
||||
|
||||
Type of TTL rule may follow each TTL expression. It affects an action which is to be done once the expression is satisfied (reaches current time):
|
||||
|
||||
- `DELETE` - delete expired rows (default action);
|
||||
- `TO DISK 'aaa'` - move part to the disk `aaa`;
|
||||
- `TO VOLUME 'bbb'` - move part to the disk `bbb`.
|
||||
- `TO VOLUME 'bbb'` - move part to the disk `bbb`;
|
||||
- `GROUP BY` - aggregate expired rows.
|
||||
|
||||
Examples:
|
||||
With `WHERE` clause you may specify which of the expired rows to delete or aggregate (it cannot be applied to moves).
|
||||
|
||||
Creating a table with TTL
|
||||
`GROUP BY` expression must be a prefix of the table primary key.
|
||||
|
||||
If a column is not part of the `GROUP BY` expression and is not set explicitely in the `SET` clause, in result row it contains an occasional value from the grouped rows (as if aggregate function `any` is applied to it).
|
||||
|
||||
**Examples**
|
||||
|
||||
Creating a table with TTL:
|
||||
|
||||
``` sql
|
||||
CREATE TABLE example_table
|
||||
@ -482,13 +495,43 @@ TTL d + INTERVAL 1 MONTH [DELETE],
|
||||
d + INTERVAL 2 WEEK TO DISK 'bbb';
|
||||
```
|
||||
|
||||
Altering TTL of the table
|
||||
Altering TTL of the table:
|
||||
|
||||
``` sql
|
||||
ALTER TABLE example_table
|
||||
MODIFY TTL d + INTERVAL 1 DAY;
|
||||
```
|
||||
|
||||
Creating a table, where the rows are expired after one month. The expired rows where dates are Mondays are deleted:
|
||||
|
||||
``` sql
|
||||
CREATE TABLE table_with_where
|
||||
(
|
||||
d DateTime,
|
||||
a Int
|
||||
)
|
||||
ENGINE = MergeTree
|
||||
PARTITION BY toYYYYMM(d)
|
||||
ORDER BY d
|
||||
TTL d + INTERVAL 1 MONTH DELETE WHERE toDayOfWeek(d) = 1;
|
||||
```
|
||||
|
||||
Creating a table, where expired rows are aggregated. In result rows `x` contains the maximum value accross the grouped rows, `y` — the minimum value, and `d` — any occasional value from grouped rows.
|
||||
|
||||
``` sql
|
||||
CREATE TABLE table_for_aggregation
|
||||
(
|
||||
d DateTime,
|
||||
k1 Int,
|
||||
k2 Int,
|
||||
x Int,
|
||||
y Int
|
||||
)
|
||||
ENGINE = MergeTree
|
||||
ORDER BY k1, k2
|
||||
TTL d + INTERVAL 1 MONTH GROUP BY k1, k2 SET x = max(x), y = min(y);
|
||||
```
|
||||
|
||||
**Removing Data**
|
||||
|
||||
Data with an expired TTL is removed when ClickHouse merges data parts.
|
||||
|
||||
@ -8,118 +8,119 @@ toc_title: Adopters
|
||||
!!! warning "Disclaimer"
|
||||
The following list of companies using ClickHouse and their success stories is assembled from public sources, thus might differ from current reality. We’d appreciate it if you share the story of adopting ClickHouse in your company and [add it to the list](https://github.com/ClickHouse/ClickHouse/edit/master/docs/en/introduction/adopters.md), but please make sure you won’t have any NDA issues by doing so. Providing updates with publications from other companies is also useful.
|
||||
|
||||
| Company | Industry | Usecase | Cluster Size | (Un)Compressed Data Size<abbr title="of single replica"><sup>\*</sup></abbr> | Reference |
|
||||
|------------------------------------------------------------------------------------------------|---------------------------------|-----------------------|------------------------------------------------------------|------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|
||||
| <a href="https://2gis.ru" class="favicon">2gis</a> | Maps | Monitoring | — | — | [Talk in Russian, July 2019](https://youtu.be/58sPkXfq6nw) |
|
||||
| <a href="https://getadmiral.com/" class="favicon">Admiral</a> | Martech | Engagement Management | — | — | [Webinar Slides, June 2020](https://altinity.com/presentations/2020/06/16/big-data-in-real-time-how-clickhouse-powers-admirals-visitor-relationships-for-publishers) |
|
||||
| <a href="https://cn.aliyun.com/" class="favicon">Alibaba Cloud</a> | Cloud | Managed Service | — | — | [Official Website](https://help.aliyun.com/product/144466.html) |
|
||||
| <a href="https://alohabrowser.com/" class="favicon">Aloha Browser</a> | Mobile App | Browser backend | — | — | [Slides in Russian, May 2019](https://presentations.clickhouse.tech/meetup22/aloha.pdf) |
|
||||
| <a href="https://amadeus.com/" class="favicon">Amadeus</a> | Travel | Analytics | — | — | [Press Release, April 2018](https://www.altinity.com/blog/2018/4/5/amadeus-technologies-launches-investment-and-insights-tool-based-on-machine-learning-and-strategy-algorithms) |
|
||||
| <a href="https://www.appsflyer.com" class="favicon">Appsflyer</a> | Mobile analytics | Main product | — | — | [Talk in Russian, July 2019](https://www.youtube.com/watch?v=M3wbRlcpBbY) |
|
||||
| <a href="https://arenadata.tech/" class="favicon">ArenaData</a> | Data Platform | Main product | — | — | [Slides in Russian, December 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup38/indexes.pdf) |
|
||||
| <a href="https://avito.ru/" class="favicon">Avito</a> | Classifieds | Monitoring | — | — | [Meetup, April 2020](https://www.youtube.com/watch?v=n1tm4j4W8ZQ) |
|
||||
| <a href="https://badoo.com" class="favicon">Badoo</a> | Dating | Timeseries | — | — | [Slides in Russian, December 2019](https://presentations.clickhouse.tech/meetup38/forecast.pdf) |
|
||||
| <a href="https://www.benocs.com/" class="favicon">Benocs</a> | Network Telemetry and Analytics | Main Product | — | — | [Slides in English, October 2017](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup9/lpm.pdf) |
|
||||
| Company | Industry | Usecase | Cluster Size | (Un)Compressed Data Size<abbr title="of single replica"><sup>\*</sup></abbr> | Reference |
|
||||
|---------|----------|---------|--------------|------------------------------------------------------------------------------|-----------|
|
||||
| <a href="https://2gis.ru" class="favicon">2gis</a> | Maps | Monitoring | — | — | [Talk in Russian, July 2019](https://youtu.be/58sPkXfq6nw) |
|
||||
| <a href="https://getadmiral.com/" class="favicon">Admiral</a> | Martech | Engagement Management | — | — | [Webinar Slides, June 2020](https://altinity.com/presentations/2020/06/16/big-data-in-real-time-how-clickhouse-powers-admirals-visitor-relationships-for-publishers) |
|
||||
| <a href="https://cn.aliyun.com/" class="favicon">Alibaba Cloud</a> | Cloud | Managed Service | — | — | [Official Website](https://help.aliyun.com/product/144466.html) |
|
||||
| <a href="https://alohabrowser.com/" class="favicon">Aloha Browser</a> | Mobile App | Browser backend | — | — | [Slides in Russian, May 2019](https://presentations.clickhouse.tech/meetup22/aloha.pdf) |
|
||||
| <a href="https://amadeus.com/" class="favicon">Amadeus</a> | Travel | Analytics | — | — | [Press Release, April 2018](https://www.altinity.com/blog/2018/4/5/amadeus-technologies-launches-investment-and-insights-tool-based-on-machine-learning-and-strategy-algorithms) |
|
||||
| <a href="https://www.appsflyer.com" class="favicon">Appsflyer</a> | Mobile analytics | Main product | — | — | [Talk in Russian, July 2019](https://www.youtube.com/watch?v=M3wbRlcpBbY) |
|
||||
| <a href="https://arenadata.tech/" class="favicon">ArenaData</a> | Data Platform | Main product | — | — | [Slides in Russian, December 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup38/indexes.pdf) |
|
||||
| <a href="https://avito.ru/" class="favicon">Avito</a> | Classifieds | Monitoring | — | — | [Meetup, April 2020](https://www.youtube.com/watch?v=n1tm4j4W8ZQ) |
|
||||
| <a href="https://badoo.com" class="favicon">Badoo</a> | Dating | Timeseries | — | — | [Slides in Russian, December 2019](https://presentations.clickhouse.tech/meetup38/forecast.pdf) |
|
||||
| <a href="https://www.benocs.com/" class="favicon">Benocs</a> | Network Telemetry and Analytics | Main Product | — | — | [Slides in English, October 2017](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup9/lpm.pdf) |
|
||||
| <a href="https://www.bigo.sg/" class="favicon">BIGO</a> | Video | Computing Platform | — | — | [Blog Article, August 2020](https://www.programmersought.com/article/44544895251/) |
|
||||
| <a href="https://www.bloomberg.com/" class="favicon">Bloomberg</a> | Finance, Media | Monitoring | 102 servers | — | [Slides, May 2018](https://www.slideshare.net/Altinity/http-analytics-for-6m-requests-per-second-using-clickhouse-by-alexander-bocharov) |
|
||||
| <a href="https://bloxy.info" class="favicon">Bloxy</a> | Blockchain | Analytics | — | — | [Slides in Russian, August 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup17/4_bloxy.pptx) |
|
||||
| <a href="https://www.bytedance.com" class="favicon">Bytedance</a> | Social platforms | — | — | — | [The ClickHouse Meetup East, October 2020](https://www.youtube.com/watch?v=ckChUkC3Pns) |
|
||||
| <a href="https://www.bloomberg.com/" class="favicon">Bloomberg</a> | Finance, Media | Monitoring | 102 servers | — | [Slides, May 2018](https://www.slideshare.net/Altinity/http-analytics-for-6m-requests-per-second-using-clickhouse-by-alexander-bocharov) |
|
||||
| <a href="https://bloxy.info" class="favicon">Bloxy</a> | Blockchain | Analytics | — | — | [Slides in Russian, August 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup17/4_bloxy.pptx) |
|
||||
| <a href="https://www.bytedance.com" class="favicon">Bytedance</a> | Social platforms | — | — | — | [The ClickHouse Meetup East, October 2020](https://www.youtube.com/watch?v=ckChUkC3Pns) |
|
||||
| <a href="https://cardsmobile.ru/" class="favicon">CardsMobile</a> | Finance | Analytics | — | — | [VC.ru](https://vc.ru/s/cardsmobile/143449-rukovoditel-gruppy-analiza-dannyh) |
|
||||
| <a href="https://carto.com/" class="favicon">CARTO</a> | Business Intelligence | Geo analytics | — | — | [Geospatial processing with ClickHouse](https://carto.com/blog/geospatial-processing-with-clickhouse/) |
|
||||
| <a href="http://public.web.cern.ch/public/" class="favicon">CERN</a> | Research | Experiment | — | — | [Press release, April 2012](https://www.yandex.com/company/press_center/press_releases/2012/2012-04-10/) |
|
||||
| <a href="http://cisco.com/" class="favicon">Cisco</a> | Networking | Traffic analysis | — | — | [Lightning talk, October 2019](https://youtu.be/-hI1vDR2oPY?t=5057) |
|
||||
| <a href="https://www.citadelsecurities.com/" class="favicon">Citadel Securities</a> | Finance | — | — | — | [Contribution, March 2019](https://github.com/ClickHouse/ClickHouse/pull/4774) |
|
||||
| <a href="https://city-mobil.ru" class="favicon">Citymobil</a> | Taxi | Analytics | — | — | [Blog Post in Russian, March 2020](https://habr.com/en/company/citymobil/blog/490660/) |
|
||||
| <a href="https://cloudflare.com" class="favicon">Cloudflare</a> | CDN | Traffic analysis | 36 servers | — | [Blog post, May 2017](https://blog.cloudflare.com/how-cloudflare-analyzes-1m-dns-queries-per-second/), [Blog post, March 2018](https://blog.cloudflare.com/http-analytics-for-6m-requests-per-second-using-clickhouse/) |
|
||||
| <a href="https://corporate.comcast.com/" class="favicon">Comcast</a> | Media | CDN Traffic Analysis | — | — | [ApacheCon 2019 Talk](https://www.youtube.com/watch?v=e9TZ6gFDjNg) |
|
||||
| <a href="https://contentsquare.com" class="favicon">ContentSquare</a> | Web analytics | Main product | — | — | [Blog post in French, November 2018](http://souslecapot.net/2018/11/21/patrick-chatain-vp-engineering-chez-contentsquare-penser-davantage-amelioration-continue-que-revolution-constante/) |
|
||||
| <a href="https://coru.net/" class="favicon">Corunet</a> | Analytics | Main product | — | — | [Slides in English, April 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup21/predictive_models.pdf) |
|
||||
| <a href="https://www.creditx.com" class="favicon">CraiditX 氪信</a> | Finance AI | Analysis | — | — | [Slides in English, November 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup33/udf.pptx) |
|
||||
| <a href="https://crazypanda.ru/en/" class="favicon">Crazypanda</a> | Games | | — | — | Live session on ClickHouse meetup |
|
||||
| <a href="https://www.criteo.com/" class="favicon">Criteo</a> | Retail | Main product | — | — | [Slides in English, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup18/3_storetail.pptx) |
|
||||
| <a href="https://www.chinatelecomglobal.com/" class="favicon">Dataliance for China Telecom</a> | Telecom | Analytics | — | — | [Slides in Chinese, January 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup12/telecom.pdf) |
|
||||
| <a href="https://db.com" class="favicon">Deutsche Bank</a> | Finance | BI Analytics | — | — | [Slides in English, October 2019](https://bigdatadays.ru/wp-content/uploads/2019/10/D2-H3-3_Yakunin-Goihburg.pdf) |
|
||||
| <a href="https://deeplay.io/eng/" class="favicon">Deeplay</a> | Gaming Analytics | — | — | — | [Job advertisement, 2020](https://career.habr.com/vacancies/1000062568) |
|
||||
| <a href="https://www.diva-e.com" class="favicon">Diva-e</a> | Digital consulting | Main Product | — | — | [Slides in English, September 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup29/ClickHouse-MeetUp-Unusual-Applications-sd-2019-09-17.pdf) |
|
||||
| <a href="https://www.ecwid.com/" class="favicon">Ecwid</a> | E-commerce SaaS | Metrics, Logging | — | — | [Slides in Russian, April 2019](https://nastachku.ru/var/files/1/presentation/backend/2_Backend_6.pdf) |
|
||||
| <a href="https://www.ebay.com/" class="favicon">eBay</a> | E-commerce | Logs, Metrics and Events | — | — | [Official website, Sep 2020](https://tech.ebayinc.com/engineering/ou-online-analytical-processing/) |
|
||||
| <a href="https://www.exness.com" class="favicon">Exness</a> | Trading | Metrics, Logging | — | — | [Talk in Russian, May 2019](https://youtu.be/_rpU-TvSfZ8?t=3215) |
|
||||
| <a href="https://fastnetmon.com/" class="favicon">FastNetMon</a> | DDoS Protection | Main Product | | — | [Official website](https://fastnetmon.com/docs-fnm-advanced/fastnetmon-advanced-traffic-persistency/) |
|
||||
| <a href="https://www.flipkart.com/" class="favicon">Flipkart</a> | e-Commerce | — | — | — | [Talk in English, July 2020](https://youtu.be/GMiXCMFDMow?t=239) |
|
||||
| <a href="https://fun.co/rp" class="favicon">FunCorp</a> | Games | | — | — | [Article](https://www.altinity.com/blog/migrating-from-redshift-to-clickhouse) |
|
||||
| <a href="https://geniee.co.jp" class="favicon">Geniee</a> | Ad network | Main product | — | — | [Blog post in Japanese, July 2017](https://tech.geniee.co.jp/entry/2017/07/20/160100) |
|
||||
| <a href="https://www.genotek.ru/" class="favicon">Genotek</a> | Bioinformatics | Main product | — | — | [Video, August 2020](https://youtu.be/v3KyZbz9lEE) |
|
||||
| <a href="https://www.huya.com/" class="favicon">HUYA</a> | Video Streaming | Analytics | — | — | [Slides in Chinese, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup19/7.%20ClickHouse万亿数据分析实践%20李本旺(sundy-li)%20虎牙.pdf) |
|
||||
| <a href="https://www.the-ica.com/" class="favicon">ICA</a> | FinTech | Risk Management | — | — | [Blog Post in English, Sep 2020](https://altinity.com/blog/clickhouse-vs-redshift-performance-for-fintech-risk-management?utm_campaign=ClickHouse%20vs%20RedShift&utm_content=143520807&utm_medium=social&utm_source=twitter&hss_channel=tw-3894792263) |
|
||||
| <a href="https://www.idealista.com" class="favicon">Idealista</a> | Real Estate | Analytics | — | — | [Blog Post in English, April 2019](https://clickhouse.tech/blog/en/clickhouse-meetup-in-madrid-on-april-2-2019) |
|
||||
| <a href="https://www.infovista.com/" class="favicon">Infovista</a> | Networks | Analytics | — | — | [Slides in English, October 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup30/infovista.pdf) |
|
||||
| <a href="https://www.innogames.com" class="favicon">InnoGames</a> | Games | Metrics, Logging | — | — | [Slides in Russian, September 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup28/graphite_and_clickHouse.pdf) |
|
||||
| <a href="https://www.instana.com" class="favicon">Instana</a> | APM Platform | Main product | — | — | [Twitter post](https://twitter.com/mieldonkers/status/1248884119158882304) |
|
||||
| <a href="https://integros.com" class="favicon">Integros</a> | Platform for video services | Analytics | — | — | [Slides in Russian, May 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup22/strategies.pdf) |
|
||||
| <a href="https://ippon.tech" class="favicon">Ippon Technologies</a> | Technology Consulting | — | — | — | [Talk in English, July 2020](https://youtu.be/GMiXCMFDMow?t=205) |
|
||||
| <a href="https://www.ivi.ru/" class="favicon">Ivi</a> | Online Cinema | Analytics, Monitoring | — | — | [Article in Russian, Jan 2018](https://habr.com/en/company/ivi/blog/347408/) |
|
||||
| <a href="https://jinshuju.net" class="favicon">Jinshuju 金数据</a> | BI Analytics | Main product | — | — | [Slides in Chinese, October 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup24/3.%20金数据数据架构调整方案Public.pdf) |
|
||||
| <a href="https://www.kodiakdata.com/" class="favicon">Kodiak Data</a> | Clouds | Main product | — | — | [Slides in Engish, April 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup13/kodiak_data.pdf) |
|
||||
| <a href="https://kontur.ru" class="favicon">Kontur</a> | Software Development | Metrics | — | — | [Talk in Russian, November 2018](https://www.youtube.com/watch?v=U4u4Bd0FtrY) |
|
||||
| <a href="https://www.kuaishou.com/" class="favicon">Kuaishou</a> | Video | — | — | — | [ClickHouse Meetup, October 2018](https://clickhouse.tech/blog/en/2018/clickhouse-community-meetup-in-beijing-on-october-28-2018/) |
|
||||
| <a href="https://www.lbl.gov" class="favicon">Lawrence Berkeley National Laboratory</a> | Research | Traffic analysis | 1 server | 11.8 TiB | [Slides in English, April 2019](https://www.smitasin.com/presentations/2019-04-17_DOE-NSM.pdf) |
|
||||
| <a href="https://lifestreet.com/" class="favicon">LifeStreet</a> | Ad network | Main product | 75 servers (3 replicas) | 5.27 PiB | [Blog post in Russian, February 2017](https://habr.com/en/post/322620/) |
|
||||
| <a href="https://mcs.mail.ru/" class="favicon">Mail.ru Cloud Solutions</a> | Cloud services | Main product | — | — | [Article in Russian](https://mcs.mail.ru/help/db-create/clickhouse#) |
|
||||
| <a href="https://tech.mymarilyn.ru" class="favicon">Marilyn</a> | Advertising | Statistics | — | — | [Talk in Russian, June 2017](https://www.youtube.com/watch?v=iXlIgx2khwc) |
|
||||
| <a href="https://mellodesign.ru/" class="favicon">Mello</a> | Marketing | Analytics | 1 server | — | [Article, Oct 2020](https://vc.ru/marketing/166180-razrabotka-tipovogo-otcheta-skvoznoy-analitiki) |
|
||||
| <a href="https://www.messagebird.com" class="favicon">MessageBird</a> | Telecommunications | Statistics | — | — | [Slides in English, November 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup20/messagebird.pdf) |
|
||||
| <a href="https://www.mindsdb.com/" class="favicon">MindsDB</a> | Machine Learning | Main Product | — | — | [Official Website](https://www.mindsdb.com/blog/machine-learning-models-as-tables-in-ch) |x
|
||||
| <a href="https://mux.com/" class="favicon">MUX</a> | Online Video | Video Analytics | — | — | [Talk in English, August 2019](https://altinity.com/presentations/2019/8/13/how-clickhouse-became-the-default-analytics-database-for-mux/) |
|
||||
| <a href="https://www.mgid.com/" class="favicon">MGID</a> | Ad network | Web-analytics | — | — | [Blog post in Russian, April 2020](http://gs-studio.com/news-about-it/32777----clickhouse---c) |
|
||||
| <a href="https://getnoc.com/" class="favicon">NOC Project</a> | Network Monitoring | Analytics | Main Product | — | [Official Website](https://getnoc.com/features/big-data/) |
|
||||
| <a href="https://www.nuna.com/" class="favicon">Nuna Inc.</a> | Health Data Analytics | — | — | — | [Talk in English, July 2020](https://youtu.be/GMiXCMFDMow?t=170) |
|
||||
| <a href="https://www.oneapm.com/" class="favicon">OneAPM</a> | Monitorings and Data Analysis | Main product | — | — | [Slides in Chinese, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup19/8.%20clickhouse在OneAPM的应用%20杜龙.pdf) |
|
||||
| <a href="https://www.percent.cn/" class="favicon">Percent 百分点</a> | Analytics | Main Product | — | — | [Slides in Chinese, June 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup24/4.%20ClickHouse万亿数据双中心的设计与实践%20.pdf) |
|
||||
| <a href="https://www.percona.com/" class="favicon">Percona</a> | Performance analysis | Percona Monitoring and Management | — | — | [Official website, Mar 2020](https://www.percona.com/blog/2020/03/30/advanced-query-analysis-in-percona-monitoring-and-management-with-direct-clickhouse-access/) |
|
||||
| <a href="https://plausible.io/" class="favicon">Plausible</a> | Analytics | Main Product | — | — | [Blog post, June 2020](https://twitter.com/PlausibleHQ/status/1273889629087969280) |
|
||||
| <a href="https://posthog.com/" class="favicon">PostHog</a> | Product Analytics | Main Product | — | — | [Release Notes, Oct 2020](https://posthog.com/blog/the-posthog-array-1-15-0) |
|
||||
| <a href="https://postmates.com/" class="favicon">Postmates</a> | Delivery | — | — | — | [Talk in English, July 2020](https://youtu.be/GMiXCMFDMow?t=188) |
|
||||
| <a href="http://www.pragma-innovation.fr/" class="favicon">Pragma Innovation</a> | Telemetry and Big Data Analysis | Main product | — | — | [Slides in English, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup18/4_pragma_innovation.pdf) |
|
||||
| <a href="https://www.qingcloud.com/" class="favicon">QINGCLOUD</a> | Cloud services | Main product | — | — | [Slides in Chinese, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup19/4.%20Cloud%20%2B%20TSDB%20for%20ClickHouse%20张健%20QingCloud.pdf) |
|
||||
| <a href="https://qrator.net" class="favicon">Qrator</a> | DDoS protection | Main product | — | — | [Blog Post, March 2019](https://blog.qrator.net/en/clickhouse-ddos-mitigation_37/) |
|
||||
| <a href="https://www.rbinternational.com/" class="favicon">Raiffeisenbank</a> | Banking | Analytics | — | — | [Lecture in Russian, December 2020](https://cs.hse.ru/announcements/421965599.html) |
|
||||
| <a href="https://rambler.ru" class="favicon">Rambler</a> | Internet services | Analytics | — | — | [Talk in Russian, April 2018](https://medium.com/@ramblertop/разработка-api-clickhouse-для-рамблер-топ-100-f4c7e56f3141) |
|
||||
| <a href="https://retell.cc/" class="favicon">Retell</a> | Speech synthesis | Analytics | — | — | [Blog Article, August 2020](https://vc.ru/services/153732-kak-sozdat-audiostati-na-vashem-sayte-i-zachem-eto-nuzhno) |
|
||||
| <a href="https://rspamd.com/" class="favicon">Rspamd</a> | Antispam | Analytics | — | — | [Official Website](https://rspamd.com/doc/modules/clickhouse.html) |
|
||||
| <a href="https://rusiem.com/en" class="favicon">RuSIEM</a> | SIEM | Main Product | — | — | [Official Website](https://rusiem.com/en/products/architecture) |
|
||||
| <a href="https://www.s7.ru" class="favicon">S7 Airlines</a> | Airlines | Metrics, Logging | — | — | [Talk in Russian, March 2019](https://www.youtube.com/watch?v=nwG68klRpPg&t=15s) |
|
||||
| <a href="https://www.scireum.de/" class="favicon">scireum GmbH</a> | e-Commerce | Main product | — | — | [Talk in German, February 2020](https://www.youtube.com/watch?v=7QWAn5RbyR4) |
|
||||
| <a href="https://segment.com/" class="favicon">Segment</a> | Data processing | Main product | 9 * i3en.3xlarge nodes 7.5TB NVME SSDs, 96GB Memory, 12 vCPUs | — | [Slides, 2019](https://slides.com/abraithwaite/segment-clickhouse) |
|
||||
| <a href="https://www.semrush.com/" class="favicon">SEMrush</a> | Marketing | Main product | — | — | [Slides in Russian, August 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup17/5_semrush.pdf) |
|
||||
| <a href="https://sentry.io/" class="favicon">Sentry</a> | Software Development | Main product | — | — | [Blog Post in English, May 2019](https://blog.sentry.io/2019/05/16/introducing-snuba-sentrys-new-search-infrastructure) |
|
||||
| <a href="https://seo.do/" class="favicon">seo.do</a> | Analytics | Main product | — | — | [Slides in English, November 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup35/CH%20Presentation-%20Metehan%20Çetinkaya.pdf) |
|
||||
| <a href="http://www.sgk.gov.tr/wps/portal/sgk/tr" class="favicon">SGK</a> | Goverment Social Security | Analytics | — | — | [Slides in English, November 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup35/ClickHouse%20Meetup-Ramazan%20POLAT.pdf) |
|
||||
| <a href="http://english.sina.com/index.html" class="favicon">Sina</a> | News | — | — | — | [Slides in Chinese, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup19/6.%20ClickHouse最佳实践%20高鹏_新浪.pdf) |
|
||||
| <a href="https://smi2.ru/" class="favicon">SMI2</a> | News | Analytics | — | — | [Blog Post in Russian, November 2017](https://habr.com/ru/company/smi2/blog/314558/) |
|
||||
| <a href="https://www.splunk.com/" class="favicon">Splunk</a> | Business Analytics | Main product | — | — | [Slides in English, January 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup12/splunk.pdf) |
|
||||
| <a href="https://www.spotify.com" class="favicon">Spotify</a> | Music | Experimentation | — | — | [Slides, July 2018](https://www.slideshare.net/glebus/using-clickhouse-for-experimentation-104247173) |
|
||||
| <a href="https://www.staffcop.ru/" class="favicon">Staffcop</a> | Information Security | Main Product | — | — | [Official website, Documentation](https://www.staffcop.ru/sce43) |
|
||||
| <a href="https://www.suning.com/" class="favicon">Suning</a> | E-Commerce | User behaviour analytics | — | — | [Blog article](https://www.sohu.com/a/434152235_411876) |
|
||||
| <a href="https://www.teralytics.net/" class="favicon">Teralytics</a> | Mobility | Analytics | — | — | [Tech blog](https://www.teralytics.net/knowledge-hub/visualizing-mobility-data-the-scalability-challenge) |
|
||||
| <a href="https://www.tencent.com" class="favicon">Tencent</a> | Big Data | Data processing | — | — | [Slides in Chinese, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup19/5.%20ClickHouse大数据集群应用_李俊飞腾讯网媒事业部.pdf) |
|
||||
| <a href="https://www.tencent.com" class="favicon">Tencent</a> | Messaging | Logging | — | — | [Talk in Chinese, November 2019](https://youtu.be/T-iVQRuw-QY?t=5050) |
|
||||
| <a href="https://www.tencentmusic.com/" class="favicon">Tencent Music Entertainment (TME)</a> | BigData | Data processing | — | — | [Blog in Chinese, June 2020](https://cloud.tencent.com/developer/article/1637840) |
|
||||
| <a href="https://trafficstars.com/" class="favicon">Traffic Stars</a> | AD network | — | — | — | [Slides in Russian, May 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup15/lightning/ninja.pdf) |
|
||||
| <a href="https://www.uber.com" class="favicon">Uber</a> | Taxi | Logging | — | — | [Slides, February 2020](https://presentations.clickhouse.tech/meetup40/uber.pdf) |
|
||||
| <a href="https://vk.com" class="favicon">VKontakte</a> | Social Network | Statistics, Logging | — | — | [Slides in Russian, August 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup17/3_vk.pdf) |
|
||||
| <a href="https://www.walmartlabs.com/" class="favicon">Walmart Labs</a> | Internet, Retail | — | — | — | [Talk in English, July 2020](https://youtu.be/GMiXCMFDMow?t=144) |
|
||||
| <a href="https://wargaming.com/en/" class="favicon">Wargaming</a> | Games | | — | — | [Interview](https://habr.com/en/post/496954/) |
|
||||
| <a href="https://wisebits.com/" class="favicon">Wisebits</a> | IT Solutions | Analytics | — | — | [Slides in Russian, May 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup22/strategies.pdf) |
|
||||
| <a href="https://www.workato.com/" class="favicon">Workato</a> | Automation Software | — | — | — | [Talk in English, July 2020](https://youtu.be/GMiXCMFDMow?t=334) |
|
||||
| <a href="http://www.xiaoxintech.cn/" class="favicon">Xiaoxin Tech</a> | Education | Common purpose | — | — | [Slides in English, November 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup33/sync-clickhouse-with-mysql-mongodb.pptx) |
