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Merge branch 'master' into fix/ISSUES-16574
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zhang2014
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CHANGELOG.md
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CHANGELOG.md
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## ClickHouse release 20.10
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### ClickHouse release v20.10.3.30, 2020-10-28
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#### Backward Incompatible Change
|
||||
|
||||
* Make `multiple_joins_rewriter_version` obsolete. Remove first version of joins rewriter. [#15472](https://github.com/ClickHouse/ClickHouse/pull/15472) ([Artem Zuikov](https://github.com/4ertus2)).
|
||||
* Change default value of `format_regexp_escaping_rule` setting (it's related to `Regexp` format) to `Raw` (it means - read whole subpattern as a value) to make the behaviour more like to what users expect. [#15426](https://github.com/ClickHouse/ClickHouse/pull/15426) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Add support for nested multiline comments `/* comment /* comment */ */` in SQL. This conforms to the SQL standard. [#14655](https://github.com/ClickHouse/ClickHouse/pull/14655) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Added MergeTree settings (`max_replicated_merges_with_ttl_in_queue` and `max_number_of_merges_with_ttl_in_pool`) to control the number of merges with TTL in the background pool and replicated queue. This change breaks compatibility with older versions only if you use delete TTL. Otherwise, replication will stay compatible. You can avoid incompatibility issues if you update all shard replicas at once or execute `SYSTEM STOP TTL MERGES` until you finish the update of all replicas. If you'll get an incompatible entry in the replication queue, first of all, execute `SYSTEM STOP TTL MERGES` and after `ALTER TABLE ... DETACH PARTITION ...` the partition where incompatible TTL merge was assigned. Attach it back on a single replica. [#14490](https://github.com/ClickHouse/ClickHouse/pull/14490) ([alesapin](https://github.com/alesapin)).
|
||||
|
||||
#### New Feature
|
||||
|
||||
* Background data recompression. Add the ability to specify `TTL ... RECOMPRESS codec_name` for MergeTree table engines family. [#14494](https://github.com/ClickHouse/ClickHouse/pull/14494) ([alesapin](https://github.com/alesapin)).
|
||||
* Add parallel quorum inserts. This closes [#15601](https://github.com/ClickHouse/ClickHouse/issues/15601). [#15601](https://github.com/ClickHouse/ClickHouse/pull/15601) ([Latysheva Alexandra](https://github.com/alexelex)).
|
||||
* Settings for additional enforcement of data durability. Useful for non-replicated setups. [#11948](https://github.com/ClickHouse/ClickHouse/pull/11948) ([Anton Popov](https://github.com/CurtizJ)).
|
||||
* When duplicate block is written to replica where it does not exist locally (has not been fetched from replicas), don't ignore it and write locally to achieve the same effect as if it was successfully replicated. [#11684](https://github.com/ClickHouse/ClickHouse/pull/11684) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Now we support `WITH <identifier> AS (subquery) ... ` to introduce named subqueries in the query context. This closes [#2416](https://github.com/ClickHouse/ClickHouse/issues/2416). This closes [#4967](https://github.com/ClickHouse/ClickHouse/issues/4967). [#14771](https://github.com/ClickHouse/ClickHouse/pull/14771) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Introduce `enable_global_with_statement` setting which propagates the first select's `WITH` statements to other select queries at the same level, and makes aliases in `WITH` statements visible to subqueries. [#15451](https://github.com/ClickHouse/ClickHouse/pull/15451) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Secure inter-cluster query execution (with initial_user as current query user). [#13156](https://github.com/ClickHouse/ClickHouse/pull/13156) ([Azat Khuzhin](https://github.com/azat)). [#15551](https://github.com/ClickHouse/ClickHouse/pull/15551) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* Add the ability to remove column properties and table TTLs. Introduced queries `ALTER TABLE MODIFY COLUMN col_name REMOVE what_to_remove` and `ALTER TABLE REMOVE TTL`. Both operations are lightweight and executed at the metadata level. [#14742](https://github.com/ClickHouse/ClickHouse/pull/14742) ([alesapin](https://github.com/alesapin)).
|
||||
* Added format `RawBLOB`. It is intended for input or output a single value without any escaping and delimiters. This closes [#15349](https://github.com/ClickHouse/ClickHouse/issues/15349). [#15364](https://github.com/ClickHouse/ClickHouse/pull/15364) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Add the `reinterpretAsUUID` function that allows to convert a big-endian byte string to UUID. [#15480](https://github.com/ClickHouse/ClickHouse/pull/15480) ([Alexander Kuzmenkov](https://github.com/akuzm)).
|
||||
* Implement `force_data_skipping_indices` setting. [#15642](https://github.com/ClickHouse/ClickHouse/pull/15642) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* Add a setting `output_format_pretty_row_numbers` to numerate the result in Pretty formats. This closes [#15350](https://github.com/ClickHouse/ClickHouse/issues/15350). [#15443](https://github.com/ClickHouse/ClickHouse/pull/15443) ([flynn](https://github.com/ucasFL)).
|
||||
* Added query obfuscation tool. It allows to share more queries for better testing. This closes [#15268](https://github.com/ClickHouse/ClickHouse/issues/15268). [#15321](https://github.com/ClickHouse/ClickHouse/pull/15321) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Add table function `null('structure')`. [#14797](https://github.com/ClickHouse/ClickHouse/pull/14797) ([vxider](https://github.com/Vxider)).
|
||||
* Added `formatReadableQuantity` function. It is useful for reading big numbers by human. [#14725](https://github.com/ClickHouse/ClickHouse/pull/14725) ([Artem Hnilov](https://github.com/BooBSD)).
|
||||
* Add format `LineAsString` that accepts a sequence of lines separated by newlines, every line is parsed as a whole as a single String field. [#14703](https://github.com/ClickHouse/ClickHouse/pull/14703) ([Nikita Mikhaylov](https://github.com/nikitamikhaylov)), [#13846](https://github.com/ClickHouse/ClickHouse/pull/13846) ([hexiaoting](https://github.com/hexiaoting)).
|
||||
* Add `JSONStrings` format which output data in arrays of strings. [#14333](https://github.com/ClickHouse/ClickHouse/pull/14333) ([hcz](https://github.com/hczhcz)).
|
||||
* Add support for "Raw" column format for `Regexp` format. It allows to simply extract subpatterns as a whole without any escaping rules. [#15363](https://github.com/ClickHouse/ClickHouse/pull/15363) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Allow configurable `NULL` representation for `TSV` output format. It is controlled by the setting `output_format_tsv_null_representation` which is `\N` by default. This closes [#9375](https://github.com/ClickHouse/ClickHouse/issues/9375). Note that the setting only controls output format and `\N` is the only supported `NULL` representation for `TSV` input format. [#14586](https://github.com/ClickHouse/ClickHouse/pull/14586) ([Kruglov Pavel](https://github.com/Avogar)).
|
||||
* Support Decimal data type for `MaterializedMySQL`. `MaterializedMySQL` is an experimental feature. [#14535](https://github.com/ClickHouse/ClickHouse/pull/14535) ([Winter Zhang](https://github.com/zhang2014)).
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* Add new feature: `SHOW DATABASES LIKE 'xxx'`. [#14521](https://github.com/ClickHouse/ClickHouse/pull/14521) ([hexiaoting](https://github.com/hexiaoting)).
|
||||
* Added a script to import (arbitrary) git repository to ClickHouse as a sample dataset. [#14471](https://github.com/ClickHouse/ClickHouse/pull/14471) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Now insert statements can have asterisk (or variants) with column transformers in the column list. [#14453](https://github.com/ClickHouse/ClickHouse/pull/14453) ([Amos Bird](https://github.com/amosbird)).
|
||||
* New query complexity limit settings `max_rows_to_read_leaf`, `max_bytes_to_read_leaf` for distributed queries to limit max rows/bytes read on the leaf nodes. Limit is applied for local reads only, *excluding* the final merge stage on the root node. [#14221](https://github.com/ClickHouse/ClickHouse/pull/14221) ([Roman Khavronenko](https://github.com/hagen1778)).
|
||||
* Allow user to specify settings for `ReplicatedMergeTree*` storage in `<replicated_merge_tree>` section of config file. It works similarly to `<merge_tree>` section. For `ReplicatedMergeTree*` storages settings from `<merge_tree>` and `<replicated_merge_tree>` are applied together, but settings from `<replicated_merge_tree>` has higher priority. Added `system.replicated_merge_tree_settings` table. [#13573](https://github.com/ClickHouse/ClickHouse/pull/13573) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Add `mapPopulateSeries` function. [#13166](https://github.com/ClickHouse/ClickHouse/pull/13166) ([Ildus Kurbangaliev](https://github.com/ildus)).
|
||||
* Supporting MySQL types: `decimal` (as ClickHouse `Decimal`) and `datetime` with sub-second precision (as `DateTime64`). [#11512](https://github.com/ClickHouse/ClickHouse/pull/11512) ([Vasily Nemkov](https://github.com/Enmk)).
|
||||
* Introduce `event_time_microseconds` field to `system.text_log`, `system.trace_log`, `system.query_log` and `system.query_thread_log` tables. [#14760](https://github.com/ClickHouse/ClickHouse/pull/14760) ([Bharat Nallan](https://github.com/bharatnc)).
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||||
* Add `event_time_microseconds` to `system.asynchronous_metric_log` & `system.metric_log` tables. [#14514](https://github.com/ClickHouse/ClickHouse/pull/14514) ([Bharat Nallan](https://github.com/bharatnc)).
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||||
* Add `query_start_time_microseconds` field to `system.query_log` & `system.query_thread_log` tables. [#14252](https://github.com/ClickHouse/ClickHouse/pull/14252) ([Bharat Nallan](https://github.com/bharatnc)).
|
||||
|
||||
#### Bug Fix
|
||||
|
||||
* Fix the case when memory can be overallocated regardless to the limit. This closes [#14560](https://github.com/ClickHouse/ClickHouse/issues/14560). [#16206](https://github.com/ClickHouse/ClickHouse/pull/16206) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fix `executable` dictionary source hang. In previous versions, when using some formats (e.g. `JSONEachRow`) data was not feed to a child process before it outputs at least something. This closes [#1697](https://github.com/ClickHouse/ClickHouse/issues/1697). This closes [#2455](https://github.com/ClickHouse/ClickHouse/issues/2455). [#14525](https://github.com/ClickHouse/ClickHouse/pull/14525) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fix double free in case of exception in function `dictGet`. It could have happened if dictionary was loaded with error. [#16429](https://github.com/ClickHouse/ClickHouse/pull/16429) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Fix group by with totals/rollup/cube modifers and min/max functions over group by keys. Fixes [#16393](https://github.com/ClickHouse/ClickHouse/issues/16393). [#16397](https://github.com/ClickHouse/ClickHouse/pull/16397) ([Anton Popov](https://github.com/CurtizJ)).
|
||||
* Fix async Distributed INSERT with prefer_localhost_replica=0 and internal_replication. [#16358](https://github.com/ClickHouse/ClickHouse/pull/16358) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* Fix a very wrong code in TwoLevelStringHashTable implementation, which might lead to memory leak. [#16264](https://github.com/ClickHouse/ClickHouse/pull/16264) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Fix segfault in some cases of wrong aggregation in lambdas. [#16082](https://github.com/ClickHouse/ClickHouse/pull/16082) ([Anton Popov](https://github.com/CurtizJ)).
|
||||
* Fix `ALTER MODIFY ... ORDER BY` query hang for `ReplicatedVersionedCollapsingMergeTree`. This fixes [#15980](https://github.com/ClickHouse/ClickHouse/issues/15980). [#16011](https://github.com/ClickHouse/ClickHouse/pull/16011) ([alesapin](https://github.com/alesapin)).
|
||||
* `MaterializedMySQL` (experimental feature): Fix collate name & charset name parser and support `length = 0` for string type. [#16008](https://github.com/ClickHouse/ClickHouse/pull/16008) ([Winter Zhang](https://github.com/zhang2014)).
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||||
* Allow to use `direct` layout for dictionaries with complex keys. [#16007](https://github.com/ClickHouse/ClickHouse/pull/16007) ([Anton Popov](https://github.com/CurtizJ)).
|
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* Prevent replica hang for 5-10 mins when replication error happens after a period of inactivity. [#15987](https://github.com/ClickHouse/ClickHouse/pull/15987) ([filimonov](https://github.com/filimonov)).
|
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* Fix rare segfaults when inserting into or selecting from MaterializedView and concurrently dropping target table (for Atomic database engine). [#15984](https://github.com/ClickHouse/ClickHouse/pull/15984) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Fix ambiguity in parsing of settings profiles: `CREATE USER ... SETTINGS profile readonly` is now considered as using a profile named `readonly`, not a setting named `profile` with the readonly constraint. This fixes [#15628](https://github.com/ClickHouse/ClickHouse/issues/15628). [#15982](https://github.com/ClickHouse/ClickHouse/pull/15982) ([Vitaly Baranov](https://github.com/vitlibar)).
|
||||
* `MaterializedMySQL` (experimental feature): Fix crash on create database failure. [#15954](https://github.com/ClickHouse/ClickHouse/pull/15954) ([Winter Zhang](https://github.com/zhang2014)).
|
||||
* Fixed `DROP TABLE IF EXISTS` failure with `Table ... doesn't exist` error when table is concurrently renamed (for Atomic database engine). Fixed rare deadlock when concurrently executing some DDL queries with multiple tables (like `DROP DATABASE` and `RENAME TABLE`) - Fixed `DROP/DETACH DATABASE` failure with `Table ... doesn't exist` when concurrently executing `DROP/DETACH TABLE`. [#15934](https://github.com/ClickHouse/ClickHouse/pull/15934) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Fix incorrect empty result for query from `Distributed` table if query has `WHERE`, `PREWHERE` and `GLOBAL IN`. Fixes [#15792](https://github.com/ClickHouse/ClickHouse/issues/15792). [#15933](https://github.com/ClickHouse/ClickHouse/pull/15933) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Fixes [#12513](https://github.com/ClickHouse/ClickHouse/issues/12513): difference expressions with same alias when query is reanalyzed. [#15886](https://github.com/ClickHouse/ClickHouse/pull/15886) ([Winter Zhang](https://github.com/zhang2014)).
|
||||
* Fix possible very rare deadlocks in RBAC implementation. [#15875](https://github.com/ClickHouse/ClickHouse/pull/15875) ([Vitaly Baranov](https://github.com/vitlibar)).
|
||||
* Fix exception `Block structure mismatch` in `SELECT ... ORDER BY DESC` queries which were executed after `ALTER MODIFY COLUMN` query. Fixes [#15800](https://github.com/ClickHouse/ClickHouse/issues/15800). [#15852](https://github.com/ClickHouse/ClickHouse/pull/15852) ([alesapin](https://github.com/alesapin)).
|
||||
* `MaterializedMySQL` (experimental feature): Fix `select count()` inaccuracy. [#15767](https://github.com/ClickHouse/ClickHouse/pull/15767) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Fix some cases of queries, in which only virtual columns are selected. Previously `Not found column _nothing in block` exception may be thrown. Fixes [#12298](https://github.com/ClickHouse/ClickHouse/issues/12298). [#15756](https://github.com/ClickHouse/ClickHouse/pull/15756) ([Anton Popov](https://github.com/CurtizJ)).
|
||||
* Fix drop of materialized view with inner table in Atomic database (hangs all subsequent DROP TABLE due to hang of the worker thread, due to recursive DROP TABLE for inner table of MV). [#15743](https://github.com/ClickHouse/ClickHouse/pull/15743) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* Possibility to move part to another disk/volume if the first attempt was failed. [#15723](https://github.com/ClickHouse/ClickHouse/pull/15723) ([Pavel Kovalenko](https://github.com/Jokser)).
|
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* Fix error `Cannot find column` which may happen at insertion into `MATERIALIZED VIEW` in case if query for `MV` containes `ARRAY JOIN`. [#15717](https://github.com/ClickHouse/ClickHouse/pull/15717) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Fixed too low default value of `max_replicated_logs_to_keep` setting, which might cause replicas to become lost too often. Improve lost replica recovery process by choosing the most up-to-date replica to clone. Also do not remove old parts from lost replica, detach them instead. [#15701](https://github.com/ClickHouse/ClickHouse/pull/15701) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Fix rare race condition in dictionaries and tables from MySQL. [#15686](https://github.com/ClickHouse/ClickHouse/pull/15686) ([alesapin](https://github.com/alesapin)).
|
||||
* Fix (benign) race condition in AMQP-CPP. [#15667](https://github.com/ClickHouse/ClickHouse/pull/15667) ([alesapin](https://github.com/alesapin)).
|
||||
* Fix error `Cannot add simple transform to empty Pipe` which happened while reading from `Buffer` table which has different structure than destination table. It was possible if destination table returned empty result for query. Fixes [#15529](https://github.com/ClickHouse/ClickHouse/issues/15529). [#15662](https://github.com/ClickHouse/ClickHouse/pull/15662) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Proper error handling during insert into MergeTree with S3. MergeTree over S3 is an experimental feature. [#15657](https://github.com/ClickHouse/ClickHouse/pull/15657) ([Pavel Kovalenko](https://github.com/Jokser)).
|
||||
* Fixed bug with S3 table function: region from URL was not applied to S3 client configuration. [#15646](https://github.com/ClickHouse/ClickHouse/pull/15646) ([Vladimir Chebotarev](https://github.com/excitoon)).
|
||||
* Fix the order of destruction for resources in `ReadFromStorage` step of query plan. It might cause crashes in rare cases. Possibly connected with [#15610](https://github.com/ClickHouse/ClickHouse/issues/15610). [#15645](https://github.com/ClickHouse/ClickHouse/pull/15645) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Subtract `ReadonlyReplica` metric when detach readonly tables. [#15592](https://github.com/ClickHouse/ClickHouse/pull/15592) ([sundyli](https://github.com/sundy-li)).
|
||||
* Fixed `Element ... is not a constant expression` error when using `JSON*` function result in `VALUES`, `LIMIT` or right side of `IN` operator. [#15589](https://github.com/ClickHouse/ClickHouse/pull/15589) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Query will finish faster in case of exception. Cancel execution on remote replicas if exception happens. [#15578](https://github.com/ClickHouse/ClickHouse/pull/15578) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* Prevent the possibility of error message `Could not calculate available disk space (statvfs), errno: 4, strerror: Interrupted system call`. This fixes [#15541](https://github.com/ClickHouse/ClickHouse/issues/15541). [#15557](https://github.com/ClickHouse/ClickHouse/pull/15557) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fix `Database <db> doesn't exist.` in queries with IN and Distributed table when there's no database on initiator. [#15538](https://github.com/ClickHouse/ClickHouse/pull/15538) ([Artem Zuikov](https://github.com/4ertus2)).
|
||||
* Mutation might hang waiting for some non-existent part after `MOVE` or `REPLACE PARTITION` or, in rare cases, after `DETACH` or `DROP PARTITION`. It's fixed. [#15537](https://github.com/ClickHouse/ClickHouse/pull/15537) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Fix bug when `ILIKE` operator stops being case insensitive if `LIKE` with the same pattern was executed. [#15536](https://github.com/ClickHouse/ClickHouse/pull/15536) ([alesapin](https://github.com/alesapin)).
|
||||
* Fix `Missing columns` errors when selecting columns which absent in data, but depend on other columns which also absent in data. Fixes [#15530](https://github.com/ClickHouse/ClickHouse/issues/15530). [#15532](https://github.com/ClickHouse/ClickHouse/pull/15532) ([alesapin](https://github.com/alesapin)).
|
||||
* Throw an error when a single parameter is passed to ReplicatedMergeTree instead of ignoring it. [#15516](https://github.com/ClickHouse/ClickHouse/pull/15516) ([nvartolomei](https://github.com/nvartolomei)).
|
||||
* Fix bug with event subscription in DDLWorker which rarely may lead to query hangs in `ON CLUSTER`. Introduced in [#13450](https://github.com/ClickHouse/ClickHouse/issues/13450). [#15477](https://github.com/ClickHouse/ClickHouse/pull/15477) ([alesapin](https://github.com/alesapin)).
|
||||
* Report proper error when the second argument of `boundingRatio` aggregate function has a wrong type. [#15407](https://github.com/ClickHouse/ClickHouse/pull/15407) ([detailyang](https://github.com/detailyang)).
|
||||
* Fixes [#15365](https://github.com/ClickHouse/ClickHouse/issues/15365): attach a database with MySQL engine throws exception (no query context). [#15384](https://github.com/ClickHouse/ClickHouse/pull/15384) ([Winter Zhang](https://github.com/zhang2014)).
|
||||
* Fix the case of multiple occurrences of column transformers in a select query. [#15378](https://github.com/ClickHouse/ClickHouse/pull/15378) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Fixed compression in `S3` storage. [#15376](https://github.com/ClickHouse/ClickHouse/pull/15376) ([Vladimir Chebotarev](https://github.com/excitoon)).
|
||||
* Fix bug where queries like `SELECT toStartOfDay(today())` fail complaining about empty time_zone argument. [#15319](https://github.com/ClickHouse/ClickHouse/pull/15319) ([Bharat Nallan](https://github.com/bharatnc)).
|
||||
* Fix race condition during MergeTree table rename and background cleanup. [#15304](https://github.com/ClickHouse/ClickHouse/pull/15304) ([alesapin](https://github.com/alesapin)).
|
||||
* Fix rare race condition on server startup when system logs are enabled. [#15300](https://github.com/ClickHouse/ClickHouse/pull/15300) ([alesapin](https://github.com/alesapin)).
|
||||
* Fix hang of queries with a lot of subqueries to same table of `MySQL` engine. Previously, if there were more than 16 subqueries to same `MySQL` table in query, it hang forever. [#15299](https://github.com/ClickHouse/ClickHouse/pull/15299) ([Anton Popov](https://github.com/CurtizJ)).
|
||||
* Fix MSan report in QueryLog. Uninitialized memory can be used for the field `memory_usage`. [#15258](https://github.com/ClickHouse/ClickHouse/pull/15258) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fix 'Unknown identifier' in GROUP BY when query has JOIN over Merge table. [#15242](https://github.com/ClickHouse/ClickHouse/pull/15242) ([Artem Zuikov](https://github.com/4ertus2)).
|
||||
* Fix instance crash when using `joinGet` with `LowCardinality` types. This fixes https://github.com/ClickHouse/ClickHouse/issues/15214. [#15220](https://github.com/ClickHouse/ClickHouse/pull/15220) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Fix bug in table engine `Buffer` which doesn't allow to insert data of new structure into `Buffer` after `ALTER` query. Fixes [#15117](https://github.com/ClickHouse/ClickHouse/issues/15117). [#15192](https://github.com/ClickHouse/ClickHouse/pull/15192) ([alesapin](https://github.com/alesapin)).
|
||||
* Adjust Decimal field size in MySQL column definition packet. [#15152](https://github.com/ClickHouse/ClickHouse/pull/15152) ([maqroll](https://github.com/maqroll)).
|
||||
* Fixes `Data compressed with different methods` in `join_algorithm='auto'`. Keep LowCardinality as type for left table join key in `join_algorithm='partial_merge'`. [#15088](https://github.com/ClickHouse/ClickHouse/pull/15088) ([Artem Zuikov](https://github.com/4ertus2)).
|
||||
* Update `jemalloc` to fix `percpu_arena` with affinity mask. [#15035](https://github.com/ClickHouse/ClickHouse/pull/15035) ([Azat Khuzhin](https://github.com/azat)). [#14957](https://github.com/ClickHouse/ClickHouse/pull/14957) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* We already use padded comparison between String and FixedString (https://github.com/ClickHouse/ClickHouse/blob/master/src/Functions/FunctionsComparison.h#L333). This PR applies the same logic to field comparison which corrects the usage of FixedString as primary keys. This fixes https://github.com/ClickHouse/ClickHouse/issues/14908. [#15033](https://github.com/ClickHouse/ClickHouse/pull/15033) ([Amos Bird](https://github.com/amosbird)).
|
||||
* If function `bar` was called with specifically crafted arguments, buffer overflow was possible. This closes [#13926](https://github.com/ClickHouse/ClickHouse/issues/13926). [#15028](https://github.com/ClickHouse/ClickHouse/pull/15028) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fixed `Cannot rename ... errno: 22, strerror: Invalid argument` error on DDL query execution in Atomic database when running clickhouse-server in Docker on Mac OS. [#15024](https://github.com/ClickHouse/ClickHouse/pull/15024) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Fix crash in RIGHT or FULL JOIN with join_algorith='auto' when memory limit exceeded and we should change HashJoin with MergeJoin. [#15002](https://github.com/ClickHouse/ClickHouse/pull/15002) ([Artem Zuikov](https://github.com/4ertus2)).
|
||||
* Now settings `number_of_free_entries_in_pool_to_execute_mutation` and `number_of_free_entries_in_pool_to_lower_max_size_of_merge` can be equal to `background_pool_size`. [#14975](https://github.com/ClickHouse/ClickHouse/pull/14975) ([alesapin](https://github.com/alesapin)).
|
||||
* Fix to make predicate push down work when subquery contains `finalizeAggregation` function. Fixes [#14847](https://github.com/ClickHouse/ClickHouse/issues/14847). [#14937](https://github.com/ClickHouse/ClickHouse/pull/14937) ([filimonov](https://github.com/filimonov)).
|
||||
* Publish CPU frequencies per logical core in `system.asynchronous_metrics`. This fixes https://github.com/ClickHouse/ClickHouse/issues/14923. [#14924](https://github.com/ClickHouse/ClickHouse/pull/14924) ([Alexander Kuzmenkov](https://github.com/akuzm)).
|
||||
* `MaterializedMySQL` (experimental feature): Fixed `.metadata.tmp File exists` error. [#14898](https://github.com/ClickHouse/ClickHouse/pull/14898) ([Winter Zhang](https://github.com/zhang2014)).
|
||||
* Fix the issue when some invocations of `extractAllGroups` function may trigger "Memory limit exceeded" error. This fixes [#13383](https://github.com/ClickHouse/ClickHouse/issues/13383). [#14889](https://github.com/ClickHouse/ClickHouse/pull/14889) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fix SIGSEGV for an attempt to INSERT into StorageFile with file descriptor. [#14887](https://github.com/ClickHouse/ClickHouse/pull/14887) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* Fixed segfault in `cache` dictionary [#14837](https://github.com/ClickHouse/ClickHouse/issues/14837). [#14879](https://github.com/ClickHouse/ClickHouse/pull/14879) ([Nikita Mikhaylov](https://github.com/nikitamikhaylov)).
|
||||
* `MaterializedMySQL` (experimental feature): Fixed bug in parsing MySQL binlog events, which causes `Attempt to read after eof` and `Packet payload is not fully read` in `MaterializeMySQL` database engine. [#14852](https://github.com/ClickHouse/ClickHouse/pull/14852) ([Winter Zhang](https://github.com/zhang2014)).
|
||||
* Fix rare error in `SELECT` queries when the queried column has `DEFAULT` expression which depends on the other column which also has `DEFAULT` and not present in select query and not exists on disk. Partially fixes [#14531](https://github.com/ClickHouse/ClickHouse/issues/14531). [#14845](https://github.com/ClickHouse/ClickHouse/pull/14845) ([alesapin](https://github.com/alesapin)).
|
||||
* Fix a problem where the server may get stuck on startup while talking to ZooKeeper, if the configuration files have to be fetched from ZK (using the `from_zk` include option). This fixes [#14814](https://github.com/ClickHouse/ClickHouse/issues/14814). [#14843](https://github.com/ClickHouse/ClickHouse/pull/14843) ([Alexander Kuzmenkov](https://github.com/akuzm)).
|
||||
* Fix wrong monotonicity detection for shrunk `Int -> Int` cast of signed types. It might lead to incorrect query result. This bug is unveiled in [#14513](https://github.com/ClickHouse/ClickHouse/issues/14513). [#14783](https://github.com/ClickHouse/ClickHouse/pull/14783) ([Amos Bird](https://github.com/amosbird)).
|
||||
* `Replace` column transformer should replace identifiers with cloned ASTs. This fixes https://github.com/ClickHouse/ClickHouse/issues/14695 . [#14734](https://github.com/ClickHouse/ClickHouse/pull/14734) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Fixed missed default database name in metadata of materialized view when executing `ALTER ... MODIFY QUERY`. [#14664](https://github.com/ClickHouse/ClickHouse/pull/14664) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Fix bug when `ALTER UPDATE` mutation with `Nullable` column in assignment expression and constant value (like `UPDATE x = 42`) leads to incorrect value in column or segfault. Fixes [#13634](https://github.com/ClickHouse/ClickHouse/issues/13634), [#14045](https://github.com/ClickHouse/ClickHouse/issues/14045). [#14646](https://github.com/ClickHouse/ClickHouse/pull/14646) ([alesapin](https://github.com/alesapin)).
|
||||
* Fix wrong Decimal multiplication result caused wrong decimal scale of result column. [#14603](https://github.com/ClickHouse/ClickHouse/pull/14603) ([Artem Zuikov](https://github.com/4ertus2)).
|
||||
* Fix function `has` with `LowCardinality` of `Nullable`. [#14591](https://github.com/ClickHouse/ClickHouse/pull/14591) ([Mike](https://github.com/myrrc)).
|
||||
* Cleanup data directory after Zookeeper exceptions during CreateQuery for StorageReplicatedMergeTree Engine. [#14563](https://github.com/ClickHouse/ClickHouse/pull/14563) ([Bharat Nallan](https://github.com/bharatnc)).
|
||||
* Fix rare segfaults in functions with combinator `-Resample`, which could appear in result of overflow with very large parameters. [#14562](https://github.com/ClickHouse/ClickHouse/pull/14562) ([Anton Popov](https://github.com/CurtizJ)).
|
||||
* Fix a bug when converting `Nullable(String)` to Enum. Introduced by https://github.com/ClickHouse/ClickHouse/pull/12745. This fixes https://github.com/ClickHouse/ClickHouse/issues/14435. [#14530](https://github.com/ClickHouse/ClickHouse/pull/14530) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Fixed the incorrect sorting order of `Nullable` column. This fixes [#14344](https://github.com/ClickHouse/ClickHouse/issues/14344). [#14495](https://github.com/ClickHouse/ClickHouse/pull/14495) ([Nikita Mikhaylov](https://github.com/nikitamikhaylov)).
|
||||
* Fix `currentDatabase()` function cannot be used in `ON CLUSTER` ddl query. [#14211](https://github.com/ClickHouse/ClickHouse/pull/14211) ([Winter Zhang](https://github.com/zhang2014)).
|
||||
* `MaterializedMySQL` (experimental feature): Fixed `Packet payload is not fully read` error in `MaterializeMySQL` database engine. [#14696](https://github.com/ClickHouse/ClickHouse/pull/14696) ([BohuTANG](https://github.com/BohuTANG)).
|
||||
|
||||
#### Improvement
|
||||
|
||||
* Enable `Atomic` database engine by default for newly created databases. [#15003](https://github.com/ClickHouse/ClickHouse/pull/15003) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Add the ability to specify specialized codecs like `Delta`, `T64`, etc. for columns with subtypes. Implements [#12551](https://github.com/ClickHouse/ClickHouse/issues/12551), fixes [#11397](https://github.com/ClickHouse/ClickHouse/issues/11397), fixes [#4609](https://github.com/ClickHouse/ClickHouse/issues/4609). [#15089](https://github.com/ClickHouse/ClickHouse/pull/15089) ([alesapin](https://github.com/alesapin)).
|
||||
* Dynamic reload of zookeeper config. [#14678](https://github.com/ClickHouse/ClickHouse/pull/14678) ([sundyli](https://github.com/sundy-li)).
|
||||
* Now it's allowed to execute `ALTER ... ON CLUSTER` queries regardless of the `<internal_replication>` setting in cluster config. [#16075](https://github.com/ClickHouse/ClickHouse/pull/16075) ([alesapin](https://github.com/alesapin)).
|
||||
* Now `joinGet` supports multi-key lookup. Continuation of [#12418](https://github.com/ClickHouse/ClickHouse/issues/12418). [#13015](https://github.com/ClickHouse/ClickHouse/pull/13015) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Wait for `DROP/DETACH TABLE` to actually finish if `NO DELAY` or `SYNC` is specified for `Atomic` database. [#15448](https://github.com/ClickHouse/ClickHouse/pull/15448) ([tavplubix](https://github.com/tavplubix)).
|
||||
* Now it's possible to change the type of version column for `VersionedCollapsingMergeTree` with `ALTER` query. [#15442](https://github.com/ClickHouse/ClickHouse/pull/15442) ([alesapin](https://github.com/alesapin)).
|
||||
* Unfold `{database}`, `{table}` and `{uuid}` macros in `zookeeper_path` on replicated table creation. Do not allow `RENAME TABLE` if it may break `zookeeper_path` after server restart. Fixes [#6917](https://github.com/ClickHouse/ClickHouse/issues/6917). [#15348](https://github.com/ClickHouse/ClickHouse/pull/15348) ([tavplubix](https://github.com/tavplubix)).
|
||||
* The function `now` allows an argument with timezone. This closes [15264](https://github.com/ClickHouse/ClickHouse/issues/15264). [#15285](https://github.com/ClickHouse/ClickHouse/pull/15285) ([flynn](https://github.com/ucasFL)).
|
||||
* Do not allow connections to ClickHouse server until all scripts in `/docker-entrypoint-initdb.d/` are executed. [#15244](https://github.com/ClickHouse/ClickHouse/pull/15244) ([Aleksei Kozharin](https://github.com/alekseik1)).
|
||||
* Added `optimize` setting to `EXPLAIN PLAN` query. If enabled, query plan level optimisations are applied. Enabled by default. [#15201](https://github.com/ClickHouse/ClickHouse/pull/15201) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Proper exception message for wrong number of arguments of CAST. This closes [#13992](https://github.com/ClickHouse/ClickHouse/issues/13992). [#15029](https://github.com/ClickHouse/ClickHouse/pull/15029) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Add option to disable TTL move on data part insert. [#15000](https://github.com/ClickHouse/ClickHouse/pull/15000) ([Pavel Kovalenko](https://github.com/Jokser)).
