mirror of
https://github.com/ClickHouse/ClickHouse.git
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Merge branch 'master' into hedged-requests
This commit is contained in:
Kruglov Pavel
GitHub
commit
598576ce70
32
.github/workflows/codeql-analysis.yml
vendored
32
.github/workflows/codeql-analysis.yml
vendored
@ -1,32 +0,0 @@
|
||||
# See the example here: https://github.com/github/codeql-action
|
||||
|
||||
name: "CodeQL Scanning"
|
||||
|
||||
on:
|
||||
schedule:
|
||||
- cron: '0 19 * * *'
|
||||
jobs:
|
||||
CodeQL-Build:
|
||||
|
||||
runs-on: self-hosted
|
||||
timeout-minutes: 1440
|
||||
|
||||
steps:
|
||||
- name: Checkout repository
|
||||
uses: actions/checkout@v2
|
||||
with:
|
||||
fetch-depth: 2
|
||||
submodules: 'recursive'
|
||||
|
||||
- name: Initialize CodeQL
|
||||
uses: github/codeql-action/init@v1
|
||||
|
||||
with:
|
||||
languages: cpp
|
||||
|
||||
- run: sudo apt-get update && sudo apt-get install -y git cmake python ninja-build gcc-10 g++-10 && mkdir build
|
||||
- run: cd build && CC=gcc-10 CXX=g++-10 cmake ..
|
||||
- run: cd build && ninja
|
||||
|
||||
- name: Perform CodeQL Analysis
|
||||
uses: github/codeql-action/analyze@v1
|
||||
2
.gitmodules
vendored
2
.gitmodules
vendored
@ -220,4 +220,4 @@
|
||||
url = https://github.com/ClickHouse-Extras/boringssl.git
|
||||
[submodule "contrib/NuRaft"]
|
||||
path = contrib/NuRaft
|
||||
url = https://github.com/eBay/NuRaft.git
|
||||
url = https://github.com/ClickHouse-Extras/NuRaft.git
|
||||
|
||||
145
CHANGELOG.md
145
CHANGELOG.md
@ -1,3 +1,148 @@
|
||||
## ClickHouse release 21.2
|
||||
|
||||
### ClickHouse release v21.2.2.8-stable, 2021-02-07
|
||||
|
||||
#### Backward Incompatible Change
|
||||
|
||||
* 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)).
|
||||
* Forbid `lcm`/`gcd` for floats. [#19532](https://github.com/ClickHouse/ClickHouse/pull/19532) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* Excessive parenthesis in type definitions no longer supported, example: `Array((UInt8))`.
|
||||
|
||||
#### New Feature
|
||||
|
||||
* 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)).
|
||||
* 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)).
|
||||
* Added `Nullable` support for `FlatDictionary`, `HashedDictionary`, `ComplexKeyHashedDictionary`, `DirectDictionary`, `ComplexKeyDirectDictionary`, `RangeHashedDictionary`. [#18236](https://github.com/ClickHouse/ClickHouse/pull/18236) ([Maksim Kita](https://github.com/kitaisreal)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* Added functions `parseDateTimeBestEffortUSOrZero`, `parseDateTimeBestEffortUSOrNull`. [#19712](https://github.com/ClickHouse/ClickHouse/pull/19712) ([Maksim Kita](https://github.com/kitaisreal)).
|
||||
* Add `sign` math function. [#19527](https://github.com/ClickHouse/ClickHouse/pull/19527) ([flynn](https://github.com/ucasFL)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* Support MetaKey+Enter hotkey binding in play UI. [#19012](https://github.com/ClickHouse/ClickHouse/pull/19012) ([sundyli](https://github.com/sundy-li)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* Add support of tuple argument to `argMin` and `argMax` functions. [#17359](https://github.com/ClickHouse/ClickHouse/pull/17359) ([Ildus Kurbangaliev](https://github.com/ildus)).
|
||||
* Support `EXISTS VIEW` syntax. [#18552](https://github.com/ClickHouse/ClickHouse/pull/18552) ([Du Chuan](https://github.com/spongedu)).
|
||||
* 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)).
|
||||
|
||||
#### Performance Improvement
|
||||
|
||||
* 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)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* Update libc++ and use another ABI to provide better performance. [#18914](https://github.com/ClickHouse/ClickHouse/pull/18914) ([Danila Kutenin](https://github.com/danlark1)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* Reduce lock contention for multiple layers of the `Buffer` engine. [#19379](https://github.com/ClickHouse/ClickHouse/pull/19379) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* 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)).
|
||||
|
||||
#### Improvement
|
||||
|
||||
* `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)).
|
||||
* 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)).
|
||||
* `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)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* Add separate pool for message brokers (RabbitMQ and Kafka). [#19722](https://github.com/ClickHouse/ClickHouse/pull/19722) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* 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)).
|
||||
* Dictionary: better error message during attribute parsing. [#19678](https://github.com/ClickHouse/ClickHouse/pull/19678) ([Maksim Kita](https://github.com/kitaisreal)).
|
||||
* 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)).
|
||||
* Support constant result in function `multiIf`. [#19533](https://github.com/ClickHouse/ClickHouse/pull/19533) ([Maksim Kita](https://github.com/kitaisreal)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* `toIPv6` function parses `IPv4` addresses. [#19518](https://github.com/ClickHouse/ClickHouse/pull/19518) ([Bharat Nallan](https://github.com/bharatnc)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* Add metrics for MergeTree parts (Wide/Compact/InMemory) types. [#19381](https://github.com/ClickHouse/ClickHouse/pull/19381) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* Allow docker to be executed with arbitrary uid. [#19374](https://github.com/ClickHouse/ClickHouse/pull/19374) ([filimonov](https://github.com/filimonov)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* Docker image: several improvements for clickhouse-server entrypoint. [#18954](https://github.com/ClickHouse/ClickHouse/pull/18954) ([filimonov](https://github.com/filimonov)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* Added prefix-based S3 endpoint settings. [#18812](https://github.com/ClickHouse/ClickHouse/pull/18812) ([Vladimir Chebotarev](https://github.com/excitoon)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
* 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)).
|
||||
|
||||
#### 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)).
|
||||
* `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)).
|
||||
* 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
|
||||
|
||||
@ -8,12 +8,8 @@ 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.
|
||||
* [Contacts](https://clickhouse.tech/#contacts) can help to get your questions answered if there are any.
|
||||
* You can also [fill this form](https://clickhouse.tech/#meet) to meet Yandex ClickHouse team in person.
|
||||
|
||||
## Upcoming Events
|
||||
* [Chinese ClickHouse Meetup (online)](http://hdxu.cn/8KxZE) on 6 February 2021.
|
||||
|
||||
@ -1,6 +1,8 @@
|
||||
#pragma once
|
||||
|
||||
#include <common/extended_types.h>
|
||||
#include <common/defines.h>
|
||||
|
||||
|
||||
namespace common
|
||||
{
|
||||
@ -156,4 +158,11 @@ namespace common
|
||||
return false;
|
||||
return (x * y) / y != x;
|
||||
}
|
||||
|
||||
/// Multiply and ignore overflow.
|
||||
template <typename T1, typename T2>
|
||||
inline auto NO_SANITIZE_UNDEFINED mulIgnoreOverflow(T1 x, T2 y)
|
||||
{
|
||||
return x * y;
|
||||
}
|
||||
}
|
||||
|
||||
@ -152,7 +152,7 @@ static void signalHandler(int sig, siginfo_t * info, void * context)
|
||||
if (sig != SIGTSTP) /// This signal is used for debugging.
|
||||
{
|
||||
/// The time that is usually enough for separate thread to print info into log.
|
||||
sleepForSeconds(10);
|
||||
sleepForSeconds(20); /// FIXME: use some feedback from threads that process stacktrace
|
||||
call_default_signal_handler(sig);
|
||||
}
|
||||
|
||||
@ -311,7 +311,8 @@ private:
|
||||
if (stack_trace.getSize())
|
||||
{
|
||||
/// Write bare stack trace (addresses) just in case if we will fail to print symbolized stack trace.
|
||||
/// NOTE This still require memory allocations and mutex lock inside logger. BTW we can also print it to stderr using write syscalls.
|
||||
/// NOTE: This still require memory allocations and mutex lock inside logger.
|
||||
/// BTW we can also print it to stderr using write syscalls.
|
||||
|
||||
std::stringstream bare_stacktrace;
|
||||
bare_stacktrace << "Stack trace:";
|
||||
@ -324,7 +325,7 @@ private:
|
||||
/// Write symbolized stack trace line by line for better grep-ability.
|
||||
stack_trace.toStringEveryLine([&](const std::string & s) { LOG_FATAL(log, s); });
|
||||
|
||||
#if defined(__linux__)
|
||||
#if defined(OS_LINUX)
|
||||
/// Write information about binary checksum. It can be difficult to calculate, so do it only after printing stack trace.
|
||||
String calculated_binary_hash = getHashOfLoadedBinaryHex();
|
||||
if (daemon.stored_binary_hash.empty())
|
||||
@ -561,6 +562,7 @@ void debugIncreaseOOMScore()
|
||||
{
|
||||
DB::WriteBufferFromFile buf("/proc/self/oom_score_adj");
|
||||
buf.write(new_score.c_str(), new_score.size());
|
||||
buf.close();
|
||||
}
|
||||
catch (const Poco::Exception & e)
|
||||
{
|
||||
@ -783,7 +785,7 @@ void BaseDaemon::initializeTerminationAndSignalProcessing()
|
||||
/// Setup signal handlers.
|
||||
/// SIGTSTP is added for debugging purposes. To output a stack trace of any running thread at anytime.
|
||||
|
||||
addSignalHandler({SIGABRT, SIGSEGV, SIGILL, SIGBUS, SIGSYS, SIGFPE, SIGPIPE, SIGTSTP}, signalHandler, &handled_signals);
|
||||
addSignalHandler({SIGABRT, SIGSEGV, SIGILL, SIGBUS, SIGSYS, SIGFPE, SIGPIPE, SIGTSTP, SIGTRAP}, signalHandler, &handled_signals);
|
||||
addSignalHandler({SIGHUP, SIGUSR1}, closeLogsSignalHandler, &handled_signals);
|
||||
addSignalHandler({SIGINT, SIGQUIT, SIGTERM}, terminateRequestedSignalHandler, &handled_signals);
|
||||
|
||||
@ -986,7 +988,7 @@ void BaseDaemon::setupWatchdog()
|
||||
if (errno == ECHILD)
|
||||
{
|
||||
logger().information("Child process no longer exists.");
|
||||
_exit(status);
|
||||
_exit(WEXITSTATUS(status));
|
||||
}
|
||||
|
||||
if (WIFEXITED(status))
|
||||
@ -1020,7 +1022,7 @@ void BaseDaemon::setupWatchdog()
|
||||
|
||||
/// Automatic restart is not enabled but you can play with it.
|
||||
#if 1
|
||||
_exit(status);
|
||||
_exit(WEXITSTATUS(status));
|
||||
#else
|
||||
logger().information("Will restart.");
|
||||
if (argv0)
|
||||
|
||||
@ -11,7 +11,7 @@ if (NOT EXISTS "${ClickHouse_SOURCE_DIR}/contrib/NuRaft/CMakeLists.txt")
|
||||
return()
|
||||
endif ()
|
||||
|
||||
if (NOT OS_FREEBSD)
|
||||
if (NOT OS_FREEBSD AND NOT OS_DARWIN)
|
||||
set (USE_NURAFT 1)
|
||||
set (NURAFT_LIBRARY nuraft)
|
||||
|
||||
@ -20,5 +20,5 @@ if (NOT OS_FREEBSD)
|
||||
message (STATUS "Using NuRaft=${USE_NURAFT}: ${NURAFT_INCLUDE_DIR} : ${NURAFT_LIBRARY}")
|
||||
else()
|
||||
set (USE_NURAFT 0)
|
||||
message (STATUS "Using internal NuRaft library on FreeBSD is not supported")
|
||||
message (STATUS "Using internal NuRaft library on FreeBSD and Darwin is not supported")
|
||||
endif()
|
||||
|
||||
2
contrib/NuRaft
vendored
2
contrib/NuRaft
vendored
@ -1 +1 @@
|
||||
Subproject commit 410bd149da84cdde60b4436b02b738749f4e87e1
|
||||
Subproject commit 7adf7ae33e7d5c307342431b577c8ab1025ee793
|
||||
@ -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 ()
|
||||
|
||||
2
contrib/boost
vendored
2
contrib/boost
vendored
@ -1 +1 @@
|
||||
Subproject commit 8e259cd2a6b60d75dd17e73432f11bb7b9351bb1
|
||||
Subproject commit 48f40ebb539220d328958f8823b094c0b07a4e79
|
||||
@ -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
|
||||
)
|
||||
|
||||
@ -30,7 +30,12 @@ set(SRCS
|
||||
|
||||
add_library(nuraft ${SRCS})
|
||||
|
||||
target_compile_definitions(nuraft PRIVATE USE_BOOST_ASIO=1 BOOST_ASIO_STANDALONE=1)
|
||||
|
||||
if (NOT OPENSSL_SSL_LIBRARY OR NOT OPENSSL_CRYPTO_LIBRARY)
|
||||
target_compile_definitions(nuraft PRIVATE USE_BOOST_ASIO=1 BOOST_ASIO_STANDALONE=1 SSL_LIBRARY_NOT_FOUND=1)
|
||||
else()
|
||||
target_compile_definitions(nuraft PRIVATE USE_BOOST_ASIO=1 BOOST_ASIO_STANDALONE=1)
|
||||
endif()
|
||||
|
||||
target_include_directories (nuraft SYSTEM PRIVATE ${LIBRARY_DIR}/include/libnuraft)