|
||||
| <a href="https://www.ximalaya.com/" class="favicon">Ximalaya</a> | Audio sharing | OLAP | — | — | [Slides in English, November 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup33/ximalaya.pdf) |
|
||||
| <a href="https://cloud.yandex.ru/services/managed-clickhouse" class="favicon">Yandex Cloud</a> | Public Cloud | Main product | — | — | [Talk in Russian, December 2019](https://www.youtube.com/watch?v=pgnak9e_E0o) |
|
||||
| <a href="https://cloud.yandex.ru/services/datalens" class="favicon">Yandex DataLens</a> | Business Intelligence | Main product | — | — | [Slides in Russian, December 2019](https://presentations.clickhouse.tech/meetup38/datalens.pdf) |
|
||||
| <a href="https://market.yandex.ru/" class="favicon">Yandex Market</a> | e-Commerce | Metrics, Logging | — | — | [Talk in Russian, January 2019](https://youtu.be/_l1qP0DyBcA?t=478) |
|
||||
| <a href="https://metrica.yandex.com" class="favicon">Yandex Metrica</a> | Web analytics | Main product | 630 servers in one cluster, 360 servers in another cluster, 1862 servers in one department | 133 PiB / 8.31 PiB / 120 trillion records | [Slides, February 2020](https://presentations.clickhouse.tech/meetup40/introduction/#13) |
|
||||
| <a href="https://htc-cs.ru/" class="favicon">ЦВТ</a> | Software Development | Metrics, Logging | — | — | [Blog Post, March 2019, in Russian](https://vc.ru/dev/62715-kak-my-stroili-monitoring-na-prometheus-clickhouse-i-elk) |
|
||||
| <a href="https://mkb.ru/" class="favicon">МКБ</a> | Bank | Web-system monitoring | — | — | [Slides in Russian, September 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup28/mkb.pdf) |
|
||||
| <a href="https://cft.ru/" class="favicon">ЦФТ</a> | Banking, Financial products, Payments | — | — | — | [Meetup in Russian, April 2020](https://team.cft.ru/events/162) |
|
||||
| <a href="https://www.kakaocorp.com/" class="favicon">kakaocorp</a> | Internet company | — | — | — | [if(kakao)2020 conference](https://if.kakao.com/session/117) |
|
||||
| <a href="https://carto.com/" class="favicon">CARTO</a> | Business Intelligence | Geo analytics | — | — | [Geospatial processing with ClickHouse](https://carto.com/blog/geospatial-processing-with-clickhouse/) |
|
||||
| <a href="http://public.web.cern.ch/public/" class="favicon">CERN</a> | Research | Experiment | — | — | [Press release, April 2012](https://www.yandex.com/company/press_center/press_releases/2012/2012-04-10/) |
|
||||
| <a href="http://cisco.com/" class="favicon">Cisco</a> | Networking | Traffic analysis | — | — | [Lightning talk, October 2019](https://youtu.be/-hI1vDR2oPY?t=5057) |
|
||||
| <a href="https://www.citadelsecurities.com/" class="favicon">Citadel Securities</a> | Finance | — | — | — | [Contribution, March 2019](https://github.com/ClickHouse/ClickHouse/pull/4774) |
|
||||
| <a href="https://city-mobil.ru" class="favicon">Citymobil</a> | Taxi | Analytics | — | — | [Blog Post in Russian, March 2020](https://habr.com/en/company/citymobil/blog/490660/) |
|
||||
| <a href="https://cloudflare.com" class="favicon">Cloudflare</a> | CDN | Traffic analysis | 36 servers | — | [Blog post, May 2017](https://blog.cloudflare.com/how-cloudflare-analyzes-1m-dns-queries-per-second/), [Blog post, March 2018](https://blog.cloudflare.com/http-analytics-for-6m-requests-per-second-using-clickhouse/) |
|
||||
| <a href="https://corporate.comcast.com/" class="favicon">Comcast</a> | Media | CDN Traffic Analysis | — | — | [ApacheCon 2019 Talk](https://www.youtube.com/watch?v=e9TZ6gFDjNg) |
|
||||
| <a href="https://contentsquare.com" class="favicon">ContentSquare</a> | Web analytics | Main product | — | — | [Blog post in French, November 2018](http://souslecapot.net/2018/11/21/patrick-chatain-vp-engineering-chez-contentsquare-penser-davantage-amelioration-continue-que-revolution-constante/) |
|
||||
| <a href="https://coru.net/" class="favicon">Corunet</a> | Analytics | Main product | — | — | [Slides in English, April 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup21/predictive_models.pdf) |
|
||||
| <a href="https://www.creditx.com" class="favicon">CraiditX 氪信</a> | Finance AI | Analysis | — | — | [Slides in English, November 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup33/udf.pptx) |
|
||||
| <a href="https://crazypanda.ru/en/" class="favicon">Crazypanda</a> | Games | | — | — | Live session on ClickHouse meetup |
|
||||
| <a href="https://www.criteo.com/" class="favicon">Criteo</a> | Retail | Main product | — | — | [Slides in English, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup18/3_storetail.pptx) |
|
||||
| <a href="https://www.chinatelecomglobal.com/" class="favicon">Dataliance for China Telecom</a> | Telecom | Analytics | — | — | [Slides in Chinese, January 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup12/telecom.pdf) |
|
||||
| <a href="https://db.com" class="favicon">Deutsche Bank</a> | Finance | BI Analytics | — | — | [Slides in English, October 2019](https://bigdatadays.ru/wp-content/uploads/2019/10/D2-H3-3_Yakunin-Goihburg.pdf) |
|
||||
| <a href="https://deeplay.io/eng/" class="favicon">Deeplay</a> | Gaming Analytics | — | — | — | [Job advertisement, 2020](https://career.habr.com/vacancies/1000062568) |
|
||||
| <a href="https://www.diva-e.com" class="favicon">Diva-e</a> | Digital consulting | Main Product | — | — | [Slides in English, September 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup29/ClickHouse-MeetUp-Unusual-Applications-sd-2019-09-17.pdf) |
|
||||
| <a href="https://www.ecwid.com/" class="favicon">Ecwid</a> | E-commerce SaaS | Metrics, Logging | — | — | [Slides in Russian, April 2019](https://nastachku.ru/var/files/1/presentation/backend/2_Backend_6.pdf) |
|
||||
| <a href="https://www.ebay.com/" class="favicon">eBay</a> | E-commerce | Logs, Metrics and Events | — | — | [Official website, Sep 2020](https://tech.ebayinc.com/engineering/ou-online-analytical-processing/) |
|
||||
| <a href="https://www.exness.com" class="favicon">Exness</a> | Trading | Metrics, Logging | — | — | [Talk in Russian, May 2019](https://youtu.be/_rpU-TvSfZ8?t=3215) |
|
||||
| <a href="https://fastnetmon.com/" class="favicon">FastNetMon</a> | DDoS Protection | Main Product | | — | [Official website](https://fastnetmon.com/docs-fnm-advanced/fastnetmon-advanced-traffic-persistency/) |
|
||||
| <a href="https://www.flipkart.com/" class="favicon">Flipkart</a> | e-Commerce | — | — | — | [Talk in English, July 2020](https://youtu.be/GMiXCMFDMow?t=239) |
|
||||
| <a href="https://fun.co/rp" class="favicon">FunCorp</a> | Games | | — | 14 bn records/day as of Jan 2021 | [Article](https://www.altinity.com/blog/migrating-from-redshift-to-clickhouse) |
|
||||
| <a href="https://geniee.co.jp" class="favicon">Geniee</a> | Ad network | Main product | — | — | [Blog post in Japanese, July 2017](https://tech.geniee.co.jp/entry/2017/07/20/160100) |
|
||||
| <a href="https://www.genotek.ru/" class="favicon">Genotek</a> | Bioinformatics | Main product | — | — | [Video, August 2020](https://youtu.be/v3KyZbz9lEE) |
|
||||
| <a href="https://www.huya.com/" class="favicon">HUYA</a> | Video Streaming | Analytics | — | — | [Slides in Chinese, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup19/7.%20ClickHouse万亿数据分析实践%20李本旺(sundy-li)%20虎牙.pdf) |
|
||||
| <a href="https://www.the-ica.com/" class="favicon">ICA</a> | FinTech | Risk Management | — | — | [Blog Post in English, Sep 2020](https://altinity.com/blog/clickhouse-vs-redshift-performance-for-fintech-risk-management?utm_campaign=ClickHouse%20vs%20RedShift&utm_content=143520807&utm_medium=social&utm_source=twitter&hss_channel=tw-3894792263) |
|
||||
| <a href="https://www.idealista.com" class="favicon">Idealista</a> | Real Estate | Analytics | — | — | [Blog Post in English, April 2019](https://clickhouse.tech/blog/en/clickhouse-meetup-in-madrid-on-april-2-2019) |
|
||||
| <a href="https://www.infovista.com/" class="favicon">Infovista</a> | Networks | Analytics | — | — | [Slides in English, October 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup30/infovista.pdf) |
|
||||
| <a href="https://www.innogames.com" class="favicon">InnoGames</a> | Games | Metrics, Logging | — | — | [Slides in Russian, September 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup28/graphite_and_clickHouse.pdf) |
|
||||
| <a href="https://www.instana.com" class="favicon">Instana</a> | APM Platform | Main product | — | — | [Twitter post](https://twitter.com/mieldonkers/status/1248884119158882304) |
|
||||
| <a href="https://integros.com" class="favicon">Integros</a> | Platform for video services | Analytics | — | — | [Slides in Russian, May 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup22/strategies.pdf) |
|
||||
| <a href="https://ippon.tech" class="favicon">Ippon Technologies</a> | Technology Consulting | — | — | — | [Talk in English, July 2020](https://youtu.be/GMiXCMFDMow?t=205) |
|
||||
| <a href="https://www.ivi.ru/" class="favicon">Ivi</a> | Online Cinema | Analytics, Monitoring | — | — | [Article in Russian, Jan 2018](https://habr.com/en/company/ivi/blog/347408/) |
|
||||
| <a href="https://jinshuju.net" class="favicon">Jinshuju 金数据</a> | BI Analytics | Main product | — | — | [Slides in Chinese, October 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup24/3.%20金数据数据架构调整方案Public.pdf) |
|
||||
| <a href="https://www.kodiakdata.com/" class="favicon">Kodiak Data</a> | Clouds | Main product | — | — | [Slides in Engish, April 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup13/kodiak_data.pdf) |
|
||||
| <a href="https://kontur.ru" class="favicon">Kontur</a> | Software Development | Metrics | — | — | [Talk in Russian, November 2018](https://www.youtube.com/watch?v=U4u4Bd0FtrY) |
|
||||
| <a href="https://www.kuaishou.com/" class="favicon">Kuaishou</a> | Video | — | — | — | [ClickHouse Meetup, October 2018](https://clickhouse.tech/blog/en/2018/clickhouse-community-meetup-in-beijing-on-october-28-2018/) |
|
||||
| <a href="https://www.lbl.gov" class="favicon">Lawrence Berkeley National Laboratory</a> | Research | Traffic analysis | 1 server | 11.8 TiB | [Slides in English, April 2019](https://www.smitasin.com/presentations/2019-04-17_DOE-NSM.pdf) |
|
||||
| <a href="https://lifestreet.com/" class="favicon">LifeStreet</a> | Ad network | Main product | 75 servers (3 replicas) | 5.27 PiB | [Blog post in Russian, February 2017](https://habr.com/en/post/322620/) |
|
||||
| <a href="https://mcs.mail.ru/" class="favicon">Mail.ru Cloud Solutions</a> | Cloud services | Main product | — | — | [Article in Russian](https://mcs.mail.ru/help/db-create/clickhouse#) |
|
||||
| <a href="https://tech.mymarilyn.ru" class="favicon">Marilyn</a> | Advertising | Statistics | — | — | [Talk in Russian, June 2017](https://www.youtube.com/watch?v=iXlIgx2khwc) |
|
||||
| <a href="https://mellodesign.ru/" class="favicon">Mello</a> | Marketing | Analytics | 1 server | — | [Article, Oct 2020](https://vc.ru/marketing/166180-razrabotka-tipovogo-otcheta-skvoznoy-analitiki) |
|
||||
| <a href="https://www.messagebird.com" class="favicon">MessageBird</a> | Telecommunications | Statistics | — | — | [Slides in English, November 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup20/messagebird.pdf) |
|
||||
| <a href="https://www.mindsdb.com/" class="favicon">MindsDB</a> | Machine Learning | Main Product | — | — | [Official Website](https://www.mindsdb.com/blog/machine-learning-models-as-tables-in-ch) |x
|
||||
| <a href="https://mux.com/" class="favicon">MUX</a> | Online Video | Video Analytics | — | — | [Talk in English, August 2019](https://altinity.com/presentations/2019/8/13/how-clickhouse-became-the-default-analytics-database-for-mux/) |
|
||||
| <a href="https://www.mgid.com/" class="favicon">MGID</a> | Ad network | Web-analytics | — | — | [Blog post in Russian, April 2020](http://gs-studio.com/news-about-it/32777----clickhouse---c) |
|
||||
| <a href="https://getnoc.com/" class="favicon">NOC Project</a> | Network Monitoring | Analytics | Main Product | — | [Official Website](https://getnoc.com/features/big-data/) |
|
||||
| <a href="https://www.nuna.com/" class="favicon">Nuna Inc.</a> | Health Data Analytics | — | — | — | [Talk in English, July 2020](https://youtu.be/GMiXCMFDMow?t=170) |
|
||||
| <a href="https://www.oneapm.com/" class="favicon">OneAPM</a> | Monitorings and Data Analysis | Main product | — | — | [Slides in Chinese, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup19/8.%20clickhouse在OneAPM的应用%20杜龙.pdf) |
|
||||
| <a href="https://panelbear.com/" class="favicon">Panelbear | Analytics | Monitoring and Analytics | — | — | [Tech Stack, November 2020](https://panelbear.com/blog/tech-stack/) |
|
||||
| <a href="https://www.percent.cn/" class="favicon">Percent 百分点</a> | Analytics | Main Product | — | — | [Slides in Chinese, June 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup24/4.%20ClickHouse万亿数据双中心的设计与实践%20.pdf) |
|
||||
| <a href="https://www.percona.com/" class="favicon">Percona</a> | Performance analysis | Percona Monitoring and Management | — | — | [Official website, Mar 2020](https://www.percona.com/blog/2020/03/30/advanced-query-analysis-in-percona-monitoring-and-management-with-direct-clickhouse-access/) |
|
||||
| <a href="https://plausible.io/" class="favicon">Plausible</a> | Analytics | Main Product | — | — | [Blog post, June 2020](https://twitter.com/PlausibleHQ/status/1273889629087969280) |
|
||||
| <a href="https://posthog.com/" class="favicon">PostHog</a> | Product Analytics | Main Product | — | — | [Release Notes, Oct 2020](https://posthog.com/blog/the-posthog-array-1-15-0) |
|
||||
| <a href="https://postmates.com/" class="favicon">Postmates</a> | Delivery | — | — | — | [Talk in English, July 2020](https://youtu.be/GMiXCMFDMow?t=188) |
|
||||
| <a href="http://www.pragma-innovation.fr/" class="favicon">Pragma Innovation</a> | Telemetry and Big Data Analysis | Main product | — | — | [Slides in English, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup18/4_pragma_innovation.pdf) |
|
||||
| <a href="https://www.qingcloud.com/" class="favicon">QINGCLOUD</a> | Cloud services | Main product | — | — | [Slides in Chinese, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup19/4.%20Cloud%20%2B%20TSDB%20for%20ClickHouse%20张健%20QingCloud.pdf) |
|
||||
| <a href="https://qrator.net" class="favicon">Qrator</a> | DDoS protection | Main product | — | — | [Blog Post, March 2019](https://blog.qrator.net/en/clickhouse-ddos-mitigation_37/) |
|
||||
| <a href="https://www.rbinternational.com/" class="favicon">Raiffeisenbank</a> | Banking | Analytics | — | — | [Lecture in Russian, December 2020](https://cs.hse.ru/announcements/421965599.html) |
|
||||
| <a href="https://rambler.ru" class="favicon">Rambler</a> | Internet services | Analytics | — | — | [Talk in Russian, April 2018](https://medium.com/@ramblertop/разработка-api-clickhouse-для-рамблер-топ-100-f4c7e56f3141) |
|
||||
| <a href="https://retell.cc/" class="favicon">Retell</a> | Speech synthesis | Analytics | — | — | [Blog Article, August 2020](https://vc.ru/services/153732-kak-sozdat-audiostati-na-vashem-sayte-i-zachem-eto-nuzhno) |
|
||||
| <a href="https://rspamd.com/" class="favicon">Rspamd</a> | Antispam | Analytics | — | — | [Official Website](https://rspamd.com/doc/modules/clickhouse.html) |
|
||||
| <a href="https://rusiem.com/en" class="favicon">RuSIEM</a> | SIEM | Main Product | — | — | [Official Website](https://rusiem.com/en/products/architecture) |
|
||||
| <a href="https://www.s7.ru" class="favicon">S7 Airlines</a> | Airlines | Metrics, Logging | — | — | [Talk in Russian, March 2019](https://www.youtube.com/watch?v=nwG68klRpPg&t=15s) |
|
||||
| <a href="https://www.scireum.de/" class="favicon">scireum GmbH</a> | e-Commerce | Main product | — | — | [Talk in German, February 2020](https://www.youtube.com/watch?v=7QWAn5RbyR4) |
|
||||
| <a href="https://segment.com/" class="favicon">Segment</a> | Data processing | Main product | 9 * i3en.3xlarge nodes 7.5TB NVME SSDs, 96GB Memory, 12 vCPUs | — | [Slides, 2019](https://slides.com/abraithwaite/segment-clickhouse) |
|
||||
| <a href="https://www.semrush.com/" class="favicon">SEMrush</a> | Marketing | Main product | — | — | [Slides in Russian, August 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup17/5_semrush.pdf) |
|
||||
| <a href="https://sentry.io/" class="favicon">Sentry</a> | Software Development | Main product | — | — | [Blog Post in English, May 2019](https://blog.sentry.io/2019/05/16/introducing-snuba-sentrys-new-search-infrastructure) |
|
||||
| <a href="https://seo.do/" class="favicon">seo.do</a> | Analytics | Main product | — | — | [Slides in English, November 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup35/CH%20Presentation-%20Metehan%20Çetinkaya.pdf) |
|
||||
| <a href="http://www.sgk.gov.tr/wps/portal/sgk/tr" class="favicon">SGK</a> | Goverment Social Security | Analytics | — | — | [Slides in English, November 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup35/ClickHouse%20Meetup-Ramazan%20POLAT.pdf) |
|
||||
| <a href="http://english.sina.com/index.html" class="favicon">Sina</a> | News | — | — | — | [Slides in Chinese, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup19/6.%20ClickHouse最佳实践%20高鹏_新浪.pdf) |
|
||||
| <a href="https://smi2.ru/" class="favicon">SMI2</a> | News | Analytics | — | — | [Blog Post in Russian, November 2017](https://habr.com/ru/company/smi2/blog/314558/) |
|
||||
| <a href="https://www.splunk.com/" class="favicon">Splunk</a> | Business Analytics | Main product | — | — | [Slides in English, January 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup12/splunk.pdf) |
|
||||
| <a href="https://www.spotify.com" class="favicon">Spotify</a> | Music | Experimentation | — | — | [Slides, July 2018](https://www.slideshare.net/glebus/using-clickhouse-for-experimentation-104247173) |
|
||||
| <a href="https://www.staffcop.ru/" class="favicon">Staffcop</a> | Information Security | Main Product | — | — | [Official website, Documentation](https://www.staffcop.ru/sce43) |
|
||||
| <a href="https://www.suning.com/" class="favicon">Suning</a> | E-Commerce | User behaviour analytics | — | — | [Blog article](https://www.sohu.com/a/434152235_411876) |
|
||||
| <a href="https://www.teralytics.net/" class="favicon">Teralytics</a> | Mobility | Analytics | — | — | [Tech blog](https://www.teralytics.net/knowledge-hub/visualizing-mobility-data-the-scalability-challenge) |
|
||||
| <a href="https://www.tencent.com" class="favicon">Tencent</a> | Big Data | Data processing | — | — | [Slides in Chinese, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup19/5.%20ClickHouse大数据集群应用_李俊飞腾讯网媒事业部.pdf) |
|
||||
| <a href="https://www.tencent.com" class="favicon">Tencent</a> | Messaging | Logging | — | — | [Talk in Chinese, November 2019](https://youtu.be/T-iVQRuw-QY?t=5050) |
|
||||
| <a href="https://www.tencentmusic.com/" class="favicon">Tencent Music Entertainment (TME)</a> | BigData | Data processing | — | — | [Blog in Chinese, June 2020](https://cloud.tencent.com/developer/article/1637840) |
|
||||
| <a href="https://trafficstars.com/" class="favicon">Traffic Stars</a> | AD network | — | — | — | [Slides in Russian, May 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup15/lightning/ninja.pdf) |
|
||||
| <a href="https://www.uber.com" class="favicon">Uber</a> | Taxi | Logging | — | — | [Slides, February 2020](https://presentations.clickhouse.tech/meetup40/uber.pdf) |
|
||||
| <a href="https://vk.com" class="favicon">VKontakte</a> | Social Network | Statistics, Logging | — | — | [Slides in Russian, August 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup17/3_vk.pdf) |
|
||||
| <a href="https://www.walmartlabs.com/" class="favicon">Walmart Labs</a> | Internet, Retail | — | — | — | [Talk in English, July 2020](https://youtu.be/GMiXCMFDMow?t=144) |
|
||||
| <a href="https://wargaming.com/en/" class="favicon">Wargaming</a> | Games | | — | — | [Interview](https://habr.com/en/post/496954/) |
|
||||
| <a href="https://wisebits.com/" class="favicon">Wisebits</a> | IT Solutions | Analytics | — | — | [Slides in Russian, May 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup22/strategies.pdf) |
|
||||
| <a href="https://www.workato.com/" class="favicon">Workato</a> | Automation Software | — | — | — | [Talk in English, July 2020](https://youtu.be/GMiXCMFDMow?t=334) |
|
||||
| <a href="http://www.xiaoxintech.cn/" class="favicon">Xiaoxin Tech</a> | Education | Common purpose | — | — | [Slides in English, November 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup33/sync-clickhouse-with-mysql-mongodb.pptx) |
|
||||
| <a href="https://www.ximalaya.com/" class="favicon">Ximalaya</a> | Audio sharing | OLAP | — | — | [Slides in English, November 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup33/ximalaya.pdf) |
|
||||
| <a href="https://cloud.yandex.ru/services/managed-clickhouse" class="favicon">Yandex Cloud</a> | Public Cloud | Main product | — | — | [Talk in Russian, December 2019](https://www.youtube.com/watch?v=pgnak9e_E0o) |
|
||||
| <a href="https://cloud.yandex.ru/services/datalens" class="favicon">Yandex DataLens</a> | Business Intelligence | Main product | — | — | [Slides in Russian, December 2019](https://presentations.clickhouse.tech/meetup38/datalens.pdf) |
|
||||
| <a href="https://market.yandex.ru/" class="favicon">Yandex Market</a> | e-Commerce | Metrics, Logging | — | — | [Talk in Russian, January 2019](https://youtu.be/_l1qP0DyBcA?t=478) |
|
||||
| <a href="https://metrica.yandex.com" class="favicon">Yandex Metrica</a> | Web analytics | Main product | 630 servers in one cluster, 360 servers in another cluster, 1862 servers in one department | 133 PiB / 8.31 PiB / 120 trillion records | [Slides, February 2020](https://presentations.clickhouse.tech/meetup40/introduction/#13) |
|
||||
| <a href="https://htc-cs.ru/" class="favicon">ЦВТ</a> | Software Development | Metrics, Logging | — | — | [Blog Post, March 2019, in Russian](https://vc.ru/dev/62715-kak-my-stroili-monitoring-na-prometheus-clickhouse-i-elk) |
|
||||
| <a href="https://mkb.ru/" class="favicon">МКБ</a> | Bank | Web-system monitoring | — | — | [Slides in Russian, September 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup28/mkb.pdf) |
|
||||
| <a href="https://cft.ru/" class="favicon">ЦФТ</a> | Banking, Financial products, Payments | — | — | — | [Meetup in Russian, April 2020](https://team.cft.ru/events/162) |
|
||||
| <a href="https://www.kakaocorp.com/" class="favicon">kakaocorp</a> | Internet company | — | — | — | [if(kakao)2020 conference](https://if.kakao.com/session/117) |
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/introduction/adopters/) <!--hide-->
|
||||
|
||||
@ -29,6 +29,8 @@ Let’s look at the section of the ‘users.xml’ file that defines quotas.
|
||||
|
||||
<!-- Unlimited. Just collect data for the specified time interval. -->
|
||||
<queries>0</queries>
|
||||
<query_selects>0</query_selects>
|
||||
<query_inserts>0</query_inserts>
|
||||
<errors>0</errors>
|
||||
<result_rows>0</result_rows>
|
||||
<read_rows>0</read_rows>
|
||||
@ -48,6 +50,8 @@ The resource consumption calculated for each interval is output to the server lo
|
||||
<duration>3600</duration>
|
||||
|
||||
<queries>1000</queries>
|
||||
<query_selects>100</query_selects>
|
||||
<query_inserts>100</query_inserts>
|
||||
<errors>100</errors>
|
||||
<result_rows>1000000000</result_rows>
|
||||
<read_rows>100000000000</read_rows>
|
||||
@ -58,6 +62,8 @@ The resource consumption calculated for each interval is output to the server lo
|
||||
<duration>86400</duration>
|
||||
|
||||
<queries>10000</queries>
|
||||
<query_selects>10000</query_selects>
|
||||
<query_inserts>10000</query_inserts>
|
||||
<errors>1000</errors>
|
||||
<result_rows>5000000000</result_rows>
|
||||
<read_rows>500000000000</read_rows>
|
||||
@ -74,6 +80,10 @@ Here are the amounts that can be restricted:
|
||||
|
||||
`queries` – The total number of requests.
|
||||
|
||||
`query_selects` – The total number of select requests.
|
||||
|
||||
`query_inserts` – The total number of insert requests.
|
||||
|
||||
`errors` – The number of queries that threw an exception.
|
||||
|
||||
`result_rows` – The total number of rows given as a result.
|
||||
|
||||
@ -296,11 +296,33 @@ Useful for breaking away from a specific network interface.
|
||||
<interserver_http_host>example.yandex.ru</interserver_http_host>
|
||||
```
|
||||
|
||||
## interserver_https_port {#interserver-https-port}
|
||||
|
||||
Port for exchanging data between ClickHouse servers over `HTTPS`.
|
||||
|
||||
**Example**
|
||||
|
||||
``` xml
|
||||
<interserver_https_port>9010</interserver_https_port>
|
||||
```
|
||||
|
||||
## interserver_https_host {#interserver-https-host}
|
||||
|
||||
Similar to `interserver_http_host`, except that this hostname can be used by other servers to access this server over `HTTPS`.
|
||||
|
||||
**Example**
|
||||
|
||||
``` xml
|
||||
<interserver_https_host>example.yandex.ru</interserver_https_host>
|
||||
```
|
||||
|
||||
## interserver_http_credentials {#server-settings-interserver-http-credentials}
|
||||
|
||||
The username and password used to authenticate during [replication](../../engines/table-engines/mergetree-family/replication.md) with the Replicated\* engines. These credentials are used only for communication between replicas and are unrelated to credentials for ClickHouse clients. The server is checking these credentials for connecting replicas and use the same credentials when connecting to other replicas. So, these credentials should be set the same for all replicas in a cluster.
|
||||
By default, the authentication is not used.
|
||||
|
||||
**Note:** These credentials are common for replication through `HTTP` and `HTTPS`.
|
||||
|
||||
This section contains the following parameters:
|
||||
|
||||
- `user` — username.
|
||||
|
||||
@ -6,29 +6,62 @@ This table contains information about events that occurred with [data parts](../
|
||||
|
||||
The `system.part_log` table contains the following columns:
|
||||
|
||||
- `event_type` (Enum) — Type of the event that occurred with the data part. Can have one of the following values:
|
||||
- `query_id` ([String](../../sql-reference/data-types/string.md)) — Identifier of the `INSERT` query that created this data part.
|
||||
- `event_type` ([Enum8](../../sql-reference/data-types/enum.md)) — Type of the event that occurred with the data part. Can have one of the following values:
|
||||
- `NEW_PART` — Inserting of a new data part.
|
||||
- `MERGE_PARTS` — Merging of data parts.
|
||||
- `DOWNLOAD_PART` — Downloading a data part.
|
||||
- `REMOVE_PART` — Removing or detaching a data part using [DETACH PARTITION](../../sql-reference/statements/alter/partition.md#alter_detach-partition).
|
||||
- `MUTATE_PART` — Mutating of a data part.
|
||||
- `MOVE_PART` — Moving the data part from the one disk to another one.
|
||||
- `event_date` (Date) — Event date.
|
||||
- `event_time` (DateTime) — Event time.
|
||||
- `duration_ms` (UInt64) — Duration.
|
||||
- `database` (String) — Name of the database the data part is in.
|
||||
- `table` (String) — Name of the table the data part is in.
|
||||
- `part_name` (String) — Name of the data part.
|
||||
- `partition_id` (String) — ID of the partition that the data part was inserted to. The column takes the ‘all’ value if the partitioning is by `tuple()`.
|
||||
- `rows` (UInt64) — The number of rows in the data part.
|
||||
- `size_in_bytes` (UInt64) — Size of the data part in bytes.
|
||||
- `merged_from` (Array(String)) — An array of names of the parts which the current part was made up from (after the merge).
|
||||
- `bytes_uncompressed` (UInt64) — Size of uncompressed bytes.