|
||||
* Ignore key constraints when doing mutations. Without this pull request, it's not possible to do mutations when `force_index_by_date = 1` or `force_primary_key = 1`. [#14973](https://github.com/ClickHouse/ClickHouse/pull/14973) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Allow to drop Replicated table if previous drop attempt was failed due to ZooKeeper session expiration. This fixes [#11891](https://github.com/ClickHouse/ClickHouse/issues/11891). [#14926](https://github.com/ClickHouse/ClickHouse/pull/14926) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fixed excessive settings constraint violation when running SELECT with SETTINGS from a distributed table. [#14876](https://github.com/ClickHouse/ClickHouse/pull/14876) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Provide a `load_balancing_first_offset` query setting to explicitly state what the first replica is. It's used together with `FIRST_OR_RANDOM` load balancing strategy, which allows to control replicas workload. [#14867](https://github.com/ClickHouse/ClickHouse/pull/14867) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Show subqueries for `SET` and `JOIN` in `EXPLAIN` result. [#14856](https://github.com/ClickHouse/ClickHouse/pull/14856) ([Nikolai Kochetov](https://github.com/KochetovNicolai)).
|
||||
* Allow using multi-volume storage configuration in storage `Distributed`. [#14839](https://github.com/ClickHouse/ClickHouse/pull/14839) ([Pavel Kovalenko](https://github.com/Jokser)).
|
||||
* Construct `query_start_time` and `query_start_time_microseconds` from the same timespec. [#14831](https://github.com/ClickHouse/ClickHouse/pull/14831) ([Bharat Nallan](https://github.com/bharatnc)).
|
||||
* Support for disabling persistency for `StorageJoin` and `StorageSet`, this feature is controlled by setting `disable_set_and_join_persistency`. And this PR solved issue [#6318](https://github.com/ClickHouse/ClickHouse/issues/6318). [#14776](https://github.com/ClickHouse/ClickHouse/pull/14776) ([vxider](https://github.com/Vxider)).
|
||||
* Now `COLUMNS` can be used to wrap over a list of columns and apply column transformers afterwards. [#14775](https://github.com/ClickHouse/ClickHouse/pull/14775) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Add `merge_algorithm` to `system.merges` table to improve merging inspections. [#14705](https://github.com/ClickHouse/ClickHouse/pull/14705) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Fix potential memory leak caused by zookeeper exists watch. [#14693](https://github.com/ClickHouse/ClickHouse/pull/14693) ([hustnn](https://github.com/hustnn)).
|
||||
* Allow parallel execution of distributed DDL. [#14684](https://github.com/ClickHouse/ClickHouse/pull/14684) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* Add `QueryMemoryLimitExceeded` event counter. This closes [#14589](https://github.com/ClickHouse/ClickHouse/issues/14589). [#14647](https://github.com/ClickHouse/ClickHouse/pull/14647) ([fastio](https://github.com/fastio)).
|
||||
* Fix some trailing whitespaces in query formatting. [#14595](https://github.com/ClickHouse/ClickHouse/pull/14595) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* ClickHouse treats partition expr and key expr differently. Partition expr is used to construct an minmax index containing related columns, while primary key expr is stored as an expr. Sometimes user might partition a table at coarser levels, such as `partition by i / 1000`. However, binary operators are not monotonic and this PR tries to fix that. It might also benifit other use cases. [#14513](https://github.com/ClickHouse/ClickHouse/pull/14513) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Add an option to skip access checks for `DiskS3`. `s3` disk is an experimental feature. [#14497](https://github.com/ClickHouse/ClickHouse/pull/14497) ([Pavel Kovalenko](https://github.com/Jokser)).
|
||||
* Speed up server shutdown process if there are ongoing S3 requests. [#14496](https://github.com/ClickHouse/ClickHouse/pull/14496) ([Pavel Kovalenko](https://github.com/Jokser)).
|
||||
* `SYSTEM RELOAD CONFIG` now throws an exception if failed to reload and continues using the previous users.xml. The background periodic reloading also continues using the previous users.xml if failed to reload. [#14492](https://github.com/ClickHouse/ClickHouse/pull/14492) ([Vitaly Baranov](https://github.com/vitlibar)).
|
||||
* For INSERTs with inline data in VALUES format in the script mode of `clickhouse-client`, support semicolon as the data terminator, in addition to the new line. Closes https://github.com/ClickHouse/ClickHouse/issues/12288. [#13192](https://github.com/ClickHouse/ClickHouse/pull/13192) ([Alexander Kuzmenkov](https://github.com/akuzm)).
|
||||
* Support custom codecs in compact parts. [#12183](https://github.com/ClickHouse/ClickHouse/pull/12183) ([Anton Popov](https://github.com/CurtizJ)).
|
||||
|
||||
#### Performance Improvement
|
||||
|
||||
* Enable compact parts by default for small parts. This will allow to process frequent inserts slightly more efficiently (4..100 times). [#11913](https://github.com/ClickHouse/ClickHouse/pull/11913) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Improve `quantileTDigest` performance. This fixes [#2668](https://github.com/ClickHouse/ClickHouse/issues/2668). [#15542](https://github.com/ClickHouse/ClickHouse/pull/15542) ([Kruglov Pavel](https://github.com/Avogar)).
|
||||
* Significantly reduce memory usage in AggregatingInOrderTransform/optimize_aggregation_in_order. [#15543](https://github.com/ClickHouse/ClickHouse/pull/15543) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* Faster 256-bit multiplication. [#15418](https://github.com/ClickHouse/ClickHouse/pull/15418) ([Artem Zuikov](https://github.com/4ertus2)).
|
||||
* Improve performance of 256-bit types using (u)int64_t as base type for wide integers. Original wide integers use 8-bit types as base. [#14859](https://github.com/ClickHouse/ClickHouse/pull/14859) ([Artem Zuikov](https://github.com/4ertus2)).
|
||||
* Explicitly use a temporary disk to store vertical merge temporary data. [#15639](https://github.com/ClickHouse/ClickHouse/pull/15639) ([Grigory Pervakov](https://github.com/GrigoryPervakov)).
|
||||
* Use one S3 DeleteObjects request instead of multiple DeleteObject in a loop. No any functionality changes, so covered by existing tests like integration/test_log_family_s3. [#15238](https://github.com/ClickHouse/ClickHouse/pull/15238) ([ianton-ru](https://github.com/ianton-ru)).
|
||||
* Fix `DateTime <op> DateTime` mistakenly choosing the slow generic implementation. This fixes https://github.com/ClickHouse/ClickHouse/issues/15153. [#15178](https://github.com/ClickHouse/ClickHouse/pull/15178) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Improve performance of GROUP BY key of type `FixedString`. [#15034](https://github.com/ClickHouse/ClickHouse/pull/15034) ([Amos Bird](https://github.com/amosbird)).
|
||||
* Only `mlock` code segment when starting clickhouse-server. In previous versions, all mapped regions were locked in memory, including debug info. Debug info is usually splitted to a separate file but if it isn't, it led to +2..3 GiB memory usage. [#14929](https://github.com/ClickHouse/ClickHouse/pull/14929) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* ClickHouse binary become smaller due to link time optimization.
|
||||
|
||||
#### Build/Testing/Packaging Improvement
|
||||
|
||||
* Now we use clang-11 for production ClickHouse build. [#15239](https://github.com/ClickHouse/ClickHouse/pull/15239) ([alesapin](https://github.com/alesapin)).
|
||||
* Now we use clang-11 to build ClickHouse in CI. [#14846](https://github.com/ClickHouse/ClickHouse/pull/14846) ([alesapin](https://github.com/alesapin)).
|
||||
* Switch binary builds (Linux, Darwin, AArch64, FreeDSD) to clang-11. [#15622](https://github.com/ClickHouse/ClickHouse/pull/15622) ([Ilya Yatsishin](https://github.com/qoega)).
|
||||
* Now all test images use `llvm-symbolizer-11`. [#15069](https://github.com/ClickHouse/ClickHouse/pull/15069) ([alesapin](https://github.com/alesapin)).
|
||||
* Allow to build with llvm-11. [#15366](https://github.com/ClickHouse/ClickHouse/pull/15366) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Switch from `clang-tidy-10` to `clang-tidy-11`. [#14922](https://github.com/ClickHouse/ClickHouse/pull/14922) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Use LLVM's experimental pass manager by default. [#15608](https://github.com/ClickHouse/ClickHouse/pull/15608) ([Danila Kutenin](https://github.com/danlark1)).
|
||||
* Don't allow any C++ translation unit to build more than 10 minutes or to use more than 10 GB or memory. This fixes [#14925](https://github.com/ClickHouse/ClickHouse/issues/14925). [#15060](https://github.com/ClickHouse/ClickHouse/pull/15060) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Make performance test more stable and representative by splitting test runs and profile runs. [#15027](https://github.com/ClickHouse/ClickHouse/pull/15027) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Attempt to make performance test more reliable. It is done by remapping the executable memory of the process on the fly with `madvise` to use transparent huge pages - it can lower the number of iTLB misses which is the main source of instabilities in performance tests. [#14685](https://github.com/ClickHouse/ClickHouse/pull/14685) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Convert to python3. This closes [#14886](https://github.com/ClickHouse/ClickHouse/issues/14886). [#15007](https://github.com/ClickHouse/ClickHouse/pull/15007) ([Azat Khuzhin](https://github.com/azat)).
|
||||
* Fail early in functional tests if server failed to respond. This closes [#15262](https://github.com/ClickHouse/ClickHouse/issues/15262). [#15267](https://github.com/ClickHouse/ClickHouse/pull/15267) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Allow to run AArch64 version of clickhouse-server without configs. This facilitates [#15174](https://github.com/ClickHouse/ClickHouse/issues/15174). [#15266](https://github.com/ClickHouse/ClickHouse/pull/15266) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Improvements in CI docker images: get rid of ZooKeeper and single script for test configs installation. [#15215](https://github.com/ClickHouse/ClickHouse/pull/15215) ([alesapin](https://github.com/alesapin)).
|
||||
* Fix CMake options forwarding in fast test script. Fixes error in [#14711](https://github.com/ClickHouse/ClickHouse/issues/14711). [#15155](https://github.com/ClickHouse/ClickHouse/pull/15155) ([alesapin](https://github.com/alesapin)).
|
||||
* Added a script to perform hardware benchmark in a single command. [#15115](https://github.com/ClickHouse/ClickHouse/pull/15115) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Splitted huge test `test_dictionaries_all_layouts_and_sources` into smaller ones. [#15110](https://github.com/ClickHouse/ClickHouse/pull/15110) ([Nikita Mikhaylov](https://github.com/nikitamikhaylov)).
|
||||
* Maybe fix MSan report in base64 (on servers with AVX-512). This fixes [#14006](https://github.com/ClickHouse/ClickHouse/issues/14006). [#15030](https://github.com/ClickHouse/ClickHouse/pull/15030) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Reformat and cleanup code in all integration test *.py files. [#14864](https://github.com/ClickHouse/ClickHouse/pull/14864) ([Bharat Nallan](https://github.com/bharatnc)).
|
||||
* Fix MaterializeMySQL empty transaction unstable test case found in CI. [#14854](https://github.com/ClickHouse/ClickHouse/pull/14854) ([Winter Zhang](https://github.com/zhang2014)).
|
||||
* Attempt to speed up build a little. [#14808](https://github.com/ClickHouse/ClickHouse/pull/14808) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Speed up build a little by removing unused headers. [#14714](https://github.com/ClickHouse/ClickHouse/pull/14714) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
* Fix build failure in OSX. [#14761](https://github.com/ClickHouse/ClickHouse/pull/14761) ([Winter Zhang](https://github.com/zhang2014)).
|
||||
* Enable ccache by default in cmake if it's found in OS. [#14575](https://github.com/ClickHouse/ClickHouse/pull/14575) ([alesapin](https://github.com/alesapin)).
|
||||
* Control CI builds configuration from the ClickHouse repository. [#14547](https://github.com/ClickHouse/ClickHouse/pull/14547) ([alesapin](https://github.com/alesapin)).
|
||||
* In CMake files: - Moved some options' descriptions' parts to comments above. - Replace 0 -> `OFF`, 1 -> `ON` in `option`s default values. - Added some descriptions and links to docs to the options. - Replaced `FUZZER` option (there is another option `ENABLE_FUZZING` which also enables same functionality). - Removed `ENABLE_GTEST_LIBRARY` option as there is `ENABLE_TESTS`. See the full description in PR: [#14711](https://github.com/ClickHouse/ClickHouse/pull/14711) ([Mike](https://github.com/myrrc)).
|
||||
* Make binary a bit smaller (~50 Mb for debug version). [#14555](https://github.com/ClickHouse/ClickHouse/pull/14555) ([Artem Zuikov](https://github.com/4ertus2)).
|
||||
* Use std::filesystem::path in ConfigProcessor for concatenating file paths. [#14558](https://github.com/ClickHouse/ClickHouse/pull/14558) ([Bharat Nallan](https://github.com/bharatnc)).
|
||||
* Fix debug assertion in `bitShiftLeft()` when called with negative big integer. [#14697](https://github.com/ClickHouse/ClickHouse/pull/14697) ([Artem Zuikov](https://github.com/4ertus2)).
|
||||
|
||||
|
||||
## ClickHouse release 20.9
|
||||
|
||||
### ClickHouse release v20.9.2.20-stable, 2020-09-22
|
||||
### ClickHouse release v20.9.2.20, 2020-09-22
|
||||
|
||||
#### New Feature
|
||||
|
||||
@ -84,7 +296,6 @@
|
||||
|
||||
#### New Feature
|
||||
|
||||
* ClickHouse can work as MySQL replica - it is implemented by `MaterializeMySQL` database engine. Implements [#4006](https://github.com/ClickHouse/ClickHouse/issues/4006). [#10851](https://github.com/ClickHouse/ClickHouse/pull/10851) ([Winter Zhang](https://github.com/zhang2014)).
|
||||
* Add the ability to specify `Default` compression codec for columns that correspond to settings specified in `config.xml`. Implements: [#9074](https://github.com/ClickHouse/ClickHouse/issues/9074). [#14049](https://github.com/ClickHouse/ClickHouse/pull/14049) ([alesapin](https://github.com/alesapin)).
|
||||
* Support Kerberos authentication in Kafka, using `krb5` and `cyrus-sasl` libraries. [#12771](https://github.com/ClickHouse/ClickHouse/pull/12771) ([Ilya Golshtein](https://github.com/ilejn)).
|
||||
* Add function `normalizeQuery` that replaces literals, sequences of literals and complex aliases with placeholders. Add function `normalizedQueryHash` that returns identical 64bit hash values for similar queries. It helps to analyze query log. This closes [#11271](https://github.com/ClickHouse/ClickHouse/issues/11271). [#13816](https://github.com/ClickHouse/ClickHouse/pull/13816) ([alexey-milovidov](https://github.com/alexey-milovidov)).
|
||||
@ -184,6 +395,7 @@
|
||||
|
||||
#### Experimental Feature
|
||||
|
||||
* ClickHouse can work as MySQL replica - it is implemented by `MaterializeMySQL` database engine. Implements [#4006](https://github.com/ClickHouse/ClickHouse/issues/4006). [#10851](https://github.com/ClickHouse/ClickHouse/pull/10851) ([Winter Zhang](https://github.com/zhang2014)).
|
||||
* Add types `Int128`, `Int256`, `UInt256` and related functions for them. Extend Decimals with Decimal256 (precision up to 76 digits). New types are under the setting `allow_experimental_bigint_types`. It is working extremely slow and bad. The implementation is incomplete. Please don't use this feature. [#13097](https://github.com/ClickHouse/ClickHouse/pull/13097) ([Artem Zuikov](https://github.com/4ertus2)).
|
||||
|
||||
#### Build/Testing/Packaging Improvement
|
||||
|
||||
@ -35,25 +35,25 @@ PEERDIR(
|
||||
CFLAGS(-g0)
|
||||
|
||||
SRCS(
|
||||
argsToConfig.cpp
|
||||
coverage.cpp
|
||||
DateLUT.cpp
|
||||
DateLUTImpl.cpp
|
||||
JSON.cpp
|
||||
LineReader.cpp
|
||||
StringRef.cpp
|
||||
argsToConfig.cpp
|
||||
coverage.cpp
|
||||
demangle.cpp
|
||||
errnoToString.cpp
|
||||
getFQDNOrHostName.cpp
|
||||
getMemoryAmount.cpp
|
||||
getResource.cpp
|
||||
getThreadId.cpp
|
||||
JSON.cpp
|
||||
LineReader.cpp
|
||||
mremap.cpp
|
||||
phdr_cache.cpp
|
||||
preciseExp10.cpp
|
||||
setTerminalEcho.cpp
|
||||
shift10.cpp
|
||||
sleep.cpp
|
||||
StringRef.cpp
|
||||
terminalColors.cpp
|
||||
|
||||
)
|
||||
|
||||
@ -1,9 +1,9 @@
|
||||
# This strings autochanged from release_lib.sh:
|
||||
SET(VERSION_REVISION 54442)
|
||||
SET(VERSION_REVISION 54443)
|
||||
SET(VERSION_MAJOR 20)
|
||||
SET(VERSION_MINOR 11)
|
||||
SET(VERSION_MINOR 12)
|
||||
SET(VERSION_PATCH 1)
|
||||
SET(VERSION_GITHASH 76a04fb4b4f6cd27ad999baf6dc9a25e88851c42)
|
||||
SET(VERSION_DESCRIBE v20.11.1.1-prestable)
|
||||
SET(VERSION_STRING 20.11.1.1)
|
||||
SET(VERSION_GITHASH c53725fb1f846fda074347607ab582fbb9c6f7a1)
|
||||
SET(VERSION_DESCRIBE v20.12.1.1-prestable)
|
||||
SET(VERSION_STRING 20.12.1.1)
|
||||
# end of autochange
|
||||
|
||||
8
contrib/CMakeLists.txt
vendored
8
contrib/CMakeLists.txt
vendored
@ -14,6 +14,11 @@ unset (_current_dir_name)
|
||||
set (CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -w")
|
||||
set (CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -w")
|
||||
|
||||
if (SANITIZE STREQUAL "undefined")
|
||||
# 3rd-party libraries usually not intended to work with UBSan.
|
||||
add_compile_options(-fno-sanitize=undefined)
|
||||
endif()
|
||||
|
||||
set_property(DIRECTORY PROPERTY EXCLUDE_FROM_ALL 1)
|
||||
|
||||
add_subdirectory (boost-cmake)
|
||||
@ -157,9 +162,6 @@ if(USE_INTERNAL_SNAPPY_LIBRARY)
|
||||
add_subdirectory(snappy)
|
||||
|
||||
set (SNAPPY_INCLUDE_DIR "${ClickHouse_SOURCE_DIR}/contrib/snappy")
|
||||
if(SANITIZE STREQUAL "undefined")
|
||||
target_compile_options(${SNAPPY_LIBRARY} PRIVATE -fno-sanitize=undefined)
|
||||
endif()
|
||||
endif()
|
||||
|
||||
if (USE_INTERNAL_PARQUET_LIBRARY)
|
||||
|
||||
2
contrib/aws
vendored
2
contrib/aws
vendored
@ -1 +1 @@
|
||||
Subproject commit 17e10c0fc77f22afe890fa6d1b283760e5edaa56
|
||||
Subproject commit a220591e335923ce1c19bbf9eb925787f7ab6c13
|
||||
2
contrib/poco
vendored
2
contrib/poco
vendored
@ -1 +1 @@
|
||||
Subproject commit 757d947235b307675cff964f29b19d388140a9eb
|
||||
Subproject commit f49c6ab8d3aa71828bd1b411485c21722e8c9d82
|
||||
4
debian/changelog
vendored
4
debian/changelog
vendored
@ -1,5 +1,5 @@
|
||||
clickhouse (20.11.1.1) unstable; urgency=low
|
||||
clickhouse (20.12.1.1) unstable; urgency=low
|
||||
|
||||
* Modified source code
|
||||
|
||||
-- clickhouse-release <clickhouse-release@yandex-team.ru> Sat, 10 Oct 2020 18:39:55 +0300
|
||||
-- clickhouse-release <clickhouse-release@yandex-team.ru> Thu, 05 Nov 2020 21:52:47 +0300
|
||||
|
||||
@ -1,7 +1,7 @@
|
||||
FROM ubuntu:18.04
|
||||
|
||||
ARG repository="deb https://repo.clickhouse.tech/deb/stable/ main/"
|
||||
ARG version=20.11.1.*
|
||||
ARG version=20.12.1.*
|
||||
|
||||
RUN apt-get update \
|
||||
&& apt-get install --yes --no-install-recommends \
|
||||
|
||||
@ -63,7 +63,7 @@ then
|
||||
mkdir -p /output/config
|
||||
cp ../programs/server/config.xml /output/config
|
||||
cp ../programs/server/users.xml /output/config
|
||||
cp -r ../programs/server/config.d /output/config
|
||||
cp -r --dereference ../programs/server/config.d /output/config
|
||||
tar -czvf "$COMBINED_OUTPUT.tgz" /output
|
||||
rm -r /output/*
|
||||
mv "$COMBINED_OUTPUT.tgz" /output
|
||||
|
||||
@ -1,7 +1,7 @@
|
||||
FROM ubuntu:20.04
|
||||
|
||||
ARG repository="deb https://repo.clickhouse.tech/deb/stable/ main/"
|
||||
ARG version=20.11.1.*
|
||||
ARG version=20.12.1.*
|
||||
ARG gosu_ver=1.10
|
||||
|
||||
RUN apt-get update \
|
||||
|
||||
@ -1,7 +1,7 @@
|
||||
FROM ubuntu:18.04
|
||||
|
||||
ARG repository="deb https://repo.clickhouse.tech/deb/stable/ main/"
|
||||
ARG version=20.11.1.*
|
||||
ARG version=20.12.1.*
|
||||
|
||||
RUN apt-get update && \
|
||||
apt-get install -y apt-transport-https dirmngr && \
|
||||
|
||||
@ -240,6 +240,10 @@ TESTS_TO_SKIP=(
|
||||
01354_order_by_tuple_collate_const
|
||||
01355_ilike
|
||||
01411_bayesian_ab_testing
|
||||
01532_collate_in_low_cardinality
|
||||
01533_collate_in_nullable
|
||||
01542_collate_in_array
|
||||
01543_collate_in_tuple
|
||||
_orc_
|
||||
arrow
|
||||
avro
|
||||
@ -277,6 +281,8 @@ TESTS_TO_SKIP=(
|
||||
|
||||
# Require python libraries like scipy, pandas and numpy
|
||||
01322_ttest_scipy
|
||||
|
||||
01545_system_errors
|
||||
)
|
||||
|
||||
time clickhouse-test -j 8 --order=random --no-long --testname --shard --zookeeper --skip "${TESTS_TO_SKIP[@]}" 2>&1 | ts '%Y-%m-%d %H:%M:%S' | tee "$FASTTEST_OUTPUT/test_log.txt"
|
||||
|
||||
@ -45,11 +45,11 @@ function configure
|
||||
{
|
||||
rm -rf db ||:
|
||||
mkdir db ||:
|
||||
cp -av "$repo_dir"/programs/server/config* db
|
||||
cp -av "$repo_dir"/programs/server/user* db
|
||||
cp -av --dereference "$repo_dir"/programs/server/config* db
|
||||
cp -av --dereference "$repo_dir"/programs/server/user* db
|
||||
# TODO figure out which ones are needed
|
||||
cp -av "$repo_dir"/tests/config/config.d/listen.xml db/config.d
|
||||
cp -av "$script_dir"/query-fuzzer-tweaks-users.xml db/users.d
|
||||
cp -av --dereference "$repo_dir"/tests/config/config.d/listen.xml db/config.d
|
||||
cp -av --dereference "$script_dir"/query-fuzzer-tweaks-users.xml db/users.d
|
||||
}
|
||||
|
||||
function watchdog
|
||||
@ -164,7 +164,7 @@ 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" server.log > description.txt
|
||||
if ! grep -ao "Received signal.*\|Logical error.*\|Assertion.*failed\|Failed assertion.*" server.log > description.txt
|
||||
then
|
||||
echo "Lost connection to server. See the logs" > description.txt
|
||||
fi
|
||||
|
||||
@ -1074,6 +1074,53 @@ wait
|
||||
unset IFS
|
||||
}
|
||||
|
||||
function upload_results
|
||||
{
|
||||
if ! [ -v CHPC_DATABASE_URL ]
|
||||
then
|
||||
echo Database for test results is not specified, will not upload them.
|
||||
return 0
|
||||
fi
|
||||
|
||||
# Surprisingly, clickhouse-client doesn't understand --host 127.0.0.1:9000
|
||||
# so I have to extract host and port with clickhouse-local. I tried to use
|
||||
# Poco URI parser to support this in the client, but it's broken and can't
|
||||
# parse host:port.
|
||||
set +x # Don't show password in the log
|
||||
clickhouse-client \
|
||||
$(clickhouse-local --query "with '${CHPC_DATABASE_URL}' as url select '--host ' || domain(url) || ' --port ' || toString(port(url)) format TSV") \
|
||||
--secure \
|
||||
--user "${CHPC_DATABASE_USER}" \
|
||||
--password "${CHPC_DATABASE_PASSWORD}" \
|
||||
--config "right/config/client_config.xml" \
|
||||
--database perftest \
|
||||
--date_time_input_format=best_effort \
|
||||
--query "
|
||||
insert into query_metrics_v2
|
||||
select
|
||||
toDate(event_time) event_date,
|
||||
toDateTime('$(cd right/ch && git show -s --format=%ci "$SHA_TO_TEST" | cut -d' ' -f-2)') event_time,
|
||||
$PR_TO_TEST pr_number,
|
||||
'$REF_SHA' old_sha,
|
||||
'$SHA_TO_TEST' new_sha,
|
||||
test,
|
||||
query_index,
|
||||
query_display_name,
|
||||
metric_name,
|
||||
old_value,
|
||||
new_value,
|
||||
diff,
|
||||
stat_threshold
|
||||
from input('metric_name text, old_value float, new_value float, diff float,
|
||||
ratio_display_text text, stat_threshold float,
|
||||
test text, query_index int, query_display_name text')
|
||||
settings date_time_input_format='best_effort'
|
||||
format TSV
|
||||
settings date_time_input_format='best_effort'
|
||||
" < report/all-query-metrics.tsv # Don't leave whitespace after INSERT: https://github.com/ClickHouse/ClickHouse/issues/16652
|
||||
set -x
|
||||
}
|
||||
|
||||
# Check that local and client are in PATH
|
||||
clickhouse-local --version > /dev/null
|
||||
clickhouse-client --version > /dev/null
|
||||
@ -1145,6 +1192,9 @@ case "$stage" in
|
||||
time "$script_dir/report.py" --report=all-queries > all-queries.html 2> >(tee -a report/errors.log 1>&2) ||:
|
||||
time "$script_dir/report.py" > report.html
|
||||
;&
|
||||
"upload_results")
|
||||
time upload_results ||:
|
||||
;&
|
||||
esac
|
||||
|
||||
# Print some final debug info to help debug Weirdness, of which there is plenty.
|
||||
|
||||
17
docker/test/performance-comparison/config/client_config.xml
Normal file
17
docker/test/performance-comparison/config/client_config.xml
Normal file
@ -0,0 +1,17 @@
|
||||
<!--
|
||||
This config is used to upload test results to a public ClickHouse instance.
|
||||
It has bad certificates so we ignore them.
|
||||
-->
|
||||
<config>
|
||||
<openSSL>
|
||||
<client>
|
||||
<loadDefaultCAFile>true</loadDefaultCAFile>
|
||||
<cacheSessions>true</cacheSessions>
|
||||
<disableProtocols>sslv2,sslv3</disableProtocols>
|
||||
<preferServerCiphers>true</preferServerCiphers>
|
||||
<invalidCertificateHandler>
|
||||
<name>AcceptCertificateHandler</name> <!-- For tests only-->
|
||||
</invalidCertificateHandler>
|
||||
</client>
|
||||
</openSSL>
|
||||
</config>
|
||||
@ -121,6 +121,9 @@ set +e
|
||||
PATH="$(readlink -f right/)":"$PATH"
|
||||
export PATH
|
||||
|
||||
export REF_PR
|
||||
export REF_SHA
|
||||
|
||||
# Start the main comparison script.
|
||||
{ \
|
||||
time ../download.sh "$REF_PR" "$REF_SHA" "$PR_TO_TEST" "$SHA_TO_TEST" && \
|
||||
|
||||
@ -1,7 +1,6 @@
|
||||
Allow to run simple ClickHouse stress test in Docker from debian packages.
|
||||
Actually it runs single copy of clickhouse-performance-test and multiple copies
|
||||
of clickhouse-test (functional tests). This allows to find problems like
|
||||
segmentation fault which cause shutdown of server.
|
||||
Actually it runs multiple copies of clickhouse-test (functional tests).
|
||||
This allows to find problems like segmentation fault which cause shutdown of server.
|
||||
|
||||
Usage:
|
||||
```
|
||||
|
||||
@ -68,8 +68,6 @@ if __name__ == "__main__":
|
||||
parser.add_argument("--test-cmd", default='/usr/bin/clickhouse-test')
|
||||
parser.add_argument("--skip-func-tests", default='')
|
||||
parser.add_argument("--client-cmd", default='clickhouse-client')
|
||||
parser.add_argument("--perf-test-cmd", default='clickhouse-performance-test')
|
||||
parser.add_argument("--perf-test-xml-path", default='/usr/share/clickhouse-test/performance/')
|
||||
parser.add_argument("--server-log-folder", default='/var/log/clickhouse-server')
|
||||
parser.add_argument("--output-folder")
|
||||
parser.add_argument("--global-time-limit", type=int, default=3600)
|
||||
|
||||
@ -35,7 +35,7 @@ RUN apt-get update \
|
||||
ENV TZ=Europe/Moscow
|
||||
RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone
|
||||
|
||||
RUN pip3 install urllib3 testflows==1.6.59 docker-compose docker dicttoxml kazoo tzlocal
|
||||
RUN pip3 install urllib3 testflows==1.6.62 docker-compose docker dicttoxml kazoo tzlocal
|
||||
|
||||
ENV DOCKER_CHANNEL stable
|
||||
ENV DOCKER_VERSION 17.09.1-ce
|
||||
|
||||
@ -23,7 +23,7 @@ $ sudo apt-get install git cmake python ninja-build
|
||||
|
||||
Or cmake3 instead of cmake on older systems.
|
||||
|
||||
### Install GCC 9 {#install-gcc-9}
|
||||
### Install GCC 10 {#install-gcc-10}
|
||||
|
||||
There are several ways to do this.
|
||||
|
||||
@ -32,7 +32,7 @@ There are several ways to do this.
|
||||
On Ubuntu 19.10 or newer:
|
||||
|
||||
$ sudo apt-get update
|
||||
$ sudo apt-get install gcc-9 g++-9
|
||||
$ sudo apt-get install gcc-10 g++-10
|
||||
|
||||
#### Install from a PPA Package {#install-from-a-ppa-package}
|
||||
|
||||
@ -42,18 +42,18 @@ On older Ubuntu:
|
||||
$ sudo apt-get install software-properties-common
|
||||
$ sudo apt-add-repository ppa:ubuntu-toolchain-r/test
|
||||
$ sudo apt-get update
|
||||
$ sudo apt-get install gcc-9 g++-9
|
||||
$ sudo apt-get install gcc-10 g++-10
|
||||
```
|
||||
|
||||
#### Install from Sources {#install-from-sources}
|
||||
|
||||
See [utils/ci/build-gcc-from-sources.sh](https://github.com/ClickHouse/ClickHouse/blob/master/utils/ci/build-gcc-from-sources.sh)
|
||||
|
||||
### Use GCC 9 for Builds {#use-gcc-9-for-builds}
|
||||
### Use GCC 10 for Builds {#use-gcc-10-for-builds}
|
||||
|
||||
``` bash
|
||||
$ export CC=gcc-9
|
||||
$ export CXX=g++-9
|
||||
$ export CC=gcc-10
|
||||
$ export CXX=g++-10
|
||||
```
|
||||
|
||||
### Checkout ClickHouse Sources {#checkout-clickhouse-sources}
|
||||
@ -88,7 +88,7 @@ The build requires the following components:
|
||||
- Git (is used only to checkout the sources, it’s not needed for the build)
|
||||
- CMake 3.10 or newer
|
||||
- Ninja (recommended) or Make
|
||||
- C++ compiler: gcc 9 or clang 8 or newer
|
||||
- C++ compiler: gcc 10 or clang 8 or newer
|
||||
- Linker: lld or gold (the classic GNU ld won’t work)
|
||||
- Python (is only used inside LLVM build and it is optional)
|
||||
|
||||
|
||||
@ -131,13 +131,13 @@ ClickHouse uses several external libraries for building. All of them do not need
|
||||
|
||||
## C++ Compiler {#c-compiler}
|
||||
|
||||
Compilers GCC starting from version 9 and Clang version 8 or above are supported for building ClickHouse.
|
||||
Compilers GCC starting from version 10 and Clang version 8 or above are supported for building ClickHouse.
|
||||
|
||||
Official Yandex builds currently use GCC because it generates machine code of slightly better performance (yielding a difference of up to several percent according to our benchmarks). And Clang is more convenient for development usually. Though, our continuous integration (CI) platform runs checks for about a dozen of build combinations.
|
||||
|
||||
To install GCC on Ubuntu run: `sudo apt install gcc g++`
|
||||
|
||||
Check the version of gcc: `gcc --version`. If it is below 9, then follow the instruction here: https://clickhouse.tech/docs/en/development/build/#install-gcc-9.
|
||||
Check the version of gcc: `gcc --version`. If it is below 10, then follow the instruction here: https://clickhouse.tech/docs/en/development/build/#install-gcc-10.
|
||||
|
||||
Mac OS X build is supported only for Clang. Just run `brew install llvm`
|
||||
|
||||
@ -152,11 +152,11 @@ Now that you are ready to build ClickHouse we recommend you to create a separate
|
||||
|
||||
You can have several different directories (build_release, build_debug, etc.) for different types of build.
|
||||
|
||||
While inside the `build` directory, configure your build by running CMake. Before the first run, you need to define environment variables that specify compiler (version 9 gcc compiler in this example).
|
||||
While inside the `build` directory, configure your build by running CMake. Before the first run, you need to define environment variables that specify compiler (version 10 gcc compiler in this example).
|
||||
|
||||
Linux:
|
||||
|
||||
export CC=gcc-9 CXX=g++-9
|
||||
export CC=gcc-10 CXX=g++-10
|
||||
cmake ..
|
||||
|
||||
Mac OS X:
|
||||
|
||||
@ -74,9 +74,9 @@ It’s not necessarily to have unit tests if the code is already covered by func
|
||||
|
||||
## Performance Tests {#performance-tests}
|
||||
|
||||
Performance tests allow to measure and compare performance of some isolated part of ClickHouse on synthetic queries. Tests are located at `tests/performance`. Each test is represented by `.xml` file with description of test case. Tests are run with `clickhouse performance-test` tool (that is embedded in `clickhouse` binary). See `--help` for invocation.