|
||||
# for some reason include "asio.h" directly without "boost/" prefix.
|
||||
|
||||
@ -54,8 +54,10 @@ docker cp -L "${ubuntu20image}":/lib/x86_64-linux-gnu/libm.so.6 "${CONTAIN
|
||||
docker cp -L "${ubuntu20image}":/lib/x86_64-linux-gnu/libpthread.so.0 "${CONTAINER_ROOT_FOLDER}/lib"
|
||||
docker cp -L "${ubuntu20image}":/lib/x86_64-linux-gnu/librt.so.1 "${CONTAINER_ROOT_FOLDER}/lib"
|
||||
docker cp -L "${ubuntu20image}":/lib/x86_64-linux-gnu/libnss_dns.so.2 "${CONTAINER_ROOT_FOLDER}/lib"
|
||||
docker cp -L "${ubuntu20image}":/lib/x86_64-linux-gnu/libnss_files.so.2 "${CONTAINER_ROOT_FOLDER}/lib"
|
||||
docker cp -L "${ubuntu20image}":/lib/x86_64-linux-gnu/libresolv.so.2 "${CONTAINER_ROOT_FOLDER}/lib"
|
||||
docker cp -L "${ubuntu20image}":/lib64/ld-linux-x86-64.so.2 "${CONTAINER_ROOT_FOLDER}/lib64"
|
||||
docker cp -L "${ubuntu20image}":/etc/nsswitch.conf "${CONTAINER_ROOT_FOLDER}/etc"
|
||||
|
||||
docker build "$DOCKER_BUILD_FOLDER" -f Dockerfile.alpine -t "${DOCKER_IMAGE}:${VERSION}-alpine" --pull
|
||||
rm -rf "$CONTAINER_ROOT_FOLDER"
|
||||
|
||||
@ -120,7 +120,7 @@ function clone_root
|
||||
git checkout FETCH_HEAD
|
||||
echo 'Clonned merge head'
|
||||
else
|
||||
git fetch
|
||||
git fetch origin "+refs/pull/$PULL_REQUEST_NUMBER/head"
|
||||
git checkout "$COMMIT_SHA"
|
||||
echo 'Checked out to commit'
|
||||
fi
|
||||
@ -163,6 +163,7 @@ function clone_submodules
|
||||
contrib/xz
|
||||
contrib/dragonbox
|
||||
contrib/fast_float
|
||||
contrib/NuRaft
|
||||
)
|
||||
|
||||
git submodule sync
|
||||
@ -182,6 +183,7 @@ function run_cmake
|
||||
"-DENABLE_EMBEDDED_COMPILER=0"
|
||||
"-DENABLE_THINLTO=0"
|
||||
"-DUSE_UNWIND=1"
|
||||
"-DENABLE_NURAFT=1"
|
||||
)
|
||||
|
||||
# TODO remove this? we don't use ccache anyway. An option would be to download it
|
||||
|
||||
@ -190,7 +190,7 @@ case "$stage" in
|
||||
# Lost connection to the server. This probably means that the server died
|
||||
# with abort.
|
||||
echo "failure" > status.txt
|
||||
if ! grep -ao "Received signal.*\|Logical error.*\|Assertion.*failed\|Failed assertion.*\|.*runtime error: .*\|.*is located.*\|SUMMARY: MemorySanitizer:.*\|SUMMARY: ThreadSanitizer:.*" server.log > description.txt
|
||||
if ! grep -ao "Received signal.*\|Logical error.*\|Assertion.*failed\|Failed assertion.*\|.*runtime error: .*\|.*is located.*\|SUMMARY: MemorySanitizer:.*\|SUMMARY: ThreadSanitizer:.*\|.*_LIBCPP_ASSERT.*" server.log > description.txt
|
||||
then
|
||||
echo "Lost connection to server. See the logs." > description.txt
|
||||
fi
|
||||
|
||||
@ -44,6 +44,7 @@ parser.add_argument('--port', nargs='*', default=[9000], help="Space-separated l
|
||||
parser.add_argument('--runs', type=int, default=1, help='Number of query runs per server.')
|
||||
parser.add_argument('--max-queries', type=int, default=None, help='Test no more than this number of queries, chosen at random.')
|
||||
parser.add_argument('--queries-to-run', nargs='*', type=int, default=None, help='Space-separated list of indexes of queries to test.')
|
||||
parser.add_argument('--max-query-seconds', type=int, default=10, help='For how many seconds at most a query is allowed to run. The script finishes with error if this time is exceeded.')
|
||||
parser.add_argument('--profile-seconds', type=int, default=0, help='For how many seconds to profile a query for which the performance has changed.')
|
||||
parser.add_argument('--long', action='store_true', help='Do not skip the tests tagged as long.')
|
||||
parser.add_argument('--print-queries', action='store_true', help='Print test queries and exit.')
|
||||
@ -323,7 +324,7 @@ for query_index in queries_to_run:
|
||||
server_seconds += elapsed
|
||||
print(f'query\t{query_index}\t{run_id}\t{conn_index}\t{elapsed}')
|
||||
|
||||
if elapsed > 10:
|
||||
if elapsed > args.max_query_seconds:
|
||||
# Stop processing pathologically slow queries, to avoid timing out
|
||||
# the entire test task. This shouldn't really happen, so we don't
|
||||
# need much handling for this case and can just exit.
|
||||
|
||||
@ -5,7 +5,10 @@ RUN apt-get update -y && \
|
||||
apt-get install -y --no-install-recommends \
|
||||
python3-pip \
|
||||
python3-setuptools \
|
||||
python3-wheel
|
||||
python3-wheel \
|
||||
brotli \
|
||||
netcat-openbsd \
|
||||
zstd
|
||||
|
||||
RUN python3 -m pip install \
|
||||
wheel \
|
||||
@ -15,7 +18,10 @@ RUN python3 -m pip install \
|
||||
pytest-randomly \
|
||||
pytest-rerunfailures \
|
||||
pytest-timeout \
|
||||
pytest-xdist
|
||||
pytest-xdist \
|
||||
pandas \
|
||||
numpy \
|
||||
scipy
|
||||
|
||||
CMD dpkg -i package_folder/clickhouse-common-static_*.deb; \
|
||||
dpkg -i package_folder/clickhouse-common-static-dbg_*.deb; \
|
||||
|
||||
29
docs/_description_templates/template-data-type.md
Normal file
29
docs/_description_templates/template-data-type.md
Normal file
@ -0,0 +1,29 @@
|
||||
---
|
||||
toc_priority:
|
||||
toc_title:
|
||||
---
|
||||
|
||||
# data_type_name {#data_type-name}
|
||||
|
||||
Description.
|
||||
|
||||
**Parameters** (Optional)
|
||||
|
||||
- `x` — Description. [Type name](relative/path/to/type/dscr.md#type).
|
||||
- `y` — Description. [Type name](relative/path/to/type/dscr.md#type).
|
||||
|
||||
**Examples**
|
||||
|
||||
```sql
|
||||
|
||||
```
|
||||
|
||||
## Additional Info {#additional-info} (Optional)
|
||||
|
||||
The name of an additional section can be any, for example, **Usage**.
|
||||
|
||||
**See Also** (Optional)
|
||||
|
||||
- [link](#)
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/data_types/<data-type-name>/) <!--hide-->
|
||||
@ -93,6 +93,7 @@ ClickHouse has only one physical order, which is determined by `ORDER BY` clause
|
||||
- Cascade `UPDATE/DELETE` queries are not supported by the `MaterializeMySQL` engine.
|
||||
- Replication can be easily broken.
|
||||
- Manual operations on database and tables are forbidden.
|
||||
- `MaterializeMySQL` is influenced by [optimize_on_insert](../../operations/settings/settings.md#optimize-on-insert) setting. The data is merged in the corresponding table in the `MaterializeMySQL` database when a table in the MySQL server changes.
|
||||
|
||||
## Examples of Use {#examples-of-use}
|
||||
|
||||
@ -156,4 +157,4 @@ SELECT * FROM mysql.test;
|
||||
└───┴─────┴──────┘
|
||||
```
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/database_engines/materialize-mysql/) <!--hide-->
|
||||
[Original article](https://clickhouse.tech/docs/en/engines/database-engines/materialize-mysql/) <!--hide-->
|
||||
|
||||
@ -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-->
|
||||
@ -136,8 +136,7 @@ The following settings can be specified in configuration file for given endpoint
|
||||
- `access_key_id` and `secret_access_key` — Optional. Specifies credentials to use with given endpoint.
|
||||
- `use_environment_credentials` — Optional, default value is `false`. If set to `true`, S3 client will try to obtain credentials from environment variables and Amazon EC2 metadata for given endpoint.
|
||||
- `header` — Optional, can be speficied multiple times. Adds specified HTTP header to a request to given endpoint.
|
||||
|
||||
This configuration also applies to S3 disks in `MergeTree` table engine family.
|
||||
- `server_side_encryption_customer_key_base64` — Optional. If specified, required headers for accessing S3 objects with SSE-C encryption will be set.
|
||||
|
||||
Example:
|
||||
|
||||
@ -149,6 +148,7 @@ Example:
|
||||
<!-- <secret_access_key>SECRET_ACCESS_KEY</secret_access_key> -->
|
||||
<!-- <use_environment_credentials>false</use_environment_credentials> -->
|
||||
<!-- <header>Authorization: Bearer SOME-TOKEN</header> -->
|
||||
<!-- <server_side_encryption_customer_key_base64>BASE64-ENCODED-KEY</server_side_encryption_customer_key_base64> -->
|
||||
</endpoint-name>
|
||||
</s3>
|
||||
```
|
||||
|
||||
@ -104,7 +104,8 @@ For a description of parameters, see the [CREATE query description](../../../sql
|
||||
- `max_parts_in_total` — Maximum number of parts in all partitions.
|
||||
- `max_compress_block_size` — Maximum size of blocks of uncompressed data before compressing for writing to a table. You can also specify this setting in the global settings (see [max_compress_block_size](../../../operations/settings/settings.md#max-compress-block-size) setting). The value specified when table is created overrides the global value for this setting.
|
||||
- `min_compress_block_size` — Minimum size of blocks of uncompressed data required for compression when writing the next mark. You can also specify this setting in the global settings (see [min_compress_block_size](../../../operations/settings/settings.md#min-compress-block-size) setting). The value specified when table is created overrides the global value for this setting.
|
||||
|
||||
- `max_partitions_to_read` — Limits the maximum number of partitions that can be accessed in one query. You can also specify setting [max_partitions_to_read](../../../operations/settings/merge-tree-settings.md#max-partitions-to-read) in the global setting.
|
||||
|
||||
**Example of Sections Setting**
|
||||
|
||||
``` sql
|
||||
@ -714,6 +715,7 @@ Configuration markup:
|
||||
<endpoint>https://storage.yandexcloud.net/my-bucket/root-path/</endpoint>
|
||||
<access_key_id>your_access_key_id</access_key_id>
|
||||
<secret_access_key>your_secret_access_key</secret_access_key>
|
||||
<server_side_encryption_customer_key_base64>your_base64_encoded_customer_key</server_side_encryption_customer_key_base64>
|
||||
<proxy>
|
||||
<uri>http://proxy1</uri>
|
||||
<uri>http://proxy2</uri>
|
||||
@ -749,7 +751,8 @@ Optional parameters:
|
||||
- `metadata_path` — Path on local FS to store metadata files for S3. Default value is `/var/lib/clickhouse/disks/<disk_name>/`.
|
||||
- `cache_enabled` — Allows to cache mark and index files on local FS. Default value is `true`.
|
||||
- `cache_path` — Path on local FS where to store cached mark and index files. Default value is `/var/lib/clickhouse/disks/<disk_name>/cache/`.
|
||||
- `skip_access_check` — If true disk access checks will not be performed on disk start-up. Default value is `false`.
|
||||
- `skip_access_check` — If true, disk access checks will not be performed on disk start-up. Default value is `false`.
|
||||
- `server_side_encryption_customer_key_base64` — If specified, required headers for accessing S3 objects with SSE-C encryption will be set.
|
||||
|
||||
|
||||
S3 disk can be configured as `main` or `cold` storage:
|
||||
|
||||
@ -39,4 +39,4 @@ More details on [manipulating partitions](../../sql-reference/statements/alter/p
|
||||
|
||||
It’s rather radical to drop all data from a table, but in some cases it might be exactly what you need.
|
||||
|
||||
More details on [table truncation](../../sql-reference/statements/alter/partition.md#alter_drop-partition).
|
||||
More details on [table truncation](../../sql-reference/statements/truncate.md).
|
||||
|
||||
@ -31,8 +31,8 @@ The supported formats are:
|
||||
| [JSONCompactString](#jsoncompactstring) | ✗ | ✔ |
|
||||
| [JSONEachRow](#jsoneachrow) | ✔ | ✔ |
|
||||
| [JSONEachRowWithProgress](#jsoneachrowwithprogress) | ✗ | ✔ |
|
||||
| [JSONStringEachRow](#jsonstringeachrow) | ✔ | ✔ |
|
||||
| [JSONStringEachRowWithProgress](#jsonstringeachrowwithprogress) | ✗ | ✔ |
|
||||
| [JSONStringsEachRow](#jsonstringseachrow) | ✔ | ✔ |
|
||||
| [JSONStringsEachRowWithProgress](#jsonstringseachrowwithprogress) | ✗ | ✔ |
|
||||
| [JSONCompactEachRow](#jsoncompacteachrow) | ✔ | ✔ |
|
||||
| [JSONCompactEachRowWithNamesAndTypes](#jsoncompacteachrowwithnamesandtypes) | ✔ | ✔ |
|
||||
| [JSONCompactStringEachRow](#jsoncompactstringeachrow) | ✔ | ✔ |
|
||||
@ -612,7 +612,7 @@ Example:
|
||||
```
|
||||
|
||||
## JSONEachRow {#jsoneachrow}
|
||||
## JSONStringEachRow {#jsonstringeachrow}
|
||||
## JSONStringsEachRow {#jsonstringseachrow}
|
||||
## JSONCompactEachRow {#jsoncompacteachrow}
|
||||
## JSONCompactStringEachRow {#jsoncompactstringeachrow}
|
||||
|
||||
@ -627,9 +627,9 @@ When using these formats, ClickHouse outputs rows as separated, newline-delimite
|
||||
When inserting the data, you should provide a separate JSON value for each row.
|
||||
|
||||
## JSONEachRowWithProgress {#jsoneachrowwithprogress}
|
||||
## JSONStringEachRowWithProgress {#jsonstringeachrowwithprogress}
|
||||
## JSONStringsEachRowWithProgress {#jsonstringseachrowwithprogress}
|
||||
|
||||
Differs from `JSONEachRow`/`JSONStringEachRow` in that ClickHouse will also yield progress information as JSON values.
|
||||
Differs from `JSONEachRow`/`JSONStringsEachRow` in that ClickHouse will also yield progress information as JSON values.
|
||||
|
||||
```json
|
||||
{"row":{"'hello'":"hello","multiply(42, number)":"0","range(5)":[0,1,2,3,4]}}
|
||||
|
||||
@ -81,6 +81,7 @@ toc_title: Adopters
|
||||
| <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://prana-system.com/en/" class="favicon">PRANA</a> | Industrial predictive analytics | Main product | — | — | [News (russian), Feb 2021](https://habr.com/en/news/t/541392/) |
|
||||
| <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) |
|
||||
|
||||
@ -5,7 +5,7 @@ toc_title: Data Backup
|
||||
|
||||
# Data Backup {#data-backup}
|
||||
|
||||
While [replication](../engines/table-engines/mergetree-family/replication.md) provides protection from hardware failures, it does not protect against human errors: accidental deletion of data, deletion of the wrong table or a table on the wrong cluster, and software bugs that result in incorrect data processing or data corruption. In many cases mistakes like these will affect all replicas. ClickHouse has built-in safeguards to prevent some types of mistakes — for example, by default [you can’t just drop tables with a MergeTree-like engine containing more than 50 Gb of data](https://github.com/ClickHouse/ClickHouse/blob/v18.14.18-stable/programs/server/config.xml#L322-L330). However, these safeguards don’t cover all possible cases and can be circumvented.
|
||||
While [replication](../engines/table-engines/mergetree-family/replication.md) provides protection from hardware failures, it does not protect against human errors: accidental deletion of data, deletion of the wrong table or a table on the wrong cluster, and software bugs that result in incorrect data processing or data corruption. In many cases mistakes like these will affect all replicas. ClickHouse has built-in safeguards to prevent some types of mistakes — for example, by default [you can’t just drop tables with a MergeTree-like engine containing more than 50 Gb of data](server-configuration-parameters/settings.md#max-table-size-to-drop). However, these safeguards don’t cover all possible cases and can be circumvented.
|
||||
|
||||
In order to effectively mitigate possible human errors, you should carefully prepare a strategy for backing up and restoring your data **in advance**.
|
||||
|
||||
|
||||
@ -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.
|
||||
|
||||
@ -186,5 +186,16 @@ Possible values:
|
||||
Default value: auto (number of CPU cores).
|
||||
|
||||
During startup ClickHouse reads all parts of all tables (reads files with metadata of parts) to build a list of all parts in memory. In some systems with a large number of parts this process can take a long time, and this time might be shortened by increasing `max_part_loading_threads` (if this process is not CPU and disk I/O bound).
|
||||
## max_partitions_to_read {#max-partitions-to-read}
|
||||
|
||||
Limits the maximum number of partitions that can be accessed in one query.
|
||||
|
||||
The setting value specified when the table is created can be overridden via query-level setting.
|
||||
|
||||
Possible values:
|
||||
|
||||
- Any positive integer.
|
||||
|
||||
Default value: -1 (unlimited).