|
||||
- `read_rows` (UInt64) — The number of rows was read during the merge.
|
||||
- `read_bytes` (UInt64) — The number of bytes was read during the merge.
|
||||
- `error` (UInt16) — The code number of the occurred error.
|
||||
- `exception` (String) — Text message of the occurred error.
|
||||
- `event_date` ([Date](../../sql-reference/data-types/date.md)) — Event date.
|
||||
- `event_time` ([DateTime](../../sql-reference/data-types/datetime.md)) — Event time.
|
||||
- `duration_ms` ([UInt64](../../sql-reference/data-types/int-uint.md)) — Duration.
|
||||
- `database` ([String](../../sql-reference/data-types/string.md)) — Name of the database the data part is in.
|
||||
- `table` ([String](../../sql-reference/data-types/string.md)) — Name of the table the data part is in.
|
||||
- `part_name` ([String](../../sql-reference/data-types/string.md)) — Name of the data part.
|
||||
- `partition_id` ([String](../../sql-reference/data-types/string.md)) — ID of the partition that the data part was inserted to. The column takes the `all` value if the partitioning is by `tuple()`.
|
||||
- `path_on_disk` ([String](../../sql-reference/data-types/string.md)) — Absolute path to the folder with data part files.
|
||||
- `rows` ([UInt64](../../sql-reference/data-types/int-uint.md)) — The number of rows in the data part.
|
||||
- `size_in_bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — Size of the data part in bytes.
|
||||
- `merged_from` ([Array(String)](../../sql-reference/data-types/array.md)) — An array of names of the parts which the current part was made up from (after the merge).
|
||||
- `bytes_uncompressed` ([UInt64](../../sql-reference/data-types/int-uint.md)) — Size of uncompressed bytes.
|
||||
- `read_rows` ([UInt64](../../sql-reference/data-types/int-uint.md)) — The number of rows was read during the merge.
|
||||
- `read_bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — The number of bytes was read during the merge.
|
||||
- `peak_memory_usage` ([Int64](../../sql-reference/data-types/int-uint.md)) — The maximum difference between the amount of allocated and freed memory in context of this thread.
|
||||
- `error` ([UInt16](../../sql-reference/data-types/int-uint.md)) — The code number of the occurred error.
|
||||
- `exception` ([String](../../sql-reference/data-types/string.md)) — Text message of the occurred error.
|
||||
|
||||
The `system.part_log` table is created after the first inserting data to the `MergeTree` table.
|
||||
|
||||
**Example**
|
||||
|
||||
``` sql
|
||||
SELECT * FROM system.part_log LIMIT 1 FORMAT Vertical;
|
||||
```
|
||||
|
||||
``` text
|
||||
Row 1:
|
||||
──────
|
||||
query_id: 983ad9c7-28d5-4ae1-844e-603116b7de31
|
||||
event_type: NewPart
|
||||
event_date: 2021-02-02
|
||||
event_time: 2021-02-02 11:14:28
|
||||
duration_ms: 35
|
||||
database: default
|
||||
table: log_mt_2
|
||||
part_name: all_1_1_0
|
||||
partition_id: all
|
||||
path_on_disk: db/data/default/log_mt_2/all_1_1_0/
|
||||
rows: 115418
|
||||
size_in_bytes: 1074311
|
||||
merged_from: []
|
||||
bytes_uncompressed: 0
|
||||
read_rows: 0
|
||||
read_bytes: 0
|
||||
peak_memory_usage: 0
|
||||
error: 0
|
||||
exception:
|
||||
```
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/operations/system_tables/part_log) <!--hide-->
|
||||
|
||||
@ -9,6 +9,8 @@ Columns:
|
||||
- `0` — Interval is not randomized.
|
||||
- `1` — Interval is randomized.
|
||||
- `max_queries` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt64](../../sql-reference/data-types/int-uint.md))) — Maximum number of queries.
|
||||
- `max_query_selects` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt64](../../sql-reference/data-types/int-uint.md))) — Maximum number of select queries.
|
||||
- `max_query_inserts` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt64](../../sql-reference/data-types/int-uint.md))) — Maximum number of insert queries.
|
||||
- `max_errors` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt64](../../sql-reference/data-types/int-uint.md))) — Maximum number of errors.
|
||||
- `max_result_rows` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt64](../../sql-reference/data-types/int-uint.md))) — Maximum number of result rows.
|
||||
- `max_result_bytes` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt64](../../sql-reference/data-types/int-uint.md))) — Maximum number of RAM volume in bytes used to store a queries result.
|
||||
|
||||
@ -9,6 +9,8 @@ Columns:
|
||||
- `end_time`([Nullable](../../sql-reference/data-types/nullable.md)([DateTime](../../sql-reference/data-types/datetime.md))) — End time for calculating resource consumption.
|
||||
- `duration` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt64](../../sql-reference/data-types/int-uint.md))) — Length of the time interval for calculating resource consumption, in seconds.
|
||||
- `queries` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt64](../../sql-reference/data-types/int-uint.md))) — The total number of requests on this interval.
|
||||
- `query_selects` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt64](../../sql-reference/data-types/int-uint.md))) — The total number of select requests on this interval.
|
||||
- `query_inserts` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt64](../../sql-reference/data-types/int-uint.md))) — The total number of insert requests on this interval.
|
||||
- `max_queries` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt64](../../sql-reference/data-types/int-uint.md))) — Maximum number of requests.
|
||||
- `errors` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt64](../../sql-reference/data-types/int-uint.md))) — The number of queries that threw an exception.
|
||||
- `max_errors` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt64](../../sql-reference/data-types/int-uint.md))) — Maximum number of errors.
|
||||
|
||||
@ -11,6 +11,10 @@ Columns:
|
||||
- `duration` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt32](../../sql-reference/data-types/int-uint.md))) — Length of the time interval for calculating resource consumption, in seconds.
|
||||
- `queries` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt64](../../sql-reference/data-types/int-uint.md))) — The total number of requests in this interval.
|
||||
- `max_queries` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt64](../../sql-reference/data-types/int-uint.md))) — Maximum number of requests.
|
||||
- `query_selects` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt64](../../sql-reference/data-types/int-uint.md))) — The total number of select requests in this interval.
|
||||
- `max_query_selects` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt64](../../sql-reference/data-types/int-uint.md))) — Maximum number of select requests.
|
||||
- `query_inserts` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt64](../../sql-reference/data-types/int-uint.md))) — The total number of insert requests in this interval.
|
||||
- `max_query_inserts` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt64](../../sql-reference/data-types/int-uint.md))) — Maximum number of insert requests.
|
||||
- `errors` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt64](../../sql-reference/data-types/int-uint.md))) — The number of queries that threw an exception.
|
||||
- `max_errors` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt64](../../sql-reference/data-types/int-uint.md))) — Maximum number of errors.
|
||||
- `result_rows` ([Nullable](../../sql-reference/data-types/nullable.md)([UInt64](../../sql-reference/data-types/int-uint.md))) — The total number of rows given as a result.
|
||||
|
||||
@ -12,7 +12,7 @@ Columns:
|
||||
|
||||
- `event_time` ([DateTime](../../sql-reference/data-types/datetime.md)) — Timestamp of the sampling moment.
|
||||
|
||||
- `event_time_microseconds` ([DateTime](../../sql-reference/data-types/datetime.md)) — Timestamp of the sampling moment with microseconds precision.
|
||||
- `event_time_microseconds` ([DateTime64](../../sql-reference/data-types/datetime64.md)) — Timestamp of the sampling moment with microseconds precision.
|
||||
|
||||
- `timestamp_ns` ([UInt64](../../sql-reference/data-types/int-uint.md)) — Timestamp of the sampling moment in nanoseconds.
|
||||
|
||||
|
||||
@ -1,12 +1,16 @@
|
||||
# system.zookeeper {#system-zookeeper}
|
||||
|
||||
The table does not exist if ZooKeeper is not configured. Allows reading data from the ZooKeeper cluster defined in the config.
|
||||
The query must have a ‘path’ equality condition in the WHERE clause. This is the path in ZooKeeper for the children that you want to get data for.
|
||||
The query must either have a ‘path =’ condition or a `path IN` condition set with the `WHERE` clause as shown below. This corresponds to the path of the children in ZooKeeper that you want to get data for.
|
||||
|
||||
The query `SELECT * FROM system.zookeeper WHERE path = '/clickhouse'` outputs data for all children on the `/clickhouse` node.
|
||||
To output data for all root nodes, write path = ‘/’.
|
||||
If the path specified in ‘path’ doesn’t exist, an exception will be thrown.
|
||||
|
||||
The query `SELECT * FROM system.zookeeper WHERE path IN ('/', '/clickhouse')` outputs data for all children on the `/` and `/clickhouse` node.
|
||||
If in the specified ‘path’ collection has doesn't exist path, an exception will be thrown.
|
||||
It can be used to do a batch of ZooKeeper path queries.
|
||||
|
||||
Columns:
|
||||
|
||||
- `name` (String) — The name of the node.
|
||||
|
||||
@ -4,13 +4,42 @@ toc_priority: 106
|
||||
|
||||
# argMax {#agg-function-argmax}
|
||||
|
||||
Syntax: `argMax(arg, val)` or `argMax(tuple(arg, val))`
|
||||
Calculates the `arg` value for a maximum `val` value. If there are several different values of `arg` for maximum values of `val`, returns the first of these values encountered.
|
||||
|
||||
Calculates the `arg` value for a maximum `val` value. If there are several different values of `arg` for maximum values of `val`, the first of these values encountered is output.
|
||||
Tuple version of this function will return the tuple with the maximum `val` value. It is convenient for use with [SimpleAggregateFunction](../../../sql-reference/data-types/simpleaggregatefunction.md).
|
||||
|
||||
Tuple version of this function will return the tuple with the maximum `val` value. It is convinient for use with `SimpleAggregateFunction`.
|
||||
**Syntax**
|
||||
|
||||
**Example:**
|
||||
``` sql
|
||||
argMax(arg, val)
|
||||
```
|
||||
|
||||
or
|
||||
|
||||
``` sql
|
||||
argMax(tuple(arg, val))
|
||||
```
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `arg` — Argument.
|
||||
- `val` — Value.
|
||||
|
||||
**Returned value**
|
||||
|
||||
- `arg` value that corresponds to maximum `val` value.
|
||||
|
||||
Type: matches `arg` type.
|
||||
|
||||
For tuple in the input:
|
||||
|
||||
- Tuple `(arg, val)`, where `val` is the maximum value and `arg` is a corresponding value.
|
||||
|
||||
Type: [Tuple](../../../sql-reference/data-types/tuple.md).
|
||||
|
||||
**Example**
|
||||
|
||||
Input table:
|
||||
|
||||
``` text
|
||||
┌─user─────┬─salary─┐
|
||||
@ -20,12 +49,18 @@ Tuple version of this function will return the tuple with the maximum `val` valu
|
||||
└──────────┴────────┘
|
||||
```
|
||||
|
||||
Query:
|
||||
|
||||
``` sql
|
||||
SELECT argMax(user, salary), argMax(tuple(user, salary)) FROM salary
|
||||
SELECT argMax(user, salary), argMax(tuple(user, salary)) FROM salary;
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
┌─argMax(user, salary)─┬─argMax(tuple(user, salary))─┐
|
||||
│ director │ ('director',5000) │
|
||||
└──────────────────────┴─────────────────────────────┘
|
||||
```
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/sql-reference/aggregate-functions/reference/argmax/) <!--hide-->
|
||||
|
||||
@ -4,13 +4,42 @@ toc_priority: 105
|
||||
|
||||
# argMin {#agg-function-argmin}
|
||||
|
||||
Syntax: `argMin(arg, val)` or `argMin(tuple(arg, val))`
|
||||
Calculates the `arg` value for a minimum `val` value. If there are several different values of `arg` for minimum values of `val`, returns the first of these values encountered.
|
||||
|
||||
Calculates the `arg` value for a minimal `val` value. If there are several different values of `arg` for minimal values of `val`, the first of these values encountered is output.
|
||||
Tuple version of this function will return the tuple with the minimum `val` value. It is convenient for use with [SimpleAggregateFunction](../../../sql-reference/data-types/simpleaggregatefunction.md).
|
||||
|
||||
Tuple version of this function will return the tuple with the minimal `val` value. It is convinient for use with `SimpleAggregateFunction`.
|
||||
**Syntax**
|
||||
|
||||
**Example:**
|
||||
``` sql
|
||||
argMin(arg, val)
|
||||
```
|
||||
|
||||
or
|
||||
|
||||
``` sql
|
||||
argMin(tuple(arg, val))
|
||||
```
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `arg` — Argument.
|
||||
- `val` — Value.
|
||||
|
||||
**Returned value**
|
||||
|
||||
- `arg` value that corresponds to minimum `val` value.
|
||||
|
||||
Type: matches `arg` type.
|
||||
|
||||
For tuple in the input:
|
||||
|
||||
- Tuple `(arg, val)`, where `val` is the minimum value and `arg` is a corresponding value.
|
||||
|
||||
Type: [Tuple](../../../sql-reference/data-types/tuple.md).
|
||||
|
||||
**Example**
|
||||
|
||||
Input table:
|
||||
|
||||
``` text
|
||||
┌─user─────┬─salary─┐
|
||||
@ -20,12 +49,18 @@ Tuple version of this function will return the tuple with the minimal `val` valu
|
||||
└──────────┴────────┘
|
||||
```
|
||||
|
||||
Query:
|
||||
|
||||
``` sql
|
||||
SELECT argMin(user, salary), argMin(tuple(user, salary)) FROM salary
|
||||
SELECT argMin(user, salary), argMin(tuple(user, salary)) FROM salary;
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
┌─argMin(user, salary)─┬─argMin(tuple(user, salary))─┐
|
||||
│ worker │ ('worker',1000) │
|
||||
└──────────────────────┴─────────────────────────────┘
|
||||
```
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/sql-reference/aggregate-functions/reference/argmin/) <!--hide-->
|
||||
|
||||
@ -0,0 +1,71 @@
|
||||
---
|
||||
toc_priority: 310
|
||||
toc_title: mannWhitneyUTest
|
||||
---
|
||||
|
||||
# mannWhitneyUTest {#mannwhitneyutest}
|
||||
|
||||
Applies the Mann-Whitney rank test to samples from two populations.
|
||||
|
||||
**Syntax**
|
||||
|
||||
``` sql
|
||||
mannWhitneyUTest[(alternative[, continuity_correction])](sample_data, sample_index)
|
||||
```
|
||||
|
||||
Values of both samples are in the `sample_data` column. If `sample_index` equals to 0 then the value in that row belongs to the sample from the first population. Otherwise it belongs to the sample from the second population.
|
||||
The null hypothesis is that two populations are stochastically equal. Also one-sided hypothesises can be tested. This test does not assume that data have normal distribution.
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `alternative` — alternative hypothesis. (Optional, default: `'two-sided'`.) [String](../../../sql-reference/data-types/string.md).
|
||||
- `'two-sided'`;
|
||||
- `'greater'`;
|
||||
- `'less'`.
|
||||
- `continuity_correction` - if not 0 then continuity correction in the normal approximation for the p-value is applied. (Optional, default: 1.) [UInt64](../../../sql-reference/data-types/int-uint.md).
|
||||
- `sample_data` — sample data. [Integer](../../../sql-reference/data-types/int-uint.md), [Float](../../../sql-reference/data-types/float.md) or [Decimal](../../../sql-reference/data-types/decimal.md).
|
||||
- `sample_index` — sample index. [Integer](../../../sql-reference/data-types/int-uint.md).
|
||||
|
||||
|
||||
**Returned values**
|
||||
|
||||
[Tuple](../../../sql-reference/data-types/tuple.md) with two elements:
|
||||
- calculated U-statistic. [Float64](../../../sql-reference/data-types/float.md).
|
||||
- calculated p-value. [Float64](../../../sql-reference/data-types/float.md).
|
||||
|
||||
|
||||
**Example**
|
||||
|
||||
Input table:
|
||||
|
||||
``` text
|
||||
┌─sample_data─┬─sample_index─┐
|
||||
│ 10 │ 0 │
|
||||
│ 11 │ 0 │
|
||||
│ 12 │ 0 │
|
||||
│ 1 │ 1 │
|
||||
│ 2 │ 1 │
|
||||
│ 3 │ 1 │
|
||||
└─────────────┴──────────────┘
|
||||
```
|
||||
|
||||
Query:
|
||||
|
||||
``` sql
|
||||
SELECT mannWhitneyUTest('greater')(sample_data, sample_index) FROM mww_ttest;
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
┌─mannWhitneyUTest('greater')(sample_data, sample_index)─┐
|
||||
│ (9,0.04042779918503192) │
|
||||
└────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
**See Also**
|
||||
|
||||
- [Mann–Whitney U test](https://en.wikipedia.org/wiki/Mann%E2%80%93Whitney_U_test)
|
||||
- [Stochastic ordering](https://en.wikipedia.org/wiki/Stochastic_ordering)
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/sql-reference/aggregate-functions/reference/mannwhitneyutest/) <!--hide-->
|
||||
@ -79,6 +79,40 @@ Result:
|
||||
└───────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
# quantilesTimingWeighted {#quantilestimingweighted}
|
||||
|
||||
Same as `quantileTimingWeighted`, but accept multiple parameters with quantile levels and return an Array filled with many values of that quantiles.
|
||||
|
||||
|
||||
**Example**
|
||||
|
||||
Input table:
|
||||
|
||||
``` text
|
||||
┌─response_time─┬─weight─┐
|
||||
│ 68 │ 1 │
|
||||
│ 104 │ 2 │
|
||||
│ 112 │ 3 │
|
||||
│ 126 │ 2 │
|
||||
│ 138 │ 1 │
|
||||
│ 162 │ 1 │
|
||||
└───────────────┴────────┘
|
||||
```
|
||||
|
||||
Query:
|
||||
|
||||
``` sql
|
||||
SELECT quantilesTimingWeighted(0,5, 0.99)(response_time, weight) FROM t
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
┌─quantilesTimingWeighted(0.5, 0.99)(response_time, weight)─┐
|
||||
│ [112,162] │
|
||||
└───────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
**See Also**
|
||||
|
||||
- [median](../../../sql-reference/aggregate-functions/reference/median.md#median)
|
||||
|
||||
@ -0,0 +1,65 @@
|
||||
---
|
||||
toc_priority: 300
|
||||
toc_title: studentTTest
|
||||
---
|
||||
|
||||
# studentTTest {#studentttest}
|
||||
|
||||
Applies Student's t-test to samples from two populations.
|
||||
|
||||
**Syntax**
|
||||
|
||||
``` sql
|
||||
studentTTest(sample_data, sample_index)
|
||||
```
|
||||
|
||||
Values of both samples are in the `sample_data` column. If `sample_index` equals to 0 then the value in that row belongs to the sample from the first population. Otherwise it belongs to the sample from the second population.
|
||||
The null hypothesis is that means of populations are equal. Normal distribution with equal variances is assumed.
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `sample_data` — sample data. [Integer](../../../sql-reference/data-types/int-uint.md), [Float](../../../sql-reference/data-types/float.md) or [Decimal](../../../sql-reference/data-types/decimal.md).
|
||||
- `sample_index` — sample index. [Integer](../../../sql-reference/data-types/int-uint.md).
|
||||
|
||||
**Returned values**
|
||||
|
||||
[Tuple](../../../sql-reference/data-types/tuple.md) with two elements:
|
||||
- calculated t-statistic. [Float64](../../../sql-reference/data-types/float.md).
|
||||
- calculated p-value. [Float64](../../../sql-reference/data-types/float.md).
|
||||
|
||||
|
||||
**Example**
|
||||
|
||||
Input table:
|
||||
|
||||
``` text
|
||||
┌─sample_data─┬─sample_index─┐
|
||||
│ 20.3 │ 0 │
|
||||
│ 21.1 │ 0 │
|
||||
│ 21.9 │ 1 │
|
||||
│ 21.7 │ 0 │
|
||||
│ 19.9 │ 1 │
|
||||
│ 21.8 │ 1 │
|
||||
└─────────────┴──────────────┘
|
||||
```
|
||||
|
||||
Query:
|
||||
|
||||
``` sql
|
||||
SELECT studentTTest(sample_data, sample_index) FROM student_ttest;
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
┌─studentTTest(sample_data, sample_index)───┐
|
||||
│ (-0.21739130434783777,0.8385421208415731) │
|
||||
└───────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
**See Also**
|
||||
|
||||
- [Student's t-test](https://en.wikipedia.org/wiki/Student%27s_t-test)
|
||||
- [welchTTest function](welchttest.md#welchttest)
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/sql-reference/aggregate-functions/reference/studentttest/) <!--hide-->
|
||||
@ -0,0 +1,65 @@
|
||||
---
|
||||
toc_priority: 301
|
||||
toc_title: welchTTest
|
||||
---
|
||||
|
||||
# welchTTest {#welchttest}
|
||||
|
||||
Applies Welch's t-test to samples from two populations.
|
||||
|
||||
**Syntax**
|
||||
|
||||
``` sql
|
||||
welchTTest(sample_data, sample_index)
|
||||
```
|
||||
|
||||
Values of both samples are in the `sample_data` column. If `sample_index` equals to 0 then the value in that row belongs to the sample from the first population. Otherwise it belongs to the sample from the second population.
|
||||
The null hypothesis is that means of populations are equal. Normal distribution is assumed. Populations may have unequal variance.
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `sample_data` — sample data. [Integer](../../../sql-reference/data-types/int-uint.md), [Float](../../../sql-reference/data-types/float.md) or [Decimal](../../../sql-reference/data-types/decimal.md).
|
||||
- `sample_index` — sample index. [Integer](../../../sql-reference/data-types/int-uint.md).
|
||||
|
||||
**Returned values**
|
||||
|
||||
[Tuple](../../../sql-reference/data-types/tuple.md) with two elements:
|
||||
- calculated t-statistic. [Float64](../../../sql-reference/data-types/float.md).
|
||||
- calculated p-value. [Float64](../../../sql-reference/data-types/float.md).
|
||||
|
||||
|
||||
**Example**
|
||||
|
||||
Input table:
|
||||
|
||||
``` text
|
||||
┌─sample_data─┬─sample_index─┐
|
||||
│ 20.3 │ 0 │
|
||||
│ 22.1 │ 0 │
|
||||
│ 21.9 │ 0 │
|
||||
│ 18.9 │ 1 │
|
||||
│ 20.3 │ 1 │
|
||||
│ 19 │ 1 │
|
||||
└─────────────┴──────────────┘
|
||||
```
|
||||
|
||||
Query:
|
||||
|
||||
``` sql
|
||||
SELECT welchTTest(sample_data, sample_index) FROM welch_ttest;
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
┌─welchTTest(sample_data, sample_index)─────┐
|
||||
│ (2.7988719532211235,0.051807360348581945) │
|
||||
└───────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
**See Also**
|
||||
|
||||
- [Welch's t-test](https://en.wikipedia.org/wiki/Welch%27s_t-test)
|
||||
- [studentTTest function](studentttest.md#studentttest)
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/sql-reference/aggregate-functions/reference/welchTTest/) <!--hide-->
|
||||
@ -45,6 +45,8 @@ SELECT [1, 2] AS x, toTypeName(x)
|
||||
|
||||
## Working with Data Types {#working-with-data-types}
|
||||
|
||||
The maximum size of an array is limited to one million elements.
|
||||
|
||||
When creating an array on the fly, ClickHouse automatically defines the argument type as the narrowest data type that can store all the listed arguments. If there are any [Nullable](../../sql-reference/data-types/nullable.md#data_type-nullable) or literal [NULL](../../sql-reference/syntax.md#null-literal) values, the type of an array element also becomes [Nullable](../../sql-reference/data-types/nullable.md).
|
||||
|
||||
If ClickHouse couldn’t determine the data type, it generates an exception. For instance, this happens when trying to create an array with strings and numbers simultaneously (`SELECT array(1, 'a')`).
|
||||
|
||||
@ -1288,73 +1288,226 @@ Returns the index of the first element in the `arr1` array for which `func` retu
|
||||
|
||||
Note that the `arrayFirstIndex` is a [higher-order function](../../sql-reference/functions/index.md#higher-order-functions). You must pass a lambda function to it as the first argument, and it can’t be omitted.
|
||||
|
||||
## arrayMin(\[func,\] arr1, …) {#array-min}
|
||||
## arrayMin {#array-min}
|
||||
|
||||
Returns the min of the `func` values. If the function is omitted, it just returns the min of the array elements.
|
||||
Returns the minimum of elements in the source array.
|
||||
|
||||
If the `func` function is specified, returns the mininum of elements converted by this function.
|
||||
|
||||
Note that the `arrayMin` is a [higher-order function](../../sql-reference/functions/index.md#higher-order-functions). You can pass a lambda function to it as the first argument.
|
||||
|
||||
Examples:
|
||||
**Syntax**
|
||||
|
||||
```sql
|
||||
SELECT arrayMin([1, 2, 4]) AS res
|
||||
arrayMin([func,] arr)
|
||||
```
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `func` — Function. [Expression](../../sql-reference/data-types/special-data-types/expression.md).
|
||||
- `arr` — Array. [Array](../../sql-reference/data-types/array.md).
|
||||
|
||||
**Returned value**
|
||||
|
||||
- The minimum of function values (or the array minimum).
|
||||
|
||||
Type: if `func` is specified, matches `func` return value type, else matches the array elements type.
|
||||
|
||||
**Examples**
|
||||
|
||||
Query:
|
||||
|
||||
```sql
|
||||
SELECT arrayMin([1, 2, 4]) AS res;
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
```text
|
||||
┌─res─┐
|
||||
│ 1 │
|
||||
└─────┘
|
||||
```
|
||||
|
||||
Query:
|
||||
|
||||
SELECT arrayMin(x -> (-x), [1, 2, 4]) AS res
|
||||
```sql
|
||||
SELECT arrayMin(x -> (-x), [1, 2, 4]) AS res;
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
```text
|
||||
┌─res─┐
|
||||
│ -4 │
|
||||
└─────┘
|
||||
```
|
||||
|
||||
## arrayMax(\[func,\] arr1, …) {#array-max}
|
||||
## arrayMax {#array-max}
|
||||
|
||||
Returns the max of the `func` values. If the function is omitted, it just returns the max of the array elements.
|
||||
Returns the maximum of elements in the source array.
|
||||
|
||||
If the `func` function is specified, returns the maximum of elements converted by this function.
|
||||
|
||||
Note that the `arrayMax` is a [higher-order function](../../sql-reference/functions/index.md#higher-order-functions). You can pass a lambda function to it as the first argument.
|
||||
|
||||
Examples:
|
||||
**Syntax**
|
||||
|
||||
```sql
|
||||
SELECT arrayMax([1, 2, 4]) AS res
|
||||
arrayMax([func,] arr)
|
||||
```
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `func` — Function. [Expression](../../sql-reference/data-types/special-data-types/expression.md).
|
||||
- `arr` — Array. [Array](../../sql-reference/data-types/array.md).
|
||||
|
||||
**Returned value**
|
||||
|
||||
- The maximum of function values (or the array maximum).
|
||||
|
||||
Type: if `func` is specified, matches `func` return value type, else matches the array elements type.
|
||||
|
||||
**Examples**
|
||||
|
||||
Query:
|
||||
|
||||
```sql
|
||||
SELECT arrayMax([1, 2, 4]) AS res;
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
```text
|
||||
┌─res─┐
|
||||
│ 4 │
|
||||
└─────┘
|
||||
```
|
||||
|
||||
Query:
|
||||
|
||||
SELECT arrayMax(x -> (-x), [1, 2, 4]) AS res
|
||||
```sql
|
||||
SELECT arrayMax(x -> (-x), [1, 2, 4]) AS res;
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
```text
|
||||
┌─res─┐
|
||||
│ -1 │
|
||||
└─────┘
|
||||
```
|
||||
|
||||
## arraySum(\[func,\] arr1, …) {#array-sum}
|
||||
## arraySum {#array-sum}
|
||||
|
||||
Returns the sum of the `func` values. If the function is omitted, it just returns the sum of the array elements.
|
||||
Returns the sum of elements in the source array.
|
||||
|
||||
If the `func` function is specified, returns the sum of elements converted by this function.
|
||||
|
||||
Note that the `arraySum` is a [higher-order function](../../sql-reference/functions/index.md#higher-order-functions). You can pass a lambda function to it as the first argument.
|
||||
|
||||
Examples:
|
||||
**Syntax**
|
||||
|
||||
```sql
|
||||
SELECT arraySum([2,3]) AS res
|
||||
arraySum([func,] arr)
|
||||
```
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `func` — Function. [Expression](../../sql-reference/data-types/special-data-types/expression.md).
|
||||
- `arr` — Array. [Array](../../sql-reference/data-types/array.md).
|
||||
|
||||
**Returned value**
|
||||
|
||||
- The sum of the function values (or the array sum).
|
||||
|
||||
Type: for decimal numbers in source array (or for converted values, if `func` is specified) — [Decimal128](../../sql-reference/data-types/decimal.md), for floating point numbers — [Float64](../../sql-reference/data-types/float.md), for numeric unsigned — [UInt64](../../sql-reference/data-types/int-uint.md), and for numeric signed — [Int64](../../sql-reference/data-types/int-uint.md).
|
||||
|
||||
**Examples**
|
||||
|
||||
Query:
|
||||
|
||||
```sql
|
||||
SELECT arraySum([2, 3]) AS res;
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
```text
|
||||
┌─res─┐
|
||||
│ 5 │
|
||||
└─────┘
|
||||
```
|
||||
|
||||
Query:
|
||||
|
||||
SELECT arraySum(x -> x*x, [2, 3]) AS res
|
||||
```sql
|
||||
SELECT arraySum(x -> x*x, [2, 3]) AS res;
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
```text
|
||||
┌─res─┐
|
||||
│ 13 │
|
||||
└─────┘
|
||||
```
|
||||
|
||||
## arrayAvg {#array-avg}
|
||||
|
||||
## arrayAvg(\[func,\] arr1, …) {#array-avg}
|
||||
Returns the average of elements in the source array.
|
||||
|
||||
Returns the average of the `func` values. If the function is omitted, it just returns the average of the array elements.
|
||||
If the `func` function is specified, returns the average of elements converted by this function.
|
||||
|
||||
Note that the `arrayAvg` is a [higher-order function](../../sql-reference/functions/index.md#higher-order-functions). You can pass a lambda function to it as the first argument.
|
||||
|
||||
**Syntax**
|
||||
|
||||
```sql
|
||||
arrayAvg([func,] arr)
|
||||
```
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `func` — Function. [Expression](../../sql-reference/data-types/special-data-types/expression.md).
|
||||
- `arr` — Array. [Array](../../sql-reference/data-types/array.md).
|
||||
|
||||
**Returned value**
|
||||
|
||||
- The average of function values (or the array average).
|
||||
|
||||
Type: [Float64](../../sql-reference/data-types/float.md).
|
||||
|
||||
**Examples**
|
||||
|
||||
Query:
|
||||
|
||||
```sql
|
||||
SELECT arrayAvg([1, 2, 4]) AS res;
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
```text
|
||||
┌────────────────res─┐
|
||||
│ 2.3333333333333335 │
|
||||
└────────────────────┘
|
||||
```
|
||||
|
||||
Query:
|
||||
|
||||
```sql
|
||||
SELECT arrayAvg(x -> (x * x), [2, 4]) AS res;
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
```text
|
||||
┌─res─┐
|
||||
│ 10 │
|
||||
└─────┘
|
||||
```
|
||||
|
||||
## arrayCumSum(\[func,\] arr1, …) {#arraycumsumfunc-arr1}
|
||||
|
||||
Returns an array of partial sums of elements in the source array (a running sum). If the `func` function is specified, then the values of the array elements are converted by this function before summing.
|
||||
|
||||
@ -380,7 +380,7 @@ Alias: `dateTrunc`.