|
||||
Performance tests allow to measure and compare performance of some isolated part of ClickHouse on synthetic queries. Tests are located at `tests/performance`. Each test is represented by `.xml` file with description of test case. Tests are run with `docker/tests/performance-comparison` tool . See the readme file for invocation.
|
||||
|
||||
Each test run one or multiple queries (possibly with combinations of parameters) in a loop with some conditions for stop (like “maximum execution speed is not changing in three seconds”) and measure some metrics about query performance (like “maximum execution speed”). Some tests can contain preconditions on preloaded test dataset.
|
||||
Each test run one or multiple queries (possibly with combinations of parameters) in a loop. Some tests can contain preconditions on preloaded test dataset.
|
||||
|
||||
If you want to improve performance of ClickHouse in some scenario, and if improvements can be observed on simple queries, it is highly recommended to write a performance test. It always makes sense to use `perf top` or other perf tools during your tests.
|
||||
|
||||
|
||||
@ -88,7 +88,7 @@ For a description of parameters, see the [CREATE query description](../../../sql
|
||||
|
||||
- `index_granularity` — Maximum number of data rows between the marks of an index. Default value: 8192. See [Data Storage](#mergetree-data-storage).
|
||||
- `index_granularity_bytes` — Maximum size of data granules in bytes. Default value: 10Mb. To restrict the granule size only by number of rows, set to 0 (not recommended). See [Data Storage](#mergetree-data-storage).
|
||||
- `min_index_granularity_bytes` — Min allowed size of data granules in bytes. Default value: 1024b. To provide safeguard against accidentally creating tables with very low index_granularity_bytes. See [Data Storage](#mergetree-data-storage).
|
||||
- `min_index_granularity_bytes` — Min allowed size of data granules in bytes. Default value: 1024b. To provide a safeguard against accidentally creating tables with very low index_granularity_bytes. See [Data Storage](#mergetree-data-storage).
|
||||
- `enable_mixed_granularity_parts` — Enables or disables transitioning to control the granule size with the `index_granularity_bytes` setting. Before version 19.11, there was only the `index_granularity` setting for restricting granule size. The `index_granularity_bytes` setting improves ClickHouse performance when selecting data from tables with big rows (tens and hundreds of megabytes). If you have tables with big rows, you can enable this setting for the tables to improve the efficiency of `SELECT` queries.
|
||||
- `use_minimalistic_part_header_in_zookeeper` — Storage method of the data parts headers in ZooKeeper. If `use_minimalistic_part_header_in_zookeeper=1`, then ZooKeeper stores less data. For more information, see the [setting description](../../../operations/server-configuration-parameters/settings.md#server-settings-use_minimalistic_part_header_in_zookeeper) in “Server configuration parameters”.
|
||||
- `min_merge_bytes_to_use_direct_io` — The minimum data volume for merge operation that is required for using direct I/O access to the storage disk. When merging data parts, ClickHouse calculates the total storage volume of all the data to be merged. If the volume exceeds `min_merge_bytes_to_use_direct_io` bytes, ClickHouse reads and writes the data to the storage disk using the direct I/O interface (`O_DIRECT` option). If `min_merge_bytes_to_use_direct_io = 0`, then direct I/O is disabled. Default value: `10 * 1024 * 1024 * 1024` bytes.
|
||||
@ -343,8 +343,8 @@ The `set` index can be used with all functions. Function subsets for other index
|
||||
|------------------------------------------------------------------------------------------------------------|-------------|--------|-------------|-------------|---------------|
|
||||
| [equals (=, ==)](../../../sql-reference/functions/comparison-functions.md#function-equals) | ✔ | ✔ | ✔ | ✔ | ✔ |
|
||||
| [notEquals(!=, \<\>)](../../../sql-reference/functions/comparison-functions.md#function-notequals) | ✔ | ✔ | ✔ | ✔ | ✔ |
|
||||
| [like](../../../sql-reference/functions/string-search-functions.md#function-like) | ✔ | ✔ | ✔ | ✔ | ✔ |
|
||||
| [notLike](../../../sql-reference/functions/string-search-functions.md#function-notlike) | ✔ | ✔ | ✗ | ✗ | ✗ |
|
||||
| [like](../../../sql-reference/functions/string-search-functions.md#function-like) | ✔ | ✔ | ✔ | ✔ | ✗ |
|
||||
| [notLike](../../../sql-reference/functions/string-search-functions.md#function-notlike) | ✔ | ✔ | ✔ | ✔ | ✗ |
|
||||
| [startsWith](../../../sql-reference/functions/string-functions.md#startswith) | ✔ | ✔ | ✔ | ✔ | ✗ |
|
||||
| [endsWith](../../../sql-reference/functions/string-functions.md#endswith) | ✗ | ✗ | ✔ | ✔ | ✗ |
|
||||
| [multiSearchAny](../../../sql-reference/functions/string-search-functions.md#function-multisearchany) | ✗ | ✗ | ✔ | ✗ | ✗ |
|
||||
|
||||
@ -98,6 +98,7 @@ When creating a table, the following settings are applied:
|
||||
- [max_bytes_in_join](../../../operations/settings/query-complexity.md#settings-max_bytes_in_join)
|
||||
- [join_overflow_mode](../../../operations/settings/query-complexity.md#settings-join_overflow_mode)
|
||||
- [join_any_take_last_row](../../../operations/settings/settings.md#settings-join_any_take_last_row)
|
||||
- [persistent](../../../operations/settings/settings.md#persistent)
|
||||
|
||||
The `Join`-engine tables can’t be used in `GLOBAL JOIN` operations.
|
||||
|
||||
|
||||
@ -14,4 +14,10 @@ Data is always located in RAM. For `INSERT`, the blocks of inserted data are als
|
||||
|
||||
For a rough server restart, the block of data on the disk might be lost or damaged. In the latter case, you may need to manually delete the file with damaged data.
|
||||
|
||||
### Limitations and Settings {#join-limitations-and-settings}
|
||||
|
||||
When creating a table, the following settings are applied:
|
||||
|
||||
- [persistent](../../../operations/settings/settings.md#persistent)
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/operations/table_engines/set/) <!--hide-->
|
||||
|
||||
@ -148,7 +148,7 @@ SETTINGS index_granularity = 8192;
|
||||
Loading data:
|
||||
|
||||
``` bash
|
||||
$ for i in *.zip; do echo $i; unzip -cq $i '*.csv' | sed 's/\.00//g' | clickhouse-client --host=example-perftest01j --query="INSERT INTO ontime FORMAT CSVWithNames"; done
|
||||
$ for i in *.zip; do echo $i; unzip -cq $i '*.csv' | sed 's/\.00//g' | clickhouse-client --input_format_with_names_use_header=0 --host=example-perftest01j --query="INSERT INTO ontime FORMAT CSVWithNames"; done
|
||||
```
|
||||
|
||||
## Download of Prepared Partitions {#download-of-prepared-partitions}
|
||||
|
||||
@ -79,7 +79,7 @@ By default, data is returned in TabSeparated format (for more information, see t
|
||||
|
||||
You use the FORMAT clause of the query to request any other format.
|
||||
|
||||
Also, you can use the ‘default_format’ URL parameter or ‘X-ClickHouse-Format’ header to specify a default format other than TabSeparated.
|
||||
Also, you can use the ‘default_format’ URL parameter or the ‘X-ClickHouse-Format’ header to specify a default format other than TabSeparated.
|
||||
|
||||
``` bash
|
||||
$ echo 'SELECT 1 FORMAT Pretty' | curl 'http://localhost:8123/?' --data-binary @-
|
||||
@ -170,7 +170,7 @@ $ echo "SELECT 1" | gzip -c | curl -sS --data-binary @- -H 'Content-Encoding: gz
|
||||
!!! note "Note"
|
||||
Some HTTP clients might decompress data from the server by default (with `gzip` and `deflate`) and you might get decompressed data even if you use the compression settings correctly.
|
||||
|
||||
You can use the ‘database’ URL parameter or ‘X-ClickHouse-Database’ header to specify the default database.
|
||||
You can use the ‘database’ URL parameter or the ‘X-ClickHouse-Database’ header to specify the default database.
|
||||
|
||||
``` bash
|
||||
$ echo 'SELECT number FROM numbers LIMIT 10' | curl 'http://localhost:8123/?database=system' --data-binary @-
|
||||
|
||||
@ -36,6 +36,7 @@ toc_title: Adopters
|
||||
| <a href="https://www.criteo.com/" class="favicon">Criteo</a> | Retail | Main product | — | — | [Slides in English, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup18/3_storetail.pptx) |
|
||||
| <a href="https://www.chinatelecomglobal.com/" class="favicon">Dataliance for China Telecom</a> | Telecom | Analytics | — | — | [Slides in Chinese, January 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup12/telecom.pdf) |
|
||||
| <a href="https://db.com" class="favicon">Deutsche Bank</a> | Finance | BI Analytics | — | — | [Slides in English, October 2019](https://bigdatadays.ru/wp-content/uploads/2019/10/D2-H3-3_Yakunin-Goihburg.pdf) |
|
||||
| <a href="https://deeplay.io/eng/" class="favicon">Deeplay</a> | Gaming Analytics | — | — | — | [Job advertisement, 2020](https://career.habr.com/vacancies/1000062568) |
|
||||
| <a href="https://www.diva-e.com" class="favicon">Diva-e</a> | Digital consulting | Main Product | — | — | [Slides in English, September 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup29/ClickHouse-MeetUp-Unusual-Applications-sd-2019-09-17.pdf) |
|
||||
| <a href="https://www.ecwid.com/" class="favicon">Ecwid</a> | E-commerce SaaS | Metrics, Logging | — | — | [Slides in Russian, April 2019](https://nastachku.ru/var/files/1/presentation/backend/2_Backend_6.pdf) |
|
||||
| <a href="https://www.ebay.com/" class="favicon">eBay</a> | E-commerce | Logs, Metrics and Events | — | — | [Official website, Sep 2020](https://tech.ebayinc.com/engineering/ou-online-analytical-processing/) |
|
||||
@ -45,6 +46,7 @@ toc_title: Adopters
|
||||
| <a href="https://fun.co/rp" class="favicon">FunCorp</a> | Games | | — | — | [Article](https://www.altinity.com/blog/migrating-from-redshift-to-clickhouse) |
|
||||
| <a href="https://geniee.co.jp" class="favicon">Geniee</a> | Ad network | Main product | — | — | [Blog post in Japanese, July 2017](https://tech.geniee.co.jp/entry/2017/07/20/160100) |
|
||||
| <a href="https://www.huya.com/" class="favicon">HUYA</a> | Video Streaming | Analytics | — | — | [Slides in Chinese, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup19/7.%20ClickHouse万亿数据分析实践%20李本旺(sundy-li)%20虎牙.pdf) |
|
||||
| <a href="https://www.the-ica.com/" class="favicon">ICA</a> | FinTech | Risk Management | — | — | [Blog Post in English, Sep 2020](https://altinity.com/blog/clickhouse-vs-redshift-performance-for-fintech-risk-management?utm_campaign=ClickHouse%20vs%20RedShift&utm_content=143520807&utm_medium=social&utm_source=twitter&hss_channel=tw-3894792263) |
|
||||
| <a href="https://www.idealista.com" class="favicon">Idealista</a> | Real Estate | Analytics | — | — | [Blog Post in English, April 2019](https://clickhouse.tech/blog/en/clickhouse-meetup-in-madrid-on-april-2-2019) |
|
||||
| <a href="https://www.infovista.com/" class="favicon">Infovista</a> | Networks | Analytics | — | — | [Slides in English, October 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup30/infovista.pdf) |
|
||||
| <a href="https://www.innogames.com" class="favicon">InnoGames</a> | Games | Metrics, Logging | — | — | [Slides in Russian, September 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup28/graphite_and_clickHouse.pdf) |
|
||||
@ -68,6 +70,7 @@ toc_title: Adopters
|
||||
| <a href="https://www.nuna.com/" class="favicon">Nuna Inc.</a> | Health Data Analytics | — | — | — | [Talk in English, July 2020](https://youtu.be/GMiXCMFDMow?t=170) |
|
||||
| <a href="https://www.oneapm.com/" class="favicon">OneAPM</a> | Monitorings and Data Analysis | Main product | — | — | [Slides in Chinese, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup19/8.%20clickhouse在OneAPM的应用%20杜龙.pdf) |
|
||||
| <a href="https://www.percent.cn/" class="favicon">Percent 百分点</a> | Analytics | Main Product | — | — | [Slides in Chinese, June 2019](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup24/4.%20ClickHouse万亿数据双中心的设计与实践%20.pdf) |
|
||||
| <a href="https://www.percona.com/" class="favicon">Percona</a> | Performance analysis | Percona Monitoring and Management | — | — | [Official website, Mar 2020](https://www.percona.com/blog/2020/03/30/advanced-query-analysis-in-percona-monitoring-and-management-with-direct-clickhouse-access/) |
|
||||
| <a href="https://plausible.io/" class="favicon">Plausible</a> | Analytics | Main Product | — | — | [Blog post, June 2020](https://twitter.com/PlausibleHQ/status/1273889629087969280) |
|
||||
| <a href="https://posthog.com/" class="favicon">PostHog</a> | Product Analytics | Main Product | — | — | [Release Notes, Oct 2020](https://posthog.com/blog/the-posthog-array-1-15-0) |
|
||||
| <a href="https://postmates.com/" class="favicon">Postmates</a> | Delivery | — | — | — | [Talk in English, July 2020](https://youtu.be/GMiXCMFDMow?t=188) |
|
||||
@ -90,6 +93,7 @@ toc_title: Adopters
|
||||
| <a href="https://www.splunk.com/" class="favicon">Splunk</a> | Business Analytics | Main product | — | — | [Slides in English, January 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup12/splunk.pdf) |
|
||||
| <a href="https://www.spotify.com" class="favicon">Spotify</a> | Music | Experimentation | — | — | [Slides, July 2018](https://www.slideshare.net/glebus/using-clickhouse-for-experimentation-104247173) |
|
||||
| <a href="https://www.staffcop.ru/" class="favicon">Staffcop</a> | Information Security | Main Product | — | — | [Official website, Documentation](https://www.staffcop.ru/sce43) |
|
||||
| <a href="https://www.teralytics.net/" class="favicon">Teralytics</a> | Mobility | Analytics | — | — | [Tech blog](https://www.teralytics.net/knowledge-hub/visualizing-mobility-data-the-scalability-challenge) |
|
||||
| <a href="https://www.tencent.com" class="favicon">Tencent</a> | Big Data | Data processing | — | — | [Slides in Chinese, October 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup19/5.%20ClickHouse大数据集群应用_李俊飞腾讯网媒事业部.pdf) |
|
||||
| <a href="https://www.tencent.com" class="favicon">Tencent</a> | Messaging | Logging | — | — | [Talk in Chinese, November 2019](https://youtu.be/T-iVQRuw-QY?t=5050) |
|
||||
| <a href="https://trafficstars.com/" class="favicon">Traffic Stars</a> | AD network | — | — | — | [Slides in Russian, May 2018](https://github.com/ClickHouse/clickhouse-presentations/blob/master/meetup15/lightning/ninja.pdf) |
|
||||
|
||||
@ -479,6 +479,26 @@ The maximum number of simultaneously processed requests.
|
||||
<max_concurrent_queries>100</max_concurrent_queries>
|
||||
```
|
||||
|
||||
## max_concurrent_queries_for_all_users {#max-concurrent-queries-for-all-users}
|
||||
|
||||
Throw exception if the value of this setting is less or equal than the current number of simultaneously processed queries.
|
||||
|
||||
Example: `max_concurrent_queries_for_all_users` can be set to 99 for all users and database administrator can set it to 100 for itself to run queries for investigation even when the server is overloaded.
|
||||
|
||||
Modifying the setting for one query or user does not affect other queries.
|
||||
|
||||
Default value: `0` that means no limit.
|
||||
|
||||
**Example**
|
||||
|
||||
``` xml
|
||||
<max_concurrent_queries_for_all_users>99</max_concurrent_queries_for_all_users>
|
||||
```
|
||||
|
||||
**See Also**
|
||||
|
||||
- [max_concurrent_queries](#max-concurrent-queries)
|
||||
|
||||
## max_connections {#max-connections}
|
||||
|
||||
The maximum number of inbound connections.
|
||||
@ -551,7 +571,7 @@ For more information, see the MergeTreeSettings.h header file.
|
||||
|
||||
Fine tuning for tables in the [ReplicatedMergeTree](../../engines/table-engines/mergetree-family/mergetree.md).
|
||||
|
||||
This setting has higher priority.
|
||||
This setting has a higher priority.
|
||||
|
||||
For more information, see the MergeTreeSettings.h header file.
|
||||
|
||||
|
||||
@ -680,6 +680,21 @@ Example:
|
||||
log_queries=1
|
||||
```
|
||||
|
||||
## log_queries_min_query_duration_ms {#settings-log-queries-min-query-duration-ms}
|
||||
|
||||
Minimal time for the query to run to get to the following tables:
|
||||
|
||||
- `system.query_log`
|
||||
- `system.query_thread_log`
|
||||
|
||||
Only the queries with the following type will get to the log:
|
||||
|
||||
- `QUERY_FINISH`
|
||||
- `EXCEPTION_WHILE_PROCESSING`
|
||||
|
||||
- Type: milliseconds
|
||||
- Default value: 0 (any query)
|
||||
|
||||
## log_queries_min_type {#settings-log-queries-min-type}
|
||||
|
||||
`query_log` minimal type to log.
|
||||
@ -1750,6 +1765,23 @@ Default value: `0`.
|
||||
|
||||
- [Distributed Table Engine](../../engines/table-engines/special/distributed.md#distributed)
|
||||
- [Managing Distributed Tables](../../sql-reference/statements/system.md#query-language-system-distributed)
|
||||
|
||||
|
||||
## use_compact_format_in_distributed_parts_names {#use_compact_format_in_distributed_parts_names}
|
||||
|
||||
Uses compact format for storing blocks for async (`insert_distributed_sync`) INSERT into tables with `Distributed` engine.
|
||||
|
||||
Possible values:
|
||||
|
||||
- 0 — Uses `user[:password]@host:port#default_database` directory format.
|
||||
- 1 — Uses `[shard{shard_index}[_replica{replica_index}]]` directory format.
|
||||
|
||||
Default value: `1`.
|
||||
|
||||
!!! note "Note"
|
||||
- with `use_compact_format_in_distributed_parts_names=0` changes from cluster definition will not be applied for async INSERT.
|
||||
- with `use_compact_format_in_distributed_parts_names=1` changing the order of the nodes in the cluster definition, will change the `shard_index`/`replica_index` so be aware.
|
||||
|
||||
## background_buffer_flush_schedule_pool_size {#background_buffer_flush_schedule_pool_size}
|
||||
|
||||
Sets the number of threads performing background flush in [Buffer](../../engines/table-engines/special/buffer.md)-engine tables. This setting is applied at the ClickHouse server start and can’t be changed in a user session.
|
||||
@ -2188,4 +2220,17 @@ Possible values:
|
||||
|
||||
Default value: `0`.
|
||||
|
||||
## persistent {#persistent}
|
||||
|
||||
Disables persistency for the [Set](../../engines/table-engines/special/set.md#set) and [Join](../../engines/table-engines/special/join.md#join) table engines.
|
||||
|
||||
Reduces the I/O overhead. Suitable for scenarios that pursue performance and do not require persistence.
|
||||
|
||||
Possible values:
|
||||
|
||||
- 1 — Enabled.
|
||||
- 0 — Disabled.
|
||||
|
||||
Default value: `1`.
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/operations/settings/settings/) <!-- hide -->
|
||||
|
||||
@ -1,6 +1,6 @@
|
||||
## system.asynchronous_metric_log {#system-tables-async-log}
|
||||
|
||||
Contains the historical values for `system.asynchronous_metrics`, which are saved once per minute. This feature is enabled by default.
|
||||
Contains the historical values for `system.asynchronous_metrics`, which are saved once per minute. Enabled by default.
|
||||
|
||||
Columns:
|
||||
|
||||
@ -33,7 +33,7 @@ SELECT * FROM system.asynchronous_metric_log LIMIT 10
|
||||
|
||||
**See Also**
|
||||
|
||||
- [system.asynchronous_metrics](../system-tables/asynchronous_metrics.md) — Contains metrics that are calculated periodically in the background.
|
||||
- [system.asynchronous_metrics](../system-tables/asynchronous_metrics.md) — Contains metrics, calculated periodically in the background.
|
||||
- [system.metric_log](../system-tables/metric_log.md) — Contains history of metrics values from tables `system.metrics` and `system.events`, periodically flushed to disk.
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/operations/system_tables/asynchronous_metric_log) <!--hide-->
|
||||
|
||||
@ -6,19 +6,21 @@ You can use this table to get information similar to the [DESCRIBE TABLE](../../
|
||||
|
||||
The `system.columns` table contains the following columns (the column type is shown in brackets):
|
||||
|
||||
- `database` (String) — Database name.
|
||||
- `table` (String) — Table name.
|
||||
- `name` (String) — Column name.
|
||||
- `type` (String) — Column type.
|
||||
- `default_kind` (String) — Expression type (`DEFAULT`, `MATERIALIZED`, `ALIAS`) for the default value, or an empty string if it is not defined.
|
||||
- `default_expression` (String) — Expression for the default value, or an empty string if it is not defined.
|
||||
- `data_compressed_bytes` (UInt64) — The size of compressed data, in bytes.
|
||||
- `data_uncompressed_bytes` (UInt64) — The size of decompressed data, in bytes.
|
||||
- `marks_bytes` (UInt64) — The size of marks, in bytes.
|
||||
- `comment` (String) — Comment on the column, or an empty string if it is not defined.
|
||||
- `is_in_partition_key` (UInt8) — Flag that indicates whether the column is in the partition expression.
|
||||
- `is_in_sorting_key` (UInt8) — Flag that indicates whether the column is in the sorting key expression.
|
||||
- `is_in_primary_key` (UInt8) — Flag that indicates whether the column is in the primary key expression.
|
||||
- `is_in_sampling_key` (UInt8) — Flag that indicates whether the column is in the sampling key expression.
|
||||
- `database` ([String](../../sql-reference/data-types/string.md)) — Database name.
|
||||
- `table` ([String](../../sql-reference/data-types/string.md)) — Table name.
|
||||
- `name` ([String](../../sql-reference/data-types/string.md)) — Column name.
|
||||
- `type` ([String](../../sql-reference/data-types/string.md)) — Column type.
|
||||
- `position` ([UInt64](../../sql-reference/data-types/int-uint.md)) — Ordinal position of a column in a table starting with 1.
|
||||
- `default_kind` ([String](../../sql-reference/data-types/string.md)) — Expression type (`DEFAULT`, `MATERIALIZED`, `ALIAS`) for the default value, or an empty string if it is not defined.
|
||||
- `default_expression` ([String](../../sql-reference/data-types/string.md)) — Expression for the default value, or an empty string if it is not defined.
|
||||
- `data_compressed_bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — The size of compressed data, in bytes.
|
||||
- `data_uncompressed_bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — The size of decompressed data, in bytes.
|
||||
- `marks_bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — The size of marks, in bytes.
|
||||
- `comment` ([String](../../sql-reference/data-types/string.md)) — Comment on the column, or an empty string if it is not defined.
|
||||
- `is_in_partition_key` ([UInt8](../../sql-reference/data-types/int-uint.md)) — Flag that indicates whether the column is in the partition expression.
|
||||
- `is_in_sorting_key` ([UInt8](../../sql-reference/data-types/int-uint.md)) — Flag that indicates whether the column is in the sorting key expression.
|
||||
- `is_in_primary_key` ([UInt8](../../sql-reference/data-types/int-uint.md)) — Flag that indicates whether the column is in the primary key expression.
|
||||
- `is_in_sampling_key` ([UInt8](../../sql-reference/data-types/int-uint.md)) — Flag that indicates whether the column is in the sampling key expression.
|
||||
- `compression_codec` ([String](../../sql-reference/data-types/string.md)) — Compression codec name.
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/operations/system_tables/columns) <!--hide-->
|
||||
|
||||
23
docs/en/operations/system-tables/errors.md
Normal file
23
docs/en/operations/system-tables/errors.md
Normal file
@ -0,0 +1,23 @@
|
||||
# system.errors {#system_tables-errors}
|
||||
|
||||
Contains error codes with number of times they have been triggered.
|
||||
|
||||
Columns:
|
||||
|
||||
- `name` ([String](../../sql-reference/data-types/string.md)) — name of the error (`errorCodeToName`).
|
||||
- `code` ([Int32](../../sql-reference/data-types/int-uint.md)) — code number of the error.
|
||||
- `value` ([UInt64](../../sql-reference/data-types/int-uint.md)) - number of times this error has been happened.
|
||||
|
||||
**Example**
|
||||
|
||||
``` sql
|
||||
SELECT *
|
||||
FROM system.errors
|
||||
WHERE value > 0
|
||||
ORDER BY code ASC
|
||||
LIMIT 1
|
||||
|
||||
┌─name─────────────┬─code─┬─value─┐
|
||||
│ CANNOT_OPEN_FILE │ 76 │ 1 │
|
||||
└──────────────────┴──────┴───────┘
|
||||
```
|
||||
@ -1,6 +1,7 @@
|
||||
# system.metric_log {#system_tables-metric_log}
|
||||
|
||||
Contains history of metrics values from tables `system.metrics` and `system.events`, periodically flushed to disk.
|
||||
|
||||
To turn on metrics history collection on `system.metric_log`, create `/etc/clickhouse-server/config.d/metric_log.xml` with following content:
|
||||
|
||||
``` xml
|
||||
@ -14,6 +15,11 @@ To turn on metrics history collection on `system.metric_log`, create `/etc/click
|
||||
</yandex>
|
||||
```
|
||||
|
||||
Columns:
|
||||
- `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 resolution.
|
||||
|
||||
**Example**
|
||||
|
||||
``` sql
|
||||
|
||||
148
docs/en/operations/system-tables/parts_columns.md
Normal file
148
docs/en/operations/system-tables/parts_columns.md
Normal file
@ -0,0 +1,148 @@
|
||||
# system.parts_columns {#system_tables-parts_columns}
|
||||
|
||||
Contains information about parts and columns of [MergeTree](../../engines/table-engines/mergetree-family/mergetree.md) tables.
|
||||
|
||||
Each row describes one data part.
|
||||
|
||||
Columns:
|
||||
|
||||
- `partition` ([String](../../sql-reference/data-types/string.md)) — The partition name. To learn what a partition is, see the description of the [ALTER](../../sql-reference/statements/alter/index.md#query_language_queries_alter) query.
|
||||
|
||||
Formats:
|
||||
|
||||
- `YYYYMM` for automatic partitioning by month.
|
||||
- `any_string` when partitioning manually.
|
||||
|
||||
- `name` ([String](../../sql-reference/data-types/string.md)) — Name of the data part.
|
||||
|
||||
- `part_type` ([String](../../sql-reference/data-types/string.md)) — The data part storing format.
|
||||
|
||||
Possible values:
|
||||
|
||||
- `Wide` — Each column is stored in a separate file in a filesystem.
|
||||
- `Compact` — All columns are stored in one file in a filesystem.
|
||||
|
||||
Data storing format is controlled by the `min_bytes_for_wide_part` and `min_rows_for_wide_part` settings of the [MergeTree](../../engines/table-engines/mergetree-family/mergetree.md) table.
|
||||
|
||||
- `active` ([UInt8](../../sql-reference/data-types/int-uint.md)) — Flag that indicates whether the data part is active. If a data part is active, it’s used in a table. Otherwise, it’s deleted. Inactive data parts remain after merging.
|
||||
|
||||
- `marks` ([UInt64](../../sql-reference/data-types/int-uint.md)) — The number of marks. To get the approximate number of rows in a data part, multiply `marks` by the index granularity (usually 8192) (this hint doesn’t work for adaptive granularity).
|
||||
|
||||
- `rows` ([UInt64](../../sql-reference/data-types/int-uint.md)) — The number of rows.
|
||||
|
||||
- `bytes_on_disk` ([UInt64](../../sql-reference/data-types/int-uint.md)) — Total size of all the data part files in bytes.
|
||||
|
||||
- `data_compressed_bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — Total size of compressed data in the data part. All the auxiliary files (for example, files with marks) are not included.
|
||||
|
||||
- `data_uncompressed_bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — Total size of uncompressed data in the data part. All the auxiliary files (for example, files with marks) are not included.
|
||||
|
||||
- `marks_bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — The size of the file with marks.
|
||||
|
||||
- `modification_time` ([DateTime](../../sql-reference/data-types/datetime.md)) — The time the directory with the data part was modified. This usually corresponds to the time of data part creation.
|
||||
|
||||
- `remove_time` ([DateTime](../../sql-reference/data-types/datetime.md)) — The time when the data part became inactive.
|
||||
|
||||
- `refcount` ([UInt32](../../sql-reference/data-types/int-uint.md)) — The number of places where the data part is used. A value greater than 2 indicates that the data part is used in queries or merges.
|
||||
|
||||
- `min_date` ([Date](../../sql-reference/data-types/date.md)) — The minimum value of the date key in the data part.
|
||||
|
||||
- `max_date` ([Date](../../sql-reference/data-types/date.md)) — The maximum value of the date key in the data part.
|
||||
|
||||
- `partition_id` ([String](../../sql-reference/data-types/string.md)) — ID of the partition.
|
||||
|
||||
- `min_block_number` ([UInt64](../../sql-reference/data-types/int-uint.md)) — The minimum number of data parts that make up the current part after merging.
|
||||
|
||||
- `max_block_number` ([UInt64](../../sql-reference/data-types/int-uint.md)) — The maximum number of data parts that make up the current part after merging.
|
||||
|
||||
- `level` ([UInt32](../../sql-reference/data-types/int-uint.md)) — Depth of the merge tree. Zero means that the current part was created by insert rather than by merging other parts.
|
||||
|
||||
- `data_version` ([UInt64](../../sql-reference/data-types/int-uint.md)) — Number that is used to determine which mutations should be applied to the data part (mutations with a version higher than `data_version`).
|
||||
|
||||
- `primary_key_bytes_in_memory` ([UInt64](../../sql-reference/data-types/int-uint.md)) — The amount of memory (in bytes) used by primary key values.
|
||||
|
||||
- `primary_key_bytes_in_memory_allocated` ([UInt64](../../sql-reference/data-types/int-uint.md)) — The amount of memory (in bytes) reserved for primary key values.
|
||||
|
||||
- `database` ([String](../../sql-reference/data-types/string.md)) — Name of the database.
|
||||
|
||||
- `table` ([String](../../sql-reference/data-types/string.md)) — Name of the table.
|
||||
|
||||
- `engine` ([String](../../sql-reference/data-types/string.md)) — Name of the table engine without parameters.
|
||||
|
||||
- `disk_name` ([String](../../sql-reference/data-types/string.md)) — Name of a disk that stores the data part.
|
||||
|
||||
- `path` ([String](../../sql-reference/data-types/string.md)) — Absolute path to the folder with data part files.
|
||||
|
||||
- `column` ([String](../../sql-reference/data-types/string.md)) — Name of the column.
|
||||
|
||||
- `type` ([String](../../sql-reference/data-types/string.md)) — Column type.
|
||||
|
||||
- `column_position` ([UInt64](../../sql-reference/data-types/int-uint.md)) — Ordinal position of a column in a table starting with 1.
|
||||
|
||||
- `default_kind` ([String](../../sql-reference/data-types/string.md)) — Expression type (`DEFAULT`, `MATERIALIZED`, `ALIAS`) for the default value, or an empty string if it is not defined.
|
||||
|
||||
- `default_expression` ([String](../../sql-reference/data-types/string.md)) — Expression for the default value, or an empty string if it is not defined.
|
||||
|
||||
- `column_bytes_on_disk` ([UInt64](../../sql-reference/data-types/int-uint.md)) — Total size of the column in bytes.
|
||||
|
||||
- `column_data_compressed_bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — Total size of compressed data in the column, in bytes.
|
||||
|
||||
- `column_data_uncompressed_bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — Total size of the decompressed data in the column, in bytes.
|
||||
|
||||
- `column_marks_bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — The size of the column with marks, in bytes.
|
||||
|
||||
- `bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — Alias for `bytes_on_disk`.
|
||||
|
||||
- `marks_size` ([UInt64](../../sql-reference/data-types/int-uint.md)) — Alias for `marks_bytes`.
|
||||
|
||||
**Example**
|
||||
|
||||
``` sql
|
||||
SELECT * FROM system.parts_columns LIMIT 1 FORMAT Vertical;
|
||||
```
|
||||
|
||||
``` text
|
||||
Row 1:
|
||||
──────
|
||||
partition: tuple()
|
||||
name: all_1_2_1
|
||||
part_type: Wide
|
||||
active: 1
|
||||
marks: 2
|
||||
rows: 2
|
||||
bytes_on_disk: 155
|
||||
data_compressed_bytes: 56
|
||||
data_uncompressed_bytes: 4
|
||||
marks_bytes: 96
|
||||
modification_time: 2020-09-23 10:13:36
|
||||
remove_time: 2106-02-07 06:28:15
|
||||
refcount: 1
|
||||
min_date: 1970-01-01
|
||||
max_date: 1970-01-01
|
||||
partition_id: all
|
||||
min_block_number: 1
|
||||
max_block_number: 2
|
||||
level: 1
|
||||
data_version: 1
|
||||
primary_key_bytes_in_memory: 2
|
||||
primary_key_bytes_in_memory_allocated: 64
|
||||
database: default
|
||||
table: 53r93yleapyears
|
||||
engine: MergeTree
|
||||
disk_name: default
|
||||
path: /var/lib/clickhouse/data/default/53r93yleapyears/all_1_2_1/
|
||||
column: id
|
||||
type: Int8
|
||||
column_position: 1
|
||||
default_kind:
|
||||
default_expression:
|
||||
column_bytes_on_disk: 76
|
||||
column_data_compressed_bytes: 28
|
||||
column_data_uncompressed_bytes: 2
|
||||
column_marks_bytes: 48
|
||||
```
|
||||
|
||||
**See Also**
|
||||
|
||||
- [MergeTree family](../../engines/table-engines/mergetree-family/mergetree.md)
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/operations/system_tables/parts_columns) <!--hide-->
|
||||
@ -7,6 +7,9 @@ toc_title: clickhouse-copier
|
||||
|
||||
Copies data from the tables in one cluster to tables in another (or the same) cluster.
|
||||
|
||||
!!! warning "Warning"
|
||||
To get a consistent copy, the data in the source tables and partitions should not change during the entire process.