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/operations/settings/merge_tree_settings/) <!--hide-->
|
||||
|
||||
@ -2592,4 +2592,58 @@ Possible values:
|
||||
|
||||
Default value: `16`.
|
||||
|
||||
## optimize_on_insert {#optimize-on-insert}
|
||||
|
||||
Enables or disables data transformation before the insertion, as if merge was done on this block (according to table engine).
|
||||
|
||||
Possible values:
|
||||
|
||||
- 0 — Disabled.
|
||||
- 1 — Enabled.
|
||||
|
||||
Default value: 1.
|
||||
|
||||
**Example**
|
||||
|
||||
The difference between enabled and disabled:
|
||||
|
||||
Query:
|
||||
|
||||
```sql
|
||||
SET optimize_on_insert = 1;
|
||||
|
||||
CREATE TABLE test1 (`FirstTable` UInt32) ENGINE = ReplacingMergeTree ORDER BY FirstTable;
|
||||
|
||||
INSERT INTO test1 SELECT number % 2 FROM numbers(5);
|
||||
|
||||
SELECT * FROM test1;
|
||||
|
||||
SET optimize_on_insert = 0;
|
||||
|
||||
CREATE TABLE test2 (`SecondTable` UInt32) ENGINE = ReplacingMergeTree ORDER BY SecondTable;
|
||||
|
||||
INSERT INTO test2 SELECT number % 2 FROM numbers(5);
|
||||
|
||||
SELECT * FROM test2;
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
┌─FirstTable─┐
|
||||
│ 0 │
|
||||
│ 1 │
|
||||
└────────────┘
|
||||
|
||||
┌─SecondTable─┐
|
||||
│ 0 │
|
||||
│ 0 │
|
||||
│ 0 │
|
||||
│ 1 │
|
||||
│ 1 │
|
||||
└─────────────┘
|
||||
```
|
||||
|
||||
Note that this setting influences [Materialized view](../../sql-reference/statements/create/view.md#materialized) and [MaterializeMySQL](../../engines/database-engines/materialize-mysql.md) behaviour.
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/operations/settings/settings/) <!-- hide -->
|
||||
|
||||
@ -6,29 +6,65 @@ 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.
|
||||
- `event_time_microseconds` ([DateTime64](../../sql-reference/data-types/datetime64.md)) — Event time with microseconds precision.
|
||||
|
||||
- `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
|
||||
event_time_microseconds: 2021-02-02 11:14:28.861919
|
||||
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.
|
||||
|
||||
@ -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.
|
||||
|
||||
@ -1,9 +1,9 @@
|
||||
---
|
||||
toc_priority: 47
|
||||
toc_title: ClickHouse Update
|
||||
toc_title: ClickHouse Upgrade
|
||||
---
|
||||
|
||||
# ClickHouse Update {#clickhouse-update}
|
||||
# ClickHouse Upgrade {#clickhouse-upgrade}
|
||||
|
||||
If ClickHouse was installed from `deb` packages, execute the following commands on the server:
|
||||
|
||||
@ -16,3 +16,19 @@ $ sudo service clickhouse-server restart
|
||||
If you installed ClickHouse using something other than the recommended `deb` packages, use the appropriate update method.
|
||||
|
||||
ClickHouse does not support a distributed update. The operation should be performed consecutively on each separate server. Do not update all the servers on a cluster simultaneously, or the cluster will be unavailable for some time.
|
||||
|
||||
The upgrade of older version of ClickHouse to specific version:
|
||||
|
||||
As an example:
|
||||
|
||||
`xx.yy.a.b` is a current stable version. The latest stable version could be found [here](https://github.com/ClickHouse/ClickHouse/releases)
|
||||
|
||||
```bash
|
||||
$ sudo apt-get update
|
||||
$ sudo apt-get install clickhouse-server=xx.yy.a.b clickhouse-client=xx.yy.a.b clickhouse-common-static=xx.yy.a.b
|
||||
$ sudo service clickhouse-server restart
|
||||
```
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
@ -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 +1,19 @@
|
||||
---
|
||||
toc_priority: 141
|
||||
---
|
||||
|
||||
# deltaSum {#agg_functions-deltasum}
|
||||
|
||||
Syntax: `deltaSum(value)`
|
||||
|
||||
Adds the differences between consecutive rows. If the difference is negative, it is ignored.
|
||||
`value` must be some integer or floating point type.
|
||||
|
||||
Example:
|
||||
|
||||
```sql
|
||||
select deltaSum(arrayJoin([1, 2, 3])); -- => 2
|
||||
select deltaSum(arrayJoin([1, 2, 3, 0, 3, 4, 2, 3])); -- => 7
|
||||
select deltaSum(arrayJoin([2.25, 3, 4.5])); -- => 2.25
|
||||
```
|
||||
|
||||
@ -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-->
|
||||
@ -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-->
|
||||
83
docs/en/sql-reference/data-types/map.md
Normal file
83
docs/en/sql-reference/data-types/map.md
Normal file
@ -0,0 +1,83 @@
|
||||
---
|
||||
toc_priority: 65
|
||||
toc_title: Map(key, value)
|
||||
---
|
||||
|
||||
# Map(key, value) {#data_type-map}
|
||||
|
||||
`Map(key, value)` data type stores `key:value` pairs.
|
||||
|
||||
**Parameters**
|
||||
- `key` — The key part of the pair. [String](../../sql-reference/data-types/string.md) or [Integer](../../sql-reference/data-types/int-uint.md).
|
||||
- `value` — The value part of the pair. [String](../../sql-reference/data-types/string.md), [Integer](../../sql-reference/data-types/int-uint.md) or [Array](../../sql-reference/data-types/array.md).
|
||||
|
||||
!!! warning "Warning"
|
||||
Currently `Map` data type is an experimental feature. To work with it you must set `allow_experimental_map_type = 1`.
|
||||
|
||||
To get the value from an `a Map('key', 'value')` column, use `a['key']` syntax. This lookup works now with a linear complexity.
|
||||
|
||||
**Examples**
|
||||
|
||||
Consider the table:
|
||||
|
||||
``` sql
|
||||
CREATE TABLE table_map (a Map(String, UInt64)) ENGINE=Memory;
|
||||
INSERT INTO table_map VALUES ({'key1':1, 'key2':10}), ({'key1':2,'key2':20}), ({'key1':3,'key2':30});
|
||||
```
|
||||
|
||||
Select all `key2` values:
|
||||
|
||||
```sql
|
||||
SELECT a['key2'] FROM table_map;
|
||||
```
|
||||
Result:
|
||||
|
||||
```text
|
||||
┌─arrayElement(a, 'key2')─┐
|
||||
│ 10 │
|
||||
│ 20 │
|
||||
│ 30 │
|
||||
└─────────────────────────┘
|
||||
```
|
||||
|
||||
If there's no such `key` in the `Map()` column, the query returns zeros for numerical values, empty strings or empty arrays.
|
||||
|
||||
```sql
|
||||
INSERT INTO table_map VALUES ({'key3':100}), ({});
|
||||
SELECT a['key3'] FROM table_map;
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
```text
|
||||
┌─arrayElement(a, 'key3')─┐
|
||||
│ 100 │
|
||||
│ 0 │
|
||||
└─────────────────────────┘
|
||||
┌─arrayElement(a, 'key3')─┐
|
||||
│ 0 │
|
||||
│ 0 │
|
||||
│ 0 │
|
||||
└─────────────────────────┘
|
||||
```
|
||||
|
||||
## Convert Tuple to Map Type {#map-and-tuple}
|
||||
|
||||
You can cast `Tuple()` as `Map()` using [CAST](../../sql-reference/functions/type-conversion-functions.md#type_conversion_function-cast) function:
|
||||
|
||||
``` sql
|
||||
SELECT CAST(([1, 2, 3], ['Ready', 'Steady', 'Go']), 'Map(UInt8, String)') AS map;
|
||||
```
|
||||
|
||||
``` text
|
||||
┌─map───────────────────────────┐
|
||||
│ {1:'Ready',2:'Steady',3:'Go'} │
|
||||
└───────────────────────────────┘
|
||||
```
|
||||
|
||||
**See Also**
|
||||
|
||||
- [map()](../../sql-reference/functions/tuple-map-functions.md#function-map) function
|
||||
- [CAST()](../../sql-reference/functions/type-conversion-functions.md#type_conversion_function-cast) function
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/data-types/map/) <!--hide-->
|
||||
@ -208,8 +208,8 @@ This function returns the value for the specified `id`s and the date range that
|
||||
Details of the algorithm:
|
||||
|
||||
- If the `id` is not found or a range is not found for the `id`, it returns the default value for the dictionary.
|
||||
- If there are overlapping ranges, you can use any.
|
||||
- If the range delimiter is `NULL` or an invalid date (such as 1900-01-01 or 2039-01-01), the range is left open. The range can be open on both sides.
|
||||
- If there are overlapping ranges, it returns value for any (random) range.
|
||||
- If the range delimiter is `NULL` or an invalid date (such as 1900-01-01), the range is open. The range can be open on both sides.
|
||||
|
||||
Configuration example:
|
||||
|
||||
|
||||
@ -380,7 +380,7 @@ Alias: `dateTrunc`.
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `unit` — The type of interval to truncate the result. [String](../../sql-reference/data-types/string.md).
|
||||
- `unit` — The type of interval to truncate the result. [String Literal](../syntax.md#syntax-string-literal).
|
||||
Possible values:
|
||||
|
||||
- `second`
|
||||
@ -518,6 +518,46 @@ Result:
|
||||
└────────────────────────────────────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
## 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.
|
||||
|
||||
@ -265,32 +265,81 @@ SELECT toIPv6('127.0.0.1')
|
||||
└─────────────────────┘
|
||||
```
|
||||
|
||||
## isIPv4String
|
||||
## isIPv4String {#isipv4string}
|
||||
|
||||
Determines if the input string is an IPv4 address or not. Returns `1` if true `0` otherwise.
|
||||
Determines whether the input string is an IPv4 address or not. If `string` is IPv6 address returns `0`.
|
||||
|
||||
``` sql
|
||||
SELECT isIPv4String('127.0.0.1')
|
||||
**Syntax**
|
||||
|
||||
```sql
|
||||
isIPv4String(string)
|
||||
```
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `string` — IP address. [String](../../sql-reference/data-types/string.md).
|
||||
|
||||
**Returned value**
|
||||
|
||||
- `1` if `string` is IPv4 address, `0` otherwise.
|
||||
|
||||
Type: [UInt8](../../sql-reference/data-types/int-uint.md).
|
||||
|
||||
**Examples**
|
||||
|
||||
Query:
|
||||
|
||||
```sql
|
||||
SELECT addr, isIPv4String(addr) FROM ( SELECT ['0.0.0.0', '127.0.0.1', '::ffff:127.0.0.1'] AS addr ) ARRAY JOIN addr
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
┌─isIPv4String('127.0.0.1')─┐
|
||||
│ 1 │
|
||||
└───────────────────────────┘
|
||||
┌─addr─────────────┬─isIPv4String(addr)─┐
|
||||
│ 0.0.0.0 │ 1 │
|
||||
│ 127.0.0.1 │ 1 │
|
||||
│ ::ffff:127.0.0.1 │ 0 │
|
||||
└──────────────────┴────────────────────┘
|
||||
```
|
||||
|
||||
## isIPv6String
|
||||
## isIPv6String {#isipv6string}
|
||||
|
||||
Determines if the input string is an IPv6 address or not. Returns `1` if true `0` otherwise.
|
||||
Determines whether the input string is an IPv6 address or not. If `string` is IPv4 address returns `0`.
|
||||
|
||||
**Syntax**
|
||||
|
||||
```sql
|
||||
isIPv6String(string)
|
||||
```
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `string` — IP address. [String](../../sql-reference/data-types/string.md).
|
||||
|
||||
**Returned value**
|
||||
|
||||
- `1` if `string` is IPv6 address, `0` otherwise.
|
||||
|
||||
Type: [UInt8](../../sql-reference/data-types/int-uint.md).
|
||||
|
||||
**Examples**
|
||||
|
||||
Query:
|
||||
|
||||
``` sql
|
||||
SELECT isIPv6String('2001:438:ffff::407d:1bc1')
|
||||
SELECT addr, isIPv6String(addr) FROM ( SELECT ['::', '1111::ffff', '::ffff:127.0.0.1', '127.0.0.1'] AS addr ) ARRAY JOIN addr
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
┌─isIPv6String('2001:438:ffff::407d:1bc1')─┐
|
||||
│ 1 │
|
||||
└──────────────────────────────────────────┘
|
||||
┌─addr─────────────┬─isIPv6String(addr)─┐
|
||||
│ :: │ 1 │
|
||||
│ 1111::ffff │ 1 │
|
||||
│ ::ffff:127.0.0.1 │ 1 │
|
||||
│ 127.0.0.1 │ 0 │
|
||||
└──────────────────┴────────────────────┘
|
||||
```
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/query_language/functions/ip_address_functions/) <!--hide-->
|
||||
|
||||
@ -909,6 +909,66 @@ WHERE diff != 1
|
||||
|
||||
Same as for [runningDifference](../../sql-reference/functions/other-functions.md#other_functions-runningdifference), the difference is the value of the first row, returned the value of the first row, and each subsequent row returns the difference from the previous row.
|
||||
|
||||
## runningConcurrency {#runningconcurrency}
|
||||
|
||||
Given a series of beginning time and ending time of events, this function calculates concurrency of the events at each of the data point, that is, the beginning time.
|
||||
|
||||
!!! warning "Warning"
|
||||
Events spanning multiple data blocks will not be processed correctly. The function resets its state for each new data block.