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `unit` — Part of date. [String](../syntax.md#syntax-string-literal).
|
||||
- `unit` — The type of interval to truncate the result. [String Literal](../syntax.md#syntax-string-literal).
|
||||
Possible values:
|
||||
|
||||
- `second`
|
||||
@ -435,6 +435,201 @@ Result:
|
||||
|
||||
- [toStartOfInterval](#tostartofintervaltime-or-data-interval-x-unit-time-zone)
|
||||
|
||||
## date\_add {#date_add}
|
||||
|
||||
Adds specified date/time interval to the provided date.
|
||||
|
||||
**Syntax**
|
||||
|
||||
``` sql
|
||||
date_add(unit, value, date)
|
||||
```
|
||||
|
||||
Aliases: `dateAdd`, `DATE_ADD`.
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `unit` — The type of interval to add. [String](../../sql-reference/data-types/string.md).
|
||||
|
||||
Supported values: second, minute, hour, day, week, month, quarter, year.
|
||||
- `value` - Value in specified unit - [Int](../../sql-reference/data-types/int-uint.md)
|
||||
- `date` — [Date](../../sql-reference/data-types/date.md) or [DateTime](../../sql-reference/data-types/datetime.md).
|
||||
|
||||
|
||||
**Returned value**
|
||||
|
||||
Returns Date or DateTime with `value` expressed in `unit` added to `date`.
|
||||
|
||||
**Example**
|
||||
|
||||
```sql
|
||||
select date_add(YEAR, 3, toDate('2018-01-01'));
|
||||
```
|
||||
|
||||
```text
|
||||
┌─plus(toDate('2018-01-01'), toIntervalYear(3))─┐
|
||||
│ 2021-01-01 │
|
||||
└───────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
## date\_diff {#date_diff}
|
||||
|
||||
Returns the difference between two Date or DateTime values.
|
||||
|
||||
**Syntax**
|
||||
|
||||
``` sql
|
||||
date_diff('unit', startdate, enddate, [timezone])
|
||||
```
|
||||
|
||||
Aliases: `dateDiff`, `DATE_DIFF`.
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `unit` — The type of interval for result [String](../../sql-reference/data-types/string.md).
|
||||
|
||||
Supported values: second, minute, hour, day, week, month, quarter, year.
|
||||
|
||||
- `startdate` — The first time value to subtract (the subtrahend). [Date](../../sql-reference/data-types/date.md) or [DateTime](../../sql-reference/data-types/datetime.md).
|
||||
|
||||
- `enddate` — The second time value to subtract from (the minuend). [Date](../../sql-reference/data-types/date.md) or [DateTime](../../sql-reference/data-types/datetime.md).
|
||||
|
||||
- `timezone` — Optional parameter. If specified, it is applied to both `startdate` and `enddate`. If not specified, timezones of `startdate` and `enddate` are used. If they are not the same, the result is unspecified.
|
||||
|
||||
**Returned value**
|
||||
|
||||
Difference between `enddate` and `startdate` expressed in `unit`.
|
||||
|
||||
Type: `int`.
|
||||
|
||||
**Example**
|
||||
|
||||
Query:
|
||||
|
||||
``` sql
|
||||
SELECT dateDiff('hour', toDateTime('2018-01-01 22:00:00'), toDateTime('2018-01-02 23:00:00'));
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
┌─dateDiff('hour', toDateTime('2018-01-01 22:00:00'), toDateTime('2018-01-02 23:00:00'))─┐
|
||||
│ 25 │
|
||||
└────────────────────────────────────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
## date\_sub {#date_sub}
|
||||
|
||||
Subtracts a time/date interval from the provided date.
|
||||
|
||||
**Syntax**
|
||||
|
||||
``` sql
|
||||
date_sub(unit, value, date)
|
||||
```
|
||||
|
||||
Aliases: `dateSub`, `DATE_SUB`.
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `unit` — The type of interval to subtract. [String](../../sql-reference/data-types/string.md).
|
||||
|
||||
Supported values: second, minute, hour, day, week, month, quarter, year.
|
||||
- `value` - Value in specified unit - [Int](../../sql-reference/data-types/int-uint.md)
|
||||
- `date` — [Date](../../sql-reference/data-types/date.md) or [DateTime](../../sql-reference/data-types/datetime.md) to subtract value from.
|
||||
|
||||
**Returned value**
|
||||
|
||||
Returns Date or DateTime with `value` expressed in `unit` subtracted from `date`.
|
||||
|
||||
**Example**
|
||||
|
||||
Query:
|
||||
|
||||
``` sql
|
||||
SELECT date_sub(YEAR, 3, toDate('2018-01-01'));
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
┌─minus(toDate('2018-01-01'), toIntervalYear(3))─┐
|
||||
│ 2015-01-01 │
|
||||
└────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
## timestamp\_add {#timestamp_add}
|
||||
|
||||
Adds the specified time value with the provided date or date time value.
|
||||
|
||||
**Syntax**
|
||||
|
||||
``` sql
|
||||
timestamp_add(date, INTERVAL value unit)
|
||||
```
|
||||
|
||||
Aliases: `timeStampAdd`, `TIMESTAMP_ADD`.
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `date` — Date or Date with time - [Date](../../sql-reference/data-types/date.md) or [DateTime](../../sql-reference/data-types/datetime.md).
|
||||
- `value` - Value in specified unit - [Int](../../sql-reference/data-types/int-uint.md)
|
||||
- `unit` — The type of interval to add. [String](../../sql-reference/data-types/string.md).
|
||||
|
||||
Supported values: second, minute, hour, day, week, month, quarter, year.
|
||||
|
||||
**Returned value**
|
||||
|
||||
Returns Date or DateTime with the specified `value` expressed in `unit` added to `date`.
|
||||
|
||||
**Example**
|
||||
|
||||
```sql
|
||||
select timestamp_add(toDate('2018-01-01'), INTERVAL 3 MONTH);
|
||||
```
|
||||
|
||||
```text
|
||||
┌─plus(toDate('2018-01-01'), toIntervalMonth(3))─┐
|
||||
│ 2018-04-01 │
|
||||
└────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
## timestamp\_sub {#timestamp_sub}
|
||||
|
||||
Returns the difference between two dates in the specified unit.
|
||||
|
||||
**Syntax**
|
||||
|
||||
``` sql
|
||||
timestamp_sub(unit, value, date)
|
||||
```
|
||||
|
||||
Aliases: `timeStampSub`, `TIMESTAMP_SUB`.
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `unit` — The type of interval to add. [String](../../sql-reference/data-types/string.md).
|
||||
|
||||
Supported values: second, minute, hour, day, week, month, quarter, year.
|
||||
- `value` - Value in specified unit - [Int](../../sql-reference/data-types/int-uint.md).
|
||||
- `date`- [Date](../../sql-reference/data-types/date.md) or [DateTime](../../sql-reference/data-types/datetime.md).
|
||||
|
||||
**Returned value**
|
||||
|
||||
Difference between `date` and the specified `value` expressed in `unit`.
|
||||
|
||||
**Example**
|
||||
|
||||
```sql
|
||||
select timestamp_sub(MONTH, 5, toDateTime('2018-12-18 01:02:03'));
|
||||
```
|
||||
|
||||
```text
|
||||
┌─minus(toDateTime('2018-12-18 01:02:03'), toIntervalMonth(5))─┐
|
||||
│ 2018-07-18 01:02:03 │
|
||||
└──────────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
## now {#now}
|
||||
|
||||
Returns the current date and time.
|
||||
@ -550,50 +745,6 @@ SELECT
|
||||
└──────────────────────────┴───────────────────────────────┘
|
||||
```
|
||||
|
||||
## dateDiff {#datediff}
|
||||
|
||||
Returns the difference between two Date or DateTime values.
|
||||
|
||||
**Syntax**
|
||||
|
||||
``` sql
|
||||
dateDiff('unit', startdate, enddate, [timezone])
|
||||
```
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `unit` — Time unit, in which the returned value is expressed. [String](../../sql-reference/syntax.md#syntax-string-literal).
|
||||
|
||||
Supported values: second, minute, hour, day, week, month, quarter, year.
|
||||
|
||||
- `startdate` — The first time value to compare. [Date](../../sql-reference/data-types/date.md) or [DateTime](../../sql-reference/data-types/datetime.md).
|
||||
|
||||
- `enddate` — The second time value to compare. [Date](../../sql-reference/data-types/date.md) or [DateTime](../../sql-reference/data-types/datetime.md).
|
||||
|
||||
- `timezone` — Optional parameter. If specified, it is applied to both `startdate` and `enddate`. If not specified, timezones of `startdate` and `enddate` are used. If they are not the same, the result is unspecified.
|
||||
|
||||
**Returned value**
|
||||
|
||||
Difference between `startdate` and `enddate` expressed in `unit`.
|
||||
|
||||
Type: `int`.
|
||||
|
||||
**Example**
|
||||
|
||||
Query:
|
||||
|
||||
``` sql
|
||||
SELECT dateDiff('hour', toDateTime('2018-01-01 22:00:00'), toDateTime('2018-01-02 23:00:00'));
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
┌─dateDiff('hour', toDateTime('2018-01-01 22:00:00'), toDateTime('2018-01-02 23:00:00'))─┐
|
||||
│ 25 │
|
||||
└────────────────────────────────────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
## timeSlots(StartTime, Duration,\[, Size\]) {#timeslotsstarttime-duration-size}
|
||||
|
||||
For a time interval starting at ‘StartTime’ and continuing for ‘Duration’ seconds, it returns an array of moments in time, consisting of points from this interval rounded down to the ‘Size’ in seconds. ‘Size’ is an optional parameter: a constant UInt32, set to 1800 by default.
|
||||
|
||||
@ -182,13 +182,102 @@ If `NULL` is passed to the function as input, then it returns the `Nullable(Noth
|
||||
Gets the size of the block.
|
||||
In ClickHouse, queries are always run on blocks (sets of column parts). This function allows getting the size of the block that you called it for.
|
||||
|
||||
## byteSize(...) {#function-bytesize}
|
||||
## byteSize {#function-bytesize}
|
||||
|
||||
Get an estimate of uncompressed byte size of its arguments in memory.
|
||||
E.g. for UInt32 argument it will return constant 4, for String argument - the string length + 9 (terminating zero + length).
|
||||
The function can take multiple arguments. The typical application is byteSize(*).
|
||||
Returns estimation of uncompressed byte size of its arguments in memory.
|
||||
|
||||
Use case: Suppose you have a service that stores data for multiple clients in one table. Users will pay per data volume. So, you need to implement accounting of users data volume. The function will allow to calculate the data size on per-row basis.
|
||||
**Syntax**
|
||||
|
||||
```sql
|
||||
byteSize(argument [, ...])
|
||||
```
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `argument` — Value.
|
||||
|
||||
**Returned value**
|
||||
|
||||
- Estimation of byte size of the arguments in memory.
|
||||
|
||||
Type: [UInt64](../../sql-reference/data-types/int-uint.md).
|
||||
|
||||
**Examples**
|
||||
|
||||
For [String](../../sql-reference/data-types/string.md) arguments the funtion returns the string length + 9 (terminating zero + length).
|
||||
|
||||
Query:
|
||||
|
||||
```sql
|
||||
SELECT byteSize('string');
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
```text
|
||||
┌─byteSize('string')─┐
|
||||
│ 15 │
|
||||
└────────────────────┘
|
||||
```
|
||||
|
||||
Query:
|
||||
|
||||
```sql
|
||||
CREATE TABLE test
|
||||
(
|
||||
`key` Int32,
|
||||
`u8` UInt8,
|
||||
`u16` UInt16,
|
||||
`u32` UInt32,
|
||||
`u64` UInt64,
|
||||
`i8` Int8,
|
||||
`i16` Int16,
|
||||
`i32` Int32,
|
||||
`i64` Int64,
|
||||
`f32` Float32,
|
||||
`f64` Float64
|
||||
)
|
||||
ENGINE = MergeTree
|
||||
ORDER BY key;
|
||||
|
||||
INSERT INTO test VALUES(1, 8, 16, 32, 64, -8, -16, -32, -64, 32.32, 64.64);
|
||||
|
||||
SELECT key, byteSize(u8) AS `byteSize(UInt8)`, byteSize(u16) AS `byteSize(UInt16)`, byteSize(u32) AS `byteSize(UInt32)`, byteSize(u64) AS `byteSize(UInt64)`, byteSize(i8) AS `byteSize(Int8)`, byteSize(i16) AS `byteSize(Int16)`, byteSize(i32) AS `byteSize(Int32)`, byteSize(i64) AS `byteSize(Int64)`, byteSize(f32) AS `byteSize(Float32)`, byteSize(f64) AS `byteSize(Float64)` FROM test ORDER BY key ASC FORMAT Vertical;
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
Row 1:
|
||||
──────
|
||||
key: 1
|
||||
byteSize(UInt8): 1
|
||||
byteSize(UInt16): 2
|
||||
byteSize(UInt32): 4
|
||||
byteSize(UInt64): 8
|
||||
byteSize(Int8): 1
|
||||
byteSize(Int16): 2
|
||||
byteSize(Int32): 4
|
||||
byteSize(Int64): 8
|
||||
byteSize(Float32): 4
|
||||
byteSize(Float64): 8
|
||||
```
|
||||
|
||||
If the function takes multiple arguments, it returns their combined byte size.
|
||||
|
||||
Query:
|
||||
|
||||
```sql
|
||||
SELECT byteSize(NULL, 1, 0.3, '');
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
```text
|
||||
┌─byteSize(NULL, 1, 0.3, '')─┐
|
||||
│ 19 │
|
||||
└────────────────────────────┘
|
||||
```
|
||||
|
||||
## materialize(x) {#materializex}
|
||||
|
||||
|
||||
@ -14,8 +14,6 @@ The search is case-sensitive by default in all these functions. There are separa
|
||||
|
||||
Returns the position (in bytes) of the found substring in the string, starting from 1.
|
||||
|
||||
Works under the assumption that the string contains a set of bytes representing a single-byte encoded text. If this assumption is not met and a character can’t be represented using a single byte, the function doesn’t throw an exception and returns some unexpected result. If character can be represented using two bytes, it will use two bytes and so on.
|
||||
|
||||
For a case-insensitive search, use the function [positionCaseInsensitive](#positioncaseinsensitive).
|
||||
|
||||
**Syntax**
|
||||
|
||||
@ -5,7 +5,7 @@ toc_title: QUOTA
|
||||
|
||||
# ALTER QUOTA {#alter-quota-statement}
|
||||
|
||||
Changes [quotas](../../../operations/access-rights.md#quotas-management).
|
||||
Changes quotas.
|
||||
|
||||
Syntax:
|
||||
|
||||
@ -14,13 +14,13 @@ ALTER QUOTA [IF EXISTS] name [ON CLUSTER cluster_name]
|
||||
[RENAME TO new_name]
|
||||
[KEYED BY {user_name | ip_address | client_key | client_key,user_name | client_key,ip_address} | NOT KEYED]
|
||||
[FOR [RANDOMIZED] INTERVAL number {second | minute | hour | day | week | month | quarter | year}
|
||||
{MAX { {queries | errors | result_rows | result_bytes | read_rows | read_bytes | execution_time} = number } [,...] |
|
||||
{MAX { {queries | query_selects | query_inserts | errors | result_rows | result_bytes | read_rows | read_bytes | execution_time} = number } [,...] |
|
||||
NO LIMITS | TRACKING ONLY} [,...]]
|
||||
[TO {role [,...] | ALL | ALL EXCEPT role [,...]}]
|
||||
```
|
||||
Keys `user_name`, `ip_address`, `client_key`, `client_key, user_name` and `client_key, ip_address` correspond to the fields in the [system.quotas](../../../operations/system-tables/quotas.md) table.
|
||||
|
||||
Parameters `queries`, `errors`, `result_rows`, `result_bytes`, `read_rows`, `read_bytes`, `execution_time` correspond to the fields in the [system.quotas_usage](../../../operations/system-tables/quotas_usage.md) table.
|
||||
Parameters `queries`, `query_selects`, 'query_inserts', errors`, `result_rows`, `result_bytes`, `read_rows`, `read_bytes`, `execution_time` correspond to the fields in the [system.quotas_usage](../../../operations/system-tables/quotas_usage.md) table.
|
||||
|
||||
`ON CLUSTER` clause allows creating quotas on a cluster, see [Distributed DDL](../../../sql-reference/distributed-ddl.md).
|
||||
|
||||
|
||||
@ -13,14 +13,14 @@ Syntax:
|
||||
CREATE QUOTA [IF NOT EXISTS | OR REPLACE] name [ON CLUSTER cluster_name]
|
||||
[KEYED BY {user_name | ip_address | client_key | client_key,user_name | client_key,ip_address} | NOT KEYED]
|
||||
[FOR [RANDOMIZED] INTERVAL number {second | minute | hour | day | week | month | quarter | year}
|
||||
{MAX { {queries | errors | result_rows | result_bytes | read_rows | read_bytes | execution_time} = number } [,...] |
|
||||
{MAX { {queries | query_selects | query_inserts | errors | result_rows | result_bytes | read_rows | read_bytes | execution_time} = number } [,...] |
|
||||
NO LIMITS | TRACKING ONLY} [,...]]
|
||||
[TO {role [,...] | ALL | ALL EXCEPT role [,...]}]
|
||||
```
|
||||
|
||||
Keys `user_name`, `ip_address`, `client_key`, `client_key, user_name` and `client_key, ip_address` correspond to the fields in the [system.quotas](../../../operations/system-tables/quotas.md) table.
|
||||
Keys `user_name`, `ip_address`, `client_key`, `client_key, user_name` and `client_key, ip_address` correspond to the fields in the [system.quotas](../../../operations/system-tables/quotas.md) table.
|
||||
|
||||
Parameters `queries`, `errors`, `result_rows`, `result_bytes`, `read_rows`, `read_bytes`, `execution_time` correspond to the fields in the [system.quotas_usage](../../../operations/system-tables/quotas_usage.md) table.
|
||||
Parameters `queries`, `query_selects`, `query_inserts`, `errors`, `result_rows`, `result_bytes`, `read_rows`, `read_bytes`, `execution_time` correspond to the fields in the [system.quotas_usage](../../../operations/system-tables/quotas_usage.md) table.
|
||||
|
||||
`ON CLUSTER` clause allows creating quotas on a cluster, see [Distributed DDL](../../../sql-reference/distributed-ddl.md).
|
||||
|
||||
|
||||
42
docs/en/sql-reference/window-functions/index.md
Normal file
42
docs/en/sql-reference/window-functions/index.md
Normal file
@ -0,0 +1,42 @@
|
||||
---
|
||||
toc_priority: 62
|
||||
toc_title: Window Functions
|
||||
---
|
||||
|
||||
# [experimental] Window Functions
|
||||
|
||||
!!! warning "Warning"
|
||||
This is an experimental feature that is currently in development and is not ready
|
||||
for general use. It will change in unpredictable backwards-incompatible ways in
|
||||
the future releases. Set `allow_experimental_window_functions = 1` to enable it.
|
||||
|
||||
ClickHouse currently supports calculation of aggregate functions over a window.
|
||||
Pure window functions such as `rank`, `lag`, `lead` and so on are not yet supported.
|
||||
|
||||
The window can be specified either with an `OVER` clause or with a separate
|
||||
`WINDOW` clause.
|
||||
|
||||
Only two variants of frame are supported, `ROWS` and `RANGE`. Offsets for the `RANGE` frame are not yet supported.
|
||||
|
||||
## References
|
||||
|
||||
### GitHub Issues
|
||||
The roadmap for the initial support of window functions is [in this issue](https://github.com/ClickHouse/ClickHouse/issues/18097).
|
||||
|
||||
All GitHub issues related to window funtions have the [comp-window-functions](https://github.com/ClickHouse/ClickHouse/labels/comp-window-functions) tag.
|
||||
|
||||
### Tests
|
||||
These tests contain the examples of the currently supported grammar:
|
||||
https://github.com/ClickHouse/ClickHouse/blob/master/tests/performance/window_functions.xml
|
||||
https://github.com/ClickHouse/ClickHouse/blob/master/tests/queries/0_stateless/01591_window_functions.sql
|
||||
|
||||
### Postgres Docs
|
||||
https://www.postgresql.org/docs/current/sql-select.html#SQL-WINDOW
|
||||
https://www.postgresql.org/docs/devel/sql-expressions.html#SYNTAX-WINDOW-FUNCTIONS
|
||||
https://www.postgresql.org/docs/devel/functions-window.html
|
||||
https://www.postgresql.org/docs/devel/tutorial-window.html
|
||||
|
||||
### MySQL Docs
|
||||
https://dev.mysql.com/doc/refman/8.0/en/window-function-descriptions.html
|
||||
https://dev.mysql.com/doc/refman/8.0/en/window-functions-usage.html
|
||||
https://dev.mysql.com/doc/refman/8.0/en/window-functions-frames.html
|
||||
@ -5,6 +5,22 @@ toc_title: '2020'
|
||||
|
||||
### ClickHouse release 20.12
|
||||
|
||||
### ClickHouse release v20.12.5.14-stable, 2020-12-28
|
||||
|
||||
#### Bug Fix
|
||||
|
||||
* Disable write with AIO during merges because it can lead to extremely rare data corruption of primary key columns during merge. [#18481](https://github.com/ClickHouse/ClickHouse/pull/18481) ([alesapin](https://github.com/alesapin)).
|
||||
* Fixed `value is too short` error when executing `toType(...)` functions (`toDate`, `toUInt32`, etc) with argument of type `Nullable(String)`. Now such functions return `NULL` on parsing errors instead of throwing exception. Fixes [#7673](https://github.com/ClickHouse/ClickHouse/issues/7673). [#18445](https://github.com/ClickHouse/ClickHouse/pull/18445) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Restrict merges from wide to compact parts. In case of vertical merge it led to broken result part. [#18381](https://github.com/ClickHouse/ClickHouse/pull/18381) ([Anton Popov](https://github.com/CurtizJ)).
|
||||
* Fix filling table `system.settings_profile_elements`. This PR fixes [#18231](https://github.com/ClickHouse/ClickHouse/issues/18231). [#18379](https://github.com/ClickHouse/ClickHouse/pull/18379) ([Vitaly Baranov](https://github.com/vitlibar)).
|
||||
* Fix possible crashes in aggregate functions with combinator `Distinct`, while using two-level aggregation. Fixes [#17682](https://github.com/ClickHouse/ClickHouse/issues/17682). [#18365](https://github.com/ClickHouse/ClickHouse/pull/18365) ([Anton Popov](https://github.com/CurtizJ)).
|
||||
* Fix error when query `MODIFY COLUMN ... REMOVE TTL` doesn't actually remove column TTL. [#18130](https://github.com/ClickHouse/ClickHouse/pull/18130) ([alesapin](https://github.com/alesapin)).
|
||||
|
||||
#### Build/Testing/Packaging Improvement
|
||||
|
||||
* Update timezones info to 2020e. [#18531](https://github.com/ClickHouse/ClickHouse/pull/18531) ([alesapin](https://github.com/alesapin)).
|
||||
|
||||
|
||||
### ClickHouse release v20.12.4.5-stable, 2020-12-24
|
||||
|
||||
#### Bug Fix
|
||||
@ -142,6 +158,70 @@ toc_title: '2020'
|
||||
|
||||
## ClickHouse release 20.11
|
||||
|
||||
### ClickHouse release v20.11.7.16-stable, 2021-03-02
|
||||
|
||||
#### Improvement
|
||||
|
||||
* Explicitly set uid / gid of clickhouse user & group to the fixed values (101) in clickhouse-server images. [#19096](https://github.com/ClickHouse/ClickHouse/pull/19096) ([filimonov](https://github.com/filimonov)).
|
||||
|
||||
#### Bug Fix
|
||||
|
||||
* BloomFilter index crash fix. Fixes [#19757](https://github.com/ClickHouse/ClickHouse/issues/19757). [#19884](https://github.com/ClickHouse/ClickHouse/pull/19884) ([Maksim Kita](https://github.com/kitaisreal)).
|
||||
* Deadlock was possible if system.text_log is enabled. This fixes [#19874](https://github.com/ClickHouse/ClickHouse/issues/19874). [#19875](https://github.com/ClickHouse/ClickHouse/pull/19875) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* In previous versions, unusual arguments for function arrayEnumerateUniq may cause crash or infinite loop. This closes [#19787](https://github.com/ClickHouse/ClickHouse/issues/19787). [#19788](https://github.com/ClickHouse/ClickHouse/pull/19788) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fixed stack overflow when using accurate comparison of arithmetic type with string type. [#19773](https://github.com/ClickHouse/ClickHouse/pull/19773) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Fix a segmentation fault in `bitmapAndnot` function. Fixes [#19668](https://github.com/ClickHouse/ClickHouse/issues/19668). [#19713](https://github.com/ClickHouse/ClickHouse/pull/19713) ([Maksim Kita](https://github.com/kitaisreal)).
|
||||
* Some functions with big integers may cause segfault. Big integers is experimental feature. This closes [#19667](https://github.com/ClickHouse/ClickHouse/issues/19667). [#19672](https://github.com/ClickHouse/ClickHouse/pull/19672) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fix wrong result of function `neighbor` for `LowCardinality` argument. Fixes [#10333](https://github.com/ClickHouse/ClickHouse/issues/10333). [#19617](https://github.com/ClickHouse/ClickHouse/pull/19617) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Fix use-after-free of the CompressedWriteBuffer in Connection after disconnect. [#19599](https://github.com/ClickHouse/ClickHouse/pull/19599) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* `DROP/DETACH TABLE table ON CLUSTER cluster SYNC` query might hang, it's fixed. Fixes [#19568](https://github.com/ClickHouse/ClickHouse/issues/19568). [#19572](https://github.com/ClickHouse/ClickHouse/pull/19572) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Query CREATE DICTIONARY id expression fix. [#19571](https://github.com/ClickHouse/ClickHouse/pull/19571) ([Maksim Kita](https://github.com/kitaisreal)).
|
||||
* Fix SIGSEGV with merge_tree_min_rows_for_concurrent_read/merge_tree_min_bytes_for_concurrent_read=0/UINT64_MAX. [#19528](https://github.com/ClickHouse/ClickHouse/pull/19528) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* Buffer overflow (on memory read) was possible if `addMonth` function was called with specifically crafted arguments. This fixes [#19441](https://github.com/ClickHouse/ClickHouse/issues/19441). This fixes [#19413](https://github.com/ClickHouse/ClickHouse/issues/19413). [#19472](https://github.com/ClickHouse/ClickHouse/pull/19472) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Mark distributed batch as broken in case of empty data block in one of files. [#19449](https://github.com/ClickHouse/ClickHouse/pull/19449) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* Fix possible buffer overflow in Uber H3 library. See https://github.com/uber/h3/issues/392. This closes [#19219](https://github.com/ClickHouse/ClickHouse/issues/19219). [#19383](https://github.com/ClickHouse/ClickHouse/pull/19383) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fix system.parts _state column (LOGICAL_ERROR when querying this column, due to incorrect order). [#19346](https://github.com/ClickHouse/ClickHouse/pull/19346) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* Fix error `Cannot convert column now64() because it is constant but values of constants are different in source and result`. Continuation of [#7156](https://github.com/ClickHouse/ClickHouse/issues/7156). [#19316](https://github.com/ClickHouse/ClickHouse/pull/19316) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Fix bug when concurrent `ALTER` and `DROP` queries may hang while processing ReplicatedMergeTree table. [#19237](https://github.com/ClickHouse/ClickHouse/pull/19237) ([alesapin](https://github.com/alesapin)).
|
||||
* Fix infinite reading from file in `ORC` format (was introduced in [#10580](https://github.com/ClickHouse/ClickHouse/issues/10580)). Fixes [#19095](https://github.com/ClickHouse/ClickHouse/issues/19095). [#19134](https://github.com/ClickHouse/ClickHouse/pull/19134) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Fix startup bug when clickhouse was not able to read compression codec from `LowCardinality(Nullable(...))` and throws exception `Attempt to read after EOF`. Fixes [#18340](https://github.com/ClickHouse/ClickHouse/issues/18340). [#19101](https://github.com/ClickHouse/ClickHouse/pull/19101) ([alesapin](https://github.com/alesapin)).