|
||||
|
||||
You can run multiple `clickhouse-copier` instances on different servers to perform the same job. ZooKeeper is used for syncing the processes.
|
||||
|
||||
After starting, `clickhouse-copier`:
|
||||
|
||||
@ -16,7 +16,7 @@ By default `clickhouse-local` does not have access to data on the same host, but
|
||||
!!! warning "Warning"
|
||||
It is not recommended to load production server configuration into `clickhouse-local` because data can be damaged in case of human error.
|
||||
|
||||
For temporary data an unique temporary data directory is created by default. If you want to override this behavior the data directory can be explicitly specified with the `-- --path` option.
|
||||
For temporary data, a unique temporary data directory is created by default. If you want to override this behavior, the data directory can be explicitly specified with the `-- --path` option.
|
||||
|
||||
## Usage {#usage}
|
||||
|
||||
|
||||
@ -53,13 +53,13 @@ Result:
|
||||
|
||||
Similar to `quantileExact`, this computes the exact [quantile](https://en.wikipedia.org/wiki/Quantile) of a numeric data sequence.
|
||||
|
||||
To get exact value, all the passed values are combined into an array, which is then fully sorted. The sorting [algorithm's](https://en.cppreference.com/w/cpp/algorithm/sort) complexity is `O(N·log(N))`, where `N = std::distance(first, last)` comparisons.
|
||||
To get the exact value, all the passed values are combined into an array, which is then fully sorted. The sorting [algorithm's](https://en.cppreference.com/w/cpp/algorithm/sort) complexity is `O(N·log(N))`, where `N = std::distance(first, last)` comparisons.
|
||||
|
||||
Depending on the level, i.e if the level is 0.5 then the exact lower median value is returned if there are even number of elements and the middle value is returned if there are odd number of elements. Median is calculated similar to the [median_low](https://docs.python.org/3/library/statistics.html#statistics.median_low) implementation which is used in python.
|
||||
The return value depends on the quantile level and the number of elements in the selection, i.e. if the level is 0.5, then the function returns the lower median value for an even number of elements and the middle median value for an odd number of elements. Median is calculated similarly to the [median_low](https://docs.python.org/3/library/statistics.html#statistics.median_low) implementation which is used in python.
|
||||
|
||||
For all other levels, the element at the the index corresponding to the value of `level * size_of_array` is returned. For example:
|
||||
For all other levels, the element at the index corresponding to the value of `level * size_of_array` is returned. For example:
|
||||
|
||||
```$sql
|
||||
``` sql
|
||||
SELECT quantileExactLow(0.1)(number) FROM numbers(10)
|
||||
|
||||
┌─quantileExactLow(0.1)(number)─┐
|
||||
@ -111,9 +111,10 @@ Result:
|
||||
|
||||
Similar to `quantileExact`, this computes the exact [quantile](https://en.wikipedia.org/wiki/Quantile) of a numeric data sequence.
|
||||
|
||||
To get exact value, all the passed values are combined into an array, which is then fully sorted. The sorting [algorithm's](https://en.cppreference.com/w/cpp/algorithm/sort) complexity is `O(N·log(N))`, where `N = std::distance(first, last)` comparisons.
|
||||
All the passed values are combined into an array, which is then fully sorted,
|
||||
to get the exact value. The sorting [algorithm's](https://en.cppreference.com/w/cpp/algorithm/sort) complexity is `O(N·log(N))`, where `N = std::distance(first, last)` comparisons.
|
||||
|
||||
Depending on the level, i.e if the level is 0.5 then the exact higher median value is returned if there are even number of elements and the middle value is returned if there are odd number of elements. Median is calculated similar to the [median_high](https://docs.python.org/3/library/statistics.html#statistics.median_high) implementation which is used in python. For all other levels, the element at the the index corresponding to the value of `level * size_of_array` is returned.
|
||||
The return value depends on the quantile level and the number of elements in the selection, i.e. if the level is 0.5, then the function returns the higher median value for an even number of elements and the middle median value for an odd number of elements. Median is calculated similarly to the [median_high](https://docs.python.org/3/library/statistics.html#statistics.median_high) implementation which is used in python. For all other levels, the element at the index corresponding to the value of `level * size_of_array` is returned.
|
||||
|
||||
This implementation behaves exactly similar to the current `quantileExact` implementation.
|
||||
|
||||
|
||||
@ -4,6 +4,6 @@ toc_priority: 140
|
||||
|
||||
# sumWithOverflow {#sumwithoverflowx}
|
||||
|
||||
Computes the sum of the numbers, using the same data type for the result as for the input parameters. If the sum exceeds the maximum value for this data type, the function returns an error.
|
||||
Computes the sum of the numbers, using the same data type for the result as for the input parameters. If the sum exceeds the maximum value for this data type, it is calculated with overflow.
|
||||
|
||||
Only works for numbers.
|
||||
|
||||
@ -59,7 +59,8 @@ LAYOUT(LAYOUT_TYPE(param value)) -- layout settings
|
||||
- [range_hashed](#range-hashed)
|
||||
- [complex_key_hashed](#complex-key-hashed)
|
||||
- [complex_key_cache](#complex-key-cache)
|
||||
- [ssd_complex_key_cache](#ssd-cache)
|
||||
- [ssd_cache](#ssd-cache)
|
||||
- [ssd_complex_key_cache](#complex-key-ssd-cache)
|
||||
- [complex_key_direct](#complex-key-direct)
|
||||
- [ip_trie](#ip-trie)
|
||||
|
||||
|
||||
@ -0,0 +1,91 @@
|
||||
---
|
||||
toc_priority: 46
|
||||
toc_title: Polygon Dictionaries With Grids
|
||||
---
|
||||
|
||||
|
||||
# Polygon dictionaries {#polygon-dictionaries}
|
||||
|
||||
Polygon dictionaries allow you to efficiently search for the polygon containing specified points.
|
||||
For example: defining a city area by geographical coordinates.
|
||||
|
||||
Example configuration:
|
||||
|
||||
``` xml
|
||||
<dictionary>
|
||||
<structure>
|
||||
<key>
|
||||
<name>key</name>
|
||||
<type>Array(Array(Array(Array(Float64))))</type>
|
||||
</key>
|
||||
|
||||
<attribute>
|
||||
<name>name</name>
|
||||
<type>String</type>
|
||||
<null_value></null_value>
|
||||
</attribute>
|
||||
|
||||
<attribute>
|
||||
<name>value</name>
|
||||
<type>UInt64</type>
|
||||
<null_value>0</null_value>
|
||||
</attribute>
|
||||
|
||||
</structure>
|
||||
|
||||
<layout>
|
||||
<polygon />
|
||||
</layout>
|
||||
|
||||
</dictionary>
|
||||
```
|
||||
|
||||
Tne corresponding [DDL-query](../../../sql-reference/statements/create/dictionary.md#create-dictionary-query):
|
||||
``` sql
|
||||
CREATE DICTIONARY polygon_dict_name (
|
||||
key Array(Array(Array(Array(Float64)))),
|
||||
name String,
|
||||
value UInt64
|
||||
)
|
||||
PRIMARY KEY key
|
||||
LAYOUT(POLYGON())
|
||||
...
|
||||
```
|
||||
|
||||
When configuring the polygon dictionary, the key must have one of two types:
|
||||
- A simple polygon. It is an array of points.
|
||||
- MultiPolygon. It is an array of polygons. Each polygon is a two-dimensional array of points. The first element of this array is the outer boundary of the polygon, and subsequent elements specify areas to be excluded from it.
|
||||
|
||||
Points can be specified as an array or a tuple of their coordinates. In the current implementation, only two-dimensional points are supported.
|
||||
|
||||
The user can [upload their own data](../../../sql-reference/dictionaries/external-dictionaries/external-dicts-dict-sources.md) in all formats supported by ClickHouse.
|
||||
|
||||
|
||||
There are 3 types of [in-memory storage](../../../sql-reference/dictionaries/external-dictionaries/external-dicts-dict-layout.md) available:
|
||||
|
||||
- POLYGON_SIMPLE. This is a naive implementation, where a linear pass through all polygons is made for each query, and membership is checked for each one without using additional indexes.
|
||||
|
||||
- POLYGON_INDEX_EACH. A separate index is built for each polygon, which allows you to quickly check whether it belongs in most cases (optimized for geographical regions).
|
||||
Also, a grid is superimposed on the area under consideration, which significantly narrows the number of polygons under consideration.
|
||||
The grid is created by recursively dividing the cell into 16 equal parts and is configured with two parameters.
|
||||
The division stops when the recursion depth reaches MAX_DEPTH or when the cell crosses no more than MIN_INTERSECTIONS polygons.
|
||||
To respond to the query, there is a corresponding cell, and the index for the polygons stored in it is accessed alternately.
|
||||
|
||||
- POLYGON_INDEX_CELL. This placement also creates the grid described above. The same options are available. For each sheet cell, an index is built on all pieces of polygons that fall into it, which allows you to quickly respond to a request.
|
||||
|
||||
- POLYGON. Synonym to POLYGON_INDEX_CELL.
|
||||
|
||||
Dictionary queries are carried out using standard [functions](../../../sql-reference/functions/ext-dict-functions.md) for working with external dictionaries.
|
||||
An important difference is that here the keys will be the points for which you want to find the polygon containing them.
|
||||
|
||||
Example of working with the dictionary defined above:
|
||||
``` sql
|
||||
CREATE TABLE points (
|
||||
x Float64,
|
||||
y Float64
|
||||
)
|
||||
...
|
||||
SELECT tuple(x, y) AS key, dictGet(dict_name, 'name', key), dictGet(dict_name, 'value', key) FROM points ORDER BY x, y;
|
||||
```
|
||||
|
||||
As a result of executing the last command for each point in the 'points' table, a minimum area polygon containing this point will be found, and the requested attributes will be output.
|
||||
@ -89,7 +89,7 @@ If the index falls outside of the bounds of an array, it returns some default va
|
||||
## has(arr, elem) {#hasarr-elem}
|
||||
|
||||
Checks whether the ‘arr’ array has the ‘elem’ element.
|
||||
Returns 0 if the the element is not in the array, or 1 if it is.
|
||||
Returns 0 if the element is not in the array, or 1 if it is.
|
||||
|
||||
`NULL` is processed as a value.
|
||||
|
||||
|
||||
@ -153,15 +153,18 @@ A fast, decent-quality non-cryptographic hash function for a string obtained fro
|
||||
`URLHash(s, N)` – Calculates a hash from a string up to the N level in the URL hierarchy, without one of the trailing symbols `/`,`?` or `#` at the end, if present.
|
||||
Levels are the same as in URLHierarchy. This function is specific to Yandex.Metrica.
|
||||
|
||||
## farmFingerprint64 {#farmfingerprint64}
|
||||
|
||||
## farmHash64 {#farmhash64}
|
||||
|
||||
Produces a 64-bit [FarmHash](https://github.com/google/farmhash) hash value.
|
||||
Produces a 64-bit [FarmHash](https://github.com/google/farmhash) or Fingerprint value. Prefer `farmFingerprint64` for a stable and portable value.
|
||||
|
||||
``` sql
|
||||
farmFingerprint64(par1, ...)
|
||||
farmHash64(par1, ...)
|
||||
```
|
||||
|
||||
The function uses the `Hash64` method from all [available methods](https://github.com/google/farmhash/blob/master/src/farmhash.h).
|
||||
These functions use the `Fingerprint64` and `Hash64` method respectively from all [available methods](https://github.com/google/farmhash/blob/master/src/farmhash.h).
|
||||
|
||||
**Parameters**
|
||||
|
||||
|
||||
@ -1657,4 +1657,24 @@ Result:
|
||||
10 10 19 19 39 39
|
||||
```
|
||||
|
||||
## errorCodeToName {#error-code-to-name}
|
||||
|
||||
**Returned value**
|
||||
|
||||
- Variable name for the error code.
|
||||
|
||||
Type: [LowCardinality(String)](../../sql-reference/data-types/lowcardinality.md).
|
||||
|
||||
**Syntax**
|
||||
|
||||
``` sql
|
||||
errorCodeToName(1)
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
UNSUPPORTED_METHOD
|
||||
```
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/query_language/functions/other_functions/) <!--hide-->
|
||||
|
||||
@ -323,6 +323,10 @@ This function accepts a number or date or date with time, and returns a string c
|
||||
|
||||
This function accepts a number or date or date with time, and returns a FixedString containing bytes representing the corresponding value in host order (little endian). Null bytes are dropped from the end. For example, a UInt32 type value of 255 is a FixedString that is one byte long.
|
||||
|
||||
## reinterpretAsUUID {#reinterpretasuuid}
|
||||
|
||||
This function accepts FixedString, and returns UUID. Takes 16 bytes string. If the string isn't long enough, the functions work as if the string is padded with the necessary number of null bytes to the end. If the string longer than 16 bytes, the extra bytes at the end are ignored.
|
||||
|
||||
## CAST(x, T) {#type_conversion_function-cast}
|
||||
|
||||
Converts ‘x’ to the ‘t’ data type. The syntax CAST(x AS t) is also supported.
|
||||
@ -780,4 +784,42 @@ Result:
|
||||
└──────────────────────────────────┘
|
||||
```
|
||||
|
||||
## formatRowNoNewline {#formatrownonewline}
|
||||
|
||||
Converts arbitrary expressions into a string via given format. The function trims the last `\n` if any.
|
||||
|
||||
**Syntax**
|
||||
|
||||
``` sql
|
||||
formatRowNoNewline(format, x, y, ...)
|
||||
```
|
||||
|
||||
**Parameters**
|
||||
|
||||
- `format` — Text format. For example, [CSV](../../interfaces/formats.md#csv), [TSV](../../interfaces/formats.md#tabseparated).
|
||||
- `x`,`y`, ... — Expressions.
|
||||
|
||||
**Returned value**
|
||||
|
||||
- A formatted string.
|
||||
|
||||
**Example**
|
||||
|
||||
Query:
|
||||
|
||||
``` sql
|
||||
SELECT formatRowNoNewline('CSV', number, 'good')
|
||||
FROM numbers(3)
|
||||
```
|
||||
|
||||
Result:
|
||||
|
||||
``` text
|
||||
┌─formatRowNoNewline('CSV', number, 'good')─┐
|
||||
│ 0,"good" │
|
||||
│ 1,"good" │
|
||||
│ 2,"good" │
|
||||
└───────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/query_language/functions/type_conversion_functions/) <!--hide-->
|
||||
|
||||
@ -151,21 +151,43 @@ Types of intervals:
|
||||
- `QUARTER`
|
||||
- `YEAR`
|
||||
|
||||
You can also use a string literal when setting the `INTERVAL` value. For example, `INTERVAL 1 HOUR` is identical to the `INTERVAL '1 hour'` or `INTERVAL '1' hour`.
|
||||
|
||||
!!! warning "Warning"
|
||||
Intervals with different types can’t be combined. You can’t use expressions like `INTERVAL 4 DAY 1 HOUR`. Specify intervals in units that are smaller or equal to the smallest unit of the interval, for example, `INTERVAL 25 HOUR`. You can use consecutive operations, like in the example below.
|
||||
|
||||
Example:
|
||||
Examples:
|
||||
|
||||
``` sql
|
||||
SELECT now() AS current_date_time, current_date_time + INTERVAL 4 DAY + INTERVAL 3 HOUR
|
||||
SELECT now() AS current_date_time, current_date_time + INTERVAL 4 DAY + INTERVAL 3 HOUR;
|
||||
```
|
||||
|
||||
``` text
|
||||
┌───current_date_time─┬─plus(plus(now(), toIntervalDay(4)), toIntervalHour(3))─┐
|
||||
│ 2019-10-23 11:16:28 │ 2019-10-27 14:16:28 │
|
||||
│ 2020-11-03 22:09:50 │ 2020-11-08 01:09:50 │
|
||||
└─────────────────────┴────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
``` sql
|
||||
SELECT now() AS current_date_time, current_date_time + INTERVAL '4 day' + INTERVAL '3 hour';
|
||||
```
|
||||
|
||||
``` text
|
||||
┌───current_date_time─┬─plus(plus(now(), toIntervalDay(4)), toIntervalHour(3))─┐
|
||||
│ 2020-11-03 22:12:10 │ 2020-11-08 01:12:10 │
|
||||
└─────────────────────┴────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
``` sql
|
||||
SELECT now() AS current_date_time, current_date_time + INTERVAL '4' day + INTERVAL '3' hour;
|
||||
```
|
||||
|
||||
``` text
|
||||
┌───current_date_time─┬─plus(plus(now(), toIntervalDay('4')), toIntervalHour('3'))─┐
|
||||
│ 2020-11-03 22:33:19 │ 2020-11-08 01:33:19 │
|
||||
└─────────────────────┴────────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
**See Also**
|
||||
|
||||
- [Interval](../../sql-reference/data-types/special-data-types/interval.md) data type
|
||||
|
||||
@ -15,7 +15,7 @@ Syntax:
|
||||
CREATE [OR REPLACE] VIEW [IF NOT EXISTS] [db.]table_name [ON CLUSTER] AS SELECT ...
|
||||
```
|
||||
|
||||
Normal views don’t store any data, they just perform a read from another table on each access. In other words, a normal view is nothing more than a saved query. When reading from a view, this saved query is used as a subquery in the [FROM](../../../sql-reference/statements/select/from.md) clause.
|
||||
Normal views don’t store any data. They just perform a read from another table on each access. In other words, a normal view is nothing more than a saved query. When reading from a view, this saved query is used as a subquery in the [FROM](../../../sql-reference/statements/select/from.md) clause.
|
||||
|
||||
As an example, assume you’ve created a view:
|
||||
|
||||
|
||||
41
docs/en/sql-reference/table-functions/null.md
Normal file
41
docs/en/sql-reference/table-functions/null.md
Normal file
@ -0,0 +1,41 @@
|
||||
---
|
||||
toc_priority: 53
|
||||
toc_title: null function
|
||||
---
|
||||
|
||||
# null {#null-function}
|
||||
|
||||
Accepts an inserted data of the specified structure and immediately drops it away. The function is used for convenience writing tests and demonstrations.
|
||||
|
||||
**Syntax**
|
||||
|
||||
``` sql
|
||||
null('structure')
|
||||
```
|
||||
|
||||
**Parameter**
|
||||
|
||||
- `structure` — A list of columns and column types. [String](../../sql-reference/data-types/string.md).
|
||||
|
||||
**Returned value**
|
||||
|
||||
A table with the specified structure, which is dropped right after the query execution.
|
||||
|
||||
**Example**
|
||||
|
||||
Query with the `null` function:
|
||||
|
||||
``` sql
|
||||
INSERT INTO function null('x UInt64') SELECT * FROM numbers_mt(1000000000);
|
||||
```
|
||||
can replace three queries:
|
||||
|
||||
```sql
|
||||
CREATE TABLE t (x UInt64) ENGINE = Null;
|
||||
INSERT INTO t SELECT * FROM numbers_mt(1000000000);
|
||||
DROP TABLE IF EXISTS t;
|
||||
```
|
||||
|
||||
See also: format **Null**.
|
||||
|
||||
[Original article](https://clickhouse.tech/docs/en/sql-reference/table-functions/null/) <!--hide-->
|
||||
@ -19,7 +19,7 @@ $ sudo apt-get install git cmake python ninja-build
|
||||
|
||||
O cmake3 en lugar de cmake en sistemas más antiguos.
|
||||
|
||||
## Instalar GCC 9 {#install-gcc-9}
|
||||
## Instalar GCC 10 {#install-gcc-10}
|
||||
|
||||
Hay varias formas de hacer esto.
|
||||
|
||||
@ -29,18 +29,18 @@ Hay varias formas de hacer esto.
|
||||
$ sudo apt-get install software-properties-common
|
||||
$ sudo apt-add-repository ppa:ubuntu-toolchain-r/test
|
||||
$ sudo apt-get update
|
||||
$ sudo apt-get install gcc-9 g++-9
|
||||
$ sudo apt-get install gcc-10 g++-10
|
||||
```
|
||||
|
||||
### Instalar desde fuentes {#install-from-sources}
|
||||
|
||||
Mira [Sistema abierto.](https://github.com/ClickHouse/ClickHouse/blob/master/utils/ci/build-gcc-from-sources.sh)
|
||||
|
||||
## Usar GCC 9 para compilaciones {#use-gcc-9-for-builds}
|
||||
## Usar GCC 10 para compilaciones {#use-gcc-10-for-builds}
|
||||
|
||||
``` bash
|
||||
$ export CC=gcc-9
|
||||
$ export CXX=g++-9
|
||||
$ export CC=gcc-10
|
||||
$ export CXX=g++-10
|
||||
```
|
||||
|
||||
## Fuentes de ClickHouse de pago {#checkout-clickhouse-sources}
|
||||
@ -76,7 +76,7 @@ La compilación requiere los siguientes componentes:
|
||||
- Git (se usa solo para verificar las fuentes, no es necesario para la compilación)
|
||||
- CMake 3.10 o más reciente
|
||||
- Ninja (recomendado) o Hacer
|
||||
- Compilador de C ++: gcc 9 o clang 8 o más reciente
|
||||
- Compilador de C ++: gcc 10 o clang 8 o más reciente
|
||||
- Enlazador: lld u oro (el clásico GNU ld no funcionará)
|
||||
- Python (solo se usa dentro de la compilación LLVM y es opcional)
|
||||
|
||||
|
||||
@ -135,13 +135,13 @@ ClickHouse utiliza varias bibliotecas externas para la construcción. Todos ello
|
||||
|
||||
# Compilador de C ++ {#c-compiler}
|
||||
|
||||
Los compiladores GCC a partir de la versión 9 y Clang versión 8 o superior son compatibles para construir ClickHouse.
|
||||
Los compiladores GCC a partir de la versión 10 y Clang versión 8 o superior son compatibles para construir ClickHouse.
|
||||
|
||||
Las compilaciones oficiales de Yandex actualmente usan GCC porque genera código de máquina de un rendimiento ligeramente mejor (con una diferencia de hasta varios por ciento según nuestros puntos de referencia). Y Clang es más conveniente para el desarrollo generalmente. Sin embargo, nuestra plataforma de integración continua (CI) ejecuta verificaciones de aproximadamente una docena de combinaciones de compilación.
|
||||
|
||||
Para instalar GCC en Ubuntu, ejecute: `sudo apt install gcc g++`
|
||||
|
||||
Compruebe la versión de gcc: `gcc --version`. Si está por debajo de 9, siga las instrucciones aquí: https://clickhouse.tech/docs/es/development/build/#install-gcc-9.
|
||||
Compruebe la versión de gcc: `gcc --version`. Si está por debajo de 9, siga las instrucciones aquí: https://clickhouse.tech/docs/es/development/build/#install-gcc-10.
|
||||
|
||||
La compilación de Mac OS X solo es compatible con Clang. Sólo tiene que ejecutar `brew install llvm`
|
||||
|
||||
@ -156,11 +156,11 @@ Ahora que está listo para construir ClickHouse, le recomendamos que cree un dir
|
||||
|
||||
Puede tener varios directorios diferentes (build_release, build_debug, etc.) para diferentes tipos de construcción.
|
||||
|
||||
Mientras que dentro de la `build` directorio, configure su compilación ejecutando CMake. Antes de la primera ejecución, debe definir variables de entorno que especifiquen el compilador (compilador gcc versión 9 en este ejemplo).
|
||||
Mientras que dentro de la `build` directorio, configure su compilación ejecutando CMake. Antes de la primera ejecución, debe definir variables de entorno que especifiquen el compilador (compilador gcc versión 10 en este ejemplo).
|
||||
|
||||
Linux:
|
||||
|
||||
export CC=gcc-9 CXX=g++-9
|
||||
export CC=gcc-10 CXX=g++-10
|
||||
cmake ..
|
||||
|
||||
Mac OS X:
|
||||
|
||||
@ -1,261 +0,0 @@
|
||||
---
|
||||
machine_translated: true
|
||||
machine_translated_rev: 72537a2d527c63c07aa5d2361a8829f3895cf2bd
|
||||
toc_priority: 69
|
||||
toc_title: "C\xF3mo ejecutar pruebas de ClickHouse"
|
||||
---
|
||||
|
||||
# Pruebas de ClickHouse {#clickhouse-testing}
|
||||
|
||||
## Pruebas funcionales {#functional-tests}
|
||||
|
||||
Las pruebas funcionales son las más simples y cómodas de usar. La mayoría de las características de ClickHouse se pueden probar con pruebas funcionales y son obligatorias para cada cambio en el código de ClickHouse que se puede probar de esa manera.
|
||||
|
||||
Cada prueba funcional envía una o varias consultas al servidor ClickHouse en ejecución y compara el resultado con la referencia.
|
||||
|
||||
Las pruebas se encuentran en `queries` directorio. Hay dos subdirectorios: `stateless` y `stateful`. Las pruebas sin estado ejecutan consultas sin datos de prueba precargados: a menudo crean pequeños conjuntos de datos sintéticos sobre la marcha, dentro de la prueba misma. Las pruebas estatales requieren datos de prueba precargados de Yandex.Métrica y no está disponible para el público en general. Tendemos a usar sólo `stateless` pruebas y evitar la adición de nuevos `stateful` prueba.
|
||||
|
||||
Cada prueba puede ser de dos tipos: `.sql` y `.sh`. `.sql` test es el script SQL simple que se canaliza a `clickhouse-client --multiquery --testmode`. `.sh` test es un script que se ejecuta por sí mismo.
|
||||
|
||||
Para ejecutar todas las pruebas, use `clickhouse-test` herramienta. Mira `--help` para la lista de posibles opciones. Simplemente puede ejecutar todas las pruebas o ejecutar un subconjunto de pruebas filtradas por subcadena en el nombre de la prueba: `./clickhouse-test substring`.
|
||||
|
||||
La forma más sencilla de invocar pruebas funcionales es copiar `clickhouse-client` a `/usr/bin/`, ejecutar `clickhouse-server` y luego ejecutar `./clickhouse-test` de su propio directorio.
|
||||
|
||||
Para agregar una nueva prueba, cree un `.sql` o `.sh` archivo en `queries/0_stateless` directorio, compruébelo manualmente y luego genere `.reference` archivo de la siguiente manera: `clickhouse-client -n --testmode < 00000_test.sql > 00000_test.reference` o `./00000_test.sh > ./00000_test.reference`.
|
||||
|
||||
Las pruebas deben usar (crear, soltar, etc.) solo tablas en `test` base de datos que se supone que se crea de antemano; también las pruebas pueden usar tablas temporales.
|
||||
|
||||
Si desea utilizar consultas distribuidas en pruebas funcionales, puede aprovechar `remote` función de la tabla con `127.0.0.{1..2}` direcciones para que el servidor se consulte; o puede usar clústeres de prueba predefinidos en el archivo de configuración del servidor como `test_shard_localhost`.
|
||||
|
||||
Algunas pruebas están marcadas con `zookeeper`, `shard` o `long` en sus nombres.
|
||||
`zookeeper` es para pruebas que están usando ZooKeeper. `shard` es para pruebas que
|
||||
requiere servidor para escuchar `127.0.0.*`; `distributed` o `global` tienen el mismo
|
||||
significado. `long` es para pruebas que duran un poco más de un segundo. Usted puede
|
||||
deshabilitar estos grupos de pruebas utilizando `--no-zookeeper`, `--no-shard` y
|
||||
`--no-long` opciones, respectivamente.
|
||||
|
||||
## Bugs Conocidos {#known-bugs}
|
||||
|
||||
Si conocemos algunos errores que se pueden reproducir fácilmente mediante pruebas funcionales, colocamos pruebas funcionales preparadas en `tests/queries/bugs` directorio. Estas pruebas se moverán a `tests/queries/0_stateless` cuando se corrigen errores.
|
||||
|
||||
## Pruebas de integración {#integration-tests}
|
||||
|
||||
Las pruebas de integración permiten probar ClickHouse en la configuración agrupada y la interacción de ClickHouse con otros servidores como MySQL, Postgres, MongoDB. Son útiles para emular divisiones de red, caídas de paquetes, etc. Estas pruebas se ejecutan bajo Docker y crean múltiples contenedores con varios software.
|
||||
|
||||
Ver `tests/integration/README.md` sobre cómo ejecutar estas pruebas.
|
||||
|
||||
Tenga en cuenta que la integración de ClickHouse con controladores de terceros no se ha probado. Además, actualmente no tenemos pruebas de integración con nuestros controladores JDBC y ODBC.
|
||||
|
||||
## Pruebas unitarias {#unit-tests}
|
||||
|
||||
Las pruebas unitarias son útiles cuando desea probar no ClickHouse como un todo, sino una sola biblioteca o clase aislada. Puede habilitar o deshabilitar la compilación de pruebas con `ENABLE_TESTS` Opción CMake. Las pruebas unitarias (y otros programas de prueba) se encuentran en `tests` subdirectorios en todo el código. Para ejecutar pruebas unitarias, escriba `ninja test`. Algunas pruebas usan `gtest`, pero algunos son solo programas que devuelven un código de salida distinto de cero en caso de fallo de prueba.
|
||||
|
||||
No es necesariamente tener pruebas unitarias si el código ya está cubierto por pruebas funcionales (y las pruebas funcionales suelen ser mucho más simples de usar).
|
||||
|
||||
## Pruebas de rendimiento {#performance-tests}
|
||||
|
||||
Las pruebas de rendimiento permiten medir y comparar el rendimiento de alguna parte aislada de ClickHouse en consultas sintéticas. Las pruebas se encuentran en `tests/performance`. Cada prueba está representada por `.xml` archivo con la descripción del caso de prueba. Las pruebas se ejecutan con `clickhouse performance-test` herramienta (que está incrustada en `clickhouse` binario). Ver `--help` para la invocación.
|
||||
|
||||
Cada prueba ejecuta una o varias consultas (posiblemente con combinaciones de parámetros) en un bucle con algunas condiciones para detener (como “maximum execution speed is not changing in three seconds”) y medir algunas métricas sobre el rendimiento de las consultas (como “maximum execution speed”). Algunas pruebas pueden contener condiciones previas en el conjunto de datos de pruebas precargado.
|
||||
|
||||
Si desea mejorar el rendimiento de ClickHouse en algún escenario, y si se pueden observar mejoras en consultas simples, se recomienda encarecidamente escribir una prueba de rendimiento. Siempre tiene sentido usar `perf top` u otras herramientas de perf durante sus pruebas.
|
||||
|
||||
## Herramientas de prueba y secuencias de comandos {#test-tools-and-scripts}
|
||||
|
||||
Algunos programas en `tests` directorio no son pruebas preparadas, pero son herramientas de prueba. Por ejemplo, para `Lexer` hay una herramienta `src/Parsers/tests/lexer` que solo hacen la tokenización de stdin y escriben el resultado coloreado en stdout. Puede usar este tipo de herramientas como ejemplos de código y para exploración y pruebas manuales.
|
||||
|
||||
También puede colocar un par de archivos `.sh` y `.reference` junto con la herramienta para ejecutarlo en alguna entrada predefinida, entonces el resultado del script se puede comparar con `.reference` file. Este tipo de pruebas no están automatizadas.
|
||||
|
||||
## Pruebas diversas {#miscellaneous-tests}
|
||||
|
||||
Hay pruebas para diccionarios externos ubicados en `tests/external_dictionaries` y para modelos aprendidos a máquina en `tests/external_models`. Estas pruebas no se actualizan y deben transferirse a pruebas de integración.
|
||||
|
||||
Hay una prueba separada para inserciones de quórum. Esta prueba ejecuta el clúster ClickHouse en servidores separados y emula varios casos de fallas: división de red, caída de paquetes (entre nodos ClickHouse, entre ClickHouse y ZooKeeper, entre el servidor ClickHouse y el cliente, etc.), `kill -9`, `kill -STOP` y `kill -CONT` , como [Jepsen](https://aphyr.com/tags/Jepsen). A continuación, la prueba comprueba que todas las inserciones reconocidas se escribieron y todas las inserciones rechazadas no.
|
||||
|
||||
La prueba de quórum fue escrita por un equipo separado antes de que ClickHouse fuera de código abierto. Este equipo ya no trabaja con ClickHouse. La prueba fue escrita accidentalmente en Java. Por estas razones, la prueba de quórum debe reescribirse y trasladarse a pruebas de integración.
|
||||
|
||||
## Pruebas manuales {#manual-testing}
|
||||
|
||||
Cuando desarrolla una nueva característica, es razonable probarla también manualmente. Puede hacerlo con los siguientes pasos:
|
||||
|
||||
Construir ClickHouse. Ejecute ClickHouse desde el terminal: cambie el directorio a `programs/clickhouse-server` y ejecutarlo con `./clickhouse-server`. Se utilizará la configuración (`config.xml`, `users.xml` y archivos dentro de `config.d` y `users.d` directorios) desde el directorio actual de forma predeterminada. Para conectarse al servidor ClickHouse, ejecute `programs/clickhouse-client/clickhouse-client`.
|
||||
|
||||
Tenga en cuenta que todas las herramientas de clickhouse (servidor, cliente, etc.) son solo enlaces simbólicos a un único binario llamado `clickhouse`. Puede encontrar este binario en `programs/clickhouse`. Todas las herramientas también se pueden invocar como `clickhouse tool` en lugar de `clickhouse-tool`.
|
||||
|
||||
Alternativamente, puede instalar el paquete ClickHouse: ya sea una versión estable del repositorio de Yandex o puede crear un paquete para usted con `./release` en la raíz de fuentes de ClickHouse. Luego inicie el servidor con `sudo service clickhouse-server start` (o detener para detener el servidor). Busque registros en `/etc/clickhouse-server/clickhouse-server.log`.
|
||||
|
||||
Cuando ClickHouse ya está instalado en su sistema, puede crear un nuevo `clickhouse` binario y reemplazar el binario existente:
|
||||
|
||||
``` bash
|
||||
$ sudo service clickhouse-server stop
|
||||
$ sudo cp ./clickhouse /usr/bin/
|
||||
$ sudo service clickhouse-server start
|
||||
```
|
||||
|
||||
También puede detener el servidor de clickhouse del sistema y ejecutar el suyo propio con la misma configuración pero con el registro en la terminal:
|
||||
|
||||
``` bash
|
||||
$ sudo service clickhouse-server stop
|
||||
$ sudo -u clickhouse /usr/bin/clickhouse server --config-file /etc/clickhouse-server/config.xml
|
||||
```
|
||||
|
||||
Ejemplo con gdb:
|
||||
|
||||
``` bash
|
||||
$ sudo -u clickhouse gdb --args /usr/bin/clickhouse server --config-file /etc/clickhouse-server/config.xml
|
||||
```
|
||||
|
||||
Si el servidor de clickhouse del sistema ya se está ejecutando y no desea detenerlo, puede cambiar los números de `config.xml` (o anularlos en un archivo en `config.d` directorio), proporcione la ruta de datos adecuada y ejecútela.