|
||||
|
||||
The result of the function depends on the order of data in the block. It assumes the beginning time is sorted in ascending order.
|
||||
|
||||
**Syntax**
|
||||
|
||||
``` sql
|
||||
runningConcurrency(begin, end)
|
||||
```
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `begin` — A column for the beginning time of events (inclusive). [Date](../../sql-reference/data-types/date.md), [DateTime](../../sql-reference/data-types/datetime.md), or [DateTime64](../../sql-reference/data-types/datetime64.md).
|
||||
- `end` — A column for the ending time of events (exclusive). [Date](../../sql-reference/data-types/date.md), [DateTime](../../sql-reference/data-types/datetime.md), or [DateTime64](../../sql-reference/data-types/datetime64.md).
|
||||
|
||||
Note that two columns `begin` and `end` must have the same type.
|
||||
|
||||
**Returned values**
|
||||
|
||||
- The concurrency of events at the data point.
|
||||
|
||||
Type: [UInt32](../../sql-reference/data-types/int-uint.md)
|
||||
|
||||
**Example**
|
||||
|
||||
Input table:
|
||||
|
||||
``` text
|
||||
┌───────────────begin─┬─────────────────end─┐
|
||||
│ 2020-12-01 00:00:00 │ 2020-12-01 00:59:59 │
|
||||
│ 2020-12-01 00:30:00 │ 2020-12-01 00:59:59 │
|
||||
│ 2020-12-01 00:40:00 │ 2020-12-01 01:30:30 │
|
||||
│ 2020-12-01 01:10:00 │ 2020-12-01 01:30:30 │
|
||||
│ 2020-12-01 01:50:00 │ 2020-12-01 01:59:59 │
|
||||
└─────────────────────┴─────────────────────┘
|
||||
```
|
||||
|
||||
Query:
|
||||
|
||||
``` sql
|
||||
SELECT runningConcurrency(begin, end) FROM example
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
┌─runningConcurrency(begin, end)─┐
|
||||
│ 1 │
|
||||
│ 2 │
|
||||
│ 3 │
|
||||
│ 2 │
|
||||
│ 1 │
|
||||
└────────────────────────────────┘
|
||||
```
|
||||
|
||||
## MACNumToString(num) {#macnumtostringnum}
|
||||
|
||||
Accepts a UInt64 number. Interprets it as a MAC address in big endian. Returns a string containing the corresponding MAC address in the format AA:BB:CC:DD:EE:FF (colon-separated numbers in hexadecimal form).
|
||||
|
||||
@ -5,6 +5,68 @@ toc_title: Working with maps
|
||||
|
||||
# Functions for maps {#functions-for-working-with-tuple-maps}
|
||||
|
||||
## map {#function-map}
|
||||
|
||||
Arranges `key:value` pairs into [Map(key, value)](../../sql-reference/data-types/map.md) data type.
|
||||
|
||||
**Syntax**
|
||||
|
||||
``` sql
|
||||
map(key1, value1[, key2, value2, ...])
|
||||
```
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `key` — The key part of the pair. [String](../../sql-reference/data-types/string.md) or [Integer](../../sql-reference/data-types/int-uint.md).
|
||||
- `value` — The value part of the pair. [String](../../sql-reference/data-types/string.md), [Integer](../../sql-reference/data-types/int-uint.md) or [Array](../../sql-reference/data-types/array.md).
|
||||
|
||||
**Returned value**
|
||||
|
||||
- Data structure as `key:value` pairs.
|
||||
|
||||
Type: [Map(key, value)](../../sql-reference/data-types/map.md).
|
||||
|
||||
**Examples**
|
||||
|
||||
Query:
|
||||
|
||||
``` sql
|
||||
SELECT map('key1', number, 'key2', number * 2) FROM numbers(3);
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
┌─map('key1', number, 'key2', multiply(number, 2))─┐
|
||||
│ {'key1':0,'key2':0} │
|
||||
│ {'key1':1,'key2':2} │
|
||||
│ {'key1':2,'key2':4} │
|
||||
└──────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
Query:
|
||||
|
||||
``` sql
|
||||
CREATE TABLE table_map (a Map(String, UInt64)) ENGINE = MergeTree() ORDER BY a;
|
||||
INSERT INTO table_map SELECT map('key1', number, 'key2', number * 2) FROM numbers(3);
|
||||
SELECT a['key2'] FROM table_map;
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
┌─arrayElement(a, 'key2')─┐
|
||||
│ 0 │
|
||||
│ 2 │
|
||||
│ 4 │
|
||||
└─────────────────────────┘
|
||||
```
|
||||
|
||||
**See Also**
|
||||
|
||||
- [Map(key, value)](../../sql-reference/data-types/map.md) data type
|
||||
|
||||
|
||||
## mapAdd {#function-mapadd}
|
||||
|
||||
Collect all the keys and sum corresponding values.
|
||||
@ -112,4 +174,4 @@ Result:
|
||||
└──────────────────────────────┴───────────────────────────────────┘
|
||||
```
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/query_language/functions/tuple-map-functions/) <!--hide-->
|
||||
[Original article](https://clickhouse.tech/docs/en/sql-reference/functions/tuple-map-functions/) <!--hide-->
|
||||
|
||||
@ -20,6 +20,7 @@ The following actions are supported:
|
||||
|
||||
- [ADD COLUMN](#alter_add-column) — Adds a new column to the table.
|
||||
- [DROP COLUMN](#alter_drop-column) — Deletes the column.
|
||||
- [RENAME COLUMN](#alter_rename-column) — Renames the column.
|
||||
- [CLEAR COLUMN](#alter_clear-column) — Resets column values.
|
||||
- [COMMENT COLUMN](#alter_comment-column) — Adds a text comment to the column.
|
||||
- [MODIFY COLUMN](#alter_modify-column) — Changes column’s type, default expression and TTL.
|
||||
@ -78,6 +79,22 @@ Example:
|
||||
ALTER TABLE visits DROP COLUMN browser
|
||||
```
|
||||
|
||||
## RENAME COLUMN {#alter_rename-column}
|
||||
|
||||
``` sql
|
||||
RENAME COLUMN [IF EXISTS] name to new_name
|
||||
```
|
||||
|
||||
Renames the column `name` to `new_name`. If the `IF EXISTS` clause is specified, the query won’t return an error if the column doesn’t exist. Since renaming does not involve the underlying data, the query is completed almost instantly.
|
||||
|
||||
**NOTE**: Columns specified in the key expression of the table (either with `ORDER BY` or `PRIMARY KEY`) cannot be renamed. Trying to change these columns will produce `SQL Error [524]`.
|
||||
|
||||
Example:
|
||||
|
||||
``` sql
|
||||
ALTER TABLE visits RENAME COLUMN webBrowser TO browser
|
||||
```
|
||||
|
||||
## CLEAR COLUMN {#alter_clear-column}
|
||||
|
||||
``` sql
|
||||
|
||||
@ -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).
|
||||
|
||||
|
||||
@ -59,6 +59,10 @@ A `SELECT` query can contain `DISTINCT`, `GROUP BY`, `ORDER BY`, `LIMIT`… Note
|
||||
|
||||
The execution of [ALTER](../../../sql-reference/statements/alter/index.md) queries on materialized views has limitations, so they might be inconvenient. If the materialized view uses the construction `TO [db.]name`, you can `DETACH` the view, run `ALTER` for the target table, and then `ATTACH` the previously detached (`DETACH`) view.
|
||||
|
||||
Note that materialized view is influenced by [optimize_on_insert](../../../operations/settings/settings.md#optimize-on-insert) setting. The data is merged before the insertion into a view.
|
||||
|
||||
Views look the same as normal tables. For example, they are listed in the result of the `SHOW TABLES` query.
|
||||
|
||||
There isn’t a separate query for deleting views. To delete a view, use [DROP TABLE](../../../sql-reference/statements/drop.md).
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/sql-reference/statements/create/view/) <!--hide-->
|
||||
|
||||
@ -62,8 +62,6 @@ If a list of columns doesn't include all existing columns, the rest of the colum
|
||||
- The values calculated from the `DEFAULT` expressions specified in the table definition.
|
||||
- Zeros and empty strings, if `DEFAULT` expressions are not defined.
|
||||
|
||||
If [strict\_insert\_defaults=1](../../operations/settings/settings.md), columns that do not have `DEFAULT` defined must be listed in the query.
|
||||
|
||||
Data can be passed to the INSERT in any [format](../../interfaces/formats.md#formats) supported by ClickHouse. The format must be specified explicitly in the query:
|
||||
|
||||
``` sql
|
||||
|
||||
@ -10,33 +10,49 @@ This is an experimental feature that is currently in development and is not read
|
||||
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.
|
||||
ClickHouse supports the standard grammar for defining windows and window functions. The following features are currently 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.
|
||||
| Feature | Support or workaround |
|
||||
| --------| ----------|
|
||||
| ad hoc window specification (`count(*) over (partition by id order by time desc)`) | yes |
|
||||
| `WINDOW` clause (`select ... from table window w as (partiton by id)`) | yes |
|
||||
| `ROWS` frame | yes |
|
||||
| `RANGE` frame | yes, it is the default |
|
||||
| `GROUPS` frame | no |
|
||||
| Calculating aggregate functions over a frame (`sum(value) over (order by time)`) | all aggregate functions are supported |
|
||||
| `rank()`, `dense_rank()`, `row_number()` | yes |
|
||||
| `lag/lead(value, offset)` | no, replace with `any(value) over (.... rows between <offset> preceding and <offset> preceding)`, or `following` for `lead`|
|
||||
|
||||
## 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
|
||||
|
||||
@ -5,7 +5,7 @@ toc_title: Copia de seguridad de datos
|
||||
|
||||
# Copia de seguridad de datos {#data-backup}
|
||||
|
||||
Mientras que la [replicación](../engines/table-engines/mergetree-family/replication.md) proporciona protección contra fallos de hardware, no protege de errores humanos: el borrado accidental de datos, elminar la tabla equivocada o una tabla en el clúster equivocado, y bugs de software que dan como resultado un procesado incorrecto de los datos o la corrupción de los datos. En muchos casos, errores como estos afectarán a todas las réplicas. ClickHouse dispone de salvaguardas para prevenir algunos tipos de errores — por ejemplo, por defecto [no se puede simplemente eliminar tablas con un motor similar a MergeTree que contenga más de 50 Gb de datos](https://github.com/ClickHouse/ClickHouse/blob/v18.14.18-stable/programs/server/config.xml#L322-L330). Sin embargo, estas salvaguardas no cubren todos los casos posibles y pueden eludirse.
|
||||
Mientras que la [replicación](../engines/table-engines/mergetree-family/replication.md) proporciona protección contra fallos de hardware, no protege de errores humanos: el borrado accidental de datos, elminar la tabla equivocada o una tabla en el clúster equivocado, y bugs de software que dan como resultado un procesado incorrecto de los datos o la corrupción de los datos. En muchos casos, errores como estos afectarán a todas las réplicas. ClickHouse dispone de salvaguardas para prevenir algunos tipos de errores — por ejemplo, por defecto [no se puede simplemente eliminar tablas con un motor similar a MergeTree que contenga más de 50 Gb de datos](server-configuration-parameters/settings.md#max-table-size-to-drop). Sin embargo, estas salvaguardas no cubren todos los casos posibles y pueden eludirse.
|
||||
|
||||
Para mitigar eficazmente los posibles errores humanos, debe preparar cuidadosamente una estrategia para realizar copias de seguridad y restaurar sus datos **previamente**.
|
||||
|
||||
|
||||
@ -7,7 +7,7 @@ toc_title: "La Sauvegarde Des Donn\xE9es"
|
||||
|
||||
# La Sauvegarde Des Données {#data-backup}
|
||||
|
||||
Alors [réplication](../engines/table-engines/mergetree-family/replication.md) provides protection from hardware failures, it does not protect against human errors: accidental deletion of data, deletion of the wrong table or a table on the wrong cluster, and software bugs that result in incorrect data processing or data corruption. In many cases mistakes like these will affect all replicas. ClickHouse has built-in safeguards to prevent some types of mistakes — for example, by default [vous ne pouvez pas simplement supprimer des tables avec un moteur de type MergeTree contenant plus de 50 Go de données](https://github.com/ClickHouse/ClickHouse/blob/v18.14.18-stable/programs/server/config.xml#L322-L330). Toutefois, ces garanties ne couvrent pas tous les cas possibles et peuvent être contournés.
|
||||
Alors [réplication](../engines/table-engines/mergetree-family/replication.md) provides protection from hardware failures, it does not protect against human errors: accidental deletion of data, deletion of the wrong table or a table on the wrong cluster, and software bugs that result in incorrect data processing or data corruption. In many cases mistakes like these will affect all replicas. ClickHouse has built-in safeguards to prevent some types of mistakes — for example, by default [vous ne pouvez pas simplement supprimer des tables avec un moteur de type MergeTree contenant plus de 50 Go de données](server-configuration-parameters/settings.md#max-table-size-to-drop). Toutefois, ces garanties ne couvrent pas tous les cas possibles et peuvent être contournés.
|
||||
|
||||
Afin d'atténuer efficacement les erreurs humaines possibles, vous devez préparer soigneusement une stratégie de sauvegarde et de restauration de vos données **préalablement**.
|
||||
|
||||
|
||||
@ -7,7 +7,7 @@ toc_title: "\u30C7\u30FC\u30BF\u30D0\u30C3\u30AF\u30A2"
|
||||
|
||||
# データバックア {#data-backup}
|
||||
|
||||
ながら [複製](../engines/table-engines/mergetree-family/replication.md) provides protection from hardware failures, it does not protect against human errors: accidental deletion of data, deletion of the wrong table or a table on the wrong cluster, and software bugs that result in incorrect data processing or data corruption. In many cases mistakes like these will affect all replicas. ClickHouse has built-in safeguards to prevent some types of mistakes — for example, by default [50Gbを超えるデータを含むMergeTreeのようなエンジンでは、テーブルを削除することはできません](https://github.com/ClickHouse/ClickHouse/blob/v18.14.18-stable/programs/server/config.xml#L322-L330). しかし、これらの保障措置がカバーしないすべてのケースで回避.
|
||||
ながら [複製](../engines/table-engines/mergetree-family/replication.md) provides protection from hardware failures, it does not protect against human errors: accidental deletion of data, deletion of the wrong table or a table on the wrong cluster, and software bugs that result in incorrect data processing or data corruption. In many cases mistakes like these will affect all replicas. ClickHouse has built-in safeguards to prevent some types of mistakes — for example, by default [50Gbを超えるデータを含むMergeTreeのようなエンジンでは、テーブルを削除することはできません](server-configuration-parameters/settings.md#max-table-size-to-drop). しかし、これらの保障措置がカバーしないすべてのケースで回避.
|
||||
|
||||
ヒューマンエラーを効果的に軽減するには、データのバックアップと復元のための戦略を慎重に準備する必要があります **事前に**.