|
||||
* Fixed `There is no checkpoint` error when inserting data through http interface using `Template` or `CustomSeparated` format. Fixes [#19021](https://github.com/ClickHouse/ClickHouse/issues/19021). [#19072](https://github.com/ClickHouse/ClickHouse/pull/19072) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Restrict `MODIFY TTL` queries for `MergeTree` tables created in old syntax. Previously the query succeeded, but actually it had no effect. [#19064](https://github.com/ClickHouse/ClickHouse/pull/19064) ([Anton Popov](https://github.com/CurtizJ)).
|
||||
* Make sure `groupUniqArray` returns correct type for argument of Enum type. This closes [#17875](https://github.com/ClickHouse/ClickHouse/issues/17875). [#19019](https://github.com/ClickHouse/ClickHouse/pull/19019) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fix possible error `Expected single dictionary argument for function` if use function `ignore` with `LowCardinality` argument. Fixes [#14275](https://github.com/ClickHouse/ClickHouse/issues/14275). [#19016](https://github.com/ClickHouse/ClickHouse/pull/19016) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Fix inserting of `LowCardinality` column to table with `TinyLog` engine. Fixes [#18629](https://github.com/ClickHouse/ClickHouse/issues/18629). [#19010](https://github.com/ClickHouse/ClickHouse/pull/19010) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Disable `optimize_move_functions_out_of_any` because optimization is not always correct. This closes [#18051](https://github.com/ClickHouse/ClickHouse/issues/18051). This closes [#18973](https://github.com/ClickHouse/ClickHouse/issues/18973). [#18981](https://github.com/ClickHouse/ClickHouse/pull/18981) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fixed very rare deadlock at shutdown. [#18977](https://github.com/ClickHouse/ClickHouse/pull/18977) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Fix bug when mutation with some escaped text (like `ALTER ... UPDATE e = CAST('foo', 'Enum8(\'foo\' = 1')` serialized incorrectly. Fixes [#18878](https://github.com/ClickHouse/ClickHouse/issues/18878). [#18944](https://github.com/ClickHouse/ClickHouse/pull/18944) ([alesapin](https://github.com/alesapin)).
|
||||
* Attach partition should reset the mutation. [#18804](https://github.com/ClickHouse/ClickHouse/issues/18804). [#18935](https://github.com/ClickHouse/ClickHouse/pull/18935) ([fastio](https://github.com/fastio)).
|
||||
* Fix possible hang at shutdown in clickhouse-local. This fixes [#18891](https://github.com/ClickHouse/ClickHouse/issues/18891). [#18893](https://github.com/ClickHouse/ClickHouse/pull/18893) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fix *If combinator with unary function and Nullable types. [#18806](https://github.com/ClickHouse/ClickHouse/pull/18806) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* Asynchronous distributed INSERTs can be rejected by the server if the setting `network_compression_method` is globally set to non-default value. This fixes [#18741](https://github.com/ClickHouse/ClickHouse/issues/18741). [#18776](https://github.com/ClickHouse/ClickHouse/pull/18776) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fixed `Attempt to read after eof` error when trying to `CAST` `NULL` from `Nullable(String)` to `Nullable(Decimal(P, S))`. Now function `CAST` returns `NULL` when it cannot parse decimal from nullable string. Fixes [#7690](https://github.com/ClickHouse/ClickHouse/issues/7690). [#18718](https://github.com/ClickHouse/ClickHouse/pull/18718) ([Winter Zhang](https://github.com/zhang2014)).
|
||||
* Fix Logger with unmatched arg size. [#18717](https://github.com/ClickHouse/ClickHouse/pull/18717) ([sundyli](https://github.com/sundy-li)).
|
||||
* Add FixedString Data type support. I'll get this exception "Code: 50, e.displayText() = DB::Exception: Unsupported type FixedString(1)" when replicating data from MySQL to ClickHouse. This patch fixes bug [#18450](https://github.com/ClickHouse/ClickHouse/issues/18450) Also fixes [#6556](https://github.com/ClickHouse/ClickHouse/issues/6556). [#18553](https://github.com/ClickHouse/ClickHouse/pull/18553) ([awesomeleo](https://github.com/awesomeleo)).
|
||||
* Fix possible `Pipeline stuck` error while using `ORDER BY` after subquery with `RIGHT` or `FULL` join. [#18550](https://github.com/ClickHouse/ClickHouse/pull/18550) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Fix bug which may lead to `ALTER` queries hung after corresponding mutation kill. Found by thread fuzzer. [#18518](https://github.com/ClickHouse/ClickHouse/pull/18518) ([alesapin](https://github.com/alesapin)).
|
||||
* Disable write with AIO during merges because it can lead to extremely rare data corruption of primary key columns during merge. [#18481](https://github.com/ClickHouse/ClickHouse/pull/18481) ([alesapin](https://github.com/alesapin)).
|
||||
* Disable constant folding for subqueries on the analysis stage, when the result cannot be calculated. [#18446](https://github.com/ClickHouse/ClickHouse/pull/18446) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* Fixed `value is too short` error when executing `toType(...)` functions (`toDate`, `toUInt32`, etc) with argument of type `Nullable(String)`. Now such functions return `NULL` on parsing errors instead of throwing exception. Fixes [#7673](https://github.com/ClickHouse/ClickHouse/issues/7673). [#18445](https://github.com/ClickHouse/ClickHouse/pull/18445) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Restrict merges from wide to compact parts. In case of vertical merge it led to broken result part. [#18381](https://github.com/ClickHouse/ClickHouse/pull/18381) ([Anton Popov](https://github.com/CurtizJ)).
|
||||
* Fix filling table `system.settings_profile_elements`. This PR fixes [#18231](https://github.com/ClickHouse/ClickHouse/issues/18231). [#18379](https://github.com/ClickHouse/ClickHouse/pull/18379) ([Vitaly Baranov](https://github.com/vitlibar)).
|
||||
* Fix index analysis of binary functions with constant argument which leads to wrong query results. This fixes [#18364](https://github.com/ClickHouse/ClickHouse/issues/18364). [#18373](https://github.com/ClickHouse/ClickHouse/pull/18373) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Fix possible crashes in aggregate functions with combinator `Distinct`, while using two-level aggregation. Fixes [#17682](https://github.com/ClickHouse/ClickHouse/issues/17682). [#18365](https://github.com/ClickHouse/ClickHouse/pull/18365) ([Anton Popov](https://github.com/CurtizJ)).
|
||||
* `SELECT count() FROM table` now can be executed if only one any column can be selected from the `table`. This PR fixes [#10639](https://github.com/ClickHouse/ClickHouse/issues/10639). [#18233](https://github.com/ClickHouse/ClickHouse/pull/18233) ([Vitaly Baranov](https://github.com/vitlibar)).
|
||||
* `SELECT JOIN` now requires the `SELECT` privilege on each of the joined tables. This PR fixes [#17654](https://github.com/ClickHouse/ClickHouse/issues/17654). [#18232](https://github.com/ClickHouse/ClickHouse/pull/18232) ([Vitaly Baranov](https://github.com/vitlibar)).
|
||||
* Fix possible incomplete query result while reading from `MergeTree*` in case of read backoff (message `<Debug> MergeTreeReadPool: Will lower number of threads` in logs). Was introduced in [#16423](https://github.com/ClickHouse/ClickHouse/issues/16423). Fixes [#18137](https://github.com/ClickHouse/ClickHouse/issues/18137). [#18216](https://github.com/ClickHouse/ClickHouse/pull/18216) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Fix error when query `MODIFY COLUMN ... REMOVE TTL` doesn't actually remove column TTL. [#18130](https://github.com/ClickHouse/ClickHouse/pull/18130) ([alesapin](https://github.com/alesapin)).
|
||||
* Fix indeterministic functions with predicate optimizer. This fixes [#17244](https://github.com/ClickHouse/ClickHouse/issues/17244). [#17273](https://github.com/ClickHouse/ClickHouse/pull/17273) ([Winter Zhang](https://github.com/zhang2014)).
|
||||
* Mutation might hang waiting for some non-existent part after `MOVE` or `REPLACE PARTITION` or, in rare cases, after `DETACH` or `DROP PARTITION`. It's fixed. [#15537](https://github.com/ClickHouse/ClickHouse/pull/15537) ([tavplubix](https://github.com/tavplubix)).
|
||||
|
||||
#### Build/Testing/Packaging Improvement
|
||||
|
||||
* Update timezones info to 2020e. [#18531](https://github.com/ClickHouse/ClickHouse/pull/18531) ([alesapin](https://github.com/alesapin)).
|
||||
|
||||
|
||||
|
||||
### ClickHouse release v20.11.6.6-stable, 2020-12-24
|
||||
|
||||
#### Bug Fix
|
||||
@ -588,6 +668,60 @@ toc_title: '2020'
|
||||
|
||||
## ClickHouse release 20.9
|
||||
|
||||
### ClickHouse release v20.9.7.11-stable, 2020-12-07
|
||||
|
||||
#### Performance Improvement
|
||||
|
||||
* Fix performance of reading from `Merge` tables over huge number of `MergeTree` tables. Fixes [#7748](https://github.com/ClickHouse/ClickHouse/issues/7748). [#16988](https://github.com/ClickHouse/ClickHouse/pull/16988) ([Anton Popov](https://github.com/CurtizJ)).
|
||||
|
||||
#### Bug Fix
|
||||
|
||||
* Do not restore parts from WAL if `in_memory_parts_enable_wal` is disabled. [#17802](https://github.com/ClickHouse/ClickHouse/pull/17802) ([detailyang](https://github.com/detailyang)).
|
||||
* Fixed segfault when there is not enough space when inserting into `Distributed` table. [#17737](https://github.com/ClickHouse/ClickHouse/pull/17737) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Fixed problem when ClickHouse fails to resume connection to MySQL servers. [#17681](https://github.com/ClickHouse/ClickHouse/pull/17681) ([Alexander Kazakov](https://github.com/Akazz)).
|
||||
* Fixed `Function not implemented` error when executing `RENAME` query in `Atomic` database with ClickHouse running on Windows Subsystem for Linux. Fixes [#17661](https://github.com/ClickHouse/ClickHouse/issues/17661). [#17664](https://github.com/ClickHouse/ClickHouse/pull/17664) ([tavplubix](https://github.com/tavplubix)).
|
||||
* When clickhouse-client is used in interactive mode with multiline queries, single line comment was erronously extended till the end of query. This fixes [#13654](https://github.com/ClickHouse/ClickHouse/issues/13654). [#17565](https://github.com/ClickHouse/ClickHouse/pull/17565) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fix the issue when server can stop accepting connections in very rare cases. [#17542](https://github.com/ClickHouse/ClickHouse/pull/17542) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fix alter query hang when the corresponding mutation was killed on the different replica. Fixes [#16953](https://github.com/ClickHouse/ClickHouse/issues/16953). [#17499](https://github.com/ClickHouse/ClickHouse/pull/17499) ([alesapin](https://github.com/alesapin)).
|
||||
* Fix bug when mark cache size was underestimated by clickhouse. It may happen when there are a lot of tiny files with marks. [#17496](https://github.com/ClickHouse/ClickHouse/pull/17496) ([alesapin](https://github.com/alesapin)).
|
||||
* Fix `ORDER BY` with enabled setting `optimize_redundant_functions_in_order_by`. [#17471](https://github.com/ClickHouse/ClickHouse/pull/17471) ([Anton Popov](https://github.com/CurtizJ)).
|
||||
* Fix duplicates after `DISTINCT` which were possible because of incorrect optimization. Fixes [#17294](https://github.com/ClickHouse/ClickHouse/issues/17294). [#17296](https://github.com/ClickHouse/ClickHouse/pull/17296) ([li chengxiang](https://github.com/chengxianglibra)). [#17439](https://github.com/ClickHouse/ClickHouse/pull/17439) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Fix crash while reading from `JOIN` table with `LowCardinality` types. Fixes [#17228](https://github.com/ClickHouse/ClickHouse/issues/17228). [#17397](https://github.com/ClickHouse/ClickHouse/pull/17397) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Fix set index invalidation when there are const columns in the subquery. This fixes [#17246](https://github.com/ClickHouse/ClickHouse/issues/17246) . [#17249](https://github.com/ClickHouse/ClickHouse/pull/17249) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Fix ColumnConst comparison which leads to crash. This fixed [#17088](https://github.com/ClickHouse/ClickHouse/issues/17088) . [#17135](https://github.com/ClickHouse/ClickHouse/pull/17135) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Fixed crash on `CREATE TABLE ... AS some_table` query when `some_table` was created `AS table_function()` Fixes [#16944](https://github.com/ClickHouse/ClickHouse/issues/16944). [#17072](https://github.com/ClickHouse/ClickHouse/pull/17072) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Bug fix for funciton fuzzBits, related issue: [#16980](https://github.com/ClickHouse/ClickHouse/issues/16980). [#17051](https://github.com/ClickHouse/ClickHouse/pull/17051) ([hexiaoting](https://github.com/hexiaoting)).
|
||||
* Avoid unnecessary network errors for remote queries which may be cancelled while execution, like queries with `LIMIT`. [#17006](https://github.com/ClickHouse/ClickHouse/pull/17006) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* TODO. [#16866](https://github.com/ClickHouse/ClickHouse/pull/16866) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Return number of affected rows for INSERT queries via MySQL protocol. Previously ClickHouse used to always return 0, it's fixed. Fixes [#16605](https://github.com/ClickHouse/ClickHouse/issues/16605). [#16715](https://github.com/ClickHouse/ClickHouse/pull/16715) ([Winter Zhang](https://github.com/zhang2014)).
|
||||
|
||||
#### Build/Testing/Packaging Improvement
|
||||
|
||||
* Update embedded timezone data to version 2020d (also update cctz to the latest master). [#17204](https://github.com/ClickHouse/ClickHouse/pull/17204) ([filimonov](https://github.com/filimonov)).
|
||||
|
||||
|
||||
### ClickHouse release v20.9.6.14-stable, 2020-11-20
|
||||
|
||||
#### Improvement
|
||||
|
||||
* Make it possible to connect to `clickhouse-server` secure endpoint which requires SNI. This is possible when `clickhouse-server` is hosted behind TLS proxy. [#16938](https://github.com/ClickHouse/ClickHouse/pull/16938) ([filimonov](https://github.com/filimonov)).
|
||||
* Conditional aggregate functions (for example: `avgIf`, `sumIf`, `maxIf`) should return `NULL` when miss rows and use nullable arguments. [#13964](https://github.com/ClickHouse/ClickHouse/pull/13964) ([Winter Zhang](https://github.com/zhang2014)).
|
||||
|
||||
#### Bug Fix
|
||||
|
||||
* Fix bug when `ON CLUSTER` queries may hang forever for non-leader ReplicatedMergeTreeTables. [#17089](https://github.com/ClickHouse/ClickHouse/pull/17089) ([alesapin](https://github.com/alesapin)).
|
||||
* Reresolve the IP of the `format_avro_schema_registry_url` in case of errors. [#16985](https://github.com/ClickHouse/ClickHouse/pull/16985) ([filimonov](https://github.com/filimonov)).
|
||||
* Fix possible server crash after `ALTER TABLE ... MODIFY COLUMN ... NewType` when `SELECT` have `WHERE` expression on altering column and alter doesn't finished yet. [#16968](https://github.com/ClickHouse/ClickHouse/pull/16968) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Install script should always create subdirs in config folders. This is only relevant for Docker build with custom config. [#16936](https://github.com/ClickHouse/ClickHouse/pull/16936) ([filimonov](https://github.com/filimonov)).
|
||||
* Fix possible error `Illegal type of argument` for queries with `ORDER BY`. Fixes [#16580](https://github.com/ClickHouse/ClickHouse/issues/16580). [#16928](https://github.com/ClickHouse/ClickHouse/pull/16928) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Abort multipart upload if no data was written to WriteBufferFromS3. [#16840](https://github.com/ClickHouse/ClickHouse/pull/16840) ([Pavel Kovalenko](https://github.com/Jokser)).
|
||||
* Fix crash when using `any` without any arguments. This is for [#16803](https://github.com/ClickHouse/ClickHouse/issues/16803) . cc @azat. [#16826](https://github.com/ClickHouse/ClickHouse/pull/16826) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Fix `IN` operator over several columns and tuples with enabled `transform_null_in` setting. Fixes [#15310](https://github.com/ClickHouse/ClickHouse/issues/15310). [#16722](https://github.com/ClickHouse/ClickHouse/pull/16722) ([Anton Popov](https://github.com/CurtizJ)).
|
||||
* This will fix optimize_read_in_order/optimize_aggregation_in_order with max_threads>0 and expression in ORDER BY. [#16637](https://github.com/ClickHouse/ClickHouse/pull/16637) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* fixes [#16574](https://github.com/ClickHouse/ClickHouse/issues/16574) fixes [#16231](https://github.com/ClickHouse/ClickHouse/issues/16231) fix remote query failure when using 'if' suffix aggregate function. [#16610](https://github.com/ClickHouse/ClickHouse/pull/16610) ([Winter Zhang](https://github.com/zhang2014)).
|
||||
* Query is finished faster in case of exception. Cancel execution on remote replicas if exception happens. [#15578](https://github.com/ClickHouse/ClickHouse/pull/15578) ([Azat Khuzhin](https://github.com/azat)).
|
||||
|
||||
|
||||
### ClickHouse release v20.9.5.5-stable, 2020-11-13
|
||||
|
||||
#### Bug Fix
|
||||
@ -744,6 +878,23 @@ toc_title: '2020'
|
||||
|
||||
## ClickHouse release 20.8
|
||||
|
||||
### ClickHouse release v20.8.12.2-lts, 2021-01-16
|
||||
|
||||
#### Bug Fix
|
||||
|
||||
* Fix *If combinator with unary function and Nullable types. [#18806](https://github.com/ClickHouse/ClickHouse/pull/18806) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* Restrict merges from wide to compact parts. In case of vertical merge it led to broken result part. [#18381](https://github.com/ClickHouse/ClickHouse/pull/18381) ([Anton Popov](https://github.com/CurtizJ)).
|
||||
|
||||
|
||||
### ClickHouse release v20.8.11.17-lts, 2020-12-25
|
||||
|
||||
#### Bug Fix
|
||||
|
||||
* Disable write with AIO during merges because it can lead to extremely rare data corruption of primary key columns during merge. [#18481](https://github.com/ClickHouse/ClickHouse/pull/18481) ([alesapin](https://github.com/alesapin)).
|
||||
* Fixed `value is too short` error when executing `toType(...)` functions (`toDate`, `toUInt32`, etc) with argument of type `Nullable(String)`. Now such functions return `NULL` on parsing errors instead of throwing exception. Fixes [#7673](https://github.com/ClickHouse/ClickHouse/issues/7673). [#18445](https://github.com/ClickHouse/ClickHouse/pull/18445) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Fix possible crashes in aggregate functions with combinator `Distinct`, while using two-level aggregation. Fixes [#17682](https://github.com/ClickHouse/ClickHouse/issues/17682). [#18365](https://github.com/ClickHouse/ClickHouse/pull/18365) ([Anton Popov](https://github.com/CurtizJ)).
|
||||
|
||||
|
||||
### ClickHouse release v20.8.10.13-lts, 2020-12-24
|
||||
|
||||
#### Bug Fix
|
||||
|
||||
@ -714,6 +714,7 @@ auto s = std::string{"Hello"};
|
||||
### Пользовательская ошибка {#error-messages-user-error}
|
||||
|
||||
Такая ошибка вызвана действиями пользователя (неверный синтаксис запроса) или конфигурацией внешних систем (кончилось место на диске). Предполагается, что пользователь может устранить её самостоятельно. Для этого в сообщении об ошибке должна содержаться следующая информация:
|
||||
|
||||
* что произошло. Это должно объясняться в пользовательских терминах (`Function pow() is not supported for data type UInt128`), а не загадочными конструкциями из кода (`runtime overload resolution failed in DB::BinaryOperationBuilder<FunctionAdaptor<pow>::Impl, UInt128, Int8>::kaboongleFastPath()`).
|
||||
* почему/где/когда -- любой контекст, который помогает отладить проблему. Представьте, как бы её отлаживали вы (программировать и пользоваться отладчиком нельзя).
|
||||
* что можно предпринять для устранения ошибки. Здесь можно перечислить типичные причины проблемы, настройки, влияющие на это поведение, и так далее.
|
||||
|
||||
@ -12,7 +12,10 @@ toc_priority: 30
|
||||
- [ODBC](../../../engines/table-engines/integrations/odbc.md)
|
||||
- [JDBC](../../../engines/table-engines/integrations/jdbc.md)
|
||||
- [MySQL](../../../engines/table-engines/integrations/mysql.md)
|
||||
- [MongoDB](../../../engines/table-engines/integrations/mongodb.md)
|
||||
- [HDFS](../../../engines/table-engines/integrations/hdfs.md)
|
||||
- [Kafka](../../../engines/table-engines/integrations/kafka.md)
|
||||
- [EmbeddedRocksDB](../../../engines/table-engines/integrations/embedded-rocksdb.md)
|
||||
- [RabbitMQ](../../../engines/table-engines/integrations/rabbitmq.md)
|
||||
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/ru/engines/table-engines/integrations/) <!--hide-->
|
||||
|
||||
57
docs/ru/engines/table-engines/integrations/mongodb.md
Normal file
57
docs/ru/engines/table-engines/integrations/mongodb.md
Normal file
@ -0,0 +1,57 @@
|
||||
---
|
||||
toc_priority: 7
|
||||
toc_title: MongoDB
|
||||
---
|
||||
|
||||
# MongoDB {#mongodb}
|
||||
|
||||
Движок таблиц MongoDB позволяет читать данные из коллекций СУБД MongoDB. В таблицах допустимы только плоские (не вложенные) типы данных. Запись (`INSERT`-запросы) не поддерживается.
|
||||
|
||||
## Создание таблицы {#creating-a-table}
|
||||
|
||||
``` sql
|
||||
CREATE TABLE [IF NOT EXISTS] [db.]table_name
|
||||
(
|
||||
name1 [type1],
|
||||
name2 [type2],
|
||||
...
|
||||
) ENGINE = MongoDB(host:port, database, collection, user, password);
|
||||
```
|
||||
|
||||
**Параметры движка**
|
||||
|
||||
- `host:port` — адрес сервера MongoDB.
|
||||
|
||||
- `database` — имя базы данных на удалённом сервере.
|
||||
|
||||
- `collection` — имя коллекции на удалённом сервере.
|
||||
|
||||
- `user` — пользователь MongoDB.
|
||||
|
||||
- `password` — пароль пользователя.
|
||||
|
||||
## Примеры использования {#usage-example}
|
||||
|
||||
Таблица в ClickHouse для чтения данных из колекции MongoDB:
|
||||
|
||||
``` text
|
||||
CREATE TABLE mongo_table
|
||||
(
|
||||
key UInt64,
|
||||
data String
|
||||
) ENGINE = MongoDB('mongo1:27017', 'test', 'simple_table', 'testuser', 'clickhouse');
|
||||
```
|
||||
|
||||
Запрос к таблице:
|
||||
|
||||
``` sql
|
||||
SELECT COUNT() FROM mongo_table;
|
||||
```
|
||||
|
||||
``` text
|
||||
┌─count()─┐
|
||||
│ 4 │
|
||||
└─────────┘
|
||||
```
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/ru/operations/table_engines/integrations/mongodb/) <!--hide-->
|
||||
@ -37,7 +37,10 @@ ORDER BY expr
|
||||
[PARTITION BY expr]
|
||||
[PRIMARY KEY expr]
|
||||
[SAMPLE BY expr]
|
||||
[TTL expr [DELETE|TO DISK 'xxx'|TO VOLUME 'xxx'], ...]
|
||||
[TTL expr
|
||||
[DELETE|TO DISK 'xxx'|TO VOLUME 'xxx' [, ...] ]
|
||||
[WHERE conditions]
|
||||
[GROUP BY key_expr [SET v1 = aggr_func(v1) [, v2 = aggr_func(v2) ...]] ] ]
|
||||
[SETTINGS name=value, ...]
|
||||
```
|
||||
|
||||
@ -71,7 +74,7 @@ ORDER BY expr
|
||||
|
||||
Выражение должно возвращать столбец `Date` или `DateTime`. Пример: `TTL date + INTERVAL 1 DAY`.
|
||||
|
||||
Тип правила `DELETE|TO DISK 'xxx'|TO VOLUME 'xxx'` указывает действие, которое будет выполнено с частью, удаление строк (прореживание), перемещение (при выполнении условия для всех строк части) на определённый диск (`TO DISK 'xxx'`) или том (`TO VOLUME 'xxx'`). Поведение по умолчанию соответствует удалению строк (`DELETE`). В списке правил может быть указано только одно выражение с поведением `DELETE`.
|
||||
Тип правила `DELETE|TO DISK 'xxx'|TO VOLUME 'xxx'|GROUP BY` указывает действие, которое будет выполнено с частью: удаление строк (прореживание), перемещение (при выполнении условия для всех строк части) на определённый диск (`TO DISK 'xxx'`) или том (`TO VOLUME 'xxx'`), или агрегирование данных в устаревших строках. Поведение по умолчанию соответствует удалению строк (`DELETE`). В списке правил может быть указано только одно выражение с поведением `DELETE`.
|
||||
|
||||
Дополнительные сведения смотрите в разделе [TTL для столбцов и таблиц](#table_engine-mergetree-ttl)
|
||||
|
||||
@ -443,16 +446,28 @@ ALTER TABLE example_table
|
||||
Для таблицы можно задать одно выражение для устаревания данных, а также несколько выражений, по срабатывании которых данные переместятся на [некоторый диск или том](#table_engine-mergetree-multiple-volumes). Когда некоторые данные в таблице устаревают, ClickHouse удаляет все соответствующие строки.
|
||||
|
||||
``` sql
|
||||
TTL expr [DELETE|TO DISK 'aaa'|TO VOLUME 'bbb'], ...
|
||||
TTL expr
|
||||
[DELETE|TO DISK 'xxx'|TO VOLUME 'xxx'][, DELETE|TO DISK 'aaa'|TO VOLUME 'bbb'] ...
|
||||
[WHERE conditions]
|
||||
[GROUP BY key_expr [SET v1 = aggr_func(v1) [, v2 = aggr_func(v2) ...]] ]
|
||||
```
|
||||
|
||||
За каждым TTL выражением может следовать тип действия, которое выполняется после достижения времени, соответствующего результату TTL выражения:
|
||||
|
||||
- `DELETE` - удалить данные (действие по умолчанию);
|
||||
- `TO DISK 'aaa'` - переместить данные на диск `aaa`;
|
||||
- `TO VOLUME 'bbb'` - переместить данные на том `bbb`.
|
||||
- `TO VOLUME 'bbb'` - переместить данные на том `bbb`;
|
||||
- `GROUP BY` - агрегировать данные.
|
||||
|
||||
Примеры:
|
||||
В секции `WHERE` можно задать условие удаления или агрегирования устаревших строк (для перемещения условие `WHERE` не применимо).
|
||||
|
||||
Колонки, по которым агрегируются данные в `GROUP BY`, должны являться префиксом первичного ключа таблицы.
|
||||
|
||||
Если колонка не является частью выражения `GROUP BY` и не задается напрямую в секции `SET`, в результирующих строках она будет содержать случайное значение, взятое из одной из сгруппированных строк (как будто к ней применяется агрегирующая функция `any`).
|
||||
|
||||
**Примеры**
|
||||
|
||||
Создание таблицы с TTL:
|
||||
|
||||
``` sql
|
||||
CREATE TABLE example_table
|
||||
@ -468,13 +483,43 @@ TTL d + INTERVAL 1 MONTH [DELETE],
|
||||
d + INTERVAL 2 WEEK TO DISK 'bbb';
|
||||
```
|
||||
|
||||
Изменение TTL
|
||||
Изменение TTL:
|
||||
|
||||
``` sql
|
||||
ALTER TABLE example_table
|
||||
MODIFY TTL d + INTERVAL 1 DAY;
|
||||
```
|
||||
|
||||
Создание таблицы, в которой строки устаревают через месяц. Устаревшие строки удаляются, если дата выпадает на понедельник:
|
||||
|
||||
``` sql
|
||||
CREATE TABLE table_with_where
|
||||
(
|
||||
d DateTime,
|
||||
a Int
|
||||
)
|
||||
ENGINE = MergeTree
|
||||
PARTITION BY toYYYYMM(d)
|
||||
ORDER BY d
|
||||
TTL d + INTERVAL 1 MONTH DELETE WHERE toDayOfWeek(d) = 1;
|
||||
```
|
||||
|
||||
Создание таблицы, где устаревшие строки агрегируются. В результирующих строках колонка `x` содержит максимальное значение по сгруппированным строкам, `y` — минимальное значение, а `d` — случайное значение из одной из сгуппированных строк.
|
||||
|
||||
``` sql
|
||||
CREATE TABLE table_for_aggregation
|
||||
(
|
||||
d DateTime,
|
||||
k1 Int,
|
||||
k2 Int,
|
||||
x Int,
|
||||
y Int
|
||||
)
|
||||
ENGINE = MergeTree
|
||||
ORDER BY k1, k2
|
||||
TTL d + INTERVAL 1 MONTH GROUP BY k1, k2 SET x = max(x), y = min(y);
|
||||
```
|
||||
|
||||
**Удаление данных**
|
||||
|
||||
Данные с истекшим TTL удаляются, когда ClickHouse мёржит куски данных.
|
||||
|
||||
@ -6,29 +6,62 @@
|
||||
|
||||
Столбцы:
|
||||
|
||||
- `event_type` (Enum) — тип события. Столбец может содержать одно из следующих значений:
|
||||
- `query_id` ([String](../../sql-reference/data-types/string.md)) — идентификатор запроса `INSERT`, создавшего этот кусок.
|
||||
- `event_type` ([Enum8](../../sql-reference/data-types/enum.md)) — тип события. Столбец может содержать одно из следующих значений:
|
||||
- `NEW_PART` — вставка нового куска.
|
||||
- `MERGE_PARTS` — слияние кусков.
|
||||
- `DOWNLOAD_PART` — загрузка с реплики.
|
||||
- `REMOVE_PART` — удаление или отсоединение из таблицы с помощью [DETACH PARTITION](../../sql-reference/statements/alter/partition.md#alter_detach-partition).