|
||||
|
||||
`clickhouse` binary casi no tiene dependencias y funciona en una amplia gama de distribuciones de Linux. Para probar rápidamente y sucio sus cambios en un servidor, simplemente puede `scp` su fresco construido `clickhouse` binario a su servidor y luego ejecútelo como en los ejemplos anteriores.
|
||||
|
||||
## Entorno de prueba {#testing-environment}
|
||||
|
||||
Antes de publicar la versión como estable, la implementamos en el entorno de prueba. El entorno de prueba es un clúster que procesa 1/39 parte de [El Yandex.Métrica](https://metrica.yandex.com/) datos. Compartimos nuestro entorno de pruebas con Yandex.Equipo de Metrica. ClickHouse se actualiza sin tiempo de inactividad sobre los datos existentes. Nos fijamos en un primer momento que los datos se procesan con éxito sin retraso de tiempo real, la replicación continúan trabajando y no hay problemas visibles para Yandex.Equipo de Metrica. La primera comprobación se puede hacer de la siguiente manera:
|
||||
|
||||
``` sql
|
||||
SELECT hostName() AS h, any(version()), any(uptime()), max(UTCEventTime), count() FROM remote('example01-01-{1..3}t', merge, hits) WHERE EventDate >= today() - 2 GROUP BY h ORDER BY h;
|
||||
```
|
||||
|
||||
En algunos casos también implementamos en el entorno de prueba de nuestros equipos de amigos en Yandex: Market, Cloud, etc. También tenemos algunos servidores de hardware que se utilizan con fines de desarrollo.
|
||||
|
||||
## Pruebas de carga {#load-testing}
|
||||
|
||||
Después de implementar en el entorno de prueba, ejecutamos pruebas de carga con consultas del clúster de producción. Esto se hace manualmente.
|
||||
|
||||
Asegúrese de que ha habilitado `query_log` en su clúster de producción.
|
||||
|
||||
Recopilar el registro de consultas para un día o más:
|
||||
|
||||
``` bash
|
||||
$ clickhouse-client --query="SELECT DISTINCT query FROM system.query_log WHERE event_date = today() AND query LIKE '%ym:%' AND query NOT LIKE '%system.query_log%' AND type = 2 AND is_initial_query" > queries.tsv
|
||||
```
|
||||
|
||||
Este es un ejemplo complicado. `type = 2` filtrará las consultas que se ejecutan correctamente. `query LIKE '%ym:%'` es seleccionar consultas relevantes de Yandex.Métrica. `is_initial_query` es seleccionar solo las consultas iniciadas por el cliente, no por ClickHouse (como partes del procesamiento de consultas distribuidas).
|
||||
|
||||
`scp` este registro en su clúster de prueba y ejecútelo de la siguiente manera:
|
||||
|
||||
``` bash
|
||||
$ clickhouse benchmark --concurrency 16 < queries.tsv
|
||||
```
|
||||
|
||||
(probablemente también desee especificar un `--user`)
|
||||
|
||||
Luego déjalo por una noche o un fin de semana e ir a tomar un descanso.
|
||||
|
||||
Usted debe comprobar que `clickhouse-server` no se bloquea, la huella de memoria está limitada y el rendimiento no se degrada con el tiempo.
|
||||
|
||||
Los tiempos de ejecución de consultas precisos no se registran y no se comparan debido a la alta variabilidad de las consultas y el entorno.
|
||||
|
||||
## Pruebas de construcción {#build-tests}
|
||||
|
||||
Las pruebas de compilación permiten verificar que la compilación no esté rota en varias configuraciones alternativas y en algunos sistemas extranjeros. Las pruebas se encuentran en `ci` directorio. Ejecutan compilación desde la fuente dentro de Docker, Vagrant y, a veces, con `qemu-user-static` dentro de Docker. Estas pruebas están en desarrollo y las ejecuciones de pruebas no están automatizadas.
|
||||
|
||||
Motivación:
|
||||
|
||||
Normalmente lanzamos y ejecutamos todas las pruebas en una sola variante de compilación ClickHouse. Pero hay variantes de construcción alternativas que no se prueban a fondo. Ejemplos:
|
||||
|
||||
- construir en FreeBSD;
|
||||
- construir en Debian con bibliotecas de paquetes del sistema;
|
||||
- construir con enlaces compartidos de bibliotecas;
|
||||
- construir en la plataforma AArch64;
|
||||
- construir en la plataforma PowerPc.
|
||||
|
||||
Por ejemplo, construir con paquetes del sistema es una mala práctica, porque no podemos garantizar qué versión exacta de paquetes tendrá un sistema. Pero esto es realmente necesario para los mantenedores de Debian. Por esta razón, al menos tenemos que admitir esta variante de construcción. Otro ejemplo: la vinculación compartida es una fuente común de problemas, pero es necesaria para algunos entusiastas.
|
||||
|
||||
Aunque no podemos ejecutar todas las pruebas en todas las variantes de compilaciones, queremos verificar al menos que varias variantes de compilación no estén rotas. Para este propósito utilizamos pruebas de construcción.
|
||||
|
||||
## Pruebas de Compatibilidad de protocolos {#testing-for-protocol-compatibility}
|
||||
|
||||
Cuando ampliamos el protocolo de red ClickHouse, probamos manualmente que el antiguo clickhouse-client funciona con el nuevo clickhouse-server y el nuevo clickhouse-client funciona con el antiguo clickhouse-server (simplemente ejecutando binarios de los paquetes correspondientes).
|
||||
|
||||
## Ayuda del compilador {#help-from-the-compiler}
|
||||
|
||||
Código principal de ClickHouse (que se encuentra en `dbms` directorio) se construye con `-Wall -Wextra -Werror` y con algunas advertencias habilitadas adicionales. Aunque estas opciones no están habilitadas para bibliotecas de terceros.
|
||||
|
||||
Clang tiene advertencias aún más útiles: puedes buscarlas con `-Weverything` y elige algo para la compilación predeterminada.
|
||||
|
||||
Para las compilaciones de producción, se usa gcc (todavía genera un código ligeramente más eficiente que clang). Para el desarrollo, el clang suele ser más conveniente de usar. Puede construir en su propia máquina con el modo de depuración (para ahorrar batería de su computadora portátil), pero tenga en cuenta que el compilador puede generar más advertencias con `-O3` debido a un mejor flujo de control y análisis entre procedimientos. Al construir con clang con el modo de depuración, la versión de depuración de `libc++` se utiliza que permite detectar más errores en tiempo de ejecución.
|
||||
|
||||
## Desinfectantes {#sanitizers}
|
||||
|
||||
**Dirección desinfectante**.
|
||||
Ejecutamos pruebas funcionales y de integración bajo ASan por compromiso.
|
||||
|
||||
**Valgrind (Memcheck)**.
|
||||
Realizamos pruebas funcionales bajo Valgrind durante la noche. Se tarda varias horas. Actualmente hay un falso positivo conocido en `re2` biblioteca, ver [este artículo](https://research.swtch.com/sparse).
|
||||
|
||||
**Desinfectante de comportamiento indefinido.**
|
||||
Ejecutamos pruebas funcionales y de integración bajo ASan por compromiso.
|
||||
|
||||
**Desinfectante de hilo**.
|
||||
Ejecutamos pruebas funcionales bajo TSan por compromiso. Todavía no ejecutamos pruebas de integración bajo TSan por compromiso.
|
||||
|
||||
**Desinfectante de memoria**.
|
||||
Actualmente todavía no usamos MSan.
|
||||
|
||||
**Asignador de depuración.**
|
||||
Versión de depuración de `jemalloc` se utiliza para la compilación de depuración.
|
||||
|
||||
## Fuzzing {#fuzzing}
|
||||
|
||||
ClickHouse fuzzing se implementa tanto usando [LibFuzzer](https://llvm.org/docs/LibFuzzer.html) y consultas SQL aleatorias.
|
||||
Todas las pruebas de fuzz deben realizarse con desinfectantes (Dirección y Undefined).
|
||||
|
||||
LibFuzzer se usa para pruebas de fuzz aisladas del código de la biblioteca. Fuzzers se implementan como parte del código de prueba y tienen “_fuzzer” nombre postfixes.
|
||||
El ejemplo de Fuzzer se puede encontrar en `src/Parsers/tests/lexer_fuzzer.cpp`. Las configuraciones, diccionarios y corpus específicos de LibFuzzer se almacenan en `tests/fuzz`.
|
||||
Le recomendamos que escriba pruebas fuzz para cada funcionalidad que maneje la entrada del usuario.
|
||||
|
||||
Fuzzers no se construyen de forma predeterminada. Para construir fuzzers ambos `-DENABLE_FUZZING=1` y `-DENABLE_TESTS=1` se deben establecer opciones.
|
||||
Recomendamos deshabilitar Jemalloc mientras se construyen fuzzers. Configuración utilizada para integrar
|
||||
Google OSS-Fuzz se puede encontrar en `docker/fuzz`.
|
||||
|
||||
También usamos una prueba de fuzz simple para generar consultas SQL aleatorias y verificar que el servidor no muera al ejecutarlas.
|
||||
Lo puedes encontrar en `00746_sql_fuzzy.pl`. Esta prueba debe ejecutarse de forma continua (de la noche a la mañana y más).
|
||||
|
||||
## Auditoría de seguridad {#security-audit}
|
||||
|
||||
La gente de Yandex Security Team hace una visión general básica de las capacidades de ClickHouse desde el punto de vista de la seguridad.
|
||||
|
||||
## Analizadores estáticos {#static-analyzers}
|
||||
|
||||
Corremos `PVS-Studio` por compromiso. Hemos evaluado `clang-tidy`, `Coverity`, `cppcheck`, `PVS-Studio`, `tscancode`. Encontrará instrucciones de uso en `tests/instructions/` directorio. También puedes leer [el artículo en ruso](https://habr.com/company/yandex/blog/342018/).
|
||||
|
||||
Si usted usa `CLion` como IDE, puede aprovechar algunos `clang-tidy` comprueba fuera de la caja.
|
||||
|
||||
## Endurecer {#hardening}
|
||||
|
||||
`FORTIFY_SOURCE` se utiliza de forma predeterminada. Es casi inútil, pero todavía tiene sentido en casos raros y no lo desactivamos.
|
||||
|
||||
## Estilo de código {#code-style}
|
||||
|
||||
Se describen las reglas de estilo de código [aqui](https://clickhouse.tech/docs/en/development/style/).
|
||||
|
||||
Para comprobar si hay algunas violaciones de estilo comunes, puede usar `utils/check-style` script.
|
||||
|
||||
Para forzar el estilo adecuado de su código, puede usar `clang-format`. File `.clang-format` se encuentra en la raíz de las fuentes. Se corresponde principalmente con nuestro estilo de código real. Pero no se recomienda aplicar `clang-format` a los archivos existentes porque empeora el formato. Usted puede utilizar `clang-format-diff` herramienta que puede encontrar en el repositorio de origen clang.
|
||||
|
||||
Alternativamente, puede intentar `uncrustify` herramienta para reformatear su código. La configuración está en `uncrustify.cfg` en la raíz de las fuentes. Es menos probado que `clang-format`.
|
||||
|
||||
`CLion` tiene su propio formateador de código que debe ajustarse para nuestro estilo de código.
|
||||
|
||||
## Pruebas Metrica B2B {#metrica-b2b-tests}
|
||||
|
||||
Cada lanzamiento de ClickHouse se prueba con los motores Yandex Metrica y AppMetrica. Las pruebas y las versiones estables de ClickHouse se implementan en máquinas virtuales y se ejecutan con una copia pequeña del motor Metrica que procesa una muestra fija de datos de entrada. A continuación, los resultados de dos instancias del motor Metrica se comparan juntos.
|
||||
|
||||
Estas pruebas son automatizadas por un equipo separado. Debido a la gran cantidad de piezas móviles, las pruebas fallan la mayor parte del tiempo por razones completamente no relacionadas, que son muy difíciles de descubrir. Lo más probable es que estas pruebas tengan un valor negativo para nosotros. Sin embargo, se demostró que estas pruebas son útiles en aproximadamente una o dos veces de cada cientos.
|
||||
|
||||
## Cobertura de prueba {#test-coverage}
|
||||
|
||||
A partir de julio de 2018, no realizamos un seguimiento de la cobertura de las pruebas.
|
||||
|
||||
## Automatización de pruebas {#test-automation}
|
||||
|
||||
Realizamos pruebas con el CI interno de Yandex y el sistema de automatización de trabajos llamado “Sandbox”.
|
||||
|
||||
Los trabajos de compilación y las pruebas se ejecutan en Sandbox por confirmación. Los paquetes resultantes y los resultados de las pruebas se publican en GitHub y se pueden descargar mediante enlaces directos. Los artefactos se almacenan eternamente. Cuando envías una solicitud de extracción en GitHub, la etiquetamos como “can be tested” y nuestro sistema CI construirá paquetes ClickHouse (liberación, depuración, con desinfectante de direcciones, etc.) para usted.
|
||||
|
||||
No usamos Travis CI debido al límite de tiempo y potencia computacional.
|
||||
No usamos Jenkins. Se usó antes y ahora estamos felices de no estar usando Jenkins.
|
||||
|
||||
[Artículo Original](https://clickhouse.tech/docs/en/development/tests/) <!--hide-->
|
||||
1
docs/es/development/tests.md
Symbolic link
1
docs/es/development/tests.md
Symbolic link
@ -0,0 +1 @@
|
||||
../../en/development/tests.md
|
||||
@ -20,7 +20,7 @@ $ sudo apt-get install git cmake python ninja-build
|
||||
|
||||
یا سیمک 3 به جای کیک در سیستم های قدیمی تر.
|
||||
|
||||
## نصب شورای همکاری خلیج فارس 9 {#install-gcc-9}
|
||||
## نصب شورای همکاری خلیج فارس 9 {#install-gcc-10}
|
||||
|
||||
راه های مختلفی برای انجام این کار وجود دارد.
|
||||
|
||||
@ -30,18 +30,18 @@ $ sudo apt-get install git cmake python ninja-build
|
||||
$ sudo apt-get install software-properties-common
|
||||
$ sudo apt-add-repository ppa:ubuntu-toolchain-r/test
|
||||
$ sudo apt-get update
|
||||
$ sudo apt-get install gcc-9 g++-9
|
||||
$ sudo apt-get install gcc-10 g++-10
|
||||
```
|
||||
|
||||
### نصب از منابع {#install-from-sources}
|
||||
|
||||
نگاه کن [utils/ci/build-gcc-from-sources.sh](https://github.com/ClickHouse/ClickHouse/blob/master/utils/ci/build-gcc-from-sources.sh)
|
||||
|
||||
## استفاده از شورای همکاری خلیج فارس 9 برای ساخت {#use-gcc-9-for-builds}
|
||||
## استفاده از شورای همکاری خلیج فارس 10 برای ساخت {#use-gcc-10-for-builds}
|
||||
|
||||
``` bash
|
||||
$ export CC=gcc-9
|
||||
$ export CXX=g++-9
|
||||
$ export CC=gcc-10
|
||||
$ export CXX=g++-10
|
||||
```
|
||||
|
||||
## پرداخت منابع کلیک {#checkout-clickhouse-sources}
|
||||
@ -77,7 +77,7 @@ $ cd ..
|
||||
- دستگاه گوارش (استفاده می شود تنها به پرداخت منابع مورد نیاز برای ساخت)
|
||||
- کیک 3.10 یا جدیدتر
|
||||
- نینجا (توصیه می شود) و یا
|
||||
- ج ++ کامپایلر: شورای همکاری خلیج فارس 9 یا صدای شیپور 8 یا جدیدتر
|
||||
- ج ++ کامپایلر: شورای همکاری خلیج فارس 10 یا صدای شیپور 8 یا جدیدتر
|
||||
- لینکر: لیلند یا طلا (کلاسیک گنو الدی کار نخواهد کرد)
|
||||
- پایتون (فقط در داخل ساخت لورم استفاده می شود و اختیاری است)
|
||||
|
||||
|
||||
@ -137,13 +137,13 @@ toc_title: "\u062F\u0633\u062A\u0648\u0631\u0627\u0644\u0639\u0645\u0644 \u062A\
|
||||
|
||||
# ج ++ کامپایلر {#c-compiler}
|
||||
|
||||
کامپایلر شورای همکاری خلیج فارس با شروع از نسخه 9 و صدای شیپور نسخه 8 یا بالاتر برای ساخت و ساز خانه عروسکی پشتیبانی می کند.
|
||||
کامپایلر شورای همکاری خلیج فارس با شروع از نسخه 10 و صدای شیپور نسخه 8 یا بالاتر برای ساخت و ساز خانه عروسکی پشتیبانی می کند.
|
||||
|
||||
یاندکس رسمی ایجاد شده در حال حاضر با استفاده از شورای همکاری خلیج فارس به دلیل تولید کد ماشین از عملکرد کمی بهتر (بازده تفاوت تا چند درصد با توجه به معیار ما). و کلانگ معمولا برای توسعه راحت تر است. هر چند, ادغام مداوم ما (سی) پلت فرم اجرا می شود چک برای حدود یک دوجین از ترکیب ساخت.
|
||||
|
||||
برای نصب شورای همکاری خلیج فارس در اوبونتو اجرای: `sudo apt install gcc g++`
|
||||
|
||||
بررسی نسخه شورای همکاری خلیج فارس: `gcc --version`. اگر زیر است 9, سپس دستورالعمل اینجا را دنبال کنید: https://clickhouse.tech/docs/fa/development/build/#install-gcc-9.
|
||||
بررسی نسخه شورای همکاری خلیج فارس: `gcc --version`. اگر زیر است 10, سپس دستورالعمل اینجا را دنبال کنید: https://clickhouse.tech/docs/fa/development/build/#install-gcc-10.
|
||||
|
||||
سیستم عامل مک ایکس ساخت فقط برای صدای جرنگ جرنگ پشتیبانی می شود. فقط فرار کن `brew install llvm`
|
||||
|
||||
@ -158,11 +158,11 @@ toc_title: "\u062F\u0633\u062A\u0648\u0631\u0627\u0644\u0639\u0645\u0644 \u062A\
|
||||
|
||||
شما می توانید چندین دایرکتوری های مختلف (build_release, build_debug ، ) برای انواع مختلف ساخت.
|
||||
|
||||
در حالی که در داخل `build` فهرست, پیکربندی ساخت خود را با در حال اجرا کیک. قبل از اولین اجرا, شما نیاز به تعریف متغیرهای محیطی که کامپایلر را مشخص (نسخه 9 کامپایلر شورای همکاری خلیج فارس در این مثال).
|
||||
در حالی که در داخل `build` فهرست, پیکربندی ساخت خود را با در حال اجرا کیک. قبل از اولین اجرا, شما نیاز به تعریف متغیرهای محیطی که کامپایلر را مشخص (نسخه 10 کامپایلر شورای همکاری خلیج فارس در این مثال).
|
||||
|
||||
لینوکس:
|
||||
|
||||
export CC=gcc-9 CXX=g++-9
|
||||
export CC=gcc-10 CXX=g++-10
|
||||
cmake ..
|
||||
|
||||
سیستم عامل مک ایکس:
|
||||
|
||||
@ -1,262 +0,0 @@
|
||||
---
|
||||
machine_translated: true
|
||||
machine_translated_rev: 72537a2d527c63c07aa5d2361a8829f3895cf2bd
|
||||
toc_priority: 69
|
||||
toc_title: "\u0646\u062D\u0648\u0647 \u0627\u062C\u0631\u0627\u06CC \u062A\u0633\u062A\
|
||||
\ \u0647\u0627\u06CC \u06A9\u0644\u06CC\u06A9 \u062E\u0627\u0646\u0647"
|
||||
---
|
||||
|
||||
# تست کلیک {#clickhouse-testing}
|
||||
|
||||
## تست های کاربردی {#functional-tests}
|
||||
|
||||
تست های کاربردی ساده ترین و راحت برای استفاده هستند. بسیاری از ClickHouse ویژگی ها را می توان مورد آزمایش با استفاده از آزمون های عملکردی و آنها را اجباری به استفاده از برای هر تغییر در ClickHouse کد است که می تواند آزمایش می شود که در راه است.
|
||||
|
||||
هر تست عملکردی یک یا چند نمایش داده شد به سرور در حال اجرا تاتر می فرستد و نتیجه را با مرجع مقایسه می کند.
|
||||
|
||||
تست ها در واقع `queries` فهرست راهنما. دو زیرشاخه وجود دارد: `stateless` و `stateful`. تست های بدون تابعیت بدون هیچ گونه داده های تست پیش بارگذاری شده نمایش داده می شوند-اغلب مجموعه داده های مصنوعی کوچک را در پرواز در داخل تست خود ایجاد می کنند. تست های نفرت انگیز نیاز به داده های تست از قبل نصب شده از یاندکس.متریکا و در دسترس عموم نیست. ما تمایل به استفاده از تنها `stateless` تست ها و جلوگیری از اضافه کردن جدید `stateful` تستها
|
||||
|
||||
هر تست می تواند یکی از دو نوع باشد: `.sql` و `.sh`. `.sql` تست اسکریپت ساده مربع است که به لوله کشی است `clickhouse-client --multiquery --testmode`. `.sh` تست یک اسکریپت است که به خودی خود اجرا است.
|
||||
|
||||
برای اجرای تمام تست ها استفاده کنید `clickhouse-test` ابزار. نگاه کن `--help` برای لیستی از گزینه های ممکن. شما به سادگی می توانید تمام تست ها را اجرا کنید یا زیر مجموعه ای از تست های فیلتر شده توسط زیر رشته را در نام تست اجرا کنید: `./clickhouse-test substring`.
|
||||
|
||||
ساده ترین راه برای فراخوانی تست های کاربردی کپی است `clickhouse-client` به `/usr/bin/` فرار کن `clickhouse-server` و سپس اجرا کنید `./clickhouse-test` از دایرکتوری خود را.
|
||||
|
||||
برای اضافه کردن تست جدید, ایجاد یک `.sql` یا `.sh` پرونده در `queries/0_stateless` فهرست راهنما را به صورت دستی بررسی کنید و سپس تولید کنید `.reference` پرونده به روش زیر: `clickhouse-client -n --testmode < 00000_test.sql > 00000_test.reference` یا `./00000_test.sh > ./00000_test.reference`.
|
||||
|
||||
تست باید استفاده کنید (ساختن, قطره, و غیره) تنها جداول در `test` پایگاه داده است که فرض بر این است که از قبل ایجاد می شود; همچنین تست می توانید جداول موقت استفاده.
|
||||
|
||||
اگر شما می خواهید به استفاده از نمایش داده شد توزیع شده در تست های کاربردی, شما می توانید اهرم `remote` تابع جدول با `127.0.0.{1..2}` یا شما می توانید خوشه تست از پیش تعریف شده در فایل پیکربندی سرور مانند استفاده کنید `test_shard_localhost`.
|
||||
|
||||
برخی از تست ها با مشخص شده اند `zookeeper`, `shard` یا `long` در نام خود.
|
||||
`zookeeper` برای تست هایی است که از باغ وحش استفاده می کنند. `shard` برای تست هایی است که
|
||||
نیاز به سرور برای گوش دادن `127.0.0.*`; `distributed` یا `global` همان
|
||||
معنی. `long` برای تست هایی است که کمی طولانی تر اجرا می شوند که یک ثانیه. شما می توانید
|
||||
غیر فعال کردن این گروه از تست با استفاده از `--no-zookeeper`, `--no-shard` و
|
||||
`--no-long` گزینه, به ترتیب.
|
||||
|
||||
## اشکالات شناخته شده {#known-bugs}
|
||||
|
||||
اگر ما می دانیم برخی از اشکالات است که می تواند به راحتی توسط تست های کاربردی تکثیر, ما تست های عملکردی تهیه شده در `tests/queries/bugs` فهرست راهنما. این تست خواهد شد به نقل مکان کرد `tests/queries/0_stateless` هنگامی که اشکالات ثابت هستند.
|
||||
|
||||
## تست های ادغام {#integration-tests}
|
||||
|
||||
ادغام آزمون اجازه می دهد برای تست ClickHouse در خوشه پیکربندی و ClickHouse تعامل با سرور های دیگر مانند MySQL, Postgres, MongoDB. مفید برای تقلید انشعابات شبکه قطره بسته و غیره هستند. این تست ها تحت کارگر بارانداز اجرا و ایجاد ظروف متعدد با نرم افزار های مختلف.
|
||||
|
||||
ببینید `tests/integration/README.md` در مورد چگونگی اجرای این تست.
|
||||
|
||||
توجه داشته باشید که ادغام کلیک با رانندگان شخص ثالث تست نشده است. همچنین ما در حال حاضر تست های یکپارچه سازی با رانندگان جی بی سی و بی سی ما ندارد.
|
||||
|
||||
## تست های واحد {#unit-tests}
|
||||
|
||||
تست واحد مفید هستند که شما می خواهید برای تست نیست خانه کلیک به عنوان یک کل, اما یک کتابخانه جدا شده و یا کلاس. شما می توانید ساخت تست ها را فعال یا غیر فعال کنید `ENABLE_TESTS` گزینه کیک. تست واحد (و دیگر برنامه های تست) در واقع `tests` زیرشاخه در سراسر کد. برای اجرای تست واحد, نوع `ninja test`. برخی از تست ها استفاده می کنند `gtest`, اما برخی فقط برنامه هایی که بازگشت کد خروج غیر صفر در شکست تست.
|
||||
|
||||
این لزوما به تست واحد اگر کد در حال حاضر توسط تست های کاربردی تحت پوشش (و تست های کاربردی معمولا بسیار ساده تر برای استفاده).
|
||||
|
||||
## تست های عملکرد {#performance-tests}
|
||||
|
||||
تست های عملکرد اجازه می دهد برای اندازه گیری و مقایسه عملکرد برخی از بخش جدا شده از خانه رعیتی در نمایش داده شد مصنوعی. تست ها در واقع `tests/performance`. هر تست توسط نمایندگی `.xml` فایل با شرح مورد تست. تست ها با اجرا `clickhouse performance-test` ابزار (که در تعبیه شده است `clickhouse` دودویی). ببینید `--help` برای نیایش.
|
||||
|
||||
هر تست یک یا چند نمایش داده شد (احتمالا با ترکیبی از پارامترهای) در یک حلقه با برخی از شرایط برای توقف (مانند “maximum execution speed is not changing in three seconds”) و اندازه گیری برخی از معیارهای مورد عملکرد پرس و جو (مانند “maximum execution speed”). برخی از تست ها می توانند پیش شرط ها را در مجموعه داده های تست پیش بارگذاری شده داشته باشند.
|
||||
|
||||
اگر شما می خواهید برای بهبود عملکرد تاتر در برخی از سناریو, و اگر پیشرفت را می توان در نمایش داده شد ساده مشاهده, بسیار توصیه می شود برای نوشتن یک تست عملکرد. همیشه حس می کند به استفاده از `perf top` و یا دیگر ابزار دقیق در طول تست های خود را.
|
||||
|
||||
## ابزار تست و اسکریپت {#test-tools-and-scripts}
|
||||
|
||||
برخی از برنامه ها در `tests` دایرکتوری تست تهیه نشده, اما ابزار تست. مثلا, برای `Lexer` یک ابزار وجود دارد `src/Parsers/tests/lexer` این فقط تقلید از استدین را انجام می دهد و نتیجه رنگی را به انحراف می نویسد. شما می توانید از این نوع ابزار به عنوان نمونه کد و برای اکتشاف و تست دستی استفاده کنید.
|
||||
|
||||
شما همچنین می توانید جفت فایل قرار دهید `.sh` و `.reference` همراه با ابزار برای اجرا در برخی از ورودی از پیش تعریف شده - سپس نتیجه اسکریپت را می توان به مقایسه `.reference` پرونده. این نوع تست ها خودکار نیستند.
|
||||
|
||||
## تست های متفرقه {#miscellaneous-tests}
|
||||
|
||||
تست برای لغت نامه های خارجی واقع در وجود دارد `tests/external_dictionaries` و برای مدل های ماشین یاد گرفته شده در `tests/external_models`. این تست ها به روز نمی شوند و باید به تست های ادغام منتقل شوند.
|
||||
|
||||
تست جداگانه برای درج حد نصاب وجود دارد. این اجرای آزمون ClickHouse خوشه در سرورهای جداگانه و شبیه سازی شکست های مختلف در موارد: شبکه تقسیم بسته رها کردن (بین ClickHouse گره بین ClickHouse و باغ وحش بین ClickHouse سرور و کلاینت ، ), `kill -9`, `kill -STOP` و `kill -CONT` مثل [جپسن](https://aphyr.com/tags/Jepsen). سپس چک تست که همه درج اذعان نوشته شده بود و همه درج رد شد.
|
||||
|
||||
تست حد نصاب توسط تیم جداگانه نوشته شده بود قبل از کلیک باز منابع بود. این تیم دیگر با کلیکهاوس کار. تست به طور تصادفی در جاوا نوشته شده بود. به این دلایل, تست حد نصاب باید بازنویسی شود و به تست ادغام نقل مکان کرد.
|
||||
|
||||
## تست دستی {#manual-testing}
|
||||
|
||||
هنگامی که شما توسعه یک ویژگی جدید معقول نیز دستی تست است. شما می توانید این کار را با مراحل زیر انجام دهید:
|
||||
|
||||
ساخت خانه کلیک. اجرای کلیک از ترمینال: تغییر دایرکتوری به `programs/clickhouse-server` و با `./clickhouse-server`. این پیکربندی استفاده کنید (`config.xml`, `users.xml` و فایل ها در `config.d` و `users.d` دایرکتوری ها) از دایرکتوری جاری به طور پیش فرض. برای اتصال به سرور کلیک اجرا کنید `programs/clickhouse-client/clickhouse-client`.
|
||||
|
||||
توجه داشته باشید که تمام clickhouse ابزار (سرور مشتری و غیره) فقط symlinks به یک باینری به نام `clickhouse`. شما می توانید این دودویی در `programs/clickhouse`. همه ابزار همچنین می توانید به عنوان استناد شود `clickhouse tool` به جای `clickhouse-tool`.
|
||||
|
||||
متناوبا شما می توانید بسته بندی کلیک را نصب کنید: در هر صورت انتشار پایدار از مخزن یاندکس و یا شما می توانید بسته را برای خودتان با ساخت `./release` در منابع کلیک خانه ریشه. سپس سرور را با شروع `sudo service clickhouse-server start` (یا توقف برای متوقف کردن سرور). به دنبال سیاهههای مربوط در `/etc/clickhouse-server/clickhouse-server.log`.
|
||||
|
||||
هنگامی که تاتر در حال حاضر بر روی سیستم شما نصب شده, شما می توانید جدید ساخت `clickhouse` دودویی و جایگزین باینری موجود:
|
||||
|
||||
``` bash
|
||||
$ sudo service clickhouse-server stop
|
||||
$ sudo cp ./clickhouse /usr/bin/
|
||||
$ sudo service clickhouse-server start
|
||||
```
|
||||
|
||||
همچنین شما می توانید سیستم کلیک سرور را متوقف و اجرا خود را با همان پیکربندی اما با ورود به ترمینال:
|
||||
|
||||
``` bash
|
||||
$ sudo service clickhouse-server stop
|
||||
$ sudo -u clickhouse /usr/bin/clickhouse server --config-file /etc/clickhouse-server/config.xml
|
||||
```
|
||||
|
||||
به عنوان مثال با دیابت بارداری:
|
||||
|
||||
``` bash
|
||||
$ sudo -u clickhouse gdb --args /usr/bin/clickhouse server --config-file /etc/clickhouse-server/config.xml
|
||||
```
|
||||
|
||||
اگر سیستم کلیک-سرور در حال اجرا است و شما نمی خواهید برای متوقف کردن, شما می توانید شماره پورت در خود تغییر دهید `config.xml` (یا نادیده گرفتن در یک فایل در `config.d` فهرست راهنما) مسیر داده مناسب را فراهم کرده و اجرا کنید.
|
||||
|
||||
`clickhouse` دودویی تقریبا هیچ وابستگی و کار در سراسر طیف گسترده ای از توزیع های لینوکس. برای تست سریع و کثیف تغییرات خود را بر روی یک سرور, شما به سادگی می توانید `scp` تازه ساخته شده است `clickhouse` باینری به سرور شما و سپس به عنوان مثال بالا اجرا شود.
|
||||
|
||||
## محیط تست {#testing-environment}
|
||||
|
||||
قبل از انتشار انتشار به عنوان پایدار ما را در محیط تست استقرار. محیط تست یک خوشه است که بخشی از 1/39 را پردازش می کند [یاندکسمتریکا](https://metrica.yandex.com/) داده ها. ما محیط تست خود را با یاندکس به اشتراک می گذاریم.تیم متریکا تاتر بدون خرابی در بالای داده های موجود به روز رسانی. ما در ابتدا نگاه کنید که داده ها با موفقیت و بدون عقب مانده از زمان واقعی پردازش, تکرار ادامه کار و هیچ مشکلی برای یاندکس قابل مشاهده وجود دارد.تیم متریکا اولین چک را می توان در راه زیر انجام داد:
|
||||
|
||||
``` sql
|
||||
SELECT hostName() AS h, any(version()), any(uptime()), max(UTCEventTime), count() FROM remote('example01-01-{1..3}t', merge, hits) WHERE EventDate >= today() - 2 GROUP BY h ORDER BY h;
|
||||
```
|
||||
|
||||
در برخی موارد ما نیز به تست محیط زیست از تیم های دوست ما در یاندکس استقرار: بازار, ابر, و غیره. همچنین در حال حاضر برخی از سرورهای سخت افزاری است که برای اهداف توسعه استفاده می شود.
|
||||
|
||||
## تست بار {#load-testing}
|
||||
|
||||
پس از استقرار به محیط تست ما تست بار با نمایش داده شد از خوشه تولید را اجرا کنید. این کار به صورت دستی انجام می شود.
|
||||
|
||||
اطمینان حاصل کنید که شما را فعال کرده اند `query_log` در خوشه تولید خود را.