|
||||
|
||||
|
||||
@ -93,6 +93,7 @@ DDL-запросы в MySQL конвертируются в соответств
|
||||
- Каскадные запросы `UPDATE/DELETE` не поддерживаются движком `MaterializeMySQL`.
|
||||
- Репликация может быть легко нарушена.
|
||||
- Прямые операции изменения данных в таблицах и базах данных `MaterializeMySQL` запрещены.
|
||||
- На работу `MaterializeMySQL` влияет настройка [optimize_on_insert](../../operations/settings/settings.md#optimize-on-insert). Когда таблица на MySQL сервере меняется, происходит слияние данных в соответсвующей таблице в базе данных `MaterializeMySQL`.
|
||||
|
||||
## Примеры использования {#examples-of-use}
|
||||
|
||||
@ -156,4 +157,4 @@ SELECT * FROM mysql.test;
|
||||
└───┴─────┴──────┘
|
||||
```
|
||||
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/ru/database_engines/materialize-mysql/) <!--hide-->
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/ru/engines/database-engines/materialize-mysql/) <!--hide-->
|
||||
|
||||
@ -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-->
|
||||
@ -94,6 +94,7 @@ ORDER BY expr
|
||||
- `max_parts_in_total` — максимальное количество кусков во всех партициях.
|
||||
- `max_compress_block_size` — максимальный размер блоков несжатых данных перед сжатием для записи в таблицу. Вы также можете задать этот параметр в глобальных настройках (смотрите [max_compress_block_size](../../../operations/settings/settings.md#max-compress-block-size)). Настройка, которая задается при создании таблицы, имеет более высокий приоритет, чем глобальная.
|
||||
- `min_compress_block_size` — минимальный размер блоков несжатых данных, необходимых для сжатия при записи следующей засечки. Вы также можете задать этот параметр в глобальных настройках (смотрите [min_compress_block_size](../../../operations/settings/settings.md#min-compress-block-size)). Настройка, которая задается при создании таблицы, имеет более высокий приоритет, чем глобальная.
|
||||
- `max_partitions_to_read` — Ограничивает максимальное число партиций для чтения в одном запросе. Также возможно указать настройку [max_partitions_to_read](../../../operations/settings/merge-tree-settings.md#max-partitions-to-read) в глобальных настройках.
|
||||
|
||||
**Пример задания секций**
|
||||
|
||||
@ -711,4 +712,4 @@ SETTINGS storage_policy = 'moving_from_ssd_to_hdd'
|
||||
|
||||
После выполнения фоновых слияний или мутаций старые куски не удаляются сразу, а через некоторое время (табличная настройка `old_parts_lifetime`). Также они не перемещаются на другие тома или диски, поэтому до момента удаления они продолжают учитываться при подсчёте занятого дискового пространства.
|
||||
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/en/engines/table-engines/mergetree-family/mergetree/) <!--hide-->
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/ru/engines/table-engines/mergetree-family/mergetree/) <!--hide-->
|
||||
|
||||
@ -5,7 +5,7 @@ toc_title: "\u0420\u0435\u0437\u0435\u0440\u0432\u043d\u043e\u0435\u0020\u043a\u
|
||||
|
||||
# Резервное копирование данных {#rezervnoe-kopirovanie-dannykh}
|
||||
|
||||
[Репликация](../engines/table-engines/mergetree-family/replication.md) обеспечивает защиту от аппаратных сбоев, но не защищает от человеческих ошибок: случайного удаления данных, удаления не той таблицы, которую надо было, или таблицы на не том кластере, а также программных ошибок, которые приводят к неправильной обработке данных или их повреждению. Во многих случаях подобные ошибки влияют на все реплики. ClickHouse имеет встроенные средства защиты для предотвращения некоторых типов ошибок — например, по умолчанию [не получится удалить таблицы \*MergeTree, содержащие более 50 Гб данных, одной командой](https://github.com/ClickHouse/ClickHouse/blob/v18.14.18-stable/programs/server/config.xml#L322-L330). Однако эти средства защиты не охватывают все возможные случаи и могут быть обойдены.
|
||||
[Репликация](../engines/table-engines/mergetree-family/replication.md) обеспечивает защиту от аппаратных сбоев, но не защищает от человеческих ошибок: случайного удаления данных, удаления не той таблицы, которую надо было, или таблицы на не том кластере, а также программных ошибок, которые приводят к неправильной обработке данных или их повреждению. Во многих случаях подобные ошибки влияют на все реплики. ClickHouse имеет встроенные средства защиты для предотвращения некоторых типов ошибок — например, по умолчанию [не получится удалить таблицы \*MergeTree, содержащие более 50 Гб данных, одной командой](server-configuration-parameters/settings.md#max-table-size-to-drop). Однако эти средства защиты не охватывают все возможные случаи и могут быть обойдены.
|
||||
|
||||
Для того чтобы эффективно уменьшить возможные человеческие ошибки, следует тщательно подготовить стратегию резервного копирования и восстановления данных **заранее**.
|
||||
|
||||
|
||||
@ -181,4 +181,16 @@ Eсли суммарное число активных кусков во все
|
||||
|
||||
При старте ClickHouse читает все куски всех таблиц (читает файлы с метаданными кусков), чтобы построить в ОЗУ список всех кусков. В некоторых системах с большим количеством кусков этот процесс может занимать длительное время, и это время можно сократить, увеличив `max_part_loading_threads` (если при этом процессе есть недозагруженность CPU и диска).
|
||||
|
||||
{## [Оригинальная статья](https://clickhouse.tech/docs/ru/operations/settings/merge-tree-settings/) ##}
|
||||
## max_partitions_to_read {#max-partitions-to-read}
|
||||
|
||||
Ограничивает максимальное число партиций для чтения в одном запросе.
|
||||
|
||||
Указанное при создании таблицы значение настройки может быть переназначено настройкой на уровне запроса.
|
||||
|
||||
Возможные значения:
|
||||
|
||||
- Любое положительное целое число.
|
||||
|
||||
Значение по умолчанию: -1 (неограниченно).
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/ru/operations/settings/merge_tree_settings/) <!--hide-->
|
||||
|
||||
@ -2473,4 +2473,58 @@ SELECT SUM(-1), MAX(0) FROM system.one WHERE 0;
|
||||
|
||||
Значение по умолчанию: `16`.
|
||||
|
||||
## optimize_on_insert {#optimize-on-insert}
|
||||
|
||||
Включает или выключает преобразование данных перед добавлением в таблицу, как будто над добавляемым блоком предварительно было произведено слияние (в соответствии с движком таблицы).
|
||||
|
||||
Возможные значения:
|
||||
|
||||
- 0 — выключена
|
||||
- 1 — включена.
|
||||
|
||||
Значение по умолчанию: 1.
|
||||
|
||||
**Пример**
|
||||
|
||||
Сравните добавление данных при включенной и выключенной настройке:
|
||||
|
||||
Запрос:
|
||||
|
||||
```sql
|
||||
SET optimize_on_insert = 1;
|
||||
|
||||
CREATE TABLE test1 (`FirstTable` UInt32) ENGINE = ReplacingMergeTree ORDER BY FirstTable;
|
||||
|
||||
INSERT INTO test1 SELECT number % 2 FROM numbers(5);
|
||||
|
||||
SELECT * FROM test1;
|
||||
|
||||
SET optimize_on_insert = 0;
|
||||
|
||||
CREATE TABLE test2 (`SecondTable` UInt32) ENGINE = ReplacingMergeTree ORDER BY SecondTable;
|
||||
|
||||
INSERT INTO test2 SELECT number % 2 FROM numbers(5);
|
||||
|
||||
SELECT * FROM test2;
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
``` text
|
||||
┌─FirstTable─┐
|
||||
│ 0 │
|
||||
│ 1 │
|
||||
└────────────┘
|
||||
|
||||
┌─SecondTable─┐
|
||||
│ 0 │
|
||||
│ 0 │
|
||||
│ 0 │
|
||||
│ 1 │
|
||||
│ 1 │
|
||||
└─────────────┘
|
||||
```
|
||||
|
||||
Обратите внимание на то, что эта настройка влияет на поведение [материализованных представлений](../../sql-reference/statements/create/view.md#materialized) и БД [MaterializeMySQL](../../engines/database-engines/materialize-mysql.md).
|
||||
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/ru/operations/settings/settings/) <!--hide-->
|
||||
|
||||
@ -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-->
|
||||
69
docs/ru/sql-reference/data-types/map.md
Normal file
69
docs/ru/sql-reference/data-types/map.md
Normal file
@ -0,0 +1,69 @@
|
||||
---
|
||||
toc_priority: 65
|
||||
toc_title: Map(key, value)
|
||||
---
|
||||
|
||||
# Map(key, value) {#data_type-map}
|
||||
|
||||
Тип данных `Map(key, value)` хранит пары `ключ:значение`.
|
||||
|
||||
**Параметры**
|
||||
- `key` — ключ. [String](../../sql-reference/data-types/string.md) или [Integer](../../sql-reference/data-types/int-uint.md).
|
||||
- `value` — значение. [String](../../sql-reference/data-types/string.md), [Integer](../../sql-reference/data-types/int-uint.md) или [Array](../../sql-reference/data-types/array.md).
|
||||
|
||||
!!! warning "Предупреждение"
|
||||
Сейчас использование типа данных `Map` является экспериментальной возможностью. Чтобы использовать этот тип данных, включите настройку `allow_experimental_map_type = 1`.
|
||||
|
||||
Чтобы получить значение из колонки `a Map('key', 'value')`, используйте синтаксис `a['key']`. В настоящее время такая подстановка работает по алгоритму с линейной сложностью.
|
||||
|
||||
**Примеры**
|
||||
|
||||
Рассмотрим таблицу:
|
||||
|
||||
``` sql
|
||||
CREATE TABLE table_map (a Map(String, UInt64)) ENGINE=Memory;
|
||||
INSERT INTO table_map VALUES ({'key1':1, 'key2':10}), ({'key1':2,'key2':20}), ({'key1':3,'key2':30});
|
||||
```
|
||||
|
||||
Выборка всех значений ключа `key2`:
|
||||
|
||||
```sql
|
||||
SELECT a['key2'] FROM table_map;
|
||||
```
|
||||
Результат:
|
||||
|
||||
```text
|
||||
┌─arrayElement(a, 'key2')─┐
|
||||
│ 10 │
|
||||
│ 20 │
|
||||
│ 30 │
|
||||
└─────────────────────────┘
|
||||
```
|
||||
|
||||
Если для какого-то ключа `key` в колонке с типом `Map()` нет значения, запрос возвращает нули для числовых колонок, пустые строки или пустые массивы.
|
||||
|
||||
```sql
|
||||
INSERT INTO table_map VALUES ({'key3':100}), ({});
|
||||
SELECT a['key3'] FROM table_map;
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
```text
|
||||
┌─arrayElement(a, 'key3')─┐
|
||||
│ 100 │
|
||||
│ 0 │
|
||||
└─────────────────────────┘
|
||||
┌─arrayElement(a, 'key3')─┐
|
||||
│ 0 │
|
||||
│ 0 │
|
||||
│ 0 │
|
||||
└─────────────────────────┘
|
||||
```
|
||||
|
||||
**См. также**
|
||||
|
||||
- функция [map()](../../sql-reference/functions/tuple-map-functions.md#function-map)
|
||||
- функция [CAST()](../../sql-reference/functions/type-conversion-functions.md#type_conversion_function-cast)
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/ru/data-types/map/) <!--hide-->
|
||||
@ -205,8 +205,8 @@ RANGE(MIN first MAX last)
|
||||
Особенности алгоритма:
|
||||
|
||||
- Если не найден `id` или для найденного `id` не найден диапазон, то возвращается значение по умолчанию для словаря.
|
||||
- Если есть перекрывающиеся диапазоны, то можно использовать любой подходящий.
|
||||
- Если граница диапазона `NULL` или некорректная дата (1900-01-01, 2039-01-01), то диапазон считается открытым. Диапазон может быть открытым с обеих сторон.
|
||||
- Если есть перекрывающиеся диапазоны, то возвращается значение из любого (случайного) подходящего диапазона.
|
||||
- Если граница диапазона `NULL` или некорректная дата (1900-01-01), то диапазон считается открытым. Диапазон может быть открытым с обеих сторон.
|
||||
|
||||
Пример конфигурации:
|
||||
|
||||
|
||||
@ -243,4 +243,81 @@ SELECT
|
||||
└───────────────────────────────────┴──────────────────────────────────┘
|
||||
```
|
||||
|
||||
## isIPv4String {#isipv4string}
|
||||
|
||||
Определяет, является ли строка адресом IPv4 или нет. Также вернет `0`, если `string` — адрес IPv6.
|
||||
|
||||
**Синтаксис**
|
||||
|
||||
```sql
|
||||
isIPv4String(string)
|
||||
```
|
||||
|
||||
**Параметры**
|
||||
|
||||
- `string` — IP адрес. [String](../../sql-reference/data-types/string.md).
|
||||
|
||||
**Возвращаемое значение**
|
||||
|
||||
- `1` если `string` является адресом IPv4 , иначе — `0`.
|
||||
|
||||
Тип: [UInt8](../../sql-reference/data-types/int-uint.md).
|
||||
|
||||
**Примеры**
|
||||
|
||||
Запрос:
|
||||
|
||||
```sql
|
||||
SELECT addr, isIPv4String(addr) FROM ( SELECT ['0.0.0.0', '127.0.0.1', '::ffff:127.0.0.1'] AS addr ) ARRAY JOIN addr
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
``` text
|
||||
┌─addr─────────────┬─isIPv4String(addr)─┐
|
||||
│ 0.0.0.0 │ 1 │
|
||||
│ 127.0.0.1 │ 1 │
|
||||
│ ::ffff:127.0.0.1 │ 0 │
|
||||
└──────────────────┴────────────────────┘
|
||||
```
|
||||
|
||||
## isIPv6String {#isipv6string}
|
||||
|
||||
Определяет, является ли строка адресом IPv6 или нет. Также вернет `0`, если `string` — адрес IPv4.
|
||||
|
||||
**Синтаксис**
|
||||
|
||||
```sql
|
||||
isIPv6String(string)
|
||||
```
|
||||
|
||||
**Параметры**
|
||||
|
||||
- `string` — IP адрес. [String](../../sql-reference/data-types/string.md).
|
||||
|
||||
**Возвращаемое значение**
|
||||
|
||||
- `1` если `string` является адресом IPv6 , иначе — `0`.
|
||||
|
||||
Тип: [UInt8](../../sql-reference/data-types/int-uint.md).