|
||||
- `MUTATE_PART` — изменение куска.
|
||||
- `MOVE_PART` — перемещение куска между дисками.
|
||||
- `event_date` (Date) — дата события.
|
||||
- `event_time` (DateTime) — время события.
|
||||
- `duration_ms` (UInt64) — длительность.
|
||||
- `database` (String) — имя базы данных, в которой находится кусок.
|
||||
- `table` (String) — имя таблицы, в которой находится кусок.
|
||||
- `part_name` (String) — имя куска.
|
||||
- `partition_id` (String) — идентификатор партиции, в которую был добавлен кусок. В столбце будет значение ‘all’, если таблица партициируется по выражению `tuple()`.
|
||||
- `rows` (UInt64) — число строк в куске.
|
||||
- `size_in_bytes` (UInt64) — размер куска данных в байтах.
|
||||
- `merged_from` (Array(String)) — массив имён кусков, из которых образован текущий кусок в результате слияния (также столбец заполняется в случае скачивания уже смерженного куска).
|
||||
- `bytes_uncompressed` (UInt64) — количество прочитанных разжатых байт.
|
||||
- `read_rows` (UInt64) — сколько было прочитано строк при слиянии кусков.
|
||||
- `read_bytes` (UInt64) — сколько было прочитано байт при слиянии кусков.
|
||||
- `error` (UInt16) — код ошибки, возникшей при текущем событии.
|
||||
- `exception` (String) — текст ошибки.
|
||||
- `event_date` ([Date](../../sql-reference/data-types/date.md)) — дата события.
|
||||
- `event_time` ([DateTime](../../sql-reference/data-types/datetime.md)) — время события.
|
||||
- `duration_ms` ([UInt64](../../sql-reference/data-types/int-uint.md)) — длительность.
|
||||
- `database` ([String](../../sql-reference/data-types/string.md)) — имя базы данных, в которой находится кусок.
|
||||
- `table` ([String](../../sql-reference/data-types/string.md)) — имя таблицы, в которой находится кусок.
|
||||
- `part_name` ([String](../../sql-reference/data-types/string.md)) — имя куска.
|
||||
- `partition_id` ([String](../../sql-reference/data-types/string.md)) — идентификатор партиции, в которую был добавлен кусок. В столбце будет значение `all`, если таблица партициируется по выражению `tuple()`.
|
||||
- `path_on_disk` ([String](../../sql-reference/data-types/string.md)) — абсолютный путь к папке с файлами кусков данных.
|
||||
- `rows` ([UInt64](../../sql-reference/data-types/int-uint.md)) — число строк в куске.
|
||||
- `size_in_bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — размер куска данных в байтах.
|
||||
- `merged_from` ([Array(String)](../../sql-reference/data-types/array.md)) — массив имён кусков, из которых образован текущий кусок в результате слияния (также столбец заполняется в случае скачивания уже смерженного куска).
|
||||
- `bytes_uncompressed` ([UInt64](../../sql-reference/data-types/int-uint.md)) — количество прочитанных не сжатых байт.
|
||||
- `read_rows` ([UInt64](../../sql-reference/data-types/int-uint.md)) — сколько было прочитано строк при слиянии кусков.
|
||||
- `read_bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — сколько было прочитано байт при слиянии кусков.
|
||||
- `peak_memory_usage` ([Int64](../../sql-reference/data-types/int-uint.md)) — максимальная разница между выделенной и освобождённой памятью в контексте потока.
|
||||
- `error` ([UInt16](../../sql-reference/data-types/int-uint.md)) — код ошибки, возникшей при текущем событии.
|
||||
- `exception` ([String](../../sql-reference/data-types/string.md)) — текст ошибки.
|
||||
|
||||
Системная таблица `system.part_log` будет создана после первой вставки данных в таблицу `MergeTree`.
|
||||
|
||||
**Пример**
|
||||
|
||||
``` sql
|
||||
SELECT * FROM system.part_log LIMIT 1 FORMAT Vertical;
|
||||
```
|
||||
|
||||
``` text
|
||||
Row 1:
|
||||
──────
|
||||
query_id: 983ad9c7-28d5-4ae1-844e-603116b7de31
|
||||
event_type: NewPart
|
||||
event_date: 2021-02-02
|
||||
event_time: 2021-02-02 11:14:28
|
||||
duration_ms: 35
|
||||
database: default
|
||||
table: log_mt_2
|
||||
part_name: all_1_1_0
|
||||
partition_id: all
|
||||
path_on_disk: db/data/default/log_mt_2/all_1_1_0/
|
||||
rows: 115418
|
||||
size_in_bytes: 1074311
|
||||
merged_from: []
|
||||
bytes_uncompressed: 0
|
||||
read_rows: 0
|
||||
read_bytes: 0
|
||||
peak_memory_usage: 0
|
||||
error: 0
|
||||
exception:
|
||||
```
|
||||
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/ru/operations/system_tables/part_log) <!--hide-->
|
||||
|
||||
@ -4,8 +4,63 @@ toc_priority: 106
|
||||
|
||||
# argMax {#agg-function-argmax}
|
||||
|
||||
Синтаксис: `argMax(arg, val)`
|
||||
Вычисляет значение `arg` при максимальном значении `val`. Если есть несколько разных значений `arg` для максимальных значений `val`, возвращает первое попавшееся из таких значений.
|
||||
|
||||
Вычисляет значение arg при максимальном значении val. Если есть несколько разных значений arg для максимальных значений val, то выдаётся первое попавшееся из таких значений.
|
||||
Если функции передан кортеж, то будет выведен кортеж с максимальным значением `val`. Удобно использовать для работы с [SimpleAggregateFunction](../../../sql-reference/data-types/simpleaggregatefunction.md).
|
||||
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/en/sql-reference/aggregate-functions/reference/argmax/) <!--hide-->
|
||||
**Синтаксис**
|
||||
|
||||
``` sql
|
||||
argMax(arg, val)
|
||||
```
|
||||
|
||||
или
|
||||
|
||||
``` sql
|
||||
argMax(tuple(arg, val))
|
||||
```
|
||||
|
||||
**Параметры**
|
||||
|
||||
- `arg` — аргумент.
|
||||
- `val` — значение.
|
||||
|
||||
**Возвращаемое значение**
|
||||
|
||||
- Значение `arg`, соответствующее максимальному значению `val`.
|
||||
|
||||
Тип: соответствует типу `arg`.
|
||||
|
||||
Если передан кортеж:
|
||||
|
||||
- Кортеж `(arg, val)` c максимальным значением `val` и соответствующим ему `arg`.
|
||||
|
||||
Тип: [Tuple](../../../sql-reference/data-types/tuple.md).
|
||||
|
||||
**Пример**
|
||||
|
||||
Исходная таблица:
|
||||
|
||||
``` text
|
||||
┌─user─────┬─salary─┐
|
||||
│ director │ 5000 │
|
||||
│ manager │ 3000 │
|
||||
│ worker │ 1000 │
|
||||
└──────────┴────────┘
|
||||
```
|
||||
|
||||
Запрос:
|
||||
|
||||
``` sql
|
||||
SELECT argMax(user, salary), argMax(tuple(user, salary)) FROM salary;
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
``` text
|
||||
┌─argMax(user, salary)─┬─argMax(tuple(user, salary))─┐
|
||||
│ director │ ('director',5000) │
|
||||
└──────────────────────┴─────────────────────────────┘
|
||||
```
|
||||
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/ru/sql-reference/aggregate-functions/reference/argmax/) <!--hide-->
|
||||
|
||||
@ -4,11 +4,42 @@ toc_priority: 105
|
||||
|
||||
# argMin {#agg-function-argmin}
|
||||
|
||||
Синтаксис: `argMin(arg, val)`
|
||||
Вычисляет значение `arg` при минимальном значении `val`. Если есть несколько разных значений `arg` для минимальных значений `val`, возвращает первое попавшееся из таких значений.
|
||||
|
||||
Вычисляет значение arg при минимальном значении val. Если есть несколько разных значений arg для минимальных значений val, то выдаётся первое попавшееся из таких значений.
|
||||
Если функции передан кортеж, то будет выведен кортеж с минимальным значением `val`. Удобно использовать для работы с [SimpleAggregateFunction](../../../sql-reference/data-types/simpleaggregatefunction.md).
|
||||
|
||||
**Пример:**
|
||||
**Синтаксис**
|
||||
|
||||
``` sql
|
||||
argMin(arg, val)
|
||||
```
|
||||
|
||||
или
|
||||
|
||||
``` sql
|
||||
argMin(tuple(arg, val))
|
||||
```
|
||||
|
||||
**Параметры**
|
||||
|
||||
- `arg` — аргумент.
|
||||
- `val` — значение.
|
||||
|
||||
**Возвращаемое значение**
|
||||
|
||||
- Значение `arg`, соответствующее минимальному значению `val`.
|
||||
|
||||
Тип: соответствует типу `arg`.
|
||||
|
||||
Если передан кортеж:
|
||||
|
||||
- Кортеж `(arg, val)` c минимальным значением `val` и соответствующим ему `arg`.
|
||||
|
||||
Тип: [Tuple](../../../sql-reference/data-types/tuple.md).
|
||||
|
||||
**Пример**
|
||||
|
||||
Исходная таблица:
|
||||
|
||||
``` text
|
||||
┌─user─────┬─salary─┐
|
||||
@ -18,14 +49,18 @@ toc_priority: 105
|
||||
└──────────┴────────┘
|
||||
```
|
||||
|
||||
Запрос:
|
||||
|
||||
``` sql
|
||||
SELECT argMin(user, salary) FROM salary
|
||||
SELECT argMin(user, salary), argMin(tuple(user, salary)) FROM salary;
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
``` text
|
||||
┌─argMin(user, salary)─┐
|
||||
│ worker │
|
||||
└──────────────────────┘
|
||||
┌─argMin(user, salary)─┬─argMin(tuple(user, salary))─┐
|
||||
│ worker │ ('worker',1000) │
|
||||
└──────────────────────┴─────────────────────────────┘
|
||||
```
|
||||
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/en/sql-reference/aggregate-functions/reference/argmin/) <!--hide-->
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/ru/sql-reference/aggregate-functions/reference/argmin/) <!--hide-->
|
||||
|
||||
@ -0,0 +1,71 @@
|
||||
---
|
||||
toc_priority: 310
|
||||
toc_title: mannWhitneyUTest
|
||||
---
|
||||
|
||||
# mannWhitneyUTest {#mannwhitneyutest}
|
||||
|
||||
Вычисляет U-критерий Манна — Уитни для выборок из двух генеральных совокупностей.
|
||||
|
||||
**Синтаксис**
|
||||
|
||||
``` sql
|
||||
mannWhitneyUTest[(alternative[, continuity_correction])](sample_data, sample_index)
|
||||
```
|
||||
|
||||
Значения выборок берутся из столбца `sample_data`. Если `sample_index` равно 0, то значение из этой строки принадлежит первой выборке. Во всех остальных случаях значение принадлежит второй выборке.
|
||||
Проверяется нулевая гипотеза, что генеральные совокупности стохастически равны. Наряду с двусторонней гипотезой могут быть проверены и односторонние.
|
||||
Для применения U-критерия Манна — Уитни закон распределения генеральных совокупностей не обязан быть нормальным.
|
||||
|
||||
**Параметры**
|
||||
|
||||
- `alternative` — альтернативная гипотеза. (Необязательный параметр, по умолчанию: `'two-sided'`.) [String](../../../sql-reference/data-types/string.md).
|
||||
- `'two-sided'`;
|
||||
- `'greater'`;
|
||||
- `'less'`.
|
||||
- `continuity_correction` - если не 0, то при вычислении p-значения применяется коррекция непрерывности. (Необязательный параметр, по умолчанию: 1.) [UInt64](../../../sql-reference/data-types/int-uint.md).
|
||||
- `sample_data` — данные выборок. [Integer](../../../sql-reference/data-types/int-uint.md), [Float](../../../sql-reference/data-types/float.md) or [Decimal](../../../sql-reference/data-types/decimal.md).
|
||||
- `sample_index` — индексы выборок. [Integer](../../../sql-reference/data-types/int-uint.md).
|
||||
|
||||
|
||||
**Возвращаемые значения**
|
||||
|
||||
[Кортеж](../../../sql-reference/data-types/tuple.md) с двумя элементами:
|
||||
- вычисленное значение критерия Манна — Уитни. [Float64](../../../sql-reference/data-types/float.md).
|
||||
- вычисленное p-значение. [Float64](../../../sql-reference/data-types/float.md).
|
||||
|
||||
|
||||
**Пример**
|
||||
|
||||
Таблица:
|
||||
|
||||
``` text
|
||||
┌─sample_data─┬─sample_index─┐
|
||||
│ 10 │ 0 │
|
||||
│ 11 │ 0 │
|
||||
│ 12 │ 0 │
|
||||
│ 1 │ 1 │
|
||||
│ 2 │ 1 │
|
||||
│ 3 │ 1 │
|
||||
└─────────────┴──────────────┘
|
||||
```
|
||||
|
||||
Запрос:
|
||||
|
||||
``` sql
|
||||
SELECT mannWhitneyUTest('greater')(sample_data, sample_index) FROM mww_ttest;
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
``` text
|
||||
┌─mannWhitneyUTest('greater')(sample_data, sample_index)─┐
|
||||
│ (9,0.04042779918503192) │
|
||||
└────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
**Смотрите также**
|
||||
|
||||
- [U-критерий Манна — Уитни](https://ru.wikipedia.org/wiki/U-%D0%BA%D1%80%D0%B8%D1%82%D0%B5%D1%80%D0%B8%D0%B9_%D0%9C%D0%B0%D0%BD%D0%BD%D0%B0_%E2%80%94_%D0%A3%D0%B8%D1%82%D0%BD%D0%B8)
|
||||
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/ru/sql-reference/aggregate-functions/reference/mannwhitneyutest/) <!--hide-->
|
||||
@ -0,0 +1,65 @@
|
||||
---
|
||||
toc_priority: 300
|
||||
toc_title: studentTTest
|
||||
---
|
||||
|
||||
# studentTTest {#studentttest}
|
||||
|
||||
Вычисляет t-критерий Стьюдента для выборок из двух генеральных совокупностей.
|
||||
|
||||
**Синтаксис**
|
||||
|
||||
``` sql
|
||||
studentTTest(sample_data, sample_index)
|
||||
```
|
||||
|
||||
Значения выборок берутся из столбца `sample_data`. Если `sample_index` равно 0, то значение из этой строки принадлежит первой выборке. Во всех остальных случаях значение принадлежит второй выборке.
|
||||
Проверяется нулевая гипотеза, что средние значения генеральных совокупностей совпадают. Для применения t-критерия Стьюдента распределение в генеральных совокупностях должно быть нормальным и дисперсии должны совпадать.
|
||||
|
||||
**Параметры**
|
||||
|
||||
- `sample_data` — данные выборок. [Integer](../../../sql-reference/data-types/int-uint.md), [Float](../../../sql-reference/data-types/float.md) or [Decimal](../../../sql-reference/data-types/decimal.md).
|
||||
- `sample_index` — индексы выборок. [Integer](../../../sql-reference/data-types/int-uint.md).
|
||||
|
||||
**Возвращаемые значения**
|
||||
|
||||
[Кортеж](../../../sql-reference/data-types/tuple.md) с двумя элементами:
|
||||
- вычисленное значение критерия Стьюдента. [Float64](../../../sql-reference/data-types/float.md).
|
||||
- вычисленное p-значение. [Float64](../../../sql-reference/data-types/float.md).
|
||||
|
||||
|
||||
**Пример**
|
||||
|
||||
Таблица:
|
||||
|
||||
``` text
|
||||
┌─sample_data─┬─sample_index─┐
|
||||
│ 20.3 │ 0 │
|
||||
│ 21.1 │ 0 │
|
||||
│ 21.9 │ 1 │
|
||||
│ 21.7 │ 0 │
|
||||
│ 19.9 │ 1 │
|
||||
│ 21.8 │ 1 │
|
||||
└─────────────┴──────────────┘
|
||||
```
|
||||
|
||||
Запрос:
|
||||
|
||||
``` sql
|
||||
SELECT studentTTest(sample_data, sample_index) FROM student_ttest;
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
``` text
|
||||
┌─studentTTest(sample_data, sample_index)───┐
|
||||
│ (-0.21739130434783777,0.8385421208415731) │
|
||||
└───────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
**Смотрите также**
|
||||
|
||||
- [t-критерий Стьюдента](https://ru.wikipedia.org/wiki/T-%D0%BA%D1%80%D0%B8%D1%82%D0%B5%D1%80%D0%B8%D0%B9_%D0%A1%D1%82%D1%8C%D1%8E%D0%B4%D0%B5%D0%BD%D1%82%D0%B0)
|
||||
- [welchTTest](welchttest.md#welchttest)
|
||||
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/ru/sql-reference/aggregate-functions/reference/studentttest/) <!--hide-->
|
||||
@ -0,0 +1,65 @@
|
||||
---
|
||||
toc_priority: 301
|
||||
toc_title: welchTTest
|
||||
---
|
||||
|
||||
# welchTTest {#welchttest}
|
||||
|
||||
Вычисляет t-критерий Уэлча для выборок из двух генеральных совокупностей.
|
||||
|
||||
**Синтаксис**
|
||||
|
||||
``` sql
|
||||
welchTTest(sample_data, sample_index)
|
||||
```
|
||||
|
||||
Значения выборок берутся из столбца `sample_data`. Если `sample_index` равно 0, то значение из этой строки принадлежит первой выборке. Во всех остальных случаях значение принадлежит второй выборке.
|
||||
Проверяется нулевая гипотеза, что средние значения генеральных совокупностей совпадают. Для применения t-критерия Уэлча распределение в генеральных совокупностях должно быть нормальным. Дисперсии могут не совпадать.
|
||||
|
||||
**Параметры**
|
||||
|
||||
- `sample_data` — данные выборок. [Integer](../../../sql-reference/data-types/int-uint.md), [Float](../../../sql-reference/data-types/float.md) or [Decimal](../../../sql-reference/data-types/decimal.md).
|
||||
- `sample_index` — индексы выборок. [Integer](../../../sql-reference/data-types/int-uint.md).
|
||||
|
||||
**Возвращаемые значения**
|
||||
|
||||
[Кортеж](../../../sql-reference/data-types/tuple.md) с двумя элементами:
|
||||
- вычисленное значение критерия Уэлча. [Float64](../../../sql-reference/data-types/float.md).
|
||||
- вычисленное p-значение. [Float64](../../../sql-reference/data-types/float.md).
|
||||
|
||||
|
||||
**Пример**
|
||||
|
||||
Таблица:
|
||||
|
||||
``` text
|
||||
┌─sample_data─┬─sample_index─┐
|
||||
│ 20.3 │ 0 │
|
||||
│ 22.1 │ 0 │
|
||||
│ 21.9 │ 0 │
|
||||
│ 18.9 │ 1 │
|
||||
│ 20.3 │ 1 │
|
||||
│ 19 │ 1 │
|
||||
└─────────────┴──────────────┘
|
||||
```
|
||||
|
||||
Запрос:
|
||||
|
||||
``` sql
|
||||
SELECT welchTTest(sample_data, sample_index) FROM welch_ttest;
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
``` text
|
||||
┌─welchTTest(sample_data, sample_index)─────┐
|
||||
│ (2.7988719532211235,0.051807360348581945) │
|
||||
└───────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
**Смотрите также**
|
||||
|
||||
- [t-критерий Уэлча](https://ru.wikipedia.org/wiki/T-%D0%BA%D1%80%D0%B8%D1%82%D0%B5%D1%80%D0%B8%D0%B9_%D0%A3%D1%8D%D0%BB%D1%87%D0%B0)
|
||||
- [studentTTest](studentttest.md#studentttest)
|
||||
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/ru/sql-reference/aggregate-functions/reference/welchTTest/) <!--hide-->
|
||||
@ -47,6 +47,8 @@ SELECT [1, 2] AS x, toTypeName(x)
|
||||
|
||||
## Особенности работы с типами данных {#osobennosti-raboty-s-tipami-dannykh}
|
||||
|
||||
Максимальный размер массива ограничен одним миллионом элементов.
|
||||
|
||||
При создании массива «на лету» ClickHouse автоматически определяет тип аргументов как наиболее узкий тип данных, в котором можно хранить все перечисленные аргументы. Если среди аргументов есть [NULL](../../sql-reference/data-types/array.md#null-literal) или аргумент типа [Nullable](nullable.md#data_type-nullable), то тип элементов массива — [Nullable](nullable.md).
|
||||
|
||||
Если ClickHouse не смог подобрать тип данных, то он сгенерирует исключение. Это произойдёт, например, при попытке создать массив одновременно со строками и числами `SELECT array(1, 'a')`.
|
||||
|
||||
@ -1135,11 +1135,225 @@ SELECT
|
||||
|
||||
Функция `arrayFirstIndex` является [функцией высшего порядка](../../sql-reference/functions/index.md#higher-order-functions) — в качестве первого аргумента ей нужно передать лямбда-функцию, и этот аргумент не может быть опущен.
|
||||
|
||||
## arraySum(\[func,\] arr1, …) {#array-sum}
|
||||
## arrayMin {#array-min}
|
||||
|
||||
Возвращает сумму значений функции `func`. Если функция не указана - просто возвращает сумму элементов массива.
|
||||
Возвращает значение минимального элемента в исходном массиве.
|
||||
|
||||
Функция `arraySum` является [функцией высшего порядка](../../sql-reference/functions/index.md#higher-order-functions) - в качестве первого аргумента ей можно передать лямбда-функцию.
|
||||
Если передана функция `func`, возвращается минимум из элементов массива, преобразованных этой функцией.
|
||||
|
||||
Функция `arrayMin` является [функцией высшего порядка](../../sql-reference/functions/index.md#higher-order-functions) — в качестве первого аргумента ей можно передать лямбда-функцию.
|
||||
|
||||
**Синтаксис**
|
||||
|
||||
```sql
|
||||
arrayMin([func,] arr)
|
||||
```
|
||||
|
||||
**Параметры**
|
||||
|
||||
- `func` — функция. [Expression](../../sql-reference/data-types/special-data-types/expression.md).
|
||||
- `arr` — массив. [Array](../../sql-reference/data-types/array.md).
|
||||
|
||||
**Возвращаемое значение**
|
||||
|
||||
- Минимальное значение функции (или минимальный элемент массива).
|
||||
|
||||
Тип: если передана `func`, соответствует типу ее возвращаемого значения, иначе соответствует типу элементов массива.
|
||||
|
||||
**Примеры**
|
||||
|
||||
Запрос:
|
||||
|
||||
```sql
|
||||
SELECT arrayMin([1, 2, 4]) AS res;
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
```text
|
||||
┌─res─┐
|
||||
│ 1 │
|
||||
└─────┘
|
||||
```
|
||||
|
||||
Запрос:
|
||||
|
||||
```sql
|
||||
SELECT arrayMin(x -> (-x), [1, 2, 4]) AS res;
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
```text
|
||||
┌─res─┐
|
||||
│ -4 │
|
||||
└─────┘
|
||||
```
|
||||
|
||||
## arrayMax {#array-max}
|
||||
|
||||
Возвращает значение максимального элемента в исходном массиве.
|
||||
|
||||
Если передана функция `func`, возвращается максимум из элементов массива, преобразованных этой функцией.
|
||||
|
||||
Функция `arrayMax` является [функцией высшего порядка](../../sql-reference/functions/index.md#higher-order-functions) — в качестве первого аргумента ей можно передать лямбда-функцию.
|
||||
|
||||
**Синтаксис**
|
||||
|
||||
```sql
|
||||
arrayMax([func,] arr)
|
||||
```
|
||||
|
||||
**Параметры**
|
||||
|
||||
- `func` — функция. [Expression](../../sql-reference/data-types/special-data-types/expression.md).
|
||||
- `arr` — массив. [Array](../../sql-reference/data-types/array.md).
|
||||
|
||||
**Возвращаемое значение**
|
||||
|
||||
- Максимальное значение функции (или максимальный элемент массива).
|
||||
|
||||
Тип: если передана `func`, соответствует типу ее возвращаемого значения, иначе соответствует типу элементов массива.
|
||||
|
||||
**Примеры**
|
||||
|
||||
Запрос:
|
||||
|
||||
```sql
|
||||
SELECT arrayMax([1, 2, 4]) AS res;
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
```text
|
||||
┌─res─┐
|
||||
│ 4 │
|
||||
└─────┘
|
||||
```
|
||||
|
||||
Запрос:
|
||||
|
||||
```sql
|
||||
SELECT arrayMax(x -> (-x), [1, 2, 4]) AS res;
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
```text
|
||||
┌─res─┐
|
||||
│ -1 │
|
||||
└─────┘
|
||||
```
|
||||
|
||||
## arraySum {#array-sum}
|
||||
|
||||
Возвращает сумму элементов в исходном массиве.
|
||||
|
||||
Если передана функция `func`, возвращается сумма элементов массива, преобразованных этой функцией.
|
||||
|
||||
Функция `arraySum` является [функцией высшего порядка](../../sql-reference/functions/index.md#higher-order-functions) — в качестве первого аргумента ей можно передать лямбда-функцию.
|
||||
|
||||
**Синтаксис**
|
||||
|
||||
```sql
|
||||
arraySum([func,] arr)
|
||||
```
|
||||
|
||||
**Параметры**
|
||||
|
||||
- `func` — функция. [Expression](../../sql-reference/data-types/special-data-types/expression.md).
|
||||
- `arr` — массив. [Array](../../sql-reference/data-types/array.md).
|
||||
|
||||
**Возвращаемое значение**
|
||||
|
||||
- Сумма значений функции (или сумма элементов массива).
|
||||
|
||||
Тип: для Decimal чисел в исходном массиве (если функция `func` была передана, то для чисел, преобразованных ею) — [Decimal128](../../sql-reference/data-types/decimal.md), для чисел с плавающей точкой — [Float64](../../sql-reference/data-types/float.md), для беззнаковых целых чисел — [UInt64](../../sql-reference/data-types/int-uint.md), для целых чисел со знаком — [Int64](../../sql-reference/data-types/int-uint.md).
|
||||
|
||||
**Примеры**
|
||||
|
||||
Запрос:
|
||||
|
||||
```sql
|
||||
SELECT arraySum([2, 3]) AS res;
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
```text
|
||||
┌─res─┐
|
||||
│ 5 │
|
||||
└─────┘
|
||||
```
|
||||
|
||||
Запрос:
|
||||
|
||||
```sql
|
||||
SELECT arraySum(x -> x*x, [2, 3]) AS res;
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
```text
|
||||
┌─res─┐
|
||||
│ 13 │
|
||||
└─────┘
|
||||
```
|
||||
|
||||
## arrayAvg {#array-avg}
|
||||
|
||||
Возвращает среднее значение элементов в исходном массиве.
|
||||
|
||||
Если передана функция `func`, возвращается среднее значение элементов массива, преобразованных этой функцией.
|
||||
|
||||
Функция `arrayAvg` является [функцией высшего порядка](../../sql-reference/functions/index.md#higher-order-functions) — в качестве первого аргумента ей можно передать лямбда-функцию.
|
||||
|
||||
**Синтаксис**
|
||||
|
||||
```sql
|
||||
arrayAvg([func,] arr)
|
||||
```
|
||||
|
||||
**Параметры**
|
||||
|
||||
- `func` — функция. [Expression](../../sql-reference/data-types/special-data-types/expression.md).
|
||||
- `arr` — массив. [Array](../../sql-reference/data-types/array.md).
|
||||
|
||||
**Возвращаемое значение**
|
||||
|
||||
- Среднее значение функции (или среднее значение элементов массива).
|
||||
|
||||
Тип: [Float64](../../sql-reference/data-types/float.md).
|
||||
|
||||
**Примеры**
|
||||
|
||||
Запрос:
|
||||
|
||||
```sql
|
||||
SELECT arrayAvg([1, 2, 4]) AS res;
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
```text
|
||||
┌────────────────res─┐
|
||||
│ 2.3333333333333335 │
|
||||
└────────────────────┘
|
||||
```
|
||||
|
||||
Запрос:
|
||||
|
||||
```sql
|
||||
SELECT arrayAvg(x -> (x * x), [2, 4]) AS res;
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
```text
|
||||
┌─res─┐
|
||||
│ 10 │
|
||||
└─────┘
|
||||
```
|
||||
|
||||
## arrayCumSum(\[func,\] arr1, …) {#arraycumsumfunc-arr1}
|
||||
|
||||
|
||||
@ -183,6 +183,103 @@ SELECT visibleWidth(NULL)
|
||||
Получить размер блока.
|
||||
В ClickHouse выполнение запроса всегда идёт по блокам (наборам кусочков столбцов). Функция позволяет получить размер блока, для которого её вызвали.
|
||||
|
||||
## byteSize {#function-bytesize}
|
||||
|
||||
Возвращает оценку в байтах размера аргументов в памяти в несжатом виде.
|
||||
|
||||
**Синтаксис**
|
||||
|
||||
```sql
|
||||
byteSize(argument [, ...])
|
||||
```
|
||||
|
||||
**Параметры**
|
||||
|
||||
- `argument` — значение.
|
||||
|
||||
**Возвращаемое значение**
|
||||
|
||||
- Оценка размера аргументов в памяти в байтах.
|
||||
|
||||
Тип: [UInt64](../../sql-reference/data-types/int-uint.md).