|
||||
|
||||
جمع کردن گزارش پرس و جو برای یک روز یا بیشتر:
|
||||
|
||||
``` bash
|
||||
$ clickhouse-client --query="SELECT DISTINCT query FROM system.query_log WHERE event_date = today() AND query LIKE '%ym:%' AND query NOT LIKE '%system.query_log%' AND type = 2 AND is_initial_query" > queries.tsv
|
||||
```
|
||||
|
||||
این یک مثال راه پیچیده است. `type = 2` نمایش داده شد که با موفقیت اجرا فیلتر کنید. `query LIKE '%ym:%'` است برای انتخاب نمایش داده شد مربوطه از یاندکس.متریکا `is_initial_query` است را انتخاب کنید تنها نمایش داده شد که توسط مشتری شروع, نه با کلیک خود (به عنوان بخش هایی از پردازش پرس و جو توزیع).
|
||||
|
||||
`scp` این ورود به خوشه تست خود را و اجرا به شرح زیر است:
|
||||
|
||||
``` bash
|
||||
$ clickhouse benchmark --concurrency 16 < queries.tsv
|
||||
```
|
||||
|
||||
(احتمالا شما همچنین می خواهید برای مشخص کردن یک `--user`)
|
||||
|
||||
پس یه شب یا هفته ولش کن و برو استراحت کن
|
||||
|
||||
شما باید بررسی کنید که `clickhouse-server` سقوط نمی کند, رد پای حافظه محدود است و عملکرد در طول زمان تنزل نمی.
|
||||
|
||||
زمان اجرای پرس و جو دقیق ثبت نشده است و با توجه به تنوع بالا از نمایش داده شد و محیط زیست در مقایسه نیست.
|
||||
|
||||
## ساخت تست {#build-tests}
|
||||
|
||||
تست های ساخت اجازه می دهد تا بررسی کنید که ساخت در تنظیمات مختلف جایگزین و در برخی از سیستم های خارجی شکسته نمی شود. تست ها در واقع `ci` فهرست راهنما. ساخت از منبع داخل کارگر بارانداز ولگرد و گاهی با اجرا می شوند `qemu-user-static` در داخل کارگر بارانداز. این تست ها در حال توسعه هستند و تست اجرا می شود خودکار نیست.
|
||||
|
||||
انگیزه:
|
||||
|
||||
به طور معمول ما انتشار و اجرای تمام تست بر روی یک نوع واحد از ساخت تاتر. اما انواع ساخت جایگزین است که به طور کامل تست شده وجود دارد. مثالها:
|
||||
|
||||
- ساخت در بورس;
|
||||
- ساخت در دبیان با کتابخانه ها از بسته های سیستم;
|
||||
- ساخت با لینک مشترک از کتابخانه ها;
|
||||
- ساخت پلت فرم AArch64;
|
||||
- ساخت بر روی پلت فرم پاور.
|
||||
|
||||
مثلا, ساخت با بسته های سیستم عمل بد است, چرا که ما نمی تواند تضمین کند که چه نسخه دقیق از بسته های یک سیستم باید. اما این واقعا توسط نگهداری دبیان مورد نیاز است. به همین دلیل ما حداقل باید برای حمایت از این نوع ساخت. مثال دیگر: ارتباط مشترک یک منبع مشترک از مشکل است, اما برای برخی از علاقه مندان مورد نیاز است.
|
||||
|
||||
هر چند ما می توانیم تمام تست در همه نوع از ایجاد اجرا کنید, ما می خواهیم برای بررسی حداقل که انواع ساخت های مختلف شکسته نمی. برای این منظور ما از تست های ساخت استفاده می کنیم.
|
||||
|
||||
## تست برای سازگاری پروتکل {#testing-for-protocol-compatibility}
|
||||
|
||||
هنگامی که ما گسترش ClickHouse پروتکل شبکه ما تست دستی که clickhouse-مشتری با این نسخهها کار جدید clickhouse-سرور و جدید clickhouse-مشتری با این نسخهها کار با clickhouse-سرور (به سادگی با در حال اجرا فایل های باینری از مربوطه بسته).
|
||||
|
||||
## کمک از کامپایلر {#help-from-the-compiler}
|
||||
|
||||
کد اصلی کلیک (که در واقع `dbms` فهرست راهنما) با ساخته شده است `-Wall -Wextra -Werror` و با برخی از هشدارهای اضافی را فعال کنید. اگر چه این گزینه ها برای کتابخانه های شخص ثالث فعال نیست.
|
||||
|
||||
کلانگ هشدارهای بیشتری دارد - شما می توانید با `-Weverything` و انتخاب چیزی به طور پیش فرض ساخت.
|
||||
|
||||
برای تولید ساخت, شورای همکاری خلیج فارس استفاده می شود (هنوز تولید کد کمی موثر تر از صدای جرنگ جرنگ). برای توسعه, صدای جرنگ جرنگ است که معمولا راحت تر به استفاده از. شما می توانید بر روی دستگاه خود را با حالت اشکال زدایی ساخت (برای صرفه جویی در باتری لپ تاپ خود را), اما لطفا توجه داشته باشید که کامپایلر قادر به تولید هشدارهای بیشتر با است `-O3` با توجه به جریان کنترل بهتر و تجزیه و تحلیل بین روش. هنگام ساخت با صدای جرنگ جرنگ, `libc++` به جای استفاده `libstdc++` و هنگامی که ساختمان با حالت اشکال زدایی, نسخه اشکال زدایی از `libc++` استفاده شده است که اجازه می دهد تا برای گرفتن خطاهای بیشتر در زمان اجرا.
|
||||
|
||||
## Sanitizers {#sanitizers}
|
||||
|
||||
**نشانی ضد عفونی کننده**.
|
||||
ما تست های کاربردی و یکپارچه سازی را تحت عنوان بر اساس هر متعهد اجرا می کنیم.
|
||||
|
||||
**Valgrind (Memcheck)**.
|
||||
ما یک شبه تست های کاربردی را تحت ارزیابی قرار می دهیم. چند ساعت طول می کشد. در حال حاضر یک مثبت کاذب شناخته شده در وجود دارد `re2` کتابخانه را ببینید [این مقاله](https://research.swtch.com/sparse).
|
||||
|
||||
**تعریف نشده رفتار ضد عفونی کننده.**
|
||||
ما تست های کاربردی و یکپارچه سازی را تحت عنوان بر اساس هر متعهد اجرا می کنیم.
|
||||
|
||||
**ضدعفونی کننده موضوع**.
|
||||
ما تست های کاربردی تحت تسان بر اساس هر مرتکب اجرا. ما هنوز تست های ادغام تحت تسان بر اساس هر متعهد اجرا کنید.
|
||||
|
||||
**ضد عفونی کننده حافظه**.
|
||||
در حال حاضر ما هنوز از خانم استفاده نمی کنیم.
|
||||
|
||||
**اشکال زدایی تخصیص.**
|
||||
نسخه اشکال زدایی از `jemalloc` برای ساخت اشکال زدایی استفاده می شود.
|
||||
|
||||
## Fuzzing {#fuzzing}
|
||||
|
||||
ریش ریش شدن کلیک هر دو با استفاده از اجرا شده است [هرزه](https://llvm.org/docs/LibFuzzer.html) و تصادفی گذاشتن نمایش داده شد.
|
||||
تمام تست ریش شدن باید با ضدعفونی کننده انجام شود (نشانی و تعریف نشده).
|
||||
|
||||
پازل برای تست ریش ریش شدن جدا شده از کد کتابخانه استفاده می شود. طبع به عنوان بخشی از کد تست اجرا و “_fuzzer” نام پسوند.
|
||||
به عنوان مثال ریش ریش شدن را می توان در یافت `src/Parsers/tests/lexer_fuzzer.cpp`. تنظیمات-پازل خاص, لغت نامه ها و جسم در ذخیره می شود `tests/fuzz`.
|
||||
ما شما را تشویق به نوشتن تست ریش ریش شدن برای هر قابلیت که دسته ورودی کاربر.
|
||||
|
||||
طبع به طور پیش فرض ساخته شده است. برای ساخت ریش ریش ریش ریش شدن هر دو `-DENABLE_FUZZING=1` و `-DENABLE_TESTS=1` گزینه ها باید تنظیم شود.
|
||||
ما توصیه می کنیم برای غیر فعال کردن Jemalloc در حالی که ساختمان fuzzers. پیکربندی مورد استفاده برای ادغام ریش ریش شدن تاتر به
|
||||
گوگل اوس فوز را می توان در یافت `docker/fuzz`.
|
||||
|
||||
ما همچنین از تست ریش ریش شدن ساده برای تولید پرس و جو تصادفی ساده استفاده می کنیم و بررسی می کنیم که سرور نمی میرد.
|
||||
شما می توانید این را در `00746_sql_fuzzy.pl`. این تست باید به طور مداوم اجرا شود (یک شبه و طولانی تر).
|
||||
|
||||
## ممیزی امنیتی {#security-audit}
|
||||
|
||||
مردم از تیم امنیتی یاندکس انجام برخی از بررسی اجمالی اساسی از قابلیت های تاتر از نقطه نظر امنیت.
|
||||
|
||||
## تجزیه و تحلیل استاتیک {#static-analyzers}
|
||||
|
||||
فرار میکنیم `PVS-Studio` بر اساس هر مرتکب. ما ارزیابی کرده ایم `clang-tidy`, `Coverity`, `cppcheck`, `PVS-Studio`, `tscancode`. شما دستورالعمل برای استفاده در پیدا `tests/instructions/` فهرست راهنما. همچنین شما می توانید به عنوان خوانده شده [مقاله در روسیه](https://habr.com/company/yandex/blog/342018/).
|
||||
|
||||
در صورت استفاده `CLion` به عنوان محیط برنامه نویسی, شما می توانید اهرم برخی از `clang-tidy` چک از جعبه.
|
||||
|
||||
## سخت شدن {#hardening}
|
||||
|
||||
`FORTIFY_SOURCE` به طور پیش فرض استفاده می شود. این تقریبا بی فایده است, اما هنوز هم حس می کند در موارد نادر و ما این کار را غیر فعال کنید.
|
||||
|
||||
## سبک کد {#code-style}
|
||||
|
||||
قوانین سبک کد شرح داده شده است [اینجا](https://clickhouse.tech/docs/en/development/style/).
|
||||
|
||||
برای بررسی برخی از نقض سبک مشترک, شما می توانید استفاده کنید `utils/check-style` خط نوشتن.
|
||||
|
||||
به زور سبک مناسب از کد خود را, شما می توانید استفاده کنید `clang-format`. پرونده `.clang-format` در منابع ریشه واقع شده است. این بیشتر با سبک کد واقعی ما مطابقت دارد. اما توصیه نمی شود که اعمال شود `clang-format` به فایل های موجود چون باعث می شود قالب بندی بدتر است. شما می توانید استفاده کنید `clang-format-diff` ابزاری است که شما می توانید در مخزن منبع صدای جرنگ جرنگ پیدا.
|
||||
|
||||
متناوبا شما می توانید سعی کنید `uncrustify` ابزار مجدد کد خود را. پیکربندی در `uncrustify.cfg` در منابع ریشه. این کمتر از تست شده است `clang-format`.
|
||||
|
||||
`CLion` فرمت کد خود را دارد که باید برای سبک کد ما تنظیم شود.
|
||||
|
||||
## تست های متریکا ب2 {#metrica-b2b-tests}
|
||||
|
||||
هر ClickHouse نسخه تست شده با Yandex Metrica و AppMetrica موتورهای. تست و نسخه های پایدار از تاتر در ماشین های مجازی مستقر و اجرا با یک کپی کوچک از موتور متریکا است که پردازش نمونه ثابت از داده های ورودی. سپس نتایج حاصل از دو نمونه از موتور متریکا با هم مقایسه می شوند.
|
||||
|
||||
این تست ها توسط تیم جداگانه خودکار می شوند. با توجه به تعداد زیادی از قطعات متحرک, تست شکست بیشتر از زمان به دلایل کاملا نامربوط, که بسیار دشوار است برای کشف کردن. به احتمال زیاد این تست ها ارزش منفی برای ما دارند. با این وجود این تست در حدود یک یا دو بار از صدها مفید ثابت شد.
|
||||
|
||||
## پوشش تست {#test-coverage}
|
||||
|
||||
تا جولای 2018 ما پوشش تست را پیگیری نمی کنیم.
|
||||
|
||||
## اتوماسیون تست {#test-automation}
|
||||
|
||||
ما تست ها را با سیستم اتوماسیون داخلی یاندکس اجرا می کنیم “Sandbox”.
|
||||
|
||||
ساخت شغل و تست ها در گودال ماسهبازی در هر مرتکب اساس اجرا شود. نتیجه بسته ها و نتایج تست در گیتهاب منتشر شده و می تواند توسط لینک مستقیم دانلود. مصنوعات ابد ذخیره می شود. هنگامی که شما یک درخواست کشش ارسال در گیتهاب, ما برچسب به عنوان “can be tested” و سیستم سی ما خواهد بسته های تاتر ساخت (رهایی, اشکال زدایی, با نشانی ضد عفونی کننده, و غیره) برای شما.
|
||||
|
||||
ما از تراویس سی به دلیل محدودیت در زمان و قدرت محاسباتی استفاده نمی کنیم.
|
||||
ما از جنکینز استفاده نمیکنیم. این قبل از استفاده شد و در حال حاضر ما خوشحال ما با استفاده از جنکینز نیست.
|
||||
|
||||
[مقاله اصلی](https://clickhouse.tech/docs/en/development/tests/) <!--hide-->
|
||||
1
docs/fa/development/tests.md
Symbolic link
1
docs/fa/development/tests.md
Symbolic link
@ -0,0 +1 @@
|
||||
../../en/development/tests.md
|
||||
@ -19,7 +19,7 @@ $ sudo apt-get install git cmake python ninja-build
|
||||
|
||||
Ou cmake3 au lieu de cmake sur les systèmes plus anciens.
|
||||
|
||||
## Installer GCC 9 {#install-gcc-9}
|
||||
## Installer GCC 10 {#install-gcc-10}
|
||||
|
||||
Il y a plusieurs façons de le faire.
|
||||
|
||||
@ -29,18 +29,18 @@ Il y a plusieurs façons de le faire.
|
||||
$ sudo apt-get install software-properties-common
|
||||
$ sudo apt-add-repository ppa:ubuntu-toolchain-r/test
|
||||
$ sudo apt-get update
|
||||
$ sudo apt-get install gcc-9 g++-9
|
||||
$ sudo apt-get install gcc-10 g++-10
|
||||
```
|
||||
|
||||
### Installer à partir de Sources {#install-from-sources}
|
||||
|
||||
Regarder [utils/ci/build-gcc-from-sources.sh](https://github.com/ClickHouse/ClickHouse/blob/master/utils/ci/build-gcc-from-sources.sh)
|
||||
|
||||
## Utilisez GCC 9 pour les Builds {#use-gcc-9-for-builds}
|
||||
## Utilisez GCC 10 pour les Builds {#use-gcc-10-for-builds}
|
||||
|
||||
``` bash
|
||||
$ export CC=gcc-9
|
||||
$ export CXX=g++-9
|
||||
$ export CC=gcc-10
|
||||
$ export CXX=g++-10
|
||||
```
|
||||
|
||||
## Commander Clickhouse Sources {#checkout-clickhouse-sources}
|
||||
@ -76,7 +76,7 @@ La construction nécessite les composants suivants:
|
||||
- Git (est utilisé uniquement pour extraire les sources, ce n'est pas nécessaire pour la construction)
|
||||
- CMake 3.10 ou plus récent
|
||||
- Ninja (recommandé) ou faire
|
||||
- Compilateur C++: gcc 9 ou clang 8 ou plus récent
|
||||
- Compilateur C++: gcc 10 ou clang 8 ou plus récent
|
||||
- Linker: lld ou gold (le classique GNU LD ne fonctionnera pas)
|
||||
- Python (est seulement utilisé dans la construction LLVM et il est facultatif)
|
||||
|
||||
|
||||
@ -135,13 +135,13 @@ ClickHouse utilise plusieurs bibliothèques externes pour la construction. Tous
|
||||
|
||||
# Compilateur C++ {#c-compiler}
|
||||
|
||||
Les compilateurs GCC à partir de la version 9 et Clang version 8 ou supérieure sont pris en charge pour construire ClickHouse.
|
||||
Les compilateurs GCC à partir de la version 10 et Clang version 8 ou supérieure sont pris en charge pour construire ClickHouse.
|
||||
|
||||
Les builds officiels de Yandex utilisent actuellement GCC car ils génèrent du code machine de performances légèrement meilleures (ce qui donne une différence allant jusqu'à plusieurs pour cent selon nos benchmarks). Et Clang est plus pratique pour le développement habituellement. Cependant, notre plate-forme d'intégration continue (CI) vérifie environ une douzaine de combinaisons de construction.
|
||||
|
||||
Pour installer GCC sur Ubuntu Exécutez: `sudo apt install gcc g++`
|
||||
|
||||
Vérifiez la version de gcc: `gcc --version`. Si elle est inférieure à 9, suivez les instructions ici: https://clickhouse.tech/docs/fr/development/build/#install-gcc-9.
|
||||
Vérifiez la version de gcc: `gcc --version`. Si elle est inférieure à 10, suivez les instructions ici: https://clickhouse.tech/docs/fr/development/build/#install-gcc-10.
|
||||
|
||||
Mac OS X build est pris en charge uniquement pour Clang. Il suffit d'exécuter `brew install llvm`
|
||||
|
||||
@ -156,11 +156,11 @@ Maintenant que vous êtes prêt à construire ClickHouse nous vous conseillons d
|
||||
|
||||
Vous pouvez avoir plusieurs répertoires différents (build_release, build_debug, etc.) pour les différents types de construction.
|
||||
|
||||
Tandis qu'à l'intérieur de la `build` répertoire, configurez votre build en exécutant CMake. Avant la première exécution, vous devez définir des variables d'environnement qui spécifient le compilateur (compilateur gcc version 9 dans cet exemple).
|
||||
Tandis qu'à l'intérieur de la `build` répertoire, configurez votre build en exécutant CMake. Avant la première exécution, vous devez définir des variables d'environnement qui spécifient le compilateur (compilateur gcc version 10 dans cet exemple).
|
||||
|
||||
Linux:
|
||||
|
||||
export CC=gcc-9 CXX=g++-9
|
||||
export CC=gcc-10 CXX=g++-10
|
||||
cmake ..
|
||||
|
||||
Mac OS X:
|
||||
|
||||
@ -1,261 +0,0 @@
|
||||
---
|
||||
machine_translated: true
|
||||
machine_translated_rev: 72537a2d527c63c07aa5d2361a8829f3895cf2bd
|
||||
toc_priority: 69
|
||||
toc_title: "Comment ex\xE9cuter des Tests ClickHouse"
|
||||
---
|
||||
|
||||
# ClickHouse Test {#clickhouse-testing}
|
||||
|
||||
## Les Tests Fonctionnels {#functional-tests}
|
||||
|
||||
Les tests fonctionnels sont les plus simples et pratiques à utiliser. La plupart des fonctionnalités de ClickHouse peuvent être testées avec des tests fonctionnels et elles sont obligatoires à utiliser pour chaque changement de code de ClickHouse qui peut être testé de cette façon.
|
||||
|
||||
Chaque test fonctionnel envoie une ou plusieurs requêtes au serveur clickhouse en cours d'exécution et compare le résultat avec la référence.
|
||||
|
||||
Les Tests sont situés dans `queries` répertoire. Il y a deux sous-répertoires: `stateless` et `stateful`. Les tests sans état exécutent des requêtes sans données de test préchargées - ils créent souvent de petits ensembles de données synthétiques à la volée, dans le test lui-même. Les tests avec État nécessitent des données de test préchargées de Yandex.Metrica et non disponible pour le grand public. Nous avons tendance à utiliser uniquement `stateless` tests et éviter d'ajouter de nouveaux `stateful` test.
|
||||
|
||||
Chaque test peut être de deux types: `.sql` et `.sh`. `.sql` test est le script SQL simple qui est canalisé vers `clickhouse-client --multiquery --testmode`. `.sh` test est un script qui est exécuté par lui-même.
|
||||
|
||||
Pour exécuter tous les tests, utilisez `clickhouse-test` outil. Regarder `--help` pour la liste des options possibles. Vous pouvez simplement exécuter tous les tests ou exécuter un sous ensemble de tests filtrés par sous chaîne dans le nom du test: `./clickhouse-test substring`.
|
||||
|
||||
Le moyen le plus simple d'invoquer des tests fonctionnels est de copier `clickhouse-client` de `/usr/bin/`, exécuter `clickhouse-server` et puis exécutez `./clickhouse-test` à partir de son propre répertoire.
|
||||
|
||||
Pour ajouter un nouveau test, créez un `.sql` ou `.sh` fichier dans `queries/0_stateless` répertoire, vérifiez-le manuellement, puis générez `.reference` fichier de la façon suivante: `clickhouse-client -n --testmode < 00000_test.sql > 00000_test.reference` ou `./00000_test.sh > ./00000_test.reference`.
|
||||
|
||||
Les Tests doivent utiliser (create, drop, etc) uniquement des tables dans `test` base de données supposée être créée au préalable; les tests peuvent également utiliser des tables temporaires.
|
||||
|
||||
Si vous souhaitez utiliser des requêtes distribuées dans les tests fonctionnels, vous pouvez tirer parti de `remote` fonction de table avec `127.0.0.{1..2}` ou vous pouvez utiliser des clusters de test prédéfinis dans le fichier de configuration du serveur comme `test_shard_localhost`.
|
||||
|
||||
Certains tests sont marqués avec `zookeeper`, `shard` ou `long` en leurs noms.
|
||||
`zookeeper` est pour les tests qui utilisent ZooKeeper. `shard` est pour les tests
|
||||
nécessite l'écoute du serveur `127.0.0.*`; `distributed` ou `global` avoir le même
|
||||
sens. `long` est pour les tests qui s'exécutent légèrement plus longtemps qu'une seconde. Vous pouvez
|
||||
désactivez ces groupes de tests en utilisant `--no-zookeeper`, `--no-shard` et
|
||||
`--no-long` options, respectivement.
|
||||
|
||||
## Bugs Connus {#known-bugs}
|
||||
|
||||
Si nous connaissons des bugs qui peuvent être facilement reproduits par des tests fonctionnels, nous plaçons des tests fonctionnels préparés dans `tests/queries/bugs` répertoire. Ces tests seront déplacés à `tests/queries/0_stateless` quand les bugs sont corrigés.
|
||||
|
||||
## Les Tests D'Intégration {#integration-tests}
|
||||
|
||||
Les tests d'intégration permettent de tester ClickHouse en configuration cluster et clickhouse interaction avec D'autres serveurs comme MySQL, Postgres, MongoDB. Ils sont utiles pour émuler les splits réseau, les chutes de paquets, etc. Ces tests sont exécutés sous Docker et créent plusieurs conteneurs avec divers logiciels.
|
||||
|
||||
Voir `tests/integration/README.md` sur la façon d'exécuter ces tests.
|
||||
|
||||
Notez que l'intégration de ClickHouse avec des pilotes tiers n'est pas testée. De plus, nous n'avons actuellement pas de tests d'intégration avec nos pilotes JDBC et ODBC.
|
||||
|
||||
## Les Tests Unitaires {#unit-tests}
|
||||
|
||||
Les tests unitaires sont utiles lorsque vous voulez tester non pas le ClickHouse dans son ensemble, mais une seule bibliothèque ou classe isolée. Vous pouvez activer ou désactiver la génération de tests avec `ENABLE_TESTS` Option CMake. Les tests unitaires (et autres programmes de test) sont situés dans `tests` sous-répertoires à travers le code. Pour exécuter des tests unitaires, tapez `ninja test`. Certains tests utilisent `gtest`, mais certains ne sont que des programmes qui renvoient un code de sortie non nul en cas d'échec du test.
|
||||
|
||||
Ce n'est pas nécessairement d'avoir des tests unitaires si le code est déjà couvert par des tests fonctionnels (et les tests fonctionnels sont généralement beaucoup plus simples à utiliser).
|
||||
|
||||
## Tests De Performance {#performance-tests}
|
||||
|
||||
Les tests de Performance permettent de mesurer et de comparer les performances d'une partie isolée de ClickHouse sur des requêtes synthétiques. Les Tests sont situés à `tests/performance`. Chaque test est représenté par `.xml` fichier avec description du cas de test. Les Tests sont exécutés avec `clickhouse performance-test` outil (qui est incorporé dans `clickhouse` binaire). Voir `--help` pour l'invocation.
|
||||
|
||||
Chaque essai d'exécuter une ou plusieurs requêtes (éventuellement avec des combinaisons de paramètres) dans une boucle avec certaines conditions pour l'arrêt (comme “maximum execution speed is not changing in three seconds”) et mesurer certaines mesures sur les performances de la requête (comme “maximum execution speed”). Certains tests peuvent contenir des conditions préalables sur un ensemble de données de test préchargé.
|
||||
|
||||
Si vous souhaitez améliorer les performances de ClickHouse dans certains scénarios, et si des améliorations peuvent être observées sur des requêtes simples, il est fortement recommandé d'écrire un test de performance. Il est toujours logique d'utiliser `perf top` ou d'autres outils perf pendant vos tests.
|
||||
|
||||
## Outils et Scripts de Test {#test-tools-and-scripts}
|
||||
|
||||
Certains programmes dans `tests` directory ne sont pas des tests préparés, mais sont des outils de test. Par exemple, pour `Lexer` il est un outil `src/Parsers/tests/lexer` Cela fait juste la tokenisation de stdin et écrit le résultat colorisé dans stdout. Vous pouvez utiliser ce genre d'outils comme exemples de code et pour l'exploration et les tests manuels.
|
||||
|
||||
Vous pouvez également placer une paire de fichiers `.sh` et `.reference` avec l'outil pour l'exécuter sur une entrée prédéfinie - alors le résultat du script peut être comparé à `.reference` fichier. Ce genre de tests ne sont pas automatisés.
|
||||
|
||||
## Divers Tests {#miscellaneous-tests}
|
||||
|
||||
Il existe des tests pour les dictionnaires externes situés à `tests/external_dictionaries` et pour machine appris modèles dans `tests/external_models`. Ces tests ne sont pas mis à jour et doivent être transférés aux tests d'intégration.
|
||||
|
||||
Il y a un test séparé pour les inserts de quorum. Ce test exécute le cluster ClickHouse sur des serveurs séparés et émule divers cas d'échec: scission réseau, chute de paquets (entre les nœuds ClickHouse, entre Clickhouse et ZooKeeper, entre le serveur ClickHouse et le client, etc.), `kill -9`, `kill -STOP` et `kill -CONT` , comme [Jepsen](https://aphyr.com/tags/Jepsen). Ensuite, le test vérifie que toutes les insertions reconnues ont été écrites et que toutes les insertions rejetées ne l'ont pas été.
|
||||
|
||||
Le test de Quorum a été écrit par une équipe distincte avant que ClickHouse ne soit open-source. Cette équipe ne travaille plus avec ClickHouse. Test a été écrit accidentellement en Java. Pour ces raisons, quorum test doit être réécrit et déplacé vers tests d'intégration.
|
||||
|
||||
## Les Tests Manuels {#manual-testing}
|
||||
|
||||
Lorsque vous développez une nouvelle fonctionnalité, il est raisonnable de tester également manuellement. Vous pouvez le faire avec les étapes suivantes:
|
||||
|
||||
Construire ClickHouse. Exécuter ClickHouse à partir du terminal: changer le répertoire à `programs/clickhouse-server` et de l'exécuter avec `./clickhouse-server`. Il utilisera la configuration (`config.xml`, `users.xml` et les fichiers à l'intérieur `config.d` et `users.d` répertoires) à partir du répertoire courant par défaut. Pour vous connecter au serveur ClickHouse, exécutez `programs/clickhouse-client/clickhouse-client`.
|
||||
|
||||
Notez que tous les outils clickhouse (serveur, client, etc.) ne sont que des liens symboliques vers un seul binaire nommé `clickhouse`. Vous pouvez trouver ce binaire à `programs/clickhouse`. Tous les outils peuvent également être invoquée comme `clickhouse tool` plutôt `clickhouse-tool`.
|
||||
|
||||
Alternativement, vous pouvez installer le paquet ClickHouse: soit une version stable du référentiel Yandex, soit vous pouvez créer un paquet pour vous-même avec `./release` dans les sources de ClickHouse racine. Puis démarrez le serveur avec `sudo service clickhouse-server start` (ou stop pour arrêter le serveur). Rechercher des journaux à `/etc/clickhouse-server/clickhouse-server.log`.
|
||||
|
||||
Lorsque ClickHouse est déjà installé sur votre système, vous pouvez créer un nouveau `clickhouse` binaire et remplacer le binaire:
|
||||
|
||||
``` bash
|
||||
$ sudo service clickhouse-server stop
|
||||
$ sudo cp ./clickhouse /usr/bin/
|
||||
$ sudo service clickhouse-server start
|
||||
```
|
||||
|
||||
Vous pouvez également arrêter system clickhouse-server et exécuter le vôtre avec la même configuration mais en vous connectant au terminal:
|
||||
|
||||
``` bash
|
||||
$ sudo service clickhouse-server stop
|
||||
$ sudo -u clickhouse /usr/bin/clickhouse server --config-file /etc/clickhouse-server/config.xml
|
||||
```
|
||||
|
||||
Exemple avec gdb:
|
||||
|
||||
``` bash
|
||||
$ sudo -u clickhouse gdb --args /usr/bin/clickhouse server --config-file /etc/clickhouse-server/config.xml
|
||||
```
|
||||
|
||||
Si le système clickhouse-server est déjà en cours d'exécution et que vous ne voulez pas l'arrêter, vous pouvez modifier les numéros de port dans votre `config.xml` (ou de les remplacer dans un fichier `config.d` répertoire), fournissez le chemin de données approprié, et exécutez-le.
|
||||
|
||||
`clickhouse` binary n'a presque aucune dépendance et fonctionne sur un large éventail de distributions Linux. Rapide et sale de tester vos modifications sur un serveur, vous pouvez simplement `scp` votre douce construite `clickhouse` binaire à votre serveur et ensuite l'exécuter comme dans les exemples ci-dessus.
|
||||
|
||||
## L'Environnement De Test {#testing-environment}
|
||||
|
||||
Avant de publier la version stable, nous la déployons sur l'environnement de test. L'environnement de test est un cluster processus 1/39 partie de [Yandex.Metrica](https://metrica.yandex.com/) données. Nous partageons notre environnement de test avec Yandex.Metrica de l'équipe. ClickHouse est mis à niveau sans temps d'arrêt au-dessus des données existantes. Nous regardons d'abord que les données sont traitées avec succès sans retard par rapport au temps réel, la réplication continue à fonctionner et il n'y a pas de problèmes visibles pour Yandex.Metrica de l'équipe. Première vérification peut être effectuée de la façon suivante:
|
||||
|
||||
``` sql
|
||||
SELECT hostName() AS h, any(version()), any(uptime()), max(UTCEventTime), count() FROM remote('example01-01-{1..3}t', merge, hits) WHERE EventDate >= today() - 2 GROUP BY h ORDER BY h;
|
||||
```
|
||||
|
||||
Dans certains cas, nous déployons également à l'environnement de test de nos équipes d'amis dans Yandex: marché, Cloud, etc. Nous avons également des serveurs matériels qui sont utilisés à des fins de développement.
|
||||
|
||||
## Les Tests De Charge {#load-testing}
|
||||
|
||||
Après le déploiement dans l'environnement de test, nous exécutons des tests de charge avec des requêtes du cluster de production. Ceci est fait manuellement.
|
||||
|
||||
Assurez-vous que vous avez activé `query_log` sur votre cluster de production.
|
||||
|
||||
Recueillir le journal des requêtes pour une journée ou plus:
|
||||
|
||||
``` bash
|
||||
$ clickhouse-client --query="SELECT DISTINCT query FROM system.query_log WHERE event_date = today() AND query LIKE '%ym:%' AND query NOT LIKE '%system.query_log%' AND type = 2 AND is_initial_query" > queries.tsv
|
||||
```
|
||||
|
||||
C'est une façon compliquée exemple. `type = 2` filtrera les requêtes exécutées avec succès. `query LIKE '%ym:%'` est de sélectionner les requêtes de Yandex.Metrica. `is_initial_query` est de sélectionner uniquement les requêtes initiées par le client, pas par ClickHouse lui-même (en tant que partie du traitement de requête distribué).
|
||||
|
||||
`scp` ce journal à votre cluster de test et l'exécuter comme suit:
|
||||
|
||||
``` bash
|
||||
$ clickhouse benchmark --concurrency 16 < queries.tsv
|
||||
```
|
||||
|
||||
(probablement vous voulez aussi spécifier un `--user`)
|
||||
|
||||
Ensuite, laissez-le pour une nuit ou un week-end et allez vous reposer.
|
||||
|
||||
Tu devrais vérifier ça `clickhouse-server` ne plante pas, l'empreinte mémoire est limitée et les performances ne se dégradent pas au fil du temps.
|
||||
|
||||
Les délais précis d'exécution des requêtes ne sont pas enregistrés et ne sont pas comparés en raison de la grande variabilité des requêtes et de l'environnement.
|
||||
|
||||
## Essais De Construction {#build-tests}
|
||||
|
||||
Les tests de construction permettent de vérifier que la construction n'est pas interrompue sur diverses configurations alternatives et sur certains systèmes étrangers. Les Tests sont situés à `ci` répertoire. Ils exécutent build from source à L'intérieur de Docker, Vagrant, et parfois avec `qemu-user-static` à l'intérieur de Docker. Ces tests sont en cours de développement et les essais ne sont pas automatisées.
|
||||
|
||||
Motivation:
|
||||
|
||||
Normalement, nous libérons et exécutons tous les tests sur une seule variante de construction ClickHouse. Mais il existe des variantes de construction alternatives qui ne sont pas complètement testées. Exemple:
|
||||
|
||||
- construire sur FreeBSD;
|
||||
- construire sur Debian avec les bibliothèques des paquets système;
|
||||
- construire avec des liens partagés de bibliothèques;
|
||||
- construire sur la plate-forme AArch64;
|
||||
- construire sur la plate-forme PowerPc.
|
||||
|
||||
Par exemple, construire avec des paquets système est une mauvaise pratique, car nous ne pouvons pas garantir quelle version exacte des paquets un système aura. Mais c'est vraiment nécessaire pour les responsables Debian. Pour cette raison, nous devons au moins soutenir cette variante de construction. Un autre exemple: la liaison partagée est une source commune de problèmes, mais elle est nécessaire pour certains amateurs.
|
||||
|
||||
Bien que nous ne puissions pas exécuter tous les tests sur toutes les variantes de builds, nous voulons vérifier au moins que les différentes variantes de build ne sont pas cassées. Pour cela nous utilisons les essais de construction.