|
||||
|
||||
**Примеры**
|
||||
|
||||
Запрос:
|
||||
|
||||
``` sql
|
||||
SELECT addr, isIPv6String(addr) FROM ( SELECT ['::', '1111::ffff', '::ffff:127.0.0.1', '127.0.0.1'] AS addr ) ARRAY JOIN addr
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
``` text
|
||||
┌─addr─────────────┬─isIPv6String(addr)─┐
|
||||
│ :: │ 1 │
|
||||
│ 1111::ffff │ 1 │
|
||||
│ ::ffff:127.0.0.1 │ 1 │
|
||||
│ 127.0.0.1 │ 0 │
|
||||
└──────────────────┴────────────────────┘
|
||||
```
|
||||
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/ru/query_language/functions/ip_address_functions/) <!--hide-->
|
||||
|
||||
@ -5,6 +5,66 @@ toc_title: Работа с контейнерами map
|
||||
|
||||
# Функции для работы с контейнерами map {#functions-for-working-with-tuple-maps}
|
||||
|
||||
## map {#function-map}
|
||||
|
||||
Преобразовывает пары `ключ:значение` в тип данных [Map(key, value)](../../sql-reference/data-types/map.md).
|
||||
|
||||
**Синтаксис**
|
||||
|
||||
``` sql
|
||||
map(key1, value1[, key2, value2, ...])
|
||||
```
|
||||
|
||||
**Параметры**
|
||||
|
||||
- `key` — ключ. [String](../../sql-reference/data-types/string.md) или [Integer](../../sql-reference/data-types/int-uint.md).
|
||||
- `value` — значение. [String](../../sql-reference/data-types/string.md), [Integer](../../sql-reference/data-types/int-uint.md) или [Array](../../sql-reference/data-types/array.md).
|
||||
|
||||
**Возвращаемое значение**
|
||||
|
||||
- Структура данных в виде пар `ключ:значение`.
|
||||
|
||||
Тип: [Map(key, value)](../../sql-reference/data-types/map.md).
|
||||
|
||||
**Примеры**
|
||||
|
||||
Запрос:
|
||||
|
||||
``` sql
|
||||
SELECT map('key1', number, 'key2', number * 2) FROM numbers(3);
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
``` text
|
||||
┌─map('key1', number, 'key2', multiply(number, 2))─┐
|
||||
│ {'key1':0,'key2':0} │
|
||||
│ {'key1':1,'key2':2} │
|
||||
│ {'key1':2,'key2':4} │
|
||||
└──────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
Запрос:
|
||||
|
||||
``` sql
|
||||
CREATE TABLE table_map (a Map(String, UInt64)) ENGINE = MergeTree() ORDER BY a;
|
||||
INSERT INTO table_map SELECT map('key1', number, 'key2', number * 2) FROM numbers(3);
|
||||
SELECT a['key2'] FROM table_map;
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
``` text
|
||||
┌─arrayElement(a, 'key2')─┐
|
||||
│ 0 │
|
||||
│ 2 │
|
||||
│ 4 │
|
||||
└─────────────────────────┘
|
||||
```
|
||||
|
||||
**См. также**
|
||||
|
||||
- тип данных [Map(key, value)](../../sql-reference/data-types/map.md)
|
||||
## mapAdd {#function-mapadd}
|
||||
|
||||
Собирает все ключи и суммирует соответствующие значения.
|
||||
|
||||
@ -56,9 +56,10 @@ CREATE MATERIALIZED VIEW [IF NOT EXISTS] [db.]table_name [ON CLUSTER] [TO[db.]na
|
||||
|
||||
Недоработано выполнение запросов `ALTER` над материализованными представлениями, поэтому они могут быть неудобными для использования. Если материализованное представление использует конструкцию `TO [db.]name`, то можно выполнить `DETACH` представления, `ALTER` для целевой таблицы и последующий `ATTACH` ранее отсоединенного (`DETACH`) представления.
|
||||
|
||||
Обратите внимание, что работа материлизованного представления находится под влиянием настройки [optimize_on_insert](../../../operations/settings/settings.md#optimize-on-insert). Перед вставкой данных в таблицу происходит их слияние.
|
||||
|
||||
Представления выглядят так же, как обычные таблицы. Например, они перечисляются в результате запроса `SHOW TABLES`.
|
||||
|
||||
Отсутствует отдельный запрос для удаления представлений. Чтобы удалить представление, следует использовать `DROP TABLE`.
|
||||
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/ru/sql-reference/statements/create/view)
|
||||
<!--hide-->
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/ru/sql-reference/statements/create/view) <!--hide-->
|
||||
|
||||
@ -63,8 +63,6 @@ SELECT * FROM insert_select_testtable
|
||||
- Значения, вычисляемые из `DEFAULT` выражений, указанных в определении таблицы.
|
||||
- Нули и пустые строки, если `DEFAULT` не определены.
|
||||
|
||||
Если [strict_insert_defaults=1](../../operations/settings/settings.md), то столбцы, для которых не определены `DEFAULT`, необходимо перечислить в запросе.
|
||||
|
||||
В INSERT можно передавать данные любого [формата](../../interfaces/formats.md#formats), который поддерживает ClickHouse. Для этого формат необходимо указать в запросе в явном виде:
|
||||
|
||||
``` sql
|
||||
|
||||
@ -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`.
|
||||
|
||||
|
||||
@ -7,7 +7,7 @@ toc_title: "\u6570\u636E\u5907\u4EFD"
|
||||
|
||||
# 数据备份 {#data-backup}
|
||||
|
||||
尽管[副本](../engines/table-engines/mergetree-family/replication.md) 可以预防硬件错误带来的数据丢失, 但是它不能防止人为操作的错误: 意外删除数据, 删除错误的 table 或者删除错误 cluster 上的 table, 可以导致错误数据处理错误或者数据损坏的 bugs. 这类意外可能会影响所有的副本. ClickHouse 有内建的保障措施可以预防一些错误 — 例如, 默认情况下[您不能使用类似MergeTree的引擎删除包含超过50Gb数据的表](https://github.com/ClickHouse/ClickHouse/blob/v18.14.18-stable/programs/server/config.xml#L322-L330). 但是，这些保障措施不能涵盖所有可能的情况，并且可以规避。
|
||||
尽管[副本](../engines/table-engines/mergetree-family/replication.md) 可以预防硬件错误带来的数据丢失, 但是它不能防止人为操作的错误: 意外删除数据, 删除错误的 table 或者删除错误 cluster 上的 table, 可以导致错误数据处理错误或者数据损坏的 bugs. 这类意外可能会影响所有的副本. ClickHouse 有内建的保障措施可以预防一些错误 — 例如, 默认情况下[您不能使用类似MergeTree的引擎删除包含超过50Gb数据的表](server-configuration-parameters/settings.md#max-table-size-to-drop). 但是，这些保障措施不能涵盖所有可能的情况，并且可以规避。
|
||||
|
||||
为了有效地减少可能的人为错误，您应该 **提前**准备备份和还原数据的策略.
|
||||
|
||||
|
||||
@ -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.
|
||||
|
||||
@ -1374,7 +1374,30 @@ private:
|
||||
{
|
||||
// Probably the server is dead because we found an assertion
|
||||
// failure. Fail fast.
|
||||
fmt::print(stderr, "Lost connection to the server\n");
|
||||
fmt::print(stderr, "Lost connection to the server.\n");
|
||||
|
||||
// Print the changed settings because they might be needed to
|
||||
// reproduce the error.
|
||||
const auto & changes = context.getSettingsRef().changes();
|
||||
if (!changes.empty())
|
||||
{
|
||||
fmt::print(stderr, "Changed settings: ");
|
||||
for (size_t i = 0; i < changes.size(); ++i)
|
||||
{
|
||||
if (i)
|
||||
{
|
||||
fmt::print(stderr, ", ");
|
||||
}
|
||||
fmt::print(stderr, "{} = '{}'", changes[i].name,
|
||||
toString(changes[i].value));
|
||||
}
|
||||
fmt::print(stderr, "\n");
|
||||
}
|
||||
else
|
||||
{
|
||||
fmt::print(stderr, "No changed settings.\n");
|
||||
}
|
||||
|
||||
return false;
|
||||
}
|
||||
|
||||
@ -1719,7 +1742,7 @@ 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)
|
||||
{
|
||||
|
||||
@ -363,6 +363,16 @@ void QueryFuzzer::fuzzWindowFrame(WindowFrame & frame)
|
||||
frame.end_offset = getRandomField(0).get<Int64>();
|
||||
break;
|
||||
}
|
||||
case 5:
|
||||
{
|
||||
frame.begin_preceding = fuzz_rand() % 2;
|
||||
break;
|
||||
}
|
||||
case 6:
|
||||
{
|
||||
frame.end_preceding = fuzz_rand() % 2;
|
||||
break;
|
||||
}
|
||||
default:
|
||||
break;
|
||||
}
|
||||
|
||||
@ -29,4 +29,25 @@
|
||||
<test>{display_name} \x01\e[1;32m\x02:)\x01\e[0m\x02 </test> <!-- if it matched to the substring "test" in the server display name - -->
|
||||
<production>{display_name} \x01\e[1;31m\x02:)\x01\e[0m\x02 </production> <!-- if it matched to the substring "production" in the server display name -->
|
||||
</prompt_by_server_display_name>
|
||||
|
||||
<!--
|
||||
Settings adjustable via command-line parameters
|
||||
can take their defaults from that config file, see examples:
|
||||
|
||||
<host>127.0.0.1</host>
|
||||
<port>9440</port>
|
||||
<secure>1</secure>
|
||||
<user>dbuser</user>
|
||||
<password>dbpwd123</password>
|
||||
<format>PrettyCompactMonoBlock</format>
|
||||
<multiline>1</multiline>
|
||||
<multiquery>1</multiquery>
|
||||
<stacktrace>1</stacktrace>
|
||||
<database>default2</database>
|
||||
<pager>less -SR</pager>
|
||||
<history_file>/home/user/clickhouse_custom_history.log</history_file>
|
||||
<max_parser_depth>2500</max_parser_depth>
|
||||
|
||||
The same can be done on user-level configuration, just create & adjust: ~/.clickhouse-client/config.xml
|
||||
-->
|
||||
</config>
|
||||
|
||||
@ -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",
|
||||
@ -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;
|
||||
}
|
||||
|
||||
@ -59,7 +59,6 @@
|
||||
#include <Disks/registerDisks.h>
|
||||
#include <Common/Config/ConfigReloader.h>
|
||||
#include <Server/HTTPHandlerFactory.h>
|
||||
#include <Server/TestKeeperTCPHandlerFactory.h>
|
||||
#include "MetricsTransmitter.h"
|
||||
#include <Common/StatusFile.h>
|
||||
#include <Server/TCPHandlerFactory.h>
|
||||
@ -94,6 +93,9 @@
|
||||
# include <Server/GRPCServer.h>
|
||||
#endif
|
||||
|
||||
#if USE_NURAFT
|
||||
# include <Server/NuKeeperTCPHandlerFactory.h>
|
||||
#endif
|
||||
|
||||
namespace CurrentMetrics
|
||||
{
|
||||
@ -842,23 +844,33 @@ int Server::main(const std::vector<std::string> & /*args*/)
|
||||
listen_try = true;
|
||||
}
|
||||
|
||||
for (const auto & listen_host : listen_hosts)
|
||||
if (config().has("test_keeper_server"))
|
||||
{
|
||||
/// TCP TestKeeper
|
||||
const char * port_name = "test_keeper_server.tcp_port";
|
||||
createServer(listen_host, port_name, listen_try, [&](UInt16 port)
|
||||
#if USE_NURAFT
|
||||
/// Initialize test keeper RAFT. Do nothing if no nu_keeper_server in config.
|
||||
global_context->initializeNuKeeperStorageDispatcher();
|
||||
for (const auto & listen_host : listen_hosts)
|
||||
{
|
||||
Poco::Net::ServerSocket socket;
|
||||
auto address = socketBindListen(socket, listen_host, port);
|
||||
socket.setReceiveTimeout(settings.receive_timeout);
|
||||
socket.setSendTimeout(settings.send_timeout);
|
||||
servers_to_start_before_tables->emplace_back(
|
||||
port_name,
|
||||
std::make_unique<Poco::Net::TCPServer>(
|
||||
new TestKeeperTCPHandlerFactory(*this), server_pool, socket, new Poco::Net::TCPServerParams));
|
||||
/// TCP NuKeeper
|
||||
const char * port_name = "test_keeper_server.tcp_port";
|
||||
createServer(listen_host, port_name, listen_try, [&](UInt16 port)
|
||||
{
|
||||
Poco::Net::ServerSocket socket;
|
||||
auto address = socketBindListen(socket, listen_host, port);
|
||||
socket.setReceiveTimeout(settings.receive_timeout);
|
||||
socket.setSendTimeout(settings.send_timeout);
|
||||
servers_to_start_before_tables->emplace_back(
|
||||
port_name,
|
||||
std::make_unique<Poco::Net::TCPServer>(
|
||||
new NuKeeperTCPHandlerFactory(*this), server_pool, socket, new Poco::Net::TCPServerParams));
|
||||
|
||||
LOG_INFO(log, "Listening for connections to NuKeeper (tcp): {}", address.toString());
|
||||
});
|
||||
}
|
||||
#else
|
||||
throw Exception(ErrorCodes::SUPPORT_IS_DISABLED, "ClickHouse server built without NuRaft library. Cannot use internal coordination.");
|
||||
#endif
|
||||
|
||||
LOG_INFO(log, "Listening for connections to fake zookeeper (tcp): {}", address.toString());
|
||||
});
|
||||
}
|
||||
|
||||
for (auto & server : *servers_to_start_before_tables)
|
||||
@ -898,6 +910,8 @@ int Server::main(const std::vector<std::string> & /*args*/)
|
||||
LOG_INFO(log, "Closed connections to servers for tables. But {} remain. Probably some tables of other users cannot finish their connections after context shutdown.", current_connections);
|
||||
else
|
||||
LOG_INFO(log, "Closed connections to servers for tables.");
|
||||
|
||||
global_context->shutdownNuKeeperStorageDispatcher();
|
||||
}
|
||||
|
||||
/** Explicitly destroy Context. It is more convenient than in destructor of Server, because logger is still available.
|
||||
|
||||
@ -421,9 +421,15 @@
|
||||
<!-- Comma-separated list of prefixes for user-defined settings. -->
|
||||
<custom_settings_prefixes></custom_settings_prefixes>
|
||||
|
||||
<!-- System profile of settings. This settings are used by internal processes (Buffer storage, Distributed DDL worker and so on). -->
|
||||
<!-- System profile of settings. This settings are used by internal processes (Distributed DDL worker and so on). -->
|
||||
<!-- <system_profile>default</system_profile> -->
|
||||
|
||||
<!-- Buffer profile of settings.
|
||||
This settings are used by Buffer storage to flush data to the underlying table.
|
||||
Default: used from system_profile directive.
|
||||
-->
|
||||
<!-- <buffer_profile>default</buffer_profile> -->
|
||||
|
||||
<!-- Default database. -->
|
||||
<default_database>default</default_database>
|
||||
|
||||
|
||||
@ -217,6 +217,7 @@ namespace
|
||||
/// Write the file.
|
||||
WriteBufferFromFile out{tmp_file_path.string()};
|
||||
out.write(file_contents.data(), file_contents.size());
|
||||
out.close();
|
||||
|
||||
/// Rename.