|
||||
|
||||
**Примеры**
|
||||
|
||||
Для аргументов типа [String](../../sql-reference/data-types/string.md) функция возвращает длину строки + 9 (нуль-терминатор + длина)
|
||||
|
||||
Запрос:
|
||||
|
||||
```sql
|
||||
SELECT byteSize('string');
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
```text
|
||||
┌─byteSize('string')─┐
|
||||
│ 15 │
|
||||
└────────────────────┘
|
||||
```
|
||||
|
||||
Запрос:
|
||||
|
||||
```sql
|
||||
CREATE TABLE test
|
||||
(
|
||||
`key` Int32,
|
||||
`u8` UInt8,
|
||||
`u16` UInt16,
|
||||
`u32` UInt32,
|
||||
`u64` UInt64,
|
||||
`i8` Int8,
|
||||
`i16` Int16,
|
||||
`i32` Int32,
|
||||
`i64` Int64,
|
||||
`f32` Float32,
|
||||
`f64` Float64
|
||||
)
|
||||
ENGINE = MergeTree
|
||||
ORDER BY key;
|
||||
|
||||
INSERT INTO test VALUES(1, 8, 16, 32, 64, -8, -16, -32, -64, 32.32, 64.64);
|
||||
|
||||
SELECT key, byteSize(u8) AS `byteSize(UInt8)`, byteSize(u16) AS `byteSize(UInt16)`, byteSize(u32) AS `byteSize(UInt32)`, byteSize(u64) AS `byteSize(UInt64)`, byteSize(i8) AS `byteSize(Int8)`, byteSize(i16) AS `byteSize(Int16)`, byteSize(i32) AS `byteSize(Int32)`, byteSize(i64) AS `byteSize(Int64)`, byteSize(f32) AS `byteSize(Float32)`, byteSize(f64) AS `byteSize(Float64)` FROM test ORDER BY key ASC FORMAT Vertical;
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
Row 1:
|
||||
──────
|
||||
key: 1
|
||||
byteSize(UInt8): 1
|
||||
byteSize(UInt16): 2
|
||||
byteSize(UInt32): 4
|
||||
byteSize(UInt64): 8
|
||||
byteSize(Int8): 1
|
||||
byteSize(Int16): 2
|
||||
byteSize(Int32): 4
|
||||
byteSize(Int64): 8
|
||||
byteSize(Float32): 4
|
||||
byteSize(Float64): 8
|
||||
```
|
||||
|
||||
Если функция принимает несколько аргументов, то она возвращает их совокупный размер в байтах.
|
||||
|
||||
Запрос:
|
||||
|
||||
```sql
|
||||
SELECT byteSize(NULL, 1, 0.3, '');
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
```text
|
||||
┌─byteSize(NULL, 1, 0.3, '')─┐
|
||||
│ 19 │
|
||||
└────────────────────────────┘
|
||||
```
|
||||
|
||||
## materialize(x) {#materializex}
|
||||
|
||||
Превращает константу в полноценный столбец, содержащий только одно значение.
|
||||
|
||||
@ -13,8 +13,6 @@ toc_title: "\u0424\u0443\u043d\u043a\u0446\u0438\u0438\u0020\u043f\u043e\u0438\u
|
||||
|
||||
Возвращает позицию (в байтах) найденной подстроки в строке, начиная с 1, или 0, если подстрока не найдена.
|
||||
|
||||
Работает при допущении, что строка содержит набор байт, представляющий текст в однобайтовой кодировке. Если допущение не выполнено — то возвращает неопределенный результат (не кидает исключение). Если символ может быть представлен с помощью двух байтов, он будет представлен двумя байтами и так далее.
|
||||
|
||||
Для поиска без учета регистра используйте функцию [positionCaseInsensitive](#positioncaseinsensitive).
|
||||
|
||||
**Синтаксис**
|
||||
|
||||
@ -37,7 +37,7 @@ CREATE TABLE [IF NOT EXISTS] [db.]table_name [ON CLUSTER cluster]
|
||||
VersionedCollapsingMergeTree(sign, version)
|
||||
```
|
||||
|
||||
- `sign` — 指定行类型的列名: `1` 是一个 “state” 行, `-1` 是一个 “cancel” 划
|
||||
- `sign` — 指定行类型的列名: `1` 是一个 “state” 行, `-1` 是一个 “cancel” 行
|
||||
|
||||
列数据类型应为 `Int8`.
|
||||
|
||||
|
||||
@ -1310,3 +1310,14 @@ SELECT idx, i FROM null_in WHERE i IN (1, NULL) SETTINGS transform_null_in = 1;
|
||||
**另请参阅**
|
||||
|
||||
- [IN 运算符中的 NULL 处理](../../sql-reference/operators/in.md#in-null-processing)
|
||||
|
||||
## max_final_threads {#max-final-threads}
|
||||
|
||||
设置使用[FINAL](../../sql-reference/statements/select/from.md#select-from-final) 限定符的`SELECT`查询, 在数据读取阶段的最大并发线程数。
|
||||
|
||||
可能的值:
|
||||
|
||||
- 正整数。
|
||||
- 0 or 1 — 禁用。 此时`SELECT` 查询单线程执行。
|
||||
|
||||
默认值: `16`。
|
||||
|
||||
@ -6,12 +6,16 @@ machine_translated_rev: 5decc73b5dc60054f19087d3690c4eb99446a6c3
|
||||
# 系统。动物园管理员 {#system-zookeeper}
|
||||
|
||||
如果未配置ZooKeeper，则表不存在。 允许从配置中定义的ZooKeeper集群读取数据。
|
||||
查询必须具有 ‘path’ WHERE子句中的平等条件。 这是ZooKeeper中您想要获取数据的孩子的路径。
|
||||
查询必须具有 ‘path’ WHERE子句中的相等条件或者在某个集合中的条件。 这是ZooKeeper中您想要获取数据的孩子的路径。
|
||||
|
||||
查询 `SELECT * FROM system.zookeeper WHERE path = '/clickhouse'` 输出对所有孩子的数据 `/clickhouse` 节点。
|
||||
要输出所有根节点的数据，write path= ‘/’.
|
||||
如果在指定的路径 ‘path’ 不存在，将引发异常。
|
||||
|
||||
查询`SELECT * FROM system.zookeeper WHERE path IN ('/', '/clickhouse')` 输出`/` 和 `/clickhouse`节点上所有子节点的数据。
|
||||
如果在指定的 ‘path’ 集合中有不存在的路径，将引发异常。
|
||||
它可以用来做一批ZooKeeper路径查询。
|
||||
|
||||
列:
|
||||
|
||||
- `name` (String) — The name of the node.
|
||||
|
||||
@ -1,11 +1,12 @@
|
||||
---
|
||||
toc_folder_title: 聚合函数
|
||||
toc_priority: 33
|
||||
toc_title: 聚合函数
|
||||
toc_title: 简介
|
||||
---
|
||||
|
||||
# 聚合函数 {#aggregate-functions}
|
||||
|
||||
聚合函数在 [正常](http://www.sql-tutorial.com/sql-aggregate-functions-sql-tutorial) 方式如预期的数据库专家。
|
||||
聚合函数如数据库专家预期的方式 [正常](http://www.sql-tutorial.com/sql-aggregate-functions-sql-tutorial) 工作。
|
||||
|
||||
ClickHouse还支持:
|
||||
|
||||
@ -14,7 +15,7 @@ ClickHouse还支持:
|
||||
|
||||
## 空处理 {#null-processing}
|
||||
|
||||
在聚合过程中，所有 `NULL`s被跳过。
|
||||
在聚合过程中，所有 `NULL` 被跳过。
|
||||
|
||||
**例:**
|
||||
|
||||
@ -30,7 +31,7 @@ ClickHouse还支持:
|
||||
└───┴──────┘
|
||||
```
|
||||
|
||||
比方说，你需要在总的值 `y` 列:
|
||||
比方说，你需要计算 `y` 列的总数:
|
||||
|
||||
``` sql
|
||||
SELECT sum(y) FROM t_null_big
|
||||
@ -40,9 +41,8 @@ SELECT sum(y) FROM t_null_big
|
||||
│ 7 │
|
||||
└────────┘
|
||||
|
||||
该 `sum` 函数解释 `NULL` 作为 `0`. 特别是，这意味着，如果函数接收输入的选择，其中所有的值 `NULL`，那么结果将是 `0`，不 `NULL`.
|
||||
|
||||
现在你可以使用 `groupArray` 函数从创建一个数组 `y` 列:
|
||||
现在你可以使用 `groupArray` 函数用 `y` 列创建一个数组:
|
||||
|
||||
``` sql
|
||||
SELECT groupArray(y) FROM t_null_big
|
||||
@ -54,6 +54,6 @@ SELECT groupArray(y) FROM t_null_big
|
||||
└───────────────┘
|
||||
```
|
||||
|
||||
`groupArray` 不包括 `NULL` 在生成的数组中。
|
||||
在 `groupArray` 生成的数组中不包括 `NULL`。
|
||||
|
||||
[原始文章](https://clickhouse.tech/docs/en/query_language/agg_functions/) <!--hide-->
|
||||
|
||||
@ -1,9 +1,9 @@
|
||||
---
|
||||
toc_priority: 36
|
||||
toc_title: 聚合函数
|
||||
toc_title: 参考手册
|
||||
---
|
||||
|
||||
# 聚合函数引用 {#aggregate-functions-reference}
|
||||
# 参考手册 {#aggregate-functions-reference}
|
||||
|
||||
## count {#agg_function-count}
|
||||
|
||||
|
||||
@ -25,11 +25,13 @@ toc_title: FROM
|
||||
- [Replicated](../../../engines/table-engines/mergetree-family/replication.md) 版本 `MergeTree` 引擎
|
||||
- [View](../../../engines/table-engines/special/view.md), [Buffer](../../../engines/table-engines/special/buffer.md), [Distributed](../../../engines/table-engines/special/distributed.md)，和 [MaterializedView](../../../engines/table-engines/special/materializedview.md) 在其他引擎上运行的引擎，只要是它们底层是 `MergeTree`-引擎表即可。
|
||||
|
||||
现在使用 `FINAL` 修饰符 的 `SELECT` 查询启用了并发执行, 这会快一点。但是仍然存在缺陷 (见下)。 [max_final_threads](../../../operations/settings/settings.md#max-final-threads) 设置使用的最大线程数限制。
|
||||
|
||||
### 缺点 {#drawbacks}
|
||||
|
||||
使用的查询 `FINAL` 执行速度不如类似的查询那么快，因为:
|
||||
使用的查询 `FINAL` 执行速度比类似的查询慢一点，因为:
|
||||
|
||||
- 查询在单个线程中执行，并在查询执行期间合并数据。
|
||||
- 在查询执行期间合并数据。
|
||||
- 查询与 `FINAL` 除了读取查询中指定的列之外，还读取主键列。
|
||||
|
||||
**在大多数情况下，避免使用 `FINAL`.** 常见的方法是使用假设后台进程的不同查询 `MergeTree` 引擎还没有发生，并通过应用聚合（例如，丢弃重复项）来处理它。 {## TODO: examples ##}
|
||||
|
||||
@ -1719,7 +1719,7 @@ private:
|
||||
}
|
||||
// Remember where the data ended. We use this info later to determine
|
||||
// where the next query begins.
|
||||
parsed_insert_query->end = data_in.buffer().begin() + data_in.count();
|
||||
parsed_insert_query->end = parsed_insert_query->data + data_in.count();
|
||||
}
|
||||
else if (!is_interactive)
|
||||
{
|
||||
@ -1900,6 +1900,9 @@ private:
|
||||
|
||||
switch (packet.type)
|
||||
{
|
||||
case Protocol::Server::PartUUIDs:
|
||||
return true;
|
||||
|
||||
case Protocol::Server::Data:
|
||||
if (!cancelled)
|
||||
onData(packet.block);
|
||||
|
||||
@ -325,6 +325,51 @@ void QueryFuzzer::fuzzColumnLikeExpressionList(IAST * ast)
|
||||
// the generic recursion into IAST.children.
|
||||
}
|
||||
|
||||
void QueryFuzzer::fuzzWindowFrame(WindowFrame & frame)
|
||||
{
|
||||
switch (fuzz_rand() % 40)
|
||||
{
|
||||
case 0:
|
||||
{
|
||||
const auto r = fuzz_rand() % 3;
|
||||
frame.type = r == 0 ? WindowFrame::FrameType::Rows
|
||||
: r == 1 ? WindowFrame::FrameType::Range
|
||||
: WindowFrame::FrameType::Groups;
|
||||
break;
|
||||
}
|
||||
case 1:
|
||||
{
|
||||
const auto r = fuzz_rand() % 3;
|
||||
frame.begin_type = r == 0 ? WindowFrame::BoundaryType::Unbounded
|
||||
: r == 1 ? WindowFrame::BoundaryType::Current
|
||||
: WindowFrame::BoundaryType::Offset;
|
||||
break;
|
||||
}
|
||||
case 2:
|
||||
{
|
||||
const auto r = fuzz_rand() % 3;
|
||||
frame.end_type = r == 0 ? WindowFrame::BoundaryType::Unbounded
|
||||
: r == 1 ? WindowFrame::BoundaryType::Current
|
||||
: WindowFrame::BoundaryType::Offset;
|
||||
break;
|
||||
}
|
||||
case 3:
|
||||
{
|
||||
frame.begin_offset = getRandomField(0).get<Int64>();
|
||||
break;
|
||||
}
|
||||
case 4:
|
||||
{
|
||||
frame.end_offset = getRandomField(0).get<Int64>();
|
||||
break;
|
||||
}
|
||||
default:
|
||||
break;
|
||||
}
|
||||
|
||||
frame.is_default = (frame == WindowFrame{});
|
||||
}
|
||||
|
||||
void QueryFuzzer::fuzz(ASTs & asts)
|
||||
{
|
||||
for (auto & ast : asts)
|
||||
@ -409,6 +454,7 @@ void QueryFuzzer::fuzz(ASTPtr & ast)
|
||||
auto & def = fn->window_definition->as<ASTWindowDefinition &>();
|
||||
fuzzColumnLikeExpressionList(def.partition_by.get());
|
||||
fuzzOrderByList(def.order_by.get());
|
||||
fuzzWindowFrame(def.frame);
|
||||
}
|
||||
|
||||
fuzz(fn->children);
|
||||
@ -421,6 +467,23 @@ void QueryFuzzer::fuzz(ASTPtr & ast)
|
||||
|
||||
fuzz(select->children);
|
||||
}
|
||||
/*
|
||||
* The time to fuzz the settings has not yet come.
|
||||
* Apparently we don't have any infractructure to validate the values of
|
||||
* the settings, and the first query with max_block_size = -1 breaks
|
||||
* because of overflows here and there.
|
||||
*//*
|
||||
* else if (auto * set = typeid_cast<ASTSetQuery *>(ast.get()))
|
||||
* {
|
||||
* for (auto & c : set->changes)
|
||||
* {
|
||||
* if (fuzz_rand() % 50 == 0)
|
||||
* {
|
||||
* c.value = fuzzField(c.value);
|
||||
* }
|
||||
* }
|
||||
* }
|
||||
*/
|
||||
else if (auto * literal = typeid_cast<ASTLiteral *>(ast.get()))
|
||||
{
|
||||
// There is a caveat with fuzzing the children: many ASTs also keep the
|
||||
|
||||
@ -14,6 +14,7 @@ namespace DB
|
||||
|
||||
class ASTExpressionList;
|
||||
class ASTOrderByElement;
|
||||
struct WindowFrame;
|
||||
|
||||
/*
|
||||
* This is an AST-based query fuzzer that makes random modifications to query
|
||||
@ -65,6 +66,7 @@ struct QueryFuzzer
|
||||
void fuzzOrderByElement(ASTOrderByElement * elem);
|
||||
void fuzzOrderByList(IAST * ast);
|
||||
void fuzzColumnLikeExpressionList(IAST * ast);
|
||||
void fuzzWindowFrame(WindowFrame & frame);
|
||||
void fuzz(ASTs & asts);
|
||||
void fuzz(ASTPtr & ast);
|
||||
void collectFuzzInfoMain(const ASTPtr ast);
|
||||
|
||||
@ -1,5 +1,6 @@
|
||||
#include "Suggest.h"
|
||||
|
||||
#include <Core/Settings.h>
|
||||
#include <Columns/ColumnString.h>
|
||||
#include <Common/typeid_cast.h>
|
||||
|
||||
@ -86,6 +87,9 @@ Suggest::Suggest()
|
||||
|
||||
void Suggest::loadImpl(Connection & connection, const ConnectionTimeouts & timeouts, size_t suggestion_limit)
|
||||
{
|
||||
/// NOTE: Once you will update the completion list,
|
||||
/// do not forget to update 01676_clickhouse_client_autocomplete.sh
|
||||
|
||||
std::stringstream query; // STYLE_CHECK_ALLOW_STD_STRING_STREAM
|
||||
query << "SELECT DISTINCT arrayJoin(extractAll(name, '[\\\\w_]{2,}')) AS res FROM ("
|
||||
"SELECT name FROM system.functions"
|
||||
@ -104,6 +108,18 @@ void Suggest::loadImpl(Connection & connection, const ConnectionTimeouts & timeo
|
||||
" UNION ALL "
|
||||
"SELECT cluster FROM system.clusters"
|
||||
" UNION ALL "
|
||||
"SELECT name FROM system.errors"
|
||||
" UNION ALL "
|
||||
"SELECT event FROM system.events"
|
||||
" UNION ALL "
|
||||
"SELECT metric FROM system.asynchronous_metrics"
|
||||
" UNION ALL "
|
||||
"SELECT metric FROM system.metrics"
|
||||
" UNION ALL "
|
||||
"SELECT macro FROM system.macros"
|
||||
" UNION ALL "
|
||||
"SELECT policy_name FROM system.storage_policies"
|
||||
" UNION ALL "
|
||||
"SELECT concat(func.name, comb.name) FROM system.functions AS func CROSS JOIN system.aggregate_function_combinators AS comb WHERE is_aggregate";
|
||||
|
||||
/// The user may disable loading of databases, tables, columns by setting suggestion_limit to zero.
|
||||
@ -123,12 +139,17 @@ void Suggest::loadImpl(Connection & connection, const ConnectionTimeouts & timeo
|
||||
|
||||
query << ") WHERE notEmpty(res)";
|
||||
|
||||
fetch(connection, timeouts, query.str());
|
||||
Settings settings;
|
||||
/// To show all rows from:
|
||||
/// - system.errors
|
||||
/// - system.events
|
||||
settings.system_events_show_zero_values = true;
|
||||
fetch(connection, timeouts, query.str(), settings);
|
||||
}
|
||||
|
||||
void Suggest::fetch(Connection & connection, const ConnectionTimeouts & timeouts, const std::string & query)
|
||||
void Suggest::fetch(Connection & connection, const ConnectionTimeouts & timeouts, const std::string & query, Settings & settings)
|
||||
{
|
||||
connection.sendQuery(timeouts, query);
|
||||
connection.sendQuery(timeouts, query, "" /* query_id */, QueryProcessingStage::Complete, &settings);
|
||||
|
||||
while (true)
|
||||
{
|
||||
|
||||
@ -33,7 +33,7 @@ public:
|
||||
private:
|
||||
|
||||
void loadImpl(Connection & connection, const ConnectionTimeouts & timeouts, size_t suggestion_limit);
|
||||
void fetch(Connection & connection, const ConnectionTimeouts & timeouts, const std::string & query);
|
||||
void fetch(Connection & connection, const ConnectionTimeouts & timeouts, const std::string & query, Settings & settings);
|
||||
void fillWordsFromBlock(const Block & block);
|
||||
|
||||
/// Words are fetched asynchronously.
|
||||
|
||||
@ -316,9 +316,6 @@ void ClusterCopier::process(const ConnectionTimeouts & timeouts)
|
||||
}
|
||||
}
|
||||
|
||||
/// Delete helping tables in both cases (whole table is done or not)
|
||||
dropHelpingTables(task_table);
|
||||
|
||||
if (!table_is_done)
|
||||
{
|
||||
throw Exception("Too many tries to process table " + task_table.table_id + ". Abort remaining execution",
|
||||
@ -642,7 +639,7 @@ TaskStatus ClusterCopier::tryMoveAllPiecesToDestinationTable(const TaskTable & t
|
||||
query_deduplicate_ast_string += " OPTIMIZE TABLE " + getQuotedTable(original_table) +
|
||||
((partition_name == "'all'") ? " PARTITION ID " : " PARTITION ") + partition_name + " DEDUPLICATE;";
|
||||
|
||||
LOG_DEBUG(log, "Executing OPTIMIZE DEDUPLICATE query: {}", query_alter_ast_string);
|
||||
LOG_DEBUG(log, "Executing OPTIMIZE DEDUPLICATE query: {}", query_deduplicate_ast_string);
|
||||
|
||||
UInt64 num_nodes = executeQueryOnCluster(
|
||||
task_table.cluster_push,
|
||||
@ -1044,6 +1041,11 @@ bool ClusterCopier::tryProcessTable(const ConnectionTimeouts & timeouts, TaskTab
|
||||
{
|
||||
LOG_INFO(log, "Table {} is not processed yet.Copied {} of {}, will retry", task_table.table_id, finished_partitions, required_partitions);
|
||||
}
|
||||
else
|
||||
{
|
||||
/// Delete helping tables in case that whole table is done
|
||||
dropHelpingTables(task_table);
|
||||
}
|
||||
|
||||
return table_is_done;
|
||||
}
|
||||
|
||||
@ -31,6 +31,8 @@ struct Quota : public IAccessEntity
|
||||
enum ResourceType
|
||||
{
|
||||
QUERIES, /// Number of queries.
|
||||
QUERY_SELECTS, /// Number of select queries.
|
||||
QUERY_INSERTS, /// Number of inserts queries.
|
||||
ERRORS, /// Number of queries with exceptions.
|
||||
RESULT_ROWS, /// Number of rows returned as result.
|
||||
RESULT_BYTES, /// Number of bytes returned as result.
|
||||
@ -152,6 +154,16 @@ inline const Quota::ResourceTypeInfo & Quota::ResourceTypeInfo::get(ResourceType
|
||||
static const auto info = make_info("QUERIES", 1);
|
||||
return info;
|
||||
}
|
||||
case Quota::QUERY_SELECTS:
|
||||
{
|
||||
static const auto info = make_info("QUERY_SELECTS", 1);
|
||||
return info;
|
||||
}
|
||||
case Quota::QUERY_INSERTS:
|
||||
{
|
||||
static const auto info = make_info("QUERY_INSERTS", 1);
|
||||
return info;
|
||||
}
|
||||
case Quota::ERRORS:
|
||||
{
|
||||
static const auto info = make_info("ERRORS", 1);
|
||||
|
||||
@ -60,7 +60,7 @@ public:
|
||||
return std::make_shared<DataTypeUInt8>();
|
||||
}
|
||||
|
||||
void create(AggregateDataPtr place) const override
|
||||
void create(AggregateDataPtr __restrict place) const override
|
||||
{
|
||||
if (std::uniform_real_distribution<>(0.0, 1.0)(thread_local_rng) <= throw_probability)
|
||||
throw Exception("Aggregate function " + getName() + " has thrown exception successfully", ErrorCodes::AGGREGATE_FUNCTION_THROW);
|
||||
@ -68,7 +68,7 @@ public:
|
||||
new (place) Data;
|
||||
}
|
||||
|
||||
void destroy(AggregateDataPtr place) const noexcept override
|
||||
void destroy(AggregateDataPtr __restrict place) const noexcept override
|
||||
{
|
||||
data(place).~Data();
|
||||
}
|
||||
|
||||
@ -70,25 +70,25 @@ public:
|
||||
return type_res;
|
||||
}
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
{
|
||||
if (this->data(place).value.changeIfBetter(*columns[1], row_num, arena))
|
||||
this->data(place).result.change(*columns[0], row_num, arena);
|
||||
}
|
||||
|
||||
void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena * arena) const override
|
||||
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena * arena) const override
|
||||
{
|
||||
if (this->data(place).value.changeIfBetter(this->data(rhs).value, arena))
|
||||
this->data(place).result.change(this->data(rhs).result, arena);
|
||||
}
|
||||
|
||||
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override
|
||||
{
|
||||
this->data(place).result.write(buf, *type_res);
|
||||
this->data(place).value.write(buf, *type_val);
|
||||
}
|
||||
|
||||
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena * arena) const override
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena * arena) const override
|
||||
{
|
||||
this->data(place).result.read(buf, *type_res, arena);
|
||||
this->data(place).value.read(buf, *type_val, arena);
|
||||
@ -96,7 +96,7 @@ public:
|
||||
|
||||
bool allocatesMemoryInArena() const override { return Data::allocatesMemoryInArena(); }
|
||||
|
||||
void insertResultInto(AggregateDataPtr place, IColumn & to, Arena *) const override
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena *) const override
|
||||
{
|
||||
if (tuple_argument)
|
||||
{
|
||||
|
||||
@ -47,12 +47,12 @@ public:
|
||||
return nested_func->getReturnType();
|
||||
}
|
||||
|
||||
void create(AggregateDataPtr place) const override
|
||||
void create(AggregateDataPtr __restrict place) const override
|
||||
{
|
||||
nested_func->create(place);
|
||||
}
|
||||
|
||||
void destroy(AggregateDataPtr place) const noexcept override
|
||||
void destroy(AggregateDataPtr __restrict place) const noexcept override
|
||||
{
|
||||
nested_func->destroy(place);
|
||||
}
|
||||
@ -77,7 +77,7 @@ public:
|
||||
return nested_func->isState();
|
||||
}
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
{
|
||||
const IColumn * nested[num_arguments];
|
||||
|
||||
@ -104,22 +104,22 @@ public:
|
||||
nested_func->add(place, nested, i, arena);
|
||||
}
|
||||
|
||||
void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena * arena) const override
|
||||
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena * arena) const override
|
||||
{
|
||||
nested_func->merge(place, rhs, arena);
|
||||
}
|
||||
|
||||
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override
|
||||
{
|
||||
nested_func->serialize(place, buf);
|
||||
}
|
||||
|
||||
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena * arena) const override
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena * arena) const override
|
||||
{
|
||||
nested_func->deserialize(place, buf, arena);
|
||||
}
|
||||
|
||||
void insertResultInto(AggregateDataPtr place, IColumn & to, Arena * arena) const override
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena * arena) const override
|
||||
{
|
||||
nested_func->insertResultInto(place, to, arena);
|
||||
}
|
||||
|
||||
@ -98,13 +98,13 @@ public:
|
||||
|
||||
DataTypePtr getReturnType() const final { return std::make_shared<DataTypeNumber<Float64>>(); }
|
||||
|
||||
void NO_SANITIZE_UNDEFINED merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
void NO_SANITIZE_UNDEFINED merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
{
|
||||
this->data(place).numerator += this->data(rhs).numerator;
|
||||
this->data(place).denominator += this->data(rhs).denominator;
|
||||
}
|
||||
|
||||
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override
|
||||
{
|
||||
writeBinary(this->data(place).numerator, buf);
|
||||
|
||||
@ -114,7 +114,7 @@ public:
|
||||
writeBinary(this->data(place).denominator, buf);
|
||||
}
|
||||
|
||||
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena *) const override
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena *) const override
|
||||
{
|
||||
readBinary(this->data(place).numerator, buf);
|
||||
|
||||
@ -124,7 +124,7 @@ public:
|
||||
readBinary(this->data(place).denominator, buf);
|
||||
}
|
||||
|
||||
void insertResultInto(AggregateDataPtr place, IColumn & to, Arena *) const override
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena *) const override
|
||||
{
|
||||
if constexpr (IsDecimalNumber<Numerator> || IsDecimalNumber<Denominator>)
|
||||
assert_cast<ColumnVector<Float64> &>(to).getData().push_back(
|
||||
@ -148,7 +148,7 @@ class AggregateFunctionAvg final : public AggregateFunctionAvgBase<AvgFieldType<
|
||||
public:
|
||||
using AggregateFunctionAvgBase<AvgFieldType<T>, UInt64, AggregateFunctionAvg<T>>::AggregateFunctionAvgBase;
|
||||
|
||||
void NO_SANITIZE_UNDEFINED add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena *) const final
|
||||
void NO_SANITIZE_UNDEFINED add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena *) const final
|
||||
{
|
||||
this->data(place).numerator += static_cast<const DecimalOrVectorCol<T> &>(*columns[0]).getData()[row_num];
|
||||
++this->data(place).denominator;
|
||||
|
||||
@ -28,7 +28,7 @@ public:
|
||||
|
||||
using ValueT = MaxFieldType<Value, Weight>;
|
||||
|
||||
void NO_SANITIZE_UNDEFINED add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena *) const override
|
||||
void NO_SANITIZE_UNDEFINED add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena *) const override
|
||||
{
|
||||
const auto& weights = static_cast<const DecimalOrVectorCol<Weight> &>(*columns[1]);
|
||||
|
||||
|
||||
@ -54,27 +54,27 @@ public:
|
||||
return std::make_shared<DataTypeNumber<T>>();
|
||||
}
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena *) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena *) const override
|
||||
{
|
||||
this->data(place).update(assert_cast<const ColumnVector<T> &>(*columns[0]).getData()[row_num]);
|
||||
}
|
||||
|
||||
void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
{
|
||||
this->data(place).update(this->data(rhs).value);
|
||||
}
|
||||
|
||||
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override
|
||||
{
|
||||
writeBinary(this->data(place).value, buf);
|
||||
}
|
||||
|
||||
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena *) const override
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena *) const override
|
||||
{
|
||||
readBinary(this->data(place).value, buf);
|
||||
}
|
||||
|
||||
void insertResultInto(AggregateDataPtr place, IColumn & to, Arena *) const override
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena *) const override
|
||||
{
|
||||
assert_cast<ColumnVector<T> &>(to).getData().push_back(this->data(place).value);
|
||||
}
|
||||
|
||||
@ -127,7 +127,7 @@ public:
|
||||
return std::make_shared<DataTypeFloat64>();
|
||||
}
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn ** columns, const size_t row_num, Arena *) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, const size_t row_num, Arena *) const override
|
||||
{
|
||||
/// NOTE Slightly inefficient.