|
||||
|
||||
## Test de compatibilité du protocole {#testing-for-protocol-compatibility}
|
||||
|
||||
Lorsque nous étendons le protocole réseau ClickHouse, nous testons manuellement que l'ancien clickhouse-client fonctionne avec le nouveau clickhouse-server et que le nouveau clickhouse-client fonctionne avec l'ancien clickhouse-server (simplement en exécutant des binaires à partir des paquets correspondants).
|
||||
|
||||
## L'aide du Compilateur {#help-from-the-compiler}
|
||||
|
||||
Code ClickHouse principal (qui est situé dans `dbms` annuaire) est construit avec `-Wall -Wextra -Werror` et avec quelques avertissements supplémentaires activés. Bien que ces options ne soient pas activées pour les bibliothèques tierces.
|
||||
|
||||
Clang a des avertissements encore plus utiles - vous pouvez les chercher avec `-Weverything` et choisissez quelque chose à construire par défaut.
|
||||
|
||||
Pour les builds de production, gcc est utilisé (il génère toujours un code légèrement plus efficace que clang). Pour le développement, clang est généralement plus pratique à utiliser. Vous pouvez construire sur votre propre machine avec le mode débogage (pour économiser la batterie de votre ordinateur portable), mais veuillez noter que le compilateur est capable de générer plus d'Avertissements avec `-O3` grâce à une meilleure analyse du flux de contrôle et de l'inter-procédure. Lors de la construction avec clang avec le mode débogage, la version de débogage de `libc++` est utilisé qui permet d'attraper plus d'erreurs à l'exécution.
|
||||
|
||||
## Désinfectant {#sanitizers}
|
||||
|
||||
**Désinfectant d'adresse**.
|
||||
Nous exécutons des tests fonctionnels et d'intégration sous ASan sur la base de per-commit.
|
||||
|
||||
**Valgrind (Memcheck)**.
|
||||
Nous effectuons des tests fonctionnels sous Valgrind pendant la nuit. Cela prend plusieurs heures. Actuellement il y a un faux positif connu dans `re2` bibliothèque, consultez [cet article](https://research.swtch.com/sparse).
|
||||
|
||||
**Désinfectant de comportement indéfini.**
|
||||
Nous exécutons des tests fonctionnels et d'intégration sous ASan sur la base de per-commit.
|
||||
|
||||
**Désinfectant pour filetage**.
|
||||
Nous exécutons des tests fonctionnels sous TSan sur la base de per-commit. Nous n'exécutons toujours pas de tests D'intégration sous TSan sur la base de la validation.
|
||||
|
||||
**Mémoire de désinfectant**.
|
||||
Actuellement, nous n'utilisons toujours pas MSan.
|
||||
|
||||
**Débogueur allocateur.**
|
||||
Version de débogage de `jemalloc` est utilisé pour la construction de débogage.
|
||||
|
||||
## Fuzzing {#fuzzing}
|
||||
|
||||
Clickhouse fuzzing est implémenté à la fois en utilisant [libFuzzer](https://llvm.org/docs/LibFuzzer.html) et des requêtes SQL aléatoires.
|
||||
Tous les tests de fuzz doivent être effectués avec des désinfectants (adresse et indéfini).
|
||||
|
||||
LibFuzzer est utilisé pour les tests de fuzz isolés du code de la bibliothèque. Les Fuzzers sont implémentés dans le cadre du code de test et ont “_fuzzer” nom postfixes.
|
||||
Exemple Fuzzer peut être trouvé à `src/Parsers/tests/lexer_fuzzer.cpp`. Les configs, dictionnaires et corpus spécifiques à LibFuzzer sont stockés à `tests/fuzz`.
|
||||
Nous vous encourageons à écrire des tests fuzz pour chaque fonctionnalité qui gère l'entrée de l'utilisateur.
|
||||
|
||||
Fuzzers ne sont pas construits par défaut. Pour construire fuzzers à la fois `-DENABLE_FUZZING=1` et `-DENABLE_TESTS=1` options doivent être définies.
|
||||
Nous vous recommandons de désactiver Jemalloc lors de la construction de fuzzers. Configuration utilisée pour intégrer clickhouse fuzzing à
|
||||
Google OSS-Fuzz peut être trouvé à `docker/fuzz`.
|
||||
|
||||
Nous utilisons également un simple test fuzz pour générer des requêtes SQL aléatoires et vérifier que le serveur ne meurt pas en les exécutant.
|
||||
Vous pouvez le trouver dans `00746_sql_fuzzy.pl`. Ce test doit être exécuté en continu (pendant la nuit et plus longtemps).
|
||||
|
||||
## Audit De Sécurité {#security-audit}
|
||||
|
||||
Les gens de L'équipe de sécurité Yandex font un aperçu de base des capacités de ClickHouse du point de vue de la sécurité.
|
||||
|
||||
## Analyseurs Statiques {#static-analyzers}
|
||||
|
||||
Nous courons `PVS-Studio` par commettre base. Nous avons évalué `clang-tidy`, `Coverity`, `cppcheck`, `PVS-Studio`, `tscancode`. Vous trouverez des instructions pour l'utilisation dans `tests/instructions/` répertoire. Aussi, vous pouvez lire [l'article en russe](https://habr.com/company/yandex/blog/342018/).
|
||||
|
||||
Si vous utilisez `CLion` en tant QU'IDE, vous pouvez tirer parti de certains `clang-tidy` contrôles de la boîte.
|
||||
|
||||
## Durcir {#hardening}
|
||||
|
||||
`FORTIFY_SOURCE` est utilisé par défaut. C'est presque inutile, mais cela a toujours du sens dans de rares cas et nous ne le désactivons pas.
|
||||
|
||||
## Code De Style {#code-style}
|
||||
|
||||
Les règles de style de Code sont décrites [ici](https://clickhouse.tech/docs/en/development/style/).
|
||||
|
||||
Pour vérifier certaines violations de style courantes, vous pouvez utiliser `utils/check-style` script.
|
||||
|
||||
Pour forcer le style approprié de votre code, vous pouvez utiliser `clang-format`. Fichier `.clang-format` est situé à la racine des sources. Il correspond principalement à notre style de code réel. Mais il n'est pas recommandé d'appliquer `clang-format` pour les fichiers existants, car il rend le formatage pire. Vous pouvez utiliser `clang-format-diff` outil que vous pouvez trouver dans clang référentiel source.
|
||||
|
||||
Alternativement vous pouvez essayer `uncrustify` outil pour reformater votre code. La Configuration est en `uncrustify.cfg` dans la racine des sources. Il est moins testé que `clang-format`.
|
||||
|
||||
`CLion` a son propre formateur de code qui doit être réglé pour notre style de code.
|
||||
|
||||
## Tests Metrica B2B {#metrica-b2b-tests}
|
||||
|
||||
Chaque version de ClickHouse est testée avec les moteurs Yandex Metrica et AppMetrica. Les versions de test et stables de ClickHouse sont déployées sur des machines virtuelles et exécutées avec une petite copie de metrica engine qui traite un échantillon fixe de données d'entrée. Ensuite, les résultats de deux instances de metrica engine sont comparés ensemble.
|
||||
|
||||
Ces tests sont automatisés par une équipe distincte. En raison du nombre élevé de pièces en mouvement, les tests échouent la plupart du temps complètement raisons, qui sont très difficiles à comprendre. Très probablement, ces tests ont une valeur négative pour nous. Néanmoins, ces tests se sont révélés utiles dans environ une ou deux fois sur des centaines.
|
||||
|
||||
## La Couverture De Test {#test-coverage}
|
||||
|
||||
En juillet 2018, nous ne suivons pas la couverture des tests.
|
||||
|
||||
## Automatisation Des Tests {#test-automation}
|
||||
|
||||
Nous exécutons des tests avec Yandex CI interne et le système d'automatisation des tâches nommé “Sandbox”.
|
||||
|
||||
Les travaux de construction et les tests sont exécutés dans Sandbox sur une base de validation. Les paquets résultants et les résultats des tests sont publiés dans GitHub et peuvent être téléchargés par des liens directs. Les artefacts sont stockés éternellement. Lorsque vous envoyez une demande de tirage sur GitHub, nous l'étiquetons comme “can be tested” et notre système CI construira des paquets ClickHouse (release, debug, avec un désinfectant d'adresse, etc.) pour vous.
|
||||
|
||||
Nous n'utilisons pas Travis CI en raison de la limite de temps et de puissance de calcul.
|
||||
On n'utilise pas Jenkins. Il a été utilisé avant et maintenant nous sommes heureux de ne pas utiliser Jenkins.
|
||||
|
||||
[Article Original](https://clickhouse.tech/docs/en/development/tests/) <!--hide-->
|
||||
1
docs/fr/development/tests.md
Symbolic link
1
docs/fr/development/tests.md
Symbolic link
@ -0,0 +1 @@
|
||||
../../en/development/tests.md
|
||||
@ -19,7 +19,7 @@ $ sudo apt-get install git cmake python ninja-build
|
||||
|
||||
古いシステムではcmakeの代わりにcmake3。
|
||||
|
||||
## GCC9のインストール {#install-gcc-9}
|
||||
## GCC9のインストール {#install-gcc-10}
|
||||
|
||||
これを行うにはいくつかの方法があります。
|
||||
|
||||
@ -29,18 +29,18 @@ $ sudo apt-get install git cmake python ninja-build
|
||||
$ sudo apt-get install software-properties-common
|
||||
$ sudo apt-add-repository ppa:ubuntu-toolchain-r/test
|
||||
$ sudo apt-get update
|
||||
$ sudo apt-get install gcc-9 g++-9
|
||||
$ sudo apt-get install gcc-10 g++-10
|
||||
```
|
||||
|
||||
### ソースからインスト {#install-from-sources}
|
||||
|
||||
見て [utils/ci/build-gcc-from-sources.sh](https://github.com/ClickHouse/ClickHouse/blob/master/utils/ci/build-gcc-from-sources.sh)
|
||||
|
||||
## ビルドにGCC9を使用する {#use-gcc-9-for-builds}
|
||||
## ビルドにGCC9を使用する {#use-gcc-10-for-builds}
|
||||
|
||||
``` bash
|
||||
$ export CC=gcc-9
|
||||
$ export CXX=g++-9
|
||||
$ export CC=gcc-10
|
||||
$ export CXX=g++-10
|
||||
```
|
||||
|
||||
## ﾂつｨﾂ姪"ﾂ債ﾂつｹ {#checkout-clickhouse-sources}
|
||||
|
||||
@ -141,7 +141,7 @@ ClickHouseのビルドには、バージョン9以降のGCCとClangバージョ
|
||||
|
||||
UBUNTUにGCCをインストールするには: `sudo apt install gcc g++`
|
||||
|
||||
Gccのバージョンを確認する: `gcc --version`. の場合は下記9その指示に従う。https://clickhouse.tech/docs/ja/development/build/#install-gcc-9.
|
||||
Gccのバージョンを確認する: `gcc --version`. の場合は下記9その指示に従う。https://clickhouse.tech/docs/ja/development/build/#install-gcc-10.
|
||||
|
||||
Mac OS XのビルドはClangでのみサポートされています。 ちょうど実行 `brew install llvm`
|
||||
|
||||
@ -160,7 +160,7 @@ ClickHouseを構築する準備ができたので、別のディレクトリを
|
||||
|
||||
Linux:
|
||||
|
||||
export CC=gcc-9 CXX=g++-9
|
||||
export CC=gcc-10 CXX=g++-10
|
||||
cmake ..
|
||||
|
||||
Mac OS X:
|
||||
|
||||
@ -1,261 +0,0 @@
|
||||
---
|
||||
machine_translated: true
|
||||
machine_translated_rev: 72537a2d527c63c07aa5d2361a8829f3895cf2bd
|
||||
toc_priority: 69
|
||||
toc_title: "ClickHouse\u30C6\u30B9\u30C8\u306E\u5B9F\u884C\u65B9\u6CD5"
|
||||
---
|
||||
|
||||
# ClickHouseのテスト {#clickhouse-testing}
|
||||
|
||||
## 機能テスト {#functional-tests}
|
||||
|
||||
機能テストは、最も簡単で使いやすいです。 ClickHouseの機能のほとんどは機能テストでテストすることができ、そのようにテストできるClickHouseコードのすべての変更に使用することが必須です。
|
||||
|
||||
各機能テストは、実行中のClickHouseサーバーに一つまたは複数のクエリを送信し、結果を参照と比較します。
|
||||
|
||||
テストは `queries` ディレクトリ。 サブディレクトリは二つあります: `stateless` と `stateful`. ステートレステストは、プリロードされたテストデータなしでクエリを実行します。 状態での検査が必要とな予圧試験データからのYandex.Metricaおよび一般に利用できない。 私たちは使用する傾向があります `stateless` テストと新しい追加を避ける `stateful` テストだ
|
||||
|
||||
それぞれの試験できるの種類: `.sql` と `.sh`. `.sql` testは、パイプ処理される単純なSQLスクリプトです `clickhouse-client --multiquery --testmode`. `.sh` testは、それ自体で実行されるスクリプトです。
|
||||
|
||||
すべてのテストを実行するには、 `clickhouse-test` ツール。 見て！ `--help` 可能なオプションのリスト。 できるだけ実行すべての試験または実行のサブセットの試験フィルター部分文字列の試験名: `./clickhouse-test substring`.
|
||||
|
||||
機能テストを呼び出す最も簡単な方法は、コピーすることです `clickhouse-client` に `/usr/bin/`,run `clickhouse-server` そして、実行 `./clickhouse-test` 独自のディレクトリから。
|
||||
|
||||
新しいテストを追加するには、 `.sql` または `.sh` ファイル `queries/0_stateless` ディレクトリでチェックを手動でその生成 `.reference` 次の方法でファイル: `clickhouse-client -n --testmode < 00000_test.sql > 00000_test.reference` または `./00000_test.sh > ./00000_test.reference`.
|
||||
|
||||
テストでは、テーブルのみを使用（create、dropなど）する必要があります `test` また、テストでは一時テーブルを使用することもできます。
|
||||
|
||||
機能テストで分散クエリを使用する場合は、以下を利用できます `remote` テーブル関数 `127.0.0.{1..2}` または、サーバー設定ファイルで次のように定義済みのテストクラスタを使用できます `test_shard_localhost`.
|
||||
|
||||
いくつかのテストには `zookeeper`, `shard` または `long` 彼らの名前で。
|
||||
`zookeeper` ZooKeeperを使用しているテスト用です。 `shard` そのテストのためです
|
||||
サーバーにリッスンが必要 `127.0.0.*`; `distributed` または `global` 同じを持っている
|
||||
意味だ `long` 少し長く実行されるテストのためのものです。 あなたはできる
|
||||
disableこれらのグループの試験を使用 `--no-zookeeper`, `--no-shard` と
|
||||
`--no-long` オプション、それぞれ。
|
||||
|
||||
## 既知のバグ {#known-bugs}
|
||||
|
||||
機能テストで簡単に再現できるいくつかのバグがわかっている場合は、準備された機能テストを `tests/queries/bugs` ディレクトリ。 これらのテストは `tests/queries/0_stateless` バグが修正されたとき。
|
||||
|
||||
## 統合テスト {#integration-tests}
|
||||
|
||||
統合テストでは、クラスター化された構成でClickHouseをテストし、Mysql、Postgres、MongoDBなどの他のサーバーとClickHouseの相互作用をテストできます。 これらをエミュレートするネットワーク分割、パケットの落下など。 これらの試験する方向に作用しDockerを複数の容器を様々なソフトウェアです。
|
||||
|
||||
見る `tests/integration/README.md` これらのテストを実行する方法について。
|
||||
|
||||
この統合ClickHouse第三者によるドライバーではない。 また、現在、JDBCおよびODBCドライバとの統合テストはありません。
|
||||
|
||||
## 単体テスト {#unit-tests}
|
||||
|
||||
単体テストは、ClickHouse全体ではなく、単一の孤立したライブラリまたはクラスをテストする場合に便利です。 テストのビルドを有効または無効にするには `ENABLE_TESTS` CMakeオプション。 単体テスト(およびその他のテストプログラム)は `tests` コード全体のサブディレクトリ。 単体テストを実行するには、 `ninja test`. 一部のテストでは `gtest` しかし、いくつかは、テストの失敗でゼロ以外の終了コードを返すプログラムです。
|
||||
|
||||
コードがすでに機能テストでカバーされている場合は、必ずしも単体テストを持つとは限りません（機能テストは通常ははるかに簡単です）。
|
||||
|
||||
## 性能テスト {#performance-tests}
|
||||
|
||||
パフォーマ テストは `tests/performance`. それぞれの試験に代表される `.xml` テストケースの説明を持つファイル。 テストは以下で実行されます `clickhouse performance-test` ツール(埋め込まれている `clickhouse` バイナリ）。 見る `--help` 呼び出し用。
|
||||
|
||||
それぞれの試験実行または複数のクエリ(このパラメータの組み合わせ）のループ条件のための停止など “maximum execution speed is not changing in three seconds” 測定一部の指標につクエリの性能など “maximum execution speed”). いくつかの試験を含むことができ前提条件に予圧試験データを得る。
|
||||
|
||||
いくつかのシナリオでClickHouseのパフォーマンスを向上させたい場合や、単純なクエリで改善が見られる場合は、パフォーマンステストを作成することを強 いう意味があるのに使用 `perf top` またはあなたのテストの間の他のperf用具。
|
||||
|
||||
## テストツールとスクリプ {#test-tools-and-scripts}
|
||||
|
||||
一部のプログラム `tests` ディレク 例えば、 `Lexer` ツールがあります `src/Parsers/tests/lexer` それはstdinのトークン化を行い、色付けされた結果をstdoutに書き込みます。 これらの種類のツールは、コード例として、また探索と手動テストに使用できます。
|
||||
|
||||
でも一対のファイル `.sh` と `.reference` いくつかの事前定義された入力でそれを実行するためのツールと一緒に-その後、スクリプトの結果は `.reference` ファイル これらの種類のテストは自動化されていません。
|
||||
|
||||
## その他のテスト {#miscellaneous-tests}
|
||||
|
||||
外部辞書のテストは次の場所にあります `tests/external_dictionaries` そして機械学んだモデルのために `tests/external_models`. これらのテストは更新されず、統合テストに転送する必要があります。
|
||||
|
||||
クォーラム挿入には別のテストがあります。 このテストでは、ネットワーク分割、パケットドロップ（ClickHouseノード間、ClickHouseとZooKeeper間、ClickHouseサーバーとクライアント間など）など、さまざまな障害ケースをエミュレートします。), `kill -9`, `kill -STOP` と `kill -CONT` 例えば [ジェプセン](https://aphyr.com/tags/Jepsen). その後、試験チェックすべての認識を挿入したすべて拒否された挿入しました。
|
||||
|
||||
定足数を緩和試験の筆に別々のチーム前ClickHouseしたオープン達した. このチームはClickHouseでは動作しなくなりました。 テストは誤ってJavaで書かれました。 これらのことから、決議の定足数テストを書き換え及び移転統合。
|
||||
|
||||
## 手動テスト {#manual-testing}
|
||||
|
||||
新しい機能を開発するときは、手動でもテストするのが妥当です。 これを行うには、次の手順を実行します:
|
||||
|
||||
ClickHouseを構築します。 ターミナルからClickHouseを実行します。 `programs/clickhouse-server` そして、それを実行します `./clickhouse-server`. それは構成を使用します (`config.xml`, `users.xml` そして内のファイル `config.d` と `users.d` ディレクトリ)から、現在のディレクトリがデフォルトです。 ClickHouseサーバーに接続するには、以下を実行します `programs/clickhouse-client/clickhouse-client`.
|
||||
|
||||
これらのclickhouseツール（サーバ、クライアント、などだそうでsymlinks単一のバイナリ名 `clickhouse`. このバイナリは `programs/clickhouse`. すべてのツ `clickhouse tool` 代わりに `clickhouse-tool`.
|
||||
|
||||
またインストールすることができClickHouseパッケージは安定したリリースからのYandexリポジトリあるいはすることで作ることができるパッケージで `./release` ClickHouseソースルートで. 次に、サーバーを起動します `sudo service clickhouse-server start` (または停止してサーバーを停止します)。 ログを探す `/etc/clickhouse-server/clickhouse-server.log`.
|
||||
|
||||
時ClickHouseでに既にインストールされているシステムを構築できる新しい `clickhouse` 既存のバイナリを置き換えます:
|
||||
|
||||
``` bash
|
||||
$ sudo service clickhouse-server stop
|
||||
$ sudo cp ./clickhouse /usr/bin/
|
||||
$ sudo service clickhouse-server start
|
||||
```
|
||||
|
||||
また、システムclickhouse-serverを停止し、同じ構成ではなく端末にログインして独自のものを実行することもできます:
|
||||
|
||||
``` bash
|
||||
$ sudo service clickhouse-server stop
|
||||
$ sudo -u clickhouse /usr/bin/clickhouse server --config-file /etc/clickhouse-server/config.xml
|
||||
```
|
||||
|
||||
Gdbの例:
|
||||
|
||||
``` bash
|
||||
$ sudo -u clickhouse gdb --args /usr/bin/clickhouse server --config-file /etc/clickhouse-server/config.xml
|
||||
```
|
||||
|
||||
システムclickhouse-serverがすでに実行されていて、それを停止したくない場合は、次のポート番号を変更できます `config.xml` （または、ファイル内でそれらを上書きする `config.d` ディレクトリ）、適切なデータパスを提供し、それを実行します。
|
||||
|
||||
`clickhouse` バイナリーはほとんどない依存関係の作品を広い範囲のLinuxディストリビューション. サーバー上で変更を迅速かつ汚いテストするには、次のことができます `scp` あなたの新鮮な構築 `clickhouse` あなたのサーバーにバイナリし、上記の例のように実行します。
|
||||
|
||||
## テスト環境 {#testing-environment}
|
||||
|
||||
リリースを安定版として公開する前に、テスト環境に展開します。 テスト環境は1/39の部分を処理する集りです [Yandex.メトリカ](https://metrica.yandex.com/) データ テスト環境をYandexと共有しています。メトリカ-チーム ClickHouseは既存のデータの上にダウンタイムなしで改善される。 私たちは、データがリアルタイムから遅れることなく正常に処理され、複製が動作し続け、Yandexに見える問題はないことを最初に見ています。メトリカ-チーム 最初のチェックは、次の方法で行うことができます:
|
||||
|
||||
``` sql
|
||||
SELECT hostName() AS h, any(version()), any(uptime()), max(UTCEventTime), count() FROM remote('example01-01-{1..3}t', merge, hits) WHERE EventDate >= today() - 2 GROUP BY h ORDER BY h;
|
||||
```
|
||||
|
||||
市場、クラウドなど：いくつかのケースでは、我々はまた、Yandexの中で私たちの友人チームのテスト環境に展開します また、開発目的で使用されるハードウェアサーバーもあります。
|
||||
|
||||
## 負荷テスト {#load-testing}
|
||||
|
||||
後の展開を試験環境を実行負荷テストクエリから生産ます。 これは手動で行われます。
|
||||
|
||||
有効にしていることを確認します `query_log` 運用クラスター上。
|
||||
|
||||
一日以上のクエリログを収集する:
|
||||
|
||||
``` bash
|
||||
$ clickhouse-client --query="SELECT DISTINCT query FROM system.query_log WHERE event_date = today() AND query LIKE '%ym:%' AND query NOT LIKE '%system.query_log%' AND type = 2 AND is_initial_query" > queries.tsv
|
||||
```
|
||||
|
||||
これは複雑な例です。 `type = 2` 正常に実行されたクエリをフィルタ処理します。 `query LIKE '%ym:%'` Yandexから関連するクエリを選択することです。メトリカ `is_initial_query` ClickHouse自体ではなく、クライアントによって開始されたクエリのみを選択することです（分散クエリ処理の一部として）。
|
||||
|
||||
`scp` このログをテストクラスタに記録し、次のように実行します:
|
||||
|
||||
``` bash
|
||||
$ clickhouse benchmark --concurrency 16 < queries.tsv
|
||||
```
|
||||
|
||||
（おそらくあなたはまた、 `--user`)
|
||||
|
||||
それから夜または週末のためにそれを残し、残りを取る行きなさい。
|
||||
|
||||
きることを確認 `clickhouse-server` なクラッシュメモリのフットプリントは有界性なつ品位を傷つける。
|
||||
|
||||
クエリと環境の変動が大きいため、正確なクエリ実行タイミングは記録されず、比較されません。
|
||||
|
||||
## ビルドテスト {#build-tests}
|
||||
|
||||
構築を試験できることを確認の構築においても様々な代替構成されており、外国のシステム。 テストは `ci` ディレクトリ。 Docker、Vagrant、時には以下のようなソースからビルドを実行します `qemu-user-static` ドッカー内部。 これらのテストは開発中であり、テストの実行は自動化されません。
|
||||
|
||||
動機:
|
||||
|
||||
通常、ClickHouse buildの単一のバリアントですべてのテストをリリースして実行します。 しかし、徹底的にテストされていない別のビルド変種があります。 例:
|
||||
|
||||
- FreeBSD上でビルド;
|
||||
- をDebianを対象として図書館システムのパッケージ;
|
||||
- ライブラリの共有リンクでビルド;
|
||||
- AArch64プラットフォ;
|
||||
- PowerPcプラットフォーム上で構築。
|
||||
|
||||
たとえば、システムパッケージを使用したビルドは悪い習慣です。 しかし、これは本当にDebianメンテナに必要です。 このため、少なくともこのビルドの変種をサポートする必要があります。 別の例：共有リンクは一般的な問題の原因ですが、一部の愛好家にとって必要です。
|
||||
|
||||
ができませんので実行した全試験はすべての変異体を構築し、チェックしたい少なくとも上記に記載された各種の構築異な破となりました。 この目的のためにビルドテストを使用します。
|
||||
|
||||
## プロトコル互換性のテスト {#testing-for-protocol-compatibility}
|
||||
|
||||
ClickHouse network protocolを拡張すると、古いclickhouse-clientが新しいclickhouse-serverで動作し、新しいclickhouse-clientが古いclickhouse-serverで動作することを手動でテストします（対応するパッケージからバイナリを
|
||||
|
||||
## コンパイラからのヘルプ {#help-from-the-compiler}
|
||||
|
||||
メインクリックハウスコード（にある `dbms` ディレクトリ)は `-Wall -Wextra -Werror` そして、いくつかの追加の有効な警告と。 これらのオプションは有効になっていないためにサードパーティーのライブラリ.
|
||||
|
||||
Clangにはさらに便利な警告があります。 `-Weverything` デフォルトのビルドに何かを選ぶ。
|
||||
|
||||
本番ビルドでは、gccが使用されます（clangよりもやや効率的なコードが生成されます）。 開発のために、clangは通常、使用する方が便利です。 あなたは（あなたのラップトップのバッテリーを節約するために）デバッグモードで自分のマシン上で構築することができますが、コンパイラがでより `-O3` よりよい制御フローおよびinter-procedure分析が原因で。 Clangでビルドする場合, `libc++` の代わりに使用されます。 `libstdc++` そして、デバッグモードでビルドするとき、 `libc++` 使用可能にするにはより誤差があります。.
|
||||
|
||||
## サニタイザー {#sanitizers}
|
||||
|
||||
**アドレスsanitizer**.
|
||||
私たちは、コミットごとにASanの下で機能テストと統合テストを実行します。
|
||||
|
||||
**ヴァルグリンド(曖昧さ回避)**.
|
||||
私たちは一晩Valgrindの下で機能テストを実行します。 数時間かかります。 現在知られている偽陽性があります `re2` 図書館、参照 [この記事](https://research.swtch.com/sparse).
|
||||
|
||||
**未定義の動作のサニタイザー。**
|
||||
私たちは、コミットごとにASanの下で機能テストと統合テストを実行します。
|
||||
|
||||
**糸のsanitizer**.
|
||||
私たちは、コミットごとにTSanの下で機能テストを実行します。 コミットごとにTSanの下で統合テストを実行することはまだありません。
|
||||
|
||||
**メモリサニタイザー**.
|
||||
現在、我々はまだMSanを使用していません。
|
||||
|
||||
**デバッグアロケータ。**
|
||||
デバッグバージョン `jemalloc` デバッグビルドに使用されます。
|
||||
|
||||
## ファジング {#fuzzing}
|
||||
|
||||
ClickHouseファジングは、両方を使用して実装されます [libFuzzer](https://llvm.org/docs/LibFuzzer.html) とランダムSQLクエリ。
|
||||
すべてのファズテストは、サニタイザー（アドレスと未定義）で実行する必要があります。
|
||||
|
||||
LibFuzzerは、ライブラリコードの分離ファズテストに使用されます。 ファザーはテストコードの一部として実装され “_fuzzer” 名前の接尾辞。
|
||||
Fuzzerの例はで見つけることができます `src/Parsers/tests/lexer_fuzzer.cpp`. LibFuzzer固有の設定、辞書、およびコーパスは次の場所に格納されます `tests/fuzz`.
|
||||
ご協力をお願いいたし書きファズ試験べての機能を取り扱うユーザー入力します。
|
||||
|
||||
ファザーはデフォルトではビルドされません。 両方のファザーを構築するには `-DENABLE_FUZZING=1` と `-DENABLE_TESTS=1` 選択は置かれるべきである。
|
||||
ファザーのビルド中にJemallocを無効にすることをお勧めします。 ClickHouseファジングを統合するために使用される設定
|
||||
Google OSS-Fuzzは次の場所にあります `docker/fuzz`.
|
||||
|
||||
また簡単なファズ試験をランダムなSQLクエリーやことを確認するにはサーバーにな金型を実行します。
|
||||
それを見つけることができる `00746_sql_fuzzy.pl`. このテストは、継続的に実行する必要があります（一晩と長い）。
|
||||
|
||||
## セキュリティ監査 {#security-audit}
|
||||
|
||||
人からのYandexセキュリティチームはいくつかの基本的な概要ClickHouse力からのセキュリティの観点から.
|
||||
|
||||
## 静的アナライザ {#static-analyzers}
|
||||
|
||||
私たちは走る `PVS-Studio` コミットごと。 私達は評価しました `clang-tidy`, `Coverity`, `cppcheck`, `PVS-Studio`, `tscancode`. 使用のための指示をで見つけます `tests/instructions/` ディレクトリ。 また読むことができます [ロシア語の記事](https://habr.com/company/yandex/blog/342018/).
|
||||
|
||||
を使用する場合 `CLion` IDEとして、いくつかを活用できます `clang-tidy` 箱から出してチェックします。
|
||||
|
||||
## 硬化 {#hardening}
|
||||
|
||||
`FORTIFY_SOURCE` デフォルトで使用されます。 それはほとんど役に立たないですが、まれに理にかなっており、それを無効にしません。
|
||||
|
||||
## コードスタイル {#code-style}
|
||||
|
||||
コードのスタイルのルールを記述 [ここに](https://clickhouse.tech/docs/en/development/style/).
|
||||
|
||||
チェックのための、共通したスタイル違反、利用できる `utils/check-style` スクリプト
|
||||
|
||||
コードの適切なスタイルを強制するには、次のようにします `clang-format`. ファイル `.clang-format` ソースルートにあります。 実際のコードスタイルにほとんど対応しています。 しかし、適用することはお勧めしません `clang-format` 既存のファイルへの書式設定が悪化するためです。 以下を使用できます `clang-format-diff` clangソースリポジトリで見つけることができるツール。
|
||||
|
||||
あるいは、 `uncrustify` コードを再フォーマットするツール。 設定は次のとおりです `uncrustify.cfg` ソースルートで。 それはより少なくテストさ `clang-format`.
|
||||
|
||||
`CLion` 独自のコードをフォーマッタしていると見ることができる調整のためのコードです。
|
||||
|
||||
## Metrica B2Bテスト {#metrica-b2b-tests}
|
||||
|
||||
各ClickHouseリリースはYandex MetricaとAppMetricaエンジンでテストされます。 ClickHouseのテスト版と安定版はVmにデプロイされ、入力データの固定サンプルを処理するMetrica engineの小さなコピーで実行されます。 次に，Ｍｅｔｒｉｃａエンジンの二つのインスタンスの結果を比較した。
|
||||
|
||||
これらの試験により自動化されており、別のチームです。 可動部分の高い数が原因で、テストは把握し非常ににくい完全に無関係な理由によって失敗ほとんどの時間です。 がこれらの試験は負の値です。 しかしこれらの試験することが明らかとなったが有用である一又は二倍の数百名
|
||||
|
||||
## テスト範囲 {#test-coverage}
|
||||
|
||||
2018年現在、テストカバーは行っていない。
|
||||
|
||||
## テスト自動化 {#test-automation}
|
||||
|
||||
Yandex内部CIとジョブ自動化システムという名前のテストを実行します “Sandbox”.
|
||||
|
||||
ビルドジョブとテストは、コミットごとにSandboxで実行されます。 結果のパッケージとテスト結果はGitHubに公開され、直接リンクでダウンロードできます。 成果物は永遠に保存されます。 GitHubでプルリクエストを送信すると、次のようにタグ付けします “can be tested” そして私達のCIシステムはあなたのためのClickHouseのパッケージ（住所sanitizerの解放、デバッグ、等）を造ります。
|
||||
|
||||
時間と計算能力の限界のため、Travis CIは使用しません。
|
||||
ジェンキンスは使わない 以前は使用されていましたが、今はJenkinsを使用していません。
|
||||
|
||||
[元の記事](https://clickhouse.tech/docs/en/development/tests/) <!--hide-->
|
||||
1
docs/ja/development/tests.md
Symbolic link
1
docs/ja/development/tests.md
Symbolic link
@ -0,0 +1 @@
|
||||
../../en/development/tests.md
|
||||
@ -142,7 +142,7 @@ ClickHouse использует для сборки некоторое коли
|
||||
|
||||
Для установки GCC под Ubuntu, выполните: `sudo apt install gcc g++`.
|
||||
|
||||
Проверьте версию gcc: `gcc --version`. Если версия меньше 9, то следуйте инструкции: https://clickhouse.tech/docs/ru/development/build/#install-gcc-9.
|
||||
Проверьте версию gcc: `gcc --version`. Если версия меньше 10, то следуйте инструкции: https://clickhouse.tech/docs/ru/development/build/#install-gcc-10.
|
||||
|
||||
Сборка под Mac OS X поддерживается только для компилятора Clang. Чтобы установить его выполните `brew install llvm`
|
||||
|
||||
@ -162,7 +162,7 @@ ClickHouse использует для сборки некоторое коли
|
||||
|
||||
Linux:
|
||||
|
||||
export CC=gcc-9 CXX=g++-9
|
||||
export CC=gcc-10 CXX=g++-10
|
||||
cmake ..