|
||||
std::filesystem::rename(tmp_file_path, file_path);
|
||||
@ -274,6 +275,7 @@ namespace
|
||||
writeStringBinary(name, out);
|
||||
writeUUIDText(id, out);
|
||||
}
|
||||
out.close();
|
||||
}
|
||||
|
||||
|
||||
|
||||
@ -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);
|
||||
|
||||
@ -34,6 +34,14 @@ void registerAggregateFunctionsAny(AggregateFunctionFactory & factory)
|
||||
factory.registerFunction("any", { createAggregateFunctionAny, properties });
|
||||
factory.registerFunction("anyLast", { createAggregateFunctionAnyLast, properties });
|
||||
factory.registerFunction("anyHeavy", { createAggregateFunctionAnyHeavy, properties });
|
||||
|
||||
// Synonyms for use as window functions.
|
||||
factory.registerFunction("first_value",
|
||||
{ createAggregateFunctionAny, properties },
|
||||
AggregateFunctionFactory::CaseInsensitive);
|
||||
factory.registerFunction("last_value",
|
||||
{ createAggregateFunctionAnyLast, properties },
|
||||
AggregateFunctionFactory::CaseInsensitive);
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
49
src/AggregateFunctions/AggregateFunctionDeltaSum.cpp
Normal file
49
src/AggregateFunctions/AggregateFunctionDeltaSum.cpp
Normal file
@ -0,0 +1,49 @@
|
||||
#include <AggregateFunctions/AggregateFunctionDeltaSum.h>
|
||||
|
||||
#include <AggregateFunctions/AggregateFunctionFactory.h>
|
||||
#include <AggregateFunctions/FactoryHelpers.h>
|
||||
#include <AggregateFunctions/Helpers.h>
|
||||
|
||||
|
||||
namespace DB
|
||||
{
|
||||
|
||||
namespace ErrorCodes
|
||||
{
|
||||
extern const int NUMBER_OF_ARGUMENTS_DOESNT_MATCH;
|
||||
extern const int ILLEGAL_TYPE_OF_ARGUMENT;
|
||||
}
|
||||
|
||||
namespace
|
||||
{
|
||||
|
||||
AggregateFunctionPtr createAggregateFunctionDeltaSum(
|
||||
const String & name,
|
||||
const DataTypes & arguments,
|
||||
const Array & params)
|
||||
{
|
||||
assertNoParameters(name, params);
|
||||
|
||||
if (arguments.size() != 1)
|
||||
throw Exception("Incorrect number of arguments for aggregate function " + name,
|
||||
ErrorCodes::NUMBER_OF_ARGUMENTS_DOESNT_MATCH);
|
||||
|
||||
DataTypePtr data_type = arguments[0];
|
||||
|
||||
if (isInteger(data_type) || isFloat(data_type))
|
||||
return AggregateFunctionPtr(createWithNumericType<AggregationFunctionDeltaSum>(
|
||||
*data_type, arguments, params));
|
||||
else
|
||||
throw Exception("Illegal type " + arguments[0]->getName() + " of argument for aggregate function " + name,
|
||||
ErrorCodes::ILLEGAL_TYPE_OF_ARGUMENT);
|
||||
}
|
||||
}
|
||||
|
||||
void registerAggregateFunctionDeltaSum(AggregateFunctionFactory & factory)
|
||||
{
|
||||
AggregateFunctionProperties properties = { .returns_default_when_only_null = true, .is_order_dependent = true };
|
||||
|
||||
factory.registerFunction("deltaSum", { createAggregateFunctionDeltaSum, properties });
|
||||
}
|
||||
|
||||
}
|
||||
129
src/AggregateFunctions/AggregateFunctionDeltaSum.h
Normal file
129
src/AggregateFunctions/AggregateFunctionDeltaSum.h
Normal file
@ -0,0 +1,129 @@
|
||||
#pragma once
|
||||
|
||||
#include <type_traits>
|
||||
#include <experimental/type_traits>
|
||||
|
||||
#include <IO/ReadHelpers.h>
|
||||
#include <IO/WriteHelpers.h>
|
||||
|
||||
#include <Columns/ColumnVector.h>
|
||||
#include <DataTypes/DataTypesDecimal.h>
|
||||
#include <DataTypes/DataTypesNumber.h>
|
||||
|
||||
#include <AggregateFunctions/IAggregateFunction.h>
|
||||
|
||||
|
||||
namespace DB
|
||||
{
|
||||
|
||||
template <typename T>
|
||||
struct AggregationFunctionDeltaSumData
|
||||
{
|
||||
T sum = 0;
|
||||
T last = 0;
|
||||
T first = 0;
|
||||
bool seen_last = false;
|
||||
bool seen_first = false;
|
||||
};
|
||||
|
||||
template <typename T>
|
||||
class AggregationFunctionDeltaSum final
|
||||
: public IAggregateFunctionDataHelper<AggregationFunctionDeltaSumData<T>, AggregationFunctionDeltaSum<T>>
|
||||
{
|
||||
public:
|
||||
AggregationFunctionDeltaSum(const DataTypes & arguments, const Array & params)
|
||||
: IAggregateFunctionDataHelper<AggregationFunctionDeltaSumData<T>, AggregationFunctionDeltaSum<T>>{arguments, params}
|
||||
{}
|
||||
|
||||
AggregationFunctionDeltaSum()
|
||||
: IAggregateFunctionDataHelper<AggregationFunctionDeltaSumData<T>, AggregationFunctionDeltaSum<T>>{}
|
||||
{}
|
||||
|
||||
String getName() const override { return "deltaSum"; }
|
||||
|
||||
DataTypePtr getReturnType() const override { return std::make_shared<DataTypeNumber<T>>(); }
|
||||
|
||||
void NO_SANITIZE_UNDEFINED ALWAYS_INLINE add(AggregateDataPtr __restrict place, const IColumn ** columns, size_t row_num, Arena *) const override
|
||||
{
|
||||
auto value = assert_cast<const ColumnVector<T> &>(*columns[0]).getData()[row_num];
|
||||
|
||||
if ((this->data(place).last < value) && this->data(place).seen_last)
|
||||
{
|
||||
this->data(place).sum += (value - this->data(place).last);
|
||||
}
|
||||
|
||||
this->data(place).last = value;
|
||||
this->data(place).seen_last = true;
|
||||
|
||||
if (!this->data(place).seen_first)
|
||||
{
|
||||
this->data(place).first = value;
|
||||
this->data(place).seen_first = true;
|
||||
}
|
||||
}
|
||||
|
||||
void NO_SANITIZE_UNDEFINED ALWAYS_INLINE merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena *) const override
|
||||
{
|
||||
auto place_data = &this->data(place);
|
||||
auto rhs_data = &this->data(rhs);
|
||||
|
||||
if ((place_data->last < rhs_data->first) && place_data->seen_last && rhs_data->seen_first)
|
||||
{
|
||||
// If the lhs last number seen is less than the first number the rhs saw, the lhs is before
|
||||
// the rhs, for example [0, 2] [4, 7]. So we want to add the deltasums, but also add the
|
||||
// difference between lhs last number and rhs first number (the 2 and 4). Then we want to
|
||||
// take last value from the rhs, so first and last become 0 and 7.
|
||||
|
||||
place_data->sum += rhs_data->sum + (rhs_data->first - place_data->last);
|
||||
place_data->last = rhs_data->last;
|
||||
}
|
||||
else if ((rhs_data->last < place_data->first && rhs_data->seen_last && place_data->seen_first))
|
||||
{
|
||||
// In the opposite scenario, the lhs comes after the rhs, e.g. [4, 6] [1, 2]. Since we
|
||||
// assume the input interval states are sorted by time, we assume this is a counter
|
||||
// reset, and therefore do *not* add the difference between our first value and the
|
||||
// rhs last value.
|
||||
|
||||
place_data->sum += rhs_data->sum;
|
||||
place_data->first = rhs_data->first;
|
||||
}
|
||||
else if (rhs_data->seen_first)
|
||||
{
|
||||
// If we're here then the lhs is an empty state and the rhs does have some state, so
|
||||
// we'll just take that state.
|
||||
|
||||
place_data->first = rhs_data->first;
|
||||
place_data->seen_first = rhs_data->seen_first;
|
||||
place_data->last = rhs_data->last;
|
||||
place_data->seen_last = rhs_data->seen_last;
|
||||
place_data->sum = rhs_data->sum;
|
||||
}
|
||||
|
||||
// Otherwise lhs either has data or is uninitialized, so we don't need to modify its values.
|
||||
}
|
||||
|
||||
void serialize(ConstAggregateDataPtr __restrict place, WriteBuffer & buf) const override
|
||||
{
|
||||
writeIntBinary(this->data(place).sum, buf);
|
||||
writeIntBinary(this->data(place).first, buf);
|
||||
writeIntBinary(this->data(place).last, buf);
|
||||
writePODBinary<bool>(this->data(place).seen_first, buf);
|
||||
writePODBinary<bool>(this->data(place).seen_last, buf);
|
||||
}
|
||||
|
||||
void deserialize(AggregateDataPtr __restrict place, ReadBuffer & buf, Arena *) const override
|
||||
{
|
||||
readIntBinary(this->data(place).sum, buf);
|
||||
readIntBinary(this->data(place).first, buf);
|
||||
readIntBinary(this->data(place).last, buf);
|
||||
readPODBinary<bool>(this->data(place).seen_first, buf);
|
||||
readPODBinary<bool>(this->data(place).seen_last, buf);
|
||||
}
|
||||
|
||||
void insertResultInto(AggregateDataPtr __restrict place, IColumn & to, Arena *) const override
|
||||
{
|
||||
assert_cast<ColumnVector<T> &>(to).getData().push_back(this->data(place).sum);
|
||||
}
|
||||
};
|
||||
|
||||
}
|
||||
@ -40,7 +40,7 @@ struct MovingData
|
||||
Array value; /// Prefix sums.
|
||||
T sum = 0;
|
||||
|
||||
void add(T val, Arena * arena)
|
||||
void NO_SANITIZE_UNDEFINED add(T val, Arena * arena)
|
||||
{
|
||||
sum += val;
|
||||
value.push_back(sum, arena);
|
||||
@ -120,7 +120,7 @@ public:
|
||||
this->data(place).add(static_cast<ResultT>(value), arena);
|
||||
}
|
||||
|
||||
void merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena * arena) const override
|
||||
void NO_SANITIZE_UNDEFINED merge(AggregateDataPtr __restrict place, ConstAggregateDataPtr rhs, Arena * arena) const override
|
||||
{
|
||||
auto & cur_elems = this->data(place);
|
||||
auto & rhs_elems = this->data(rhs);
|
||||
|
||||
@ -16,6 +16,22 @@ namespace ErrorCodes
|
||||
|
||||
namespace
|
||||
{
|
||||
|
||||
template <template <typename, typename> class AggregateFunctionTemplate, template <typename> class Data, typename... TArgs>
|
||||
static IAggregateFunction * createWithIntegerType(const IDataType & argument_type, TArgs && ... args)
|
||||
{
|
||||
WhichDataType which(argument_type);
|
||||
if (which.idx == TypeIndex::UInt8) return new AggregateFunctionTemplate<UInt8, Data<UInt8>>(std::forward<TArgs>(args)...);
|
||||
if (which.idx == TypeIndex::UInt16) return new AggregateFunctionTemplate<UInt16, Data<UInt16>>(std::forward<TArgs>(args)...);
|
||||
if (which.idx == TypeIndex::UInt32) return new AggregateFunctionTemplate<UInt32, Data<UInt32>>(std::forward<TArgs>(args)...);
|
||||
if (which.idx == TypeIndex::UInt64) return new AggregateFunctionTemplate<UInt64, Data<UInt64>>(std::forward<TArgs>(args)...);
|
||||
if (which.idx == TypeIndex::Int8) return new AggregateFunctionTemplate<Int8, Data<Int8>>(std::forward<TArgs>(args)...);
|
||||
if (which.idx == TypeIndex::Int16) return new AggregateFunctionTemplate<Int16, Data<Int16>>(std::forward<TArgs>(args)...);
|
||||
if (which.idx == TypeIndex::Int32) return new AggregateFunctionTemplate<Int32, Data<Int32>>(std::forward<TArgs>(args)...);
|
||||
if (which.idx == TypeIndex::Int64) return new AggregateFunctionTemplate<Int64, Data<Int64>>(std::forward<TArgs>(args)...);
|
||||
return nullptr;
|
||||
}
|
||||
|
||||
template <template <typename> class Data>
|
||||
AggregateFunctionPtr createAggregateFunctionBitmap(const std::string & name, const DataTypes & argument_types, const Array & parameters)
|
||||
{
|
||||
@ -28,7 +44,7 @@ namespace
|
||||
+ " is illegal, because it cannot be used in Bitmap operations",
|
||||
ErrorCodes::ILLEGAL_TYPE_OF_ARGUMENT);
|
||||
|
||||
AggregateFunctionPtr res(createWithUnsignedIntegerType<AggregateFunctionBitmap, Data>(*argument_types[0], argument_types[0]));
|
||||
AggregateFunctionPtr res(createWithIntegerType<AggregateFunctionBitmap, Data>(*argument_types[0], argument_types[0]));
|
||||
|
||||
if (!res)
|
||||
throw Exception(
|
||||
@ -55,7 +71,7 @@ namespace
|
||||
const DataTypeAggregateFunction & datatype_aggfunc = dynamic_cast<const DataTypeAggregateFunction &>(*argument_type_ptr);
|
||||
AggregateFunctionPtr aggfunc = datatype_aggfunc.getFunction();
|
||||
argument_type_ptr = aggfunc->getArgumentTypes()[0];
|
||||
AggregateFunctionPtr res(createWithUnsignedIntegerType<AggregateFunctionTemplate, AggregateFunctionGroupBitmapData>(
|
||||
AggregateFunctionPtr res(createWithIntegerType<AggregateFunctionTemplate, AggregateFunctionGroupBitmapData>(
|
||||
*argument_type_ptr, argument_type_ptr));
|
||||
if (!res)
|
||||
throw Exception(
|
||||
|
||||
@ -32,6 +32,7 @@ template <typename T, UInt8 small_set_size>
|
||||
class RoaringBitmapWithSmallSet : private boost::noncopyable
|
||||
{
|
||||
private:
|
||||
using UnsignedT = std::make_unsigned_t<T>;
|
||||
SmallSet<T, small_set_size> small;
|
||||
using ValueBuffer = std::vector<T>;
|
||||
using RoaringBitmap = std::conditional_t<sizeof(T) >= 8, roaring::Roaring64Map, roaring::Roaring>;
|
||||
@ -363,6 +364,7 @@ public:
|
||||
/**
|
||||
* Check whether the argument is the subset of this set.
|
||||
* Empty set is a subset of any other set (consistent with hasAll).