|
||||
const auto x = columns[0]->getFloat64(row_num);
|
||||
@ -135,22 +135,22 @@ public:
|
||||
data(place).add(x, y);
|
||||
}
|
||||
|
||||
void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
{
|
||||
data(place).merge(data(rhs));
|
||||
}
|
||||
|
||||
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override
|
||||
{
|
||||
data(place).serialize(buf);
|
||||
}
|
||||
|
||||
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena *) const override
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena *) const override
|
||||
{
|
||||
data(place).deserialize(buf);
|
||||
}
|
||||
|
||||
void insertResultInto(AggregateDataPtr place, IColumn & to, Arena *) const override
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena *) const override
|
||||
{
|
||||
assert_cast<ColumnFloat64 &>(to).getData().push_back(getBoundingRatio(data(place)));
|
||||
}
|
||||
|
||||
@ -33,7 +33,7 @@ public:
|
||||
return "categoricalInformationValue";
|
||||
}
|
||||
|
||||
void create(AggregateDataPtr place) const override
|
||||
void create(AggregateDataPtr __restrict place) const override
|
||||
{
|
||||
memset(place, 0, sizeOfData());
|
||||
}
|
||||
|
||||
@ -38,7 +38,7 @@ public:
|
||||
return std::make_shared<DataTypeUInt64>();
|
||||
}
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn **, size_t, Arena *) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn **, size_t, Arena *) const override
|
||||
{
|
||||
++data(place).count;
|
||||
}
|
||||
@ -76,28 +76,28 @@ public:
|
||||
}
|
||||
}
|
||||
|
||||
void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
{
|
||||
data(place).count += data(rhs).count;
|
||||
}
|
||||
|
||||
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override
|
||||
{
|
||||
writeVarUInt(data(place).count, buf);
|
||||
}
|
||||
|
||||
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena *) const override
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena *) const override
|
||||
{
|
||||
readVarUInt(data(place).count, buf);
|
||||
}
|
||||
|
||||
void insertResultInto(AggregateDataPtr place, IColumn & to, Arena *) const override
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena *) const override
|
||||
{
|
||||
assert_cast<ColumnUInt64 &>(to).getData().push_back(data(place).count);
|
||||
}
|
||||
|
||||
/// Reset the state to specified value. This function is not the part of common interface.
|
||||
void set(AggregateDataPtr place, UInt64 new_count)
|
||||
void set(AggregateDataPtr __restrict place, UInt64 new_count)
|
||||
{
|
||||
data(place).count = new_count;
|
||||
}
|
||||
@ -126,27 +126,27 @@ public:
|
||||
return std::make_shared<DataTypeUInt64>();
|
||||
}
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena *) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena *) const override
|
||||
{
|
||||
data(place).count += !assert_cast<const ColumnNullable &>(*columns[0]).isNullAt(row_num);
|
||||
}
|
||||
|
||||
void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
{
|
||||
data(place).count += data(rhs).count;
|
||||
}
|
||||
|
||||
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override
|
||||
{
|
||||
writeVarUInt(data(place).count, buf);
|
||||
}
|
||||
|
||||
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena *) const override
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena *) const override
|
||||
{
|
||||
readVarUInt(data(place).count, buf);
|
||||
}
|
||||
|
||||
void insertResultInto(AggregateDataPtr place, IColumn & to, Arena *) const override
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena *) const override
|
||||
{
|
||||
assert_cast<ColumnUInt64 &>(to).getData().push_back(data(place).count);
|
||||
}
|
||||
|
||||
@ -156,12 +156,12 @@ private:
|
||||
AggregateFunctionPtr nested_func;
|
||||
size_t arguments_num;
|
||||
|
||||
AggregateDataPtr getNestedPlace(AggregateDataPtr place) const noexcept
|
||||
AggregateDataPtr getNestedPlace(AggregateDataPtr __restrict place) const noexcept
|
||||
{
|
||||
return place + prefix_size;
|
||||
}
|
||||
|
||||
ConstAggregateDataPtr getNestedPlace(ConstAggregateDataPtr place) const noexcept
|
||||
ConstAggregateDataPtr getNestedPlace(ConstAggregateDataPtr __restrict place) const noexcept
|
||||
{
|
||||
return place + prefix_size;
|
||||
}
|
||||
@ -172,27 +172,27 @@ public:
|
||||
, nested_func(nested_func_)
|
||||
, arguments_num(arguments.size()) {}
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
{
|
||||
this->data(place).add(columns, arguments_num, row_num, arena);
|
||||
}
|
||||
|
||||
void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena * arena) const override
|
||||
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena * arena) const override
|
||||
{
|
||||
this->data(place).merge(this->data(rhs), arena);
|
||||
}
|
||||
|
||||
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override
|
||||
{
|
||||
this->data(place).serialize(buf);
|
||||
}
|
||||
|
||||
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena * arena) const override
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena * arena) const override
|
||||
{
|
||||
this->data(place).deserialize(buf, arena);
|
||||
}
|
||||
|
||||
void insertResultInto(AggregateDataPtr place, IColumn & to, Arena * arena) const override
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena * arena) const override
|
||||
{
|
||||
auto arguments = this->data(place).getArguments(this->argument_types);
|
||||
ColumnRawPtrs arguments_raw(arguments.size());
|
||||
@ -209,13 +209,13 @@ public:
|
||||
return prefix_size + nested_func->sizeOfData();
|
||||
}
|
||||
|
||||
void create(AggregateDataPtr place) const override
|
||||
void create(AggregateDataPtr __restrict place) const override
|
||||
{
|
||||
new (place) Data;
|
||||
nested_func->create(getNestedPlace(place));
|
||||
}
|
||||
|
||||
void destroy(AggregateDataPtr place) const noexcept override
|
||||
void destroy(AggregateDataPtr __restrict place) const noexcept override
|
||||
{
|
||||
this->data(place).~Data();
|
||||
nested_func->destroy(getNestedPlace(place));
|
||||
|
||||
@ -103,7 +103,7 @@ public:
|
||||
return std::make_shared<DataTypeNumber<Float64>>();
|
||||
}
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena *) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena *) const override
|
||||
{
|
||||
if constexpr (!std::is_same_v<UInt128, Value>)
|
||||
{
|
||||
@ -117,22 +117,22 @@ public:
|
||||
}
|
||||
}
|
||||
|
||||
void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
{
|
||||
this->data(place).merge(this->data(rhs));
|
||||
}
|
||||
|
||||
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override
|
||||
{
|
||||
this->data(const_cast<AggregateDataPtr>(place)).serialize(buf);
|
||||
}
|
||||
|
||||
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena *) const override
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena *) const override
|
||||
{
|
||||
this->data(place).deserialize(buf);
|
||||
}
|
||||
|
||||
void insertResultInto(AggregateDataPtr place, IColumn & to, Arena *) const override
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena *) const override
|
||||
{
|
||||
auto & column = assert_cast<ColumnVector<Float64> &>(to);
|
||||
column.getData().push_back(this->data(place).get());
|
||||
|
||||
@ -50,7 +50,7 @@ private:
|
||||
size_t nested_size_of_data = 0;
|
||||
size_t num_arguments;
|
||||
|
||||
AggregateFunctionForEachData & ensureAggregateData(AggregateDataPtr place, size_t new_size, Arena & arena) const
|
||||
AggregateFunctionForEachData & ensureAggregateData(AggregateDataPtr __restrict place, size_t new_size, Arena & arena) const
|
||||
{
|
||||
AggregateFunctionForEachData & state = data(place);
|
||||
|
||||
@ -128,7 +128,7 @@ public:
|
||||
return std::make_shared<DataTypeArray>(nested_func->getReturnType());
|
||||
}
|
||||
|
||||
void destroy(AggregateDataPtr place) const noexcept override
|
||||
void destroy(AggregateDataPtr __restrict place) const noexcept override
|
||||
{
|
||||
AggregateFunctionForEachData & state = data(place);
|
||||
|
||||
@ -145,7 +145,7 @@ public:
|
||||
return nested_func->hasTrivialDestructor();
|
||||
}
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
{
|
||||
const IColumn * nested[num_arguments];
|
||||
|
||||
@ -178,7 +178,7 @@ public:
|
||||
}
|
||||
}
|
||||
|
||||
void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena * arena) const override
|
||||
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena * arena) const override
|
||||
{
|
||||
const AggregateFunctionForEachData & rhs_state = data(rhs);
|
||||
AggregateFunctionForEachData & state = ensureAggregateData(place, rhs_state.dynamic_array_size, *arena);
|
||||
@ -195,7 +195,7 @@ public:
|
||||
}
|
||||
}
|
||||
|
||||
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override
|
||||
{
|
||||
const AggregateFunctionForEachData & state = data(place);
|
||||
writeBinary(state.dynamic_array_size, buf);
|
||||
@ -208,7 +208,7 @@ public:
|
||||
}
|
||||
}
|
||||
|
||||
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena * arena) const override
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena * arena) const override
|
||||
{
|
||||
AggregateFunctionForEachData & state = data(place);
|
||||
|
||||
@ -225,7 +225,7 @@ public:
|
||||
}
|
||||
}
|
||||
|
||||
void insertResultInto(AggregateDataPtr place, IColumn & to, Arena * arena) const override
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena * arena) const override
|
||||
{
|
||||
AggregateFunctionForEachData & state = data(place);
|
||||
|
||||
|
||||
@ -142,14 +142,14 @@ public:
|
||||
}
|
||||
}
|
||||
|
||||
void create(AggregateDataPtr place) const override
|
||||
void create(AggregateDataPtr __restrict place) const override
|
||||
{
|
||||
[[maybe_unused]] auto a = new (place) Data;
|
||||
if constexpr (Trait::sampler == Sampler::RNG)
|
||||
a->rng.seed(seed);
|
||||
}
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
{
|
||||
if constexpr (Trait::sampler == Sampler::NONE)
|
||||
{
|
||||
@ -176,7 +176,7 @@ public:
|
||||
// if constexpr (Trait::sampler == Sampler::DETERMINATOR)
|
||||
}
|
||||
|
||||
void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena * arena) const override
|
||||
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena * arena) const override
|
||||
{
|
||||
if constexpr (Trait::sampler == Sampler::NONE)
|
||||
{
|
||||
@ -235,7 +235,7 @@ public:
|
||||
// if constexpr (Trait::sampler == Sampler::DETERMINATOR)
|
||||
}
|
||||
|
||||
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override
|
||||
{
|
||||
const auto & value = this->data(place).value;
|
||||
size_t size = value.size();
|
||||
@ -254,7 +254,7 @@ public:
|
||||
// if constexpr (Trait::sampler == Sampler::DETERMINATOR)
|
||||
}
|
||||
|
||||
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena * arena) const override
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena * arena) const override
|
||||
{
|
||||
size_t size = 0;
|
||||
readVarUInt(size, buf);
|
||||
@ -283,7 +283,7 @@ public:
|
||||
// if constexpr (Trait::sampler == Sampler::DETERMINATOR)
|
||||
}
|
||||
|
||||
void insertResultInto(AggregateDataPtr place, IColumn & to, Arena *) const override
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena *) const override
|
||||
{
|
||||
const auto & value = this->data(place).value;
|
||||
size_t size = value.size();
|
||||
@ -416,8 +416,8 @@ class GroupArrayGeneralImpl final
|
||||
{
|
||||
static constexpr bool limit_num_elems = Trait::has_limit;
|
||||
using Data = GroupArrayGeneralData<Node, Trait::sampler != Sampler::NONE>;
|
||||
static Data & data(AggregateDataPtr place) { return *reinterpret_cast<Data *>(place); }
|
||||
static const Data & data(ConstAggregateDataPtr place) { return *reinterpret_cast<const Data *>(place); }
|
||||
static Data & data(AggregateDataPtr __restrict place) { return *reinterpret_cast<Data *>(place); }
|
||||
static const Data & data(ConstAggregateDataPtr __restrict place) { return *reinterpret_cast<const Data *>(place); }
|
||||
|
||||
DataTypePtr & data_type;
|
||||
UInt64 max_elems;
|
||||
@ -450,14 +450,14 @@ public:
|
||||
}
|
||||
}
|
||||
|
||||
void create(AggregateDataPtr place) const override
|
||||
void create(AggregateDataPtr __restrict place) const override
|
||||
{
|
||||
[[maybe_unused]] auto a = new (place) Data;
|
||||
if constexpr (Trait::sampler == Sampler::RNG)
|
||||
a->rng.seed(seed);
|
||||
}
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
{
|
||||
if constexpr (Trait::sampler == Sampler::NONE)
|
||||
{
|
||||
@ -485,7 +485,7 @@ public:
|
||||
// if constexpr (Trait::sampler == Sampler::DETERMINATOR)
|
||||
}
|
||||
|
||||
void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena * arena) const override
|
||||
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena * arena) const override
|
||||
{
|
||||
if constexpr (Trait::sampler == Sampler::NONE)
|
||||
mergeNoSampler(place, rhs, arena);
|
||||
@ -495,7 +495,7 @@ public:
|
||||
// else if constexpr (Trait::sampler == Sampler::DETERMINATOR)
|
||||
}
|
||||
|
||||
void ALWAYS_INLINE mergeNoSampler(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena * arena) const
|
||||
void ALWAYS_INLINE mergeNoSampler(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena * arena) const
|
||||
{
|
||||
if (data(rhs).value.empty()) /// rhs state is empty
|
||||
return;
|
||||
@ -517,7 +517,7 @@ public:
|
||||
a.push_back(b[i]->clone(arena), arena);
|
||||
}
|
||||
|
||||
void ALWAYS_INLINE mergeWithRNGSampler(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena * arena) const
|
||||
void ALWAYS_INLINE mergeWithRNGSampler(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena * arena) const
|
||||
{
|
||||
if (data(rhs).value.empty()) /// rhs state is empty
|
||||
return;
|
||||
@ -553,7 +553,7 @@ public:
|
||||
}
|
||||
}
|
||||
|
||||
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override
|
||||
{
|
||||
writeVarUInt(data(place).value.size(), buf);
|
||||
|
||||
@ -573,7 +573,7 @@ public:
|
||||
// if constexpr (Trait::sampler == Sampler::DETERMINATOR)
|
||||
}
|
||||
|
||||
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena * arena) const override
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena * arena) const override
|
||||
{
|
||||
UInt64 elems;
|
||||
readVarUInt(elems, buf);
|
||||
@ -606,7 +606,7 @@ public:
|
||||
// if constexpr (Trait::sampler == Sampler::DETERMINATOR)
|
||||
}
|
||||
|
||||
void insertResultInto(AggregateDataPtr place, IColumn & to, Arena *) const override
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena *) const override
|
||||
{
|
||||
auto & column_array = assert_cast<ColumnArray &>(to);
|
||||
|
||||
@ -692,8 +692,8 @@ class GroupArrayGeneralListImpl final
|
||||
{
|
||||
static constexpr bool limit_num_elems = Trait::has_limit;
|
||||
using Data = GroupArrayGeneralListData<Node>;
|
||||
static Data & data(AggregateDataPtr place) { return *reinterpret_cast<Data *>(place); }
|
||||
static const Data & data(ConstAggregateDataPtr place) { return *reinterpret_cast<const Data *>(place); }
|
||||
static Data & data(AggregateDataPtr __restrict place) { return *reinterpret_cast<Data *>(place); }
|
||||
static const Data & data(ConstAggregateDataPtr __restrict place) { return *reinterpret_cast<const Data *>(place); }
|
||||
|
||||
DataTypePtr & data_type;
|
||||
UInt64 max_elems;
|
||||
@ -710,7 +710,7 @@ public:
|
||||
|
||||
DataTypePtr getReturnType() const override { return std::make_shared<DataTypeArray>(data_type); }
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
{
|
||||
if (limit_num_elems && data(place).elems >= max_elems)
|
||||
return;
|
||||
@ -731,7 +731,7 @@ public:
|
||||
++data(place).elems;
|
||||
}
|
||||
|
||||
void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena * arena) const override
|
||||
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena * arena) const override
|
||||
{
|
||||
/// It is sadly, but rhs's Arena could be destroyed
|
||||
|
||||
@ -780,7 +780,7 @@ public:
|
||||
data(place).elems = new_elems;
|
||||
}
|
||||
|
||||
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override
|
||||
{
|
||||
writeVarUInt(data(place).elems, buf);
|
||||
|
||||
@ -792,7 +792,7 @@ public:
|
||||
}
|
||||
}
|
||||
|
||||
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena * arena) const override
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena * arena) const override
|
||||
{
|
||||
UInt64 elems;
|
||||
readVarUInt(elems, buf);
|
||||
@ -821,7 +821,7 @@ public:
|
||||
data(place).last = prev;
|
||||
}
|
||||
|
||||
void insertResultInto(AggregateDataPtr place, IColumn & to, Arena *) const override
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena *) const override
|
||||
{
|
||||
auto & column_array = assert_cast<ColumnArray &>(to);
|
||||
|
||||
|
||||
@ -102,7 +102,7 @@ public:
|
||||
return std::make_shared<DataTypeArray>(type);
|
||||
}
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena *) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena *) const override
|
||||
{
|
||||
/// TODO Do positions need to be 1-based for this function?
|
||||
size_t position = columns[1]->getUInt(row_num);
|
||||
@ -126,7 +126,7 @@ public:
|
||||
columns[0]->get(row_num, arr[position]);
|
||||
}
|
||||
|
||||
void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
{
|
||||
Array & arr_lhs = data(place).value;
|
||||
const Array & arr_rhs = data(rhs).value;
|
||||
@ -139,7 +139,7 @@ public:
|
||||
arr_lhs[i] = arr_rhs[i];
|
||||
}
|
||||
|
||||
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override
|
||||
{
|
||||
const Array & arr = data(place).value;
|
||||
size_t size = arr.size();
|
||||
@ -159,7 +159,7 @@ public:
|
||||
}
|
||||
}
|
||||
|
||||
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena *) const override
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena *) const override
|
||||
{
|
||||
size_t size = 0;
|
||||
readVarUInt(size, buf);
|
||||
@ -179,7 +179,7 @@ public:
|
||||
}
|
||||
}
|
||||
|
||||
void insertResultInto(AggregateDataPtr place, IColumn & to, Arena *) const override
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena *) const override
|
||||
{
|
||||
ColumnArray & to_array = assert_cast<ColumnArray &>(to);
|
||||
IColumn & to_data = to_array.getData();
|
||||
|
||||
@ -114,13 +114,13 @@ public:
|
||||
return std::make_shared<DataTypeArray>(std::make_shared<DataTypeResult>());
|
||||
}
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
{
|
||||
auto value = static_cast<const ColumnSource &>(*columns[0]).getData()[row_num];
|
||||
this->data(place).add(static_cast<ResultT>(value), arena);
|
||||
}
|
||||
|
||||
void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena * arena) const override
|
||||
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena * arena) const override
|
||||
{
|
||||
auto & cur_elems = this->data(place);
|
||||
auto & rhs_elems = this->data(rhs);
|
||||
@ -138,7 +138,7 @@ public:
|
||||
cur_elems.sum += rhs_elems.sum;
|
||||
}
|
||||
|
||||
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override
|
||||
{
|
||||
const auto & value = this->data(place).value;
|
||||
size_t size = value.size();
|
||||
@ -146,7 +146,7 @@ public:
|
||||
buf.write(reinterpret_cast<const char *>(value.data()), size * sizeof(value[0]));
|
||||
}
|
||||
|
||||
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena * arena) const override
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena * arena) const override
|
||||
{
|
||||
size_t size = 0;
|
||||
readVarUInt(size, buf);
|
||||
@ -163,7 +163,7 @@ public:
|
||||
}
|
||||
}
|
||||
|
||||
void insertResultInto(AggregateDataPtr place, IColumn & to, Arena *) const override
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena *) const override
|
||||
{
|
||||
const auto & data = this->data(place);
|
||||
size_t size = data.value.size();
|
||||
|
||||
@ -22,21 +22,21 @@ public:
|
||||
|
||||
DataTypePtr getReturnType() const override { return std::make_shared<DataTypeNumber<T>>(); }
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena *) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena *) const override
|
||||
{
|
||||
this->data(place).rbs.add(assert_cast<const ColumnVector<T> &>(*columns[0]).getData()[row_num]);
|
||||
}
|
||||
|
||||
void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
{
|
||||
this->data(place).rbs.merge(this->data(rhs).rbs);
|
||||
}
|
||||
|
||||
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override { this->data(place).rbs.write(buf); }
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override { this->data(place).rbs.write(buf); }
|
||||
|
||||
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena *) const override { this->data(place).rbs.read(buf); }
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena *) const override { this->data(place).rbs.read(buf); }
|
||||
|
||||
void insertResultInto(AggregateDataPtr place, IColumn & to, Arena *) const override
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena *) const override
|
||||
{
|
||||
assert_cast<ColumnVector<T> &>(to).getData().push_back(this->data(place).rbs.size());
|
||||
}
|
||||
@ -56,7 +56,7 @@ public:
|
||||
|
||||
DataTypePtr getReturnType() const override { return std::make_shared<DataTypeNumber<T>>(); }
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena *) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena *) const override
|
||||
{
|
||||
Data & data_lhs = this->data(place);
|
||||
const Data & data_rhs = this->data(assert_cast<const ColumnAggregateFunction &>(*columns[0]).getData()[row_num]);
|
||||
@ -71,7 +71,7 @@ public:
|
||||
}
|
||||
}
|
||||
|
||||
void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
{
|
||||
Data & data_lhs = this->data(place);
|
||||
const Data & data_rhs = this->data(rhs);
|
||||
@ -90,11 +90,11 @@ public:
|
||||
}
|
||||
}
|
||||
|
||||
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override { this->data(place).rbs.write(buf); }
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override { this->data(place).rbs.write(buf); }
|
||||
|
||||
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena *) const override { this->data(place).rbs.read(buf); }
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena *) const override { this->data(place).rbs.read(buf); }
|
||||
|
||||
void insertResultInto(AggregateDataPtr place, IColumn & to, Arena *) const override
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena *) const override
|
||||
{
|
||||
assert_cast<ColumnVector<T> &>(to).getData().push_back(this->data(place).rbs.size());
|
||||
}
|
||||
|
||||
@ -59,14 +59,14 @@ public:
|
||||
return std::make_shared<DataTypeArray>(this->argument_types[0]);
|
||||
}
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena *) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena *) const override
|
||||
{
|
||||
if (limit_num_elems && this->data(place).value.size() >= max_elems)
|
||||
return;
|
||||
this->data(place).value.insert(assert_cast<const ColumnVector<T> &>(*columns[0]).getData()[row_num]);
|
||||
}
|
||||
|
||||
void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
{
|
||||
if (!limit_num_elems)
|
||||
this->data(place).value.merge(this->data(rhs).value);
|
||||
@ -84,7 +84,7 @@ public:
|
||||
}
|
||||
}
|
||||
|
||||
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override
|
||||
{
|
||||
auto & set = this->data(place).value;
|
||||
size_t size = set.size();
|
||||
@ -93,12 +93,12 @@ public:
|
||||
writeIntBinary(elem, buf);
|
||||
}
|
||||
|
||||
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena *) const override
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena *) const override
|
||||
{
|
||||
this->data(place).value.read(buf);
|
||||
}
|
||||
|
||||
void insertResultInto(AggregateDataPtr place, IColumn & to, Arena *) const override
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena *) const override
|
||||
{
|
||||
ColumnArray & arr_to = assert_cast<ColumnArray &>(to);
|
||||
ColumnArray::Offsets & offsets_to = arr_to.getOffsets();
|
||||
@ -166,7 +166,7 @@ public:
|
||||
return true;
|
||||
}
|
||||
|
||||
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override
|
||||
{
|
||||
auto & set = this->data(place).value;
|
||||
writeVarUInt(set.size(), buf);
|
||||
@ -177,7 +177,7 @@ public:
|
||||
}
|
||||
}
|
||||
|
||||
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena * arena) const override
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena * arena) const override
|
||||
{
|
||||
auto & set = this->data(place).value;
|
||||
size_t size;
|
||||
@ -188,7 +188,7 @@ public:
|
||||
set.insert(readStringBinaryInto(*arena, buf));
|
||||
}
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
{
|
||||
auto & set = this->data(place).value;
|
||||
if (limit_num_elems && set.size() >= max_elems)
|
||||
@ -200,7 +200,7 @@ public:
|
||||
set.emplace(key_holder, it, inserted);
|
||||
}
|
||||
|
||||
void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena * arena) const override
|
||||
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena * arena) const override
|
||||
{
|
||||
auto & cur_set = this->data(place).value;
|
||||
auto & rhs_set = this->data(rhs).value;
|
||||
@ -218,7 +218,7 @@ public:
|
||||
}
|
||||
}
|
||||
|
||||
void insertResultInto(AggregateDataPtr place, IColumn & to, Arena *) const override
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena *) const override
|
||||
{
|
||||
ColumnArray & arr_to = assert_cast<ColumnArray &>(to);
|
||||
ColumnArray::Offsets & offsets_to = arr_to.getOffsets();
|
||||
|
||||
@ -332,28 +332,28 @@ public:
|
||||
return std::make_shared<DataTypeArray>(tuple);
|
||||
}
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena *) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena *) const override
|
||||
{
|
||||
auto val = assert_cast<const ColumnVector<T> &>(*columns[0]).getData()[row_num];
|
||||
this->data(place).add(static_cast<Data::Mean>(val), 1, max_bins);
|
||||
}
|
||||
|
||||
void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
{
|
||||
this->data(place).merge(this->data(rhs), max_bins);
|
||||
}
|
||||
|
||||
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override
|
||||
{
|
||||
this->data(place).write(buf);
|
||||
}
|
||||
|
||||
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena *) const override
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena *) const override
|
||||
{
|
||||
this->data(place).read(buf, max_bins);
|
||||
}
|
||||
|
||||
void insertResultInto(AggregateDataPtr place, IColumn & to, Arena *) const override
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena *) const override
|
||||
{
|
||||
auto & data = this->data(place);
|
||||
|
||||
|
||||
@ -97,7 +97,7 @@ public:
|
||||
return assert_cast<const ColumnUInt8 &>(*filter_column).getData()[row_num];
|
||||
}
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
{
|
||||
const ColumnNullable * column = assert_cast<const ColumnNullable *>(columns[0]);
|
||||
const IColumn * nested_column = &column->getNestedColumn();
|
||||
@ -140,7 +140,7 @@ public:
|
||||
return assert_cast<const ColumnUInt8 &>(*columns[num_arguments - 1]).getData()[row_num];
|
||||
}
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
{
|
||||
/// This container stores the columns we really pass to the nested function.
|
||||
const IColumn * nested_columns[number_of_arguments];
|
||||
|
||||
@ -49,12 +49,12 @@ public:
|
||||
return nested_func->getReturnType();
|
||||
}
|
||||
|
||||
void create(AggregateDataPtr place) const override
|
||||
void create(AggregateDataPtr __restrict place) const override
|
||||
{
|
||||
nested_func->create(place);
|
||||
}
|
||||
|
||||
void destroy(AggregateDataPtr place) const noexcept override
|
||||
void destroy(AggregateDataPtr __restrict place) const noexcept override
|
||||
{
|
||||
nested_func->destroy(place);
|
||||
}
|
||||
@ -74,7 +74,7 @@ public:
|
||||
return nested_func->alignOfData();
|
||||
}
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena * arena) const override
|
||||
{
|
||||
if (assert_cast<const ColumnUInt8 &>(*columns[num_arguments - 1]).getData()[row_num])
|
||||
nested_func->add(place, columns, row_num, arena);
|
||||
@ -108,22 +108,22 @@ public:
|
||||
nested_func->addBatchSinglePlaceNotNull(batch_size, place, columns, null_map, arena, num_arguments - 1);
|
||||
}
|
||||
|
||||
void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena * arena) const override
|
||||
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena * arena) const override
|
||||
{
|
||||
nested_func->merge(place, rhs, arena);
|
||||
}
|
||||
|
||||
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override
|
||||
{
|
||||
nested_func->serialize(place, buf);
|
||||
}
|
||||
|
||||
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena * arena) const override
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena * arena) const override
|
||||
{
|
||||
nested_func->deserialize(place, buf, arena);
|
||||
}
|
||||
|
||||
void insertResultInto(AggregateDataPtr place, IColumn & to, Arena * arena) const override
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena * arena) const override
|
||||
{
|
||||
nested_func->insertResultInto(place, to, arena);
|
||||
}
|
||||
|
||||
@ -329,7 +329,7 @@ public:
|
||||
return std::make_shared<DataTypeNumber<Float64>>();
|
||||
}
|
||||
|
||||
void create(AggregateDataPtr place) const override
|
||||
void create(AggregateDataPtr __restrict place) const override
|
||||
{
|
||||
std::shared_ptr<IWeightsUpdater> new_weights_updater;
|
||||
if (weights_updater_name == "SGD")
|
||||
@ -346,16 +346,16 @@ public:
|
||||
new (place) Data(learning_rate, l2_reg_coef, param_num, batch_size, gradient_computer, new_weights_updater);
|
||||
}
|
||||
|
||||
void add(AggregateDataPtr place, const IColumn ** columns, size_t row_num, Arena *) const override
|
||||
void add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena *) const override
|
||||
{
|
||||
this->data(place).add(columns, row_num);
|
||||
}
|
||||
|
||||
void merge(AggregateDataPtr place, ConstAggregateDataPtr rhs, Arena *) const override { this->data(place).merge(this->data(rhs)); }
|
||||
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena *) const override { this->data(place).merge(this->data(rhs)); }
|
||||
|
||||
void serialize(ConstAggregateDataPtr place, WriteBuffer & buf) const override { this->data(place).write(buf); }
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override { this->data(place).write(buf); }
|
||||
|
||||
void deserialize(AggregateDataPtr place, ReadBuffer & buf, Arena *) const override { this->data(place).read(buf); }
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena *) const override { this->data(place).read(buf); }
|
||||
|
||||
void predictValues(
|
||||
ConstAggregateDataPtr place,
|
||||
@ -383,7 +383,7 @@ public:
|
||||
/** This function is called if aggregate function without State modifier is selected in a query.
|
||||
* Inserts all weights of the model into the column 'to', so user may use such information if needed
|
||||
*/
|
||||
void insertResultInto(AggregateDataPtr place, IColumn & to, Arena *) const override
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena *) const override
|
||||
{
|
||||
this->data(place).returnWeights(to);
|
||||
}
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Loading…
Reference in New Issue
Block a user