|
||||
|
||||
Mac OS X:
|
||||
|
||||
@ -159,6 +159,22 @@ Kafka(kafka_broker_list, kafka_topic_list, kafka_group_name, kafka_format
|
||||
|
||||
В документе [librdkafka configuration reference](https://github.com/edenhill/librdkafka/blob/master/CONFIGURATION.md) можно увидеть список возможных опций конфигурации. Используйте подчеркивание (`_`) вместо точки в конфигурации ClickHouse. Например, `check.crcs=true` будет соответствовать `<check_crcs>true</check_crcs>`.
|
||||
|
||||
### Поддержка Kerberos {#kafka-kerberos-support}
|
||||
|
||||
Чтобы начать работу с Kafka с поддержкой Kerberos, добавьте дочерний элемент `security_protocol` со значением `sasl_plaintext`. Этого будет достаточно, если получен тикет на получение тикета (ticket-granting ticket) Kerberos и он кэшируется средствами ОС.
|
||||
ClickHouse может поддерживать учетные данные Kerberos с помощью файла keytab. Рассмотрим дочерние элементы `sasl_kerberos_service_name`, `sasl_kerberos_keytab`, `sasl_kerberos_principal` и `sasl.kerberos.kinit.cmd`.
|
||||
|
||||
Пример:
|
||||
|
||||
``` xml
|
||||
<!-- Kerberos-aware Kafka -->
|
||||
<kafka>
|
||||
<security_protocol>SASL_PLAINTEXT</security_protocol>
|
||||
<sasl_kerberos_keytab>/home/kafkauser/kafkauser.keytab</sasl_kerberos_keytab>
|
||||
<sasl_kerberos_principal>kafkauser/kafkahost@EXAMPLE.COM</sasl_kerberos_principal>
|
||||
</kafka>
|
||||
```
|
||||
|
||||
## Виртуальные столбцы {#virtualnye-stolbtsy}
|
||||
|
||||
- `_topic` — топик Kafka.
|
||||
|
||||
@ -79,6 +79,7 @@ ORDER BY expr
|
||||
|
||||
- `index_granularity` — максимальное количество строк данных между засечками индекса. По умолчанию — 8192. Смотрите [Хранение данных](#mergetree-data-storage).
|
||||
- `index_granularity_bytes` — максимальный размер гранул данных в байтах. По умолчанию — 10Mb. Чтобы ограничить размер гранул только количеством строк, установите значение 0 (не рекомендовано). Смотрите [Хранение данных](#mergetree-data-storage).
|
||||
- `min_index_granularity_bytes` — минимально допустимый размер гранул данных в байтах. Значение по умолчанию — 1024b. Для обеспечения защиты от случайного создания таблиц с очень низким значением `index_granularity_bytes`. Смотрите [Хранение данных](#mergetree-data-storage).
|
||||
- `enable_mixed_granularity_parts` — включает или выключает переход к ограничению размера гранул с помощью настройки `index_granularity_bytes`. Настройка `index_granularity_bytes` улучшает производительность ClickHouse при выборке данных из таблиц с большими (десятки и сотни мегабайтов) строками. Если у вас есть таблицы с большими строками, можно включить эту настройку, чтобы повысить эффективность запросов `SELECT`.
|
||||
- `use_minimalistic_part_header_in_zookeeper` — Способ хранения заголовков кусков данных в ZooKeeper. Если `use_minimalistic_part_header_in_zookeeper = 1`, то ZooKeeper хранит меньше данных. Подробнее читайте в [описании настройки](../../../operations/server-configuration-parameters/settings.md#server-settings-use_minimalistic_part_header_in_zookeeper) в разделе "Конфигурационные параметры сервера".
|
||||
- `min_merge_bytes_to_use_direct_io` — минимальный объём данных при слиянии, необходимый для прямого (небуферизованного) чтения/записи (direct I/O) на диск. При слиянии частей данных ClickHouse вычисляет общий объём хранения всех данных, подлежащих слиянию. Если общий объём хранения всех данных для чтения превышает `min_bytes_to_use_direct_io` байт, тогда ClickHouse использует флаг `O_DIRECT` при чтении данных с диска. Если `min_merge_bytes_to_use_direct_io = 0`, тогда прямой ввод-вывод отключен. Значение по умолчанию: `10 * 1024 * 1024 * 1024` байтов.
|
||||
@ -331,8 +332,8 @@ INDEX b (u64 * length(str), i32 + f64 * 100, date, str) TYPE set(100) GRANULARIT
|
||||
|------------------------------------------------------------------------------------------------------------|-------------|--------|-------------|-------------|---------------|
|
||||
| [equals (=, ==)](../../../sql-reference/functions/comparison-functions.md#function-equals) | ✔ | ✔ | ✔ | ✔ | ✔ |
|
||||
| [notEquals(!=, \<\>)](../../../sql-reference/functions/comparison-functions.md#function-notequals) | ✔ | ✔ | ✔ | ✔ | ✔ |
|
||||
| [like](../../../sql-reference/functions/string-search-functions.md#function-like) | ✔ | ✔ | ✔ | ✗ | ✗ |
|
||||
| [notLike](../../../sql-reference/functions/string-search-functions.md#function-notlike) | ✔ | ✔ | ✔ | ✗ | ✗ |
|
||||
| [like](../../../sql-reference/functions/string-search-functions.md#function-like) | ✔ | ✔ | ✔ | ✔ | ✗ |
|
||||
| [notLike](../../../sql-reference/functions/string-search-functions.md#function-notlike) | ✔ | ✔ | ✔ | ✔ | ✗ |
|
||||
| [startsWith](../../../sql-reference/functions/string-functions.md#startswith) | ✔ | ✔ | ✔ | ✔ | ✗ |
|
||||
| [endsWith](../../../sql-reference/functions/string-functions.md#endswith) | ✗ | ✗ | ✔ | ✔ | ✗ |
|
||||
| [multiSearchAny](../../../sql-reference/functions/string-search-functions.md#function-multisearchany) | ✗ | ✗ | ✔ | ✗ | ✗ |
|
||||
|
||||
@ -64,6 +64,6 @@ CREATE TABLE merge.hits_buffer AS merge.hits ENGINE = Buffer(merge, hits, 16, 10
|
||||
|
||||
Таблицы типа Buffer используются в тех случаях, когда от большого количества серверов поступает слишком много INSERT-ов в единицу времени, и нет возможности заранее самостоятельно буферизовать данные перед вставкой, в результате чего, INSERT-ы не успевают выполняться.
|
||||
|
||||
Заметим, что даже для таблиц типа Buffer не имеет смысла вставлять данные по одной строке, так как таким образом будет достигнута скорость всего лишь в несколько тысяч строк в секунду, тогда как при вставке более крупными блоками, достижимо более миллиона строк в секунду (смотрите раздел «Производительность»).
|
||||
Заметим, что даже для таблиц типа Buffer не имеет смысла вставлять данные по одной строке, так как таким образом будет достигнута скорость всего лишь в несколько тысяч строк в секунду, тогда как при вставке более крупными блоками, достижимо более миллиона строк в секунду (смотрите раздел [«Производительность»](../../../introduction/performance/).
|
||||
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/ru/operations/table_engines/buffer/) <!--hide-->
|
||||
|
||||
@ -95,6 +95,7 @@ SELECT joinGet('id_val_join', 'val', toUInt32(1))
|
||||
- [max_bytes_in_join](../../../operations/settings/query-complexity.md#settings-max_bytes_in_join)
|
||||
- [join_overflow_mode](../../../operations/settings/query-complexity.md#settings-join_overflow_mode)
|
||||
- [join_any_take_last_row](../../../operations/settings/settings.md#settings-join_any_take_last_row)
|
||||
- [persistent](../../../operations/settings/settings.md#persistent)
|
||||
|
||||
Таблицы с движком `Join` нельзя использовать в операциях `GLOBAL JOIN`.
|
||||
|
||||
|
||||
@ -14,4 +14,10 @@ toc_title: Set
|
||||
|
||||
При грубом перезапуске сервера, блок данных на диске может быть потерян или повреждён. В последнем случае, может потребоваться вручную удалить файл с повреждёнными данными.
|
||||
|
||||
### Ограничения и настройки {#join-limitations-and-settings}
|
||||
|
||||
При создании таблицы, применяются следующие параметры:
|
||||
|
||||
- [persistent](../../../operations/settings/settings.md#persistent)
|
||||
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/ru/operations/table_engines/set/) <!--hide-->
|
||||
|
||||
@ -76,8 +76,11 @@ ECT 1
|
||||
```
|
||||
|
||||
По умолчанию, данные возвращаются в формате TabSeparated (подробнее смотри раздел «Форматы»).
|
||||
|
||||
Можно попросить любой другой формат - с помощью секции FORMAT запроса.
|
||||
|
||||
Кроме того, вы можете использовать параметр URL-адреса `default_format` или заголовок `X-ClickHouse-Format`, чтобы указать формат по умолчанию, отличный от `TabSeparated`.
|
||||
|
||||
``` bash
|
||||
$ echo 'SELECT 1 FORMAT Pretty' | curl 'http://localhost:8123/?' --data-binary @-
|
||||
┏━━━┓
|
||||
@ -168,7 +171,7 @@ $ echo "SELECT 1" | gzip -c | curl -sS --data-binary @- -H 'Content-Encoding: gz
|
||||
!!! note "Примечание"
|
||||
Некоторые HTTP-клиенты могут по умолчанию распаковывать данные (`gzip` и `deflate`) с сервера в фоновом режиме и вы можете получить распакованные данные, даже если правильно используете настройки сжатия.
|
||||
|
||||
В параметре URL database может быть указана БД по умолчанию.
|
||||
Вы можете использовать параметр URL `database` или заголовок `X-ClickHouse-Database`, чтобы указать БД по умолчанию.
|
||||
|
||||
``` bash
|
||||
$ echo 'SELECT number FROM numbers LIMIT 10' | curl 'http://localhost:8123/?database=system' --data-binary @-
|
||||
|
||||
@ -467,6 +467,26 @@ ClickHouse проверяет условия для `min_part_size` и `min_part
|
||||
<max_concurrent_queries>100</max_concurrent_queries>
|
||||
```
|
||||
|
||||
## max_concurrent_queries_for_all_users {#max-concurrent-queries-for-all-users}
|
||||
|
||||
Если значение этой настройки меньше или равно текущему количеству одновременно обрабатываемых запросов, то будет сгенерировано исключение.
|
||||
|
||||
Пример: `max_concurrent_queries_for_all_users` установлен на 99 для всех пользователей. Чтобы выполнять запросы даже когда сервер перегружен, администратор баз данных устанавливает для себя значение настройки на 100.
|
||||
|
||||
Изменение настройки для одного запроса или пользователя не влияет на другие запросы.
|
||||
|
||||
Значение по умолчанию: `0` — отсутствие ограничений.
|
||||
|
||||
**Пример**
|
||||
|
||||
``` xml
|
||||
<max_concurrent_queries_for_all_users>99</max_concurrent_queries_for_all_users>
|
||||
```
|
||||
|
||||
**Смотрите также**
|
||||
|
||||
- [max_concurrent_queries](#max-concurrent-queries)
|
||||
|
||||
## max_connections {#max-connections}
|
||||
|
||||
Максимальное количество входящих соединений.
|
||||
@ -535,6 +555,22 @@ ClickHouse проверяет условия для `min_part_size` и `min_part
|
||||
</merge_tree>
|
||||
```
|
||||
|
||||
## replicated\_merge\_tree {#server_configuration_parameters-replicated_merge_tree}
|
||||
|
||||
Тонкая настройка таблиц в [ReplicatedMergeTree](../../engines/table-engines/mergetree-family/mergetree.md).
|
||||
|
||||
Эта настройка имеет более высокий приоритет.
|
||||
|
||||
Подробнее смотрите в заголовочном файле MergeTreeSettings.h.
|
||||
|
||||
**Пример**
|
||||
|
||||
``` xml
|
||||
<replicated_merge_tree>
|
||||
<max_suspicious_broken_parts>5</max_suspicious_broken_parts>
|
||||
</replicated_merge_tree>
|
||||
```
|
||||
|
||||
## openSSL {#server_configuration_parameters-openssl}
|
||||
|
||||
Настройки клиента/сервера SSL.
|
||||
|
||||
@ -2082,4 +2082,17 @@ SELECT CAST(toNullable(toInt32(0)) AS Int32) as x, toTypeName(x);
|
||||
|
||||
- Функция [CAST](../../sql-reference/functions/type-conversion-functions.md#type_conversion_function-cast)
|
||||
|
||||
## persistent {#persistent}
|
||||
|
||||
Отключает перманентность для табличных движков [Set](../../engines/table-engines/special/set.md#set) и [Join](../../engines/table-engines/special/join.md#join).
|
||||
|
||||
Уменьшает расходы на ввод/вывод. Может быть полезно, когда требуется высокая производительность, а перманентность не обязательна.
|
||||
|
||||
Возможные значения:
|
||||
|
||||
- 1 — включено.
|
||||
- 0 — отключено.
|
||||
|
||||
Значение по умолчанию: `1`.
|
||||
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/ru/operations/settings/settings/) <!--hide-->
|
||||
|
||||
@ -5,6 +5,7 @@
|
||||
Столбцы:
|
||||
- `event_date` ([Date](../../sql-reference/data-types/date.md)) — дата события.
|
||||
- `event_time` ([DateTime](../../sql-reference/data-types/datetime.md)) — время события.
|
||||
- `event_time_microseconds` ([DateTime64](../../sql-reference/data-types/datetime64.md)) — время события в микросекундах.
|
||||
- `name` ([String](../../sql-reference/data-types/string.md)) — название метрики.
|
||||
- `value` ([Float64](../../sql-reference/data-types/float.md)) — значение метрики.
|
||||
|
||||
|
||||
@ -6,19 +6,21 @@
|
||||
|
||||
Таблица `system.columns` содержит столбцы (тип столбца указан в скобках):
|
||||
|
||||
- `database` (String) — имя базы данных.
|
||||
- `table` (String) — имя таблицы.
|
||||
- `name` (String) — имя столбца.
|
||||
- `type` (String) — тип столбца.
|
||||
- `default_kind` (String) — тип выражения (`DEFAULT`, `MATERIALIZED`, `ALIAS`) значения по умолчанию, или пустая строка.
|
||||
- `default_expression` (String) — выражение для значения по умолчанию или пустая строка.
|
||||
- `data_compressed_bytes` (UInt64) — размер сжатых данных в байтах.
|
||||
- `data_uncompressed_bytes` (UInt64) — размер распакованных данных в байтах.
|
||||
- `marks_bytes` (UInt64) — размер засечек в байтах.
|
||||
- `comment` (String) — комментарий к столбцу или пустая строка.
|
||||
- `is_in_partition_key` (UInt8) — флаг, показывающий включение столбца в ключ партиционирования.
|
||||
- `is_in_sorting_key` (UInt8) — флаг, показывающий включение столбца в ключ сортировки.
|
||||
- `is_in_primary_key` (UInt8) — флаг, показывающий включение столбца в первичный ключ.
|
||||
- `is_in_sampling_key` (UInt8) — флаг, показывающий включение столбца в ключ выборки.
|
||||
- `database` ([String](../../sql-reference/data-types/string.md)) — имя базы данных.
|
||||
- `table` ([String](../../sql-reference/data-types/string.md)) — имя таблицы.
|
||||
- `name` ([String](../../sql-reference/data-types/string.md)) — имя столбца.
|
||||
- `type` ([String](../../sql-reference/data-types/string.md)) — тип столбца.
|
||||
- `position` ([UInt64](../../sql-reference/data-types/int-uint.md)) — порядковый номер столбца в таблице (нумерация начинается с 1).
|
||||
- `default_kind` ([String](../../sql-reference/data-types/string.md)) — тип выражения (`DEFAULT`, `MATERIALIZED`, `ALIAS`) для значения по умолчанию или пустая строка.
|
||||
- `default_expression` ([String](../../sql-reference/data-types/string.md)) — выражение для значения по умолчанию или пустая строка.
|
||||
- `data_compressed_bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — размер сжатых данных в байтах.
|
||||
- `data_uncompressed_bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — размер распакованных данных в байтах.
|
||||
- `marks_bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — размер засечек в байтах.
|
||||
- `comment` ([String](../../sql-reference/data-types/string.md)) — комментарий к столбцу или пустая строка.
|
||||
- `is_in_partition_key` ([UInt8](../../sql-reference/data-types/int-uint.md)) — флаг, показывающий включение столбца в ключ партиционирования.
|
||||
- `is_in_sorting_key` ([UInt8](../../sql-reference/data-types/int-uint.md)) — флаг, показывающий включение столбца в ключ сортировки.
|
||||
- `is_in_primary_key` ([UInt8](../../sql-reference/data-types/int-uint.md)) — флаг, показывающий включение столбца в первичный ключ.
|
||||
- `is_in_sampling_key` ([UInt8](../../sql-reference/data-types/int-uint.md)) — флаг, показывающий включение столбца в ключ выборки.
|
||||
- `compression_codec` ([String](../../sql-reference/data-types/string.md)) — имя кодека сжатия.
|
||||
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/ru/operations/system_tables/columns) <!--hide-->
|
||||
|
||||
@ -1,6 +1,7 @@
|
||||
# system.metric_log {#system_tables-metric_log}
|
||||
|
||||
Содержит историю значений метрик из таблиц `system.metrics` и `system.events`, периодически сбрасываемую на диск.
|
||||
|
||||
Для включения сбора истории метрик в таблице `system.metric_log` создайте `/etc/clickhouse-server/config.d/metric_log.xml` следующего содержания:
|
||||
|
||||
``` xml
|
||||
@ -14,6 +15,11 @@
|
||||
</yandex>
|
||||
```
|
||||
|
||||
Столбцы:
|
||||
- `event_date` ([Date](../../sql-reference/data-types/date.md)) — дата события.
|
||||
- `event_time` ([DateTime](../../sql-reference/data-types/datetime.md)) — время события.
|
||||
- `event_time_microseconds` ([DateTime64](../../sql-reference/data-types/datetime64.md)) — время события в микросекундах.
|
||||
|
||||
**Пример**
|
||||
|
||||
``` sql
|
||||
|
||||
148
docs/ru/operations/system-tables/parts_columns.md
Normal file
148
docs/ru/operations/system-tables/parts_columns.md
Normal file
@ -0,0 +1,148 @@
|
||||
# system.parts_columns {#system_tables-parts_columns}
|
||||
|
||||
Содержит информацию о кусках данных и столбцах таблиц семейства [MergeTree](../../engines/table-engines/mergetree-family/mergetree.md).
|
||||
|
||||
Каждая строка описывает один кусок данных.
|
||||
|
||||
Столбцы:
|
||||
|
||||
- `partition` ([String](../../sql-reference/data-types/string.md)) — имя партиции. Что такое партиция вы можете узнать из описания запроса [ALTER](../../sql-reference/statements/alter/index.md#query_language_queries_alter).
|
||||
|
||||
Форматы:
|
||||
|
||||
- `YYYYMM` для автоматической схемы партиционирования по месяцам.
|
||||
- `any_string` при партиционировании вручную.
|
||||
|
||||
- `name` ([String](../../sql-reference/data-types/string.md)) — имя куска данных.
|
||||
|
||||
- `part_type` ([String](../../sql-reference/data-types/string.md)) — формат хранения данных.
|
||||
|
||||
Возможные значения:
|
||||
|
||||
- `Wide` — каждая колонка хранится в отдельном файле.
|
||||
- `Compact` — все колонки хранятся в одном файле.
|
||||
|
||||
Формат хранения данных определяется настройками `min_bytes_for_wide_part` и `min_rows_for_wide_part` таблицы [MergeTree](../../engines/table-engines/mergetree-family/mergetree.md).
|
||||
|
||||
- `active` ([UInt8](../../sql-reference/data-types/int-uint.md)) — признак активности. Если кусок данных активен, то он используется таблицей, в противном случае он будет удален. Неактивные куски остаются после слияний.
|
||||
|
||||
- `marks` ([UInt64](../../sql-reference/data-types/int-uint.md)) — количество засечек. Чтобы получить примерное количество строк в куске данных, умножьте `marks` на гранулированность индекса (обычно 8192).
|
||||
|
||||
- `rows` ([UInt64](../../sql-reference/data-types/int-uint.md)) — количество строк.
|
||||
|
||||
- `bytes_on_disk` ([UInt64](../../sql-reference/data-types/int-uint.md)) — общий размер всех файлов кусков данных в байтах.
|
||||
|
||||
- `data_compressed_bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — общий размер сжатой информации в куске данных. Размер всех дополнительных файлов (например, файлов с засечками) не учитывается.
|
||||
|
||||
- `data_uncompressed_bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — общий размер распакованной информации в куске данных. Размер всех дополнительных файлов (например, файлов с засечками) не учитывается.
|
||||
|
||||
- `marks_bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — размер файла с засечками.
|
||||
|
||||
- `modification_time` ([DateTime](../../sql-reference/data-types/datetime.md)) — время модификации директории с куском данных. Обычно соответствует времени создания куска.
|
||||
|
||||
- `remove_time` ([DateTime](../../sql-reference/data-types/datetime.md)) — время, когда кусок данных стал неактивным.
|
||||
|
||||
- `refcount` ([UInt32](../../sql-reference/data-types/int-uint.md)) — количество мест, в котором кусок данных используется. Значение больше 2 говорит о том, что кусок участвует в запросах или в слияниях.
|
||||
|
||||
- `min_date` ([Date](../../sql-reference/data-types/date.md)) — минимальное значение ключа даты в куске данных.
|
||||
|
||||
- `max_date` ([Date](../../sql-reference/data-types/date.md)) — максимальное значение ключа даты в куске данных.
|
||||
|
||||
- `partition_id` ([String](../../sql-reference/data-types/string.md)) — ID партиции.
|
||||
|
||||
- `min_block_number` ([UInt64](../../sql-reference/data-types/int-uint.md)) — минимальное число кусков данных, из которых состоит текущий после слияния.
|
||||
|
||||
- `max_block_number` ([UInt64](../../sql-reference/data-types/int-uint.md)) — максимальное число кусков данных, из которых состоит текущий после слияния.
|
||||
|
||||
- `level` ([UInt32](../../sql-reference/data-types/int-uint.md)) — глубина дерева слияний. Если слияний не было, то `level=0`.
|
||||
|
||||
- `data_version` ([UInt64](../../sql-reference/data-types/int-uint.md)) — число, которое используется для определения того, какие мутации необходимо применить к куску данных (мутации с версией большей, чем `data_version`).
|
||||
|
||||
- `primary_key_bytes_in_memory` ([UInt64](../../sql-reference/data-types/int-uint.md)) — объём памяти в байтах, занимаемой значениями первичных ключей.
|
||||
|
||||
- `primary_key_bytes_in_memory_allocated` ([UInt64](../../sql-reference/data-types/int-uint.md)) — объём памяти в байтах, выделенный для размещения первичных ключей.
|
||||
|
||||
- `database` ([String](../../sql-reference/data-types/string.md)) — имя базы данных.
|
||||
|
||||
- `table` ([String](../../sql-reference/data-types/string.md)) — имя таблицы.
|
||||
|
||||
- `engine` ([String](../../sql-reference/data-types/string.md)) — имя движка таблицы, без параметров.
|
||||
|
||||
- `disk_name` ([String](../../sql-reference/data-types/string.md)) — имя диска, на котором находится кусок данных.
|
||||
|
||||
- `path` ([String](../../sql-reference/data-types/string.md)) — абсолютный путь к папке с файлами кусков данных.
|
||||
|
||||
- `column` ([String](../../sql-reference/data-types/string.md)) — имя столбца.
|
||||
|
||||
- `type` ([String](../../sql-reference/data-types/string.md)) — тип столбца.
|
||||
|
||||
- `column_position` ([UInt64](../../sql-reference/data-types/int-uint.md)) — порядковый номер столбца (нумерация начинается с 1).
|
||||
|
||||
- `default_kind` ([String](../../sql-reference/data-types/string.md)) — тип выражения (`DEFAULT`, `MATERIALIZED`, `ALIAS`) для значения по умолчанию или пустая строка.
|
||||
|
||||
- `default_expression` ([String](../../sql-reference/data-types/string.md)) — выражение для значения по умолчанию или пустая строка.
|
||||
|
||||
- `column_bytes_on_disk` ([UInt64](../../sql-reference/data-types/int-uint.md)) — общий размер столбца в байтах.
|
||||
|
||||
- `column_data_compressed_bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — общий размер сжатой информации в столбце в байтах.
|
||||
|
||||
- `column_data_uncompressed_bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — общий размер распакованной информации в столбце в байтах.
|
||||
|
||||
- `column_marks_bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — размер столбца с засечками в байтах.
|
||||
|
||||
- `bytes` ([UInt64](../../sql-reference/data-types/int-uint.md)) — алиас для `bytes_on_disk`.
|
||||
|
||||
- `marks_size` ([UInt64](../../sql-reference/data-types/int-uint.md)) — алиас для `marks_bytes`.
|
||||
|
||||
**Пример**
|
||||
|
||||
``` sql
|
||||
SELECT * FROM system.parts_columns LIMIT 1 FORMAT Vertical;
|
||||
```
|
||||
|
||||
``` text
|
||||
Row 1:
|
||||
──────
|
||||
partition: tuple()
|
||||
name: all_1_2_1
|
||||
part_type: Wide
|
||||
active: 1
|
||||
marks: 2
|
||||
rows: 2
|
||||
bytes_on_disk: 155
|
||||
data_compressed_bytes: 56
|
||||
data_uncompressed_bytes: 4
|
||||
marks_bytes: 96
|
||||
modification_time: 2020-09-23 10:13:36
|
||||
remove_time: 2106-02-07 06:28:15
|
||||
refcount: 1
|
||||
min_date: 1970-01-01
|
||||
max_date: 1970-01-01
|
||||
partition_id: all
|
||||
min_block_number: 1
|
||||
max_block_number: 2
|
||||
level: 1
|
||||
data_version: 1
|
||||
primary_key_bytes_in_memory: 2
|
||||
primary_key_bytes_in_memory_allocated: 64
|
||||
database: default
|
||||
table: 53r93yleapyears
|
||||
engine: MergeTree
|
||||
disk_name: default
|
||||
path: /var/lib/clickhouse/data/default/53r93yleapyears/all_1_2_1/
|
||||
column: id
|
||||
type: Int8
|
||||
column_position: 1
|
||||
default_kind:
|
||||
default_expression:
|
||||
column_bytes_on_disk: 76
|
||||
column_data_compressed_bytes: 28
|
||||
column_data_uncompressed_bytes: 2
|
||||
column_marks_bytes: 48
|
||||
```
|
||||
|
||||
**Смотрите также**
|
||||
|
||||
- [Движок MergeTree](../../engines/table-engines/mergetree-family/mergetree.md)
|
||||
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/en/operations/system_tables/parts_columns) <!--hide-->
|
||||
@ -14,6 +14,8 @@ toc_title: clickhouse-local
|
||||
!!! warning "Warning"
|
||||
Мы не рекомендуем подключать серверную конфигурацию к `clickhouse-local`, поскольку данные можно легко повредить неосторожными действиями.
|
||||
|
||||
Для временных данных по умолчанию создается специальный каталог. Если вы хотите обойти это действие, каталог данных можно указать с помощью опции `-- --path`.
|
||||
|
||||
## Вызов программы {#vyzov-programmy}
|
||||
|
||||
Основной формат вызова:
|
||||
@ -39,25 +41,51 @@ $ clickhouse-local --structure "table_structure" --input-format "format_of_incom
|
||||
## Примеры вызова {#primery-vyzova}
|
||||
|
||||
``` bash
|
||||
$ echo -e "1,2\n3,4" | clickhouse-local -S "a Int64, b Int64" -if "CSV" -q "SELECT * FROM table"
|
||||
$ echo -e "1,2\n3,4" | clickhouse-local --structure "a Int64, b Int64" \
|
||||
--input-format "CSV" --query "SELECT * FROM table"
|
||||
Read 2 rows, 32.00 B in 0.000 sec., 5182 rows/sec., 80.97 KiB/sec.
|
||||
1 2
|
||||
3 4
|
||||
1 2
|
||||
3 4
|
||||
```
|
||||
|
||||
Вызов выше эквивалентен следующему:
|
||||
|
||||
``` bash
|
||||
$ echo -e "1,2\n3,4" | clickhouse-local -q "CREATE TABLE table (a Int64, b Int64) ENGINE = File(CSV, stdin); SELECT a, b FROM table; DROP TABLE table"
|
||||
$ echo -e "1,2\n3,4" | clickhouse-local --query "
|
||||
CREATE TABLE table (a Int64, b Int64) ENGINE = File(CSV, stdin);
|
||||
SELECT a, b FROM table;
|
||||
DROP TABLE table"
|
||||
Read 2 rows, 32.00 B in 0.000 sec., 4987 rows/sec., 77.93 KiB/sec.
|
||||
1 2
|
||||
3 4
|
||||
1 2
|
||||
3 4
|
||||
```
|
||||
|
||||
|
||||
Необязательно использовать ключи `stdin` или `--file`. Вы можете открывать любое количество файлов с помощью [табличной функции `file`](../../sql-reference/table-functions/file.md):
|
||||
|
||||
``` bash
|
||||
$ echo 1 | tee 1.tsv
|
||||
1
|
||||
|
||||
$ echo 2 | tee 2.tsv
|
||||
2
|
||||
|
||||
$ clickhouse-local --query "
|
||||
select * from file('1.tsv', TSV, 'a int') t1
|
||||
cross join file('2.tsv', TSV, 'b int') t2"
|
||||
1 2
|
||||
```
|
||||
|
||||
А теперь давайте выведем на экран объём оперативной памяти, занимаемой пользователями (Unix):
|
||||
|
||||
``` bash
|
||||
$ ps aux | tail -n +2 | awk '{ printf("%s\t%s\n", $1, $4) }' | clickhouse-local -S "user String, mem Float64" -q "SELECT user, round(sum(mem), 2) as memTotal FROM table GROUP BY user ORDER BY memTotal DESC FORMAT Pretty"
|
||||
$ ps aux | tail -n +2 | awk '{ printf("%s\t%s\n", $1, $4) }' \
|
||||
| clickhouse-local --structure "user String, mem Float64" \
|
||||
--query "SELECT user, round(sum(mem), 2) as memTotal
|
||||
FROM table GROUP BY user ORDER BY memTotal DESC FORMAT Pretty"
|
||||
```
|
||||
|
||||
``` text
|
||||
Read 186 rows, 4.15 KiB in 0.035 sec., 5302 rows/sec., 118.34 KiB/sec.
|
||||
┏━━━━━━━━━━┳━━━━━━━━━━┓
|
||||
┃ user ┃ memTotal ┃
|
||||
|
||||
@ -55,6 +55,8 @@ toc_hidden: true
|
||||
- [quantile](../../../sql-reference/aggregate-functions/reference/quantile.md)
|
||||
- [quantiles](../../../sql-reference/aggregate-functions/reference/quantiles.md)
|
||||
- [quantileExact](../../../sql-reference/aggregate-functions/reference/quantileexact.md)
|
||||
- [quantileExactLow](../../../sql-reference/aggregate-functions/reference/quantileexact.md#quantileexactlow)
|
||||
- [quantileExactHigh](../../../sql-reference/aggregate-functions/reference/quantileexact.md#quantileexacthigh)
|
||||
- [quantileExactWeighted](../../../sql-reference/aggregate-functions/reference/quantileexactweighted.md)
|
||||
- [quantileTiming](../../../sql-reference/aggregate-functions/reference/quantiletiming.md)
|
||||
- [quantileTimingWeighted](../../../sql-reference/aggregate-functions/reference/quantiletimingweighted.md)
|
||||
|
||||
@ -32,6 +32,7 @@ quantileExact(level)(expr)
|
||||
- [Float64](../../../sql-reference/data-types/float.md) для входных данных числового типа.
|
||||
- [Date](../../../sql-reference/data-types/date.md), если входные значения имеют тип `Date`.
|
||||
- [DateTime](../../../sql-reference/data-types/datetime.md), если входные значения имеют тип `DateTime`.
|
||||
|
||||
**Пример**
|
||||
|
||||
Запрос:
|
||||
@ -48,6 +49,115 @@ SELECT quantileExact(number) FROM numbers(10)
|
||||
└───────────────────────┘
|
||||
```
|
||||
|
||||
# quantileExactLow {#quantileexactlow}
|
||||
|
||||
Как и `quantileExact`, эта функция вычисляет точный [квантиль](https://en.wikipedia.org/wiki/Quantile) числовой последовательности данных.
|
||||
|
||||
Чтобы получить точное значение, все переданные значения объединяются в массив, который затем полностью сортируется. Сложность [алгоритма сортировки](https://en.cppreference.com/w/cpp/algorithm/sort) равна `O(N·log(N))`, где `N = std::distance(first, last)`.
|
||||
|
||||
Возвращаемое значение зависит от уровня квантили и количества элементов в выборке, то есть если уровень 0,5, то функция возвращает нижнюю медиану при чётном количестве элементов и медиану при нечётном. Медиана вычисляется аналогично реализации [median_low](https://docs.python.org/3/library/statistics.html#statistics.median_low), которая используется в python.
|
||||
|
||||
Для всех остальных уровней возвращается элемент с индексом, соответствующим значению `level * size_of_array`. Например:
|
||||
|
||||
``` sql
|
||||
SELECT quantileExactLow(0.1)(number) FROM numbers(10)
|
||||
|
||||
┌─quantileExactLow(0.1)(number)─┐
|
||||
│ 1 │
|
||||
└───────────────────────────────┘
|
||||
```
|
||||
|
||||
При использовании в запросе нескольких функций `quantile*` с разными уровнями, внутренние состояния не объединяются (то есть запрос работает менее эффективно). В этом случае используйте функцию [quantiles](../../../sql-reference/aggregate-functions/reference/quantiles.md#quantiles).
|
||||
|
||||
**Синтаксис**
|
||||
|
||||
``` sql
|
||||
quantileExact(level)(expr)
|
||||
```
|
||||
|
||||
Алиас: `medianExactLow`.
|
||||
|
||||
**Параметры**
|
||||
|
||||
- `level` — Уровень квантили. Опциональный параметр. Константное занчение с плавающей запятой от 0 до 1. Мы рекомендуем использовать значение `level` из диапазона `[0.01, 0.99]`. Значение по умолчанию: 0.5. При `