|
||||
* It's used in subset and currently only support comparing same type
|
||||
*/
|
||||
UInt8 rb_is_subset(const RoaringBitmapWithSmallSet & r1) const
|
||||
{
|
||||
@ -486,6 +488,7 @@ public:
|
||||
|
||||
/**
|
||||
* Return new set with specified range (not include the range_end)
|
||||
* It's used in subset and currently only support UInt32
|
||||
*/
|
||||
UInt64 rb_range(UInt64 range_start, UInt64 range_end, RoaringBitmapWithSmallSet & r1) const
|
||||
{
|
||||
@ -525,6 +528,7 @@ public:
|
||||
|
||||
/**
|
||||
* Return new set of the smallest `limit` values in set which is no less than `range_start`.
|
||||
* It's used in subset and currently only support UInt32
|
||||
*/
|
||||
UInt64 rb_limit(UInt64 range_start, UInt64 limit, RoaringBitmapWithSmallSet & r1) const
|
||||
{
|
||||
@ -578,10 +582,10 @@ public:
|
||||
{
|
||||
if (small.empty())
|
||||
return 0;
|
||||
auto min_val = std::numeric_limits<std::make_unsigned_t<T>>::max();
|
||||
auto min_val = std::numeric_limits<UnsignedT>::max();
|
||||
for (const auto & x : small)
|
||||
{
|
||||
auto val = x.getValue();
|
||||
UnsignedT val = x.getValue();
|
||||
if (val < min_val)
|
||||
min_val = val;
|
||||
}
|
||||
@ -597,10 +601,10 @@ public:
|
||||
{
|
||||
if (small.empty())
|
||||
return 0;
|
||||
auto max_val = std::numeric_limits<std::make_unsigned_t<T>>::min();
|
||||
UnsignedT max_val = 0;
|
||||
for (const auto & x : small)
|
||||
{
|
||||
auto val = x.getValue();
|
||||
UnsignedT val = x.getValue();
|
||||
if (val > max_val)
|
||||
max_val = val;
|
||||
}
|
||||
@ -611,7 +615,8 @@ public:
|
||||
}
|
||||
|
||||
/**
|
||||
* Replace value
|
||||
* Replace value.
|
||||
* It's used in transform and currently can only support UInt32
|
||||
*/
|
||||
void rb_replace(const UInt64 * from_vals, const UInt64 * to_vals, size_t num)
|
||||
{
|
||||
|
||||
@ -147,7 +147,7 @@ public:
|
||||
}
|
||||
|
||||
if (params[0].getType() != Field::Types::String)
|
||||
throw Exception("Aggregate function " + getName() + " require require first parameter to be a String", ErrorCodes::ILLEGAL_TYPE_OF_ARGUMENT);
|
||||
throw Exception("Aggregate function " + getName() + " require first parameter to be a String", ErrorCodes::ILLEGAL_TYPE_OF_ARGUMENT);
|
||||
|
||||
auto param = params[0].get<String>();
|
||||
if (param == "two-sided")
|
||||
@ -158,13 +158,13 @@ public:
|
||||
alternative = Alternative::Greater;
|
||||
else
|
||||
throw Exception("Unknown parameter in aggregate function " + getName() +
|
||||
". It must be one of: 'two sided', 'less', 'greater'", ErrorCodes::BAD_ARGUMENTS);
|
||||
". It must be one of: 'two-sided', 'less', 'greater'", ErrorCodes::BAD_ARGUMENTS);
|
||||
|
||||
if (params.size() != 2)
|
||||
return;
|
||||
|
||||
if (params[1].getType() != Field::Types::UInt64)
|
||||
throw Exception("Aggregate function " + getName() + " require require second parameter to be a UInt64", ErrorCodes::ILLEGAL_TYPE_OF_ARGUMENT);
|
||||
throw Exception("Aggregate function " + getName() + " require second parameter to be a UInt64", ErrorCodes::ILLEGAL_TYPE_OF_ARGUMENT);
|
||||
|
||||
continuity_correction = static_cast<bool>(params[1].get<UInt64>());
|
||||
}
|
||||
|
||||
@ -26,6 +26,7 @@ class ReadBuffer;
|
||||
class WriteBuffer;
|
||||
class IColumn;
|
||||
class IDataType;
|
||||
class IWindowFunction;
|
||||
|
||||
using DataTypePtr = std::shared_ptr<const IDataType>;
|
||||
using DataTypes = std::vector<DataTypePtr>;
|
||||
@ -215,6 +216,20 @@ public:
|
||||
const DataTypes & getArgumentTypes() const { return argument_types; }
|
||||
const Array & getParameters() const { return parameters; }
|
||||
|
||||
// Any aggregate function can be calculated over a window, but there are some
|
||||
// window functions such as rank() that require a different interface, e.g.
|
||||
// because they don't respect the window frame, or need to be notified when
|
||||
// a new peer group starts. They pretend to be normal aggregate functions,
|
||||
// but will fail if you actually try to use them in Aggregator. The
|
||||
// WindowTransform recognizes these functions and handles them differently.
|
||||
// We could have a separate factory for window functions, and make all
|
||||
// aggregate functions implement IWindowFunction interface and so on. This
|
||||
// would be more logically correct, but more complex. We only have a handful
|
||||
// of true window functions, so this hack-ish interface suffices.
|
||||
virtual IWindowFunction * asWindowFunction() { return nullptr; }
|
||||
virtual const IWindowFunction * asWindowFunction() const
|
||||
{ return const_cast<IAggregateFunction *>(this)->asWindowFunction(); }
|
||||
|
||||
protected:
|
||||
DataTypes argument_types;
|
||||
Array parameters;
|
||||
|
||||
@ -11,6 +11,7 @@ class AggregateFunctionFactory;
|
||||
void registerAggregateFunctionAvg(AggregateFunctionFactory &);
|
||||
void registerAggregateFunctionAvgWeighted(AggregateFunctionFactory &);
|
||||
void registerAggregateFunctionCount(AggregateFunctionFactory &);
|
||||
void registerAggregateFunctionDeltaSum(AggregateFunctionFactory &);
|
||||
void registerAggregateFunctionGroupArray(AggregateFunctionFactory &);
|
||||
void registerAggregateFunctionGroupUniqArray(AggregateFunctionFactory &);
|
||||
void registerAggregateFunctionGroupArrayInsertAt(AggregateFunctionFactory &);
|
||||
@ -57,6 +58,8 @@ void registerAggregateFunctionCombinatorOrFill(AggregateFunctionCombinatorFactor
|
||||
void registerAggregateFunctionCombinatorResample(AggregateFunctionCombinatorFactory &);
|
||||
void registerAggregateFunctionCombinatorDistinct(AggregateFunctionCombinatorFactory &);
|
||||
|
||||
void registerWindowFunctions(AggregateFunctionFactory & factory);
|
||||
|
||||
|
||||
void registerAggregateFunctions()
|
||||
{
|
||||
@ -66,6 +69,7 @@ void registerAggregateFunctions()
|
||||
registerAggregateFunctionAvg(factory);
|
||||
registerAggregateFunctionAvgWeighted(factory);
|
||||
registerAggregateFunctionCount(factory);
|
||||
registerAggregateFunctionDeltaSum(factory);
|
||||
registerAggregateFunctionGroupArray(factory);
|
||||
registerAggregateFunctionGroupUniqArray(factory);
|
||||
registerAggregateFunctionGroupArrayInsertAt(factory);
|
||||
@ -101,6 +105,8 @@ void registerAggregateFunctions()
|
||||
registerAggregateFunctionMannWhitney(factory);
|
||||
registerAggregateFunctionWelchTTest(factory);
|
||||
registerAggregateFunctionStudentTTest(factory);
|
||||
|
||||
registerWindowFunctions(factory);
|
||||
}
|
||||
|
||||
{
|
||||
|
||||
@ -19,6 +19,7 @@ SRCS(
|
||||
AggregateFunctionCategoricalInformationValue.cpp
|
||||
AggregateFunctionCombinatorFactory.cpp
|
||||
AggregateFunctionCount.cpp
|
||||
AggregateFunctionDeltaSum.cpp
|
||||
AggregateFunctionDistinct.cpp
|
||||
AggregateFunctionEntropy.cpp
|
||||
AggregateFunctionFactory.cpp
|
||||
|
||||
@ -60,6 +60,7 @@ add_subdirectory (Processors)
|
||||
add_subdirectory (Formats)
|
||||
add_subdirectory (Compression)
|
||||
add_subdirectory (Server)
|
||||
add_subdirectory (Coordination)
|
||||
|
||||
|
||||
set(dbms_headers)
|
||||
@ -100,8 +101,8 @@ endif()
|
||||
list (APPEND clickhouse_common_io_sources ${CONFIG_BUILD})
|
||||
list (APPEND clickhouse_common_io_headers ${CONFIG_VERSION} ${CONFIG_COMMON})
|
||||
|
||||
list (APPEND dbms_sources Functions/IFunction.cpp Functions/FunctionFactory.cpp Functions/FunctionHelpers.cpp Functions/extractTimeZoneFromFunctionArguments.cpp)
|
||||
list (APPEND dbms_headers Functions/IFunctionImpl.h Functions/FunctionFactory.h Functions/FunctionHelpers.h Functions/extractTimeZoneFromFunctionArguments.h)
|
||||
list (APPEND dbms_sources Functions/IFunction.cpp Functions/FunctionFactory.cpp Functions/FunctionHelpers.cpp Functions/extractTimeZoneFromFunctionArguments.cpp Functions/replicate.cpp)
|
||||
list (APPEND dbms_headers Functions/IFunctionImpl.h Functions/FunctionFactory.h Functions/FunctionHelpers.h Functions/extractTimeZoneFromFunctionArguments.h Functions/replicate.h)
|
||||
|
||||
list (APPEND dbms_sources
|
||||
AggregateFunctions/AggregateFunctionFactory.cpp
|
||||
@ -192,6 +193,10 @@ add_object_library(clickhouse_processors_merges_algorithms Processors/Merges/Alg
|
||||
add_object_library(clickhouse_processors_queryplan Processors/QueryPlan)
|
||||
add_object_library(clickhouse_processors_queryplan_optimizations Processors/QueryPlan/Optimizations)
|
||||
|
||||
if (USE_NURAFT)
|
||||
add_object_library(clickhouse_coordination Coordination)
|
||||
endif()
|
||||
|
||||
set (DBMS_COMMON_LIBRARIES)
|
||||
# libgcc_s does not provide an implementation of an atomics library. Instead,
|
||||
# GCC’s libatomic library can be used to supply these when using libgcc_s.
|
||||
@ -314,7 +319,7 @@ if (USE_KRB5)
|
||||
endif()
|
||||
|
||||
if (USE_NURAFT)
|
||||
dbms_target_link_libraries(PRIVATE ${NURAFT_LIBRARY})
|
||||
dbms_target_link_libraries(PUBLIC ${NURAFT_LIBRARY})
|
||||
endif()
|
||||
|
||||
if(RE2_INCLUDE_DIR)
|
||||
|
||||
@ -75,8 +75,28 @@ void ColumnAggregateFunction::set(const AggregateFunctionPtr & func_)
|
||||
ColumnAggregateFunction::~ColumnAggregateFunction()
|
||||
{
|
||||
if (!func->hasTrivialDestructor() && !src)
|
||||
for (auto * val : data)
|
||||
func->destroy(val);
|
||||
{
|
||||
if (copiedDataInfo.empty())
|
||||
{
|
||||
for (auto * val : data)
|
||||
{
|
||||
func->destroy(val);
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
size_t pos;
|
||||
for (Map::iterator it = copiedDataInfo.begin(), it_end = copiedDataInfo.end(); it != it_end; ++it)
|
||||
{
|
||||
pos = it->getValue().second;
|
||||
if (data[pos] != nullptr)
|
||||
{
|
||||
func->destroy(data[pos]);
|
||||
data[pos] = nullptr;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
void ColumnAggregateFunction::addArena(ConstArenaPtr arena_)
|
||||
@ -455,14 +475,37 @@ void ColumnAggregateFunction::insertFrom(const IColumn & from, size_t n)
|
||||
/// (only as a whole, see comment above).
|
||||
ensureOwnership();
|
||||
insertDefault();
|
||||
insertMergeFrom(from, n);
|
||||
insertCopyFrom(assert_cast<const ColumnAggregateFunction &>(from).data[n]);
|
||||
}
|
||||
|
||||
void ColumnAggregateFunction::insertFrom(ConstAggregateDataPtr place)
|
||||
{
|
||||
ensureOwnership();
|
||||
insertDefault();
|
||||
insertMergeFrom(place);
|
||||
insertCopyFrom(place);
|
||||
}
|
||||
|
||||
void ColumnAggregateFunction::insertCopyFrom(ConstAggregateDataPtr place)
|
||||
{
|
||||
Map::LookupResult result;
|
||||
result = copiedDataInfo.find(place);
|
||||
if (result == nullptr)
|
||||
{
|
||||
copiedDataInfo[place] = data.size()-1;
|
||||
func->merge(data.back(), place, &createOrGetArena());
|
||||
}
|
||||
else
|
||||
{
|
||||
size_t pos = result->getValue().second;
|
||||
if (pos != data.size() - 1)
|
||||
{
|
||||
data[data.size() - 1] = data[pos];
|
||||
}
|
||||
else /// insert same data to same pos, merge them.
|
||||
{
|
||||
func->merge(data.back(), place, &createOrGetArena());
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
void ColumnAggregateFunction::insertMergeFrom(ConstAggregateDataPtr place)
|
||||
@ -697,5 +740,4 @@ MutableColumnPtr ColumnAggregateFunction::cloneResized(size_t size) const
|
||||
return cloned_col;
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
@ -13,6 +13,8 @@
|
||||
|
||||
#include <Functions/FunctionHelpers.h>
|
||||
|
||||
#include <Common/HashTable/HashMap.h>
|
||||
|
||||
namespace DB
|
||||
{
|
||||
|
||||
@ -82,6 +84,17 @@ private:
|
||||
/// Name of the type to distinguish different aggregation states.
|
||||
String type_string;
|
||||
|
||||
/// MergedData records, used to avoid duplicated data copy.
|
||||
///key: src pointer, val: pos in current column.
|
||||
using Map = HashMap<
|
||||
ConstAggregateDataPtr,
|
||||
size_t,
|
||||
DefaultHash<ConstAggregateDataPtr>,
|
||||
HashTableGrower<3>,
|
||||
HashTableAllocatorWithStackMemory<sizeof(std::pair<ConstAggregateDataPtr, size_t>) * (1 << 3)>>;
|
||||
|
||||
Map copiedDataInfo;
|
||||
|
||||
ColumnAggregateFunction() {}
|
||||
|
||||
/// Create a new column that has another column as a source.
|
||||
@ -140,6 +153,8 @@ public:
|
||||
|
||||
void insertFrom(ConstAggregateDataPtr place);
|
||||
|
||||
void insertCopyFrom(ConstAggregateDataPtr place);
|
||||
|
||||
/// Merge state at last row with specified state in another column.
|
||||
void insertMergeFrom(ConstAggregateDataPtr place);
|
||||
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Loading…
Reference in New Issue
Block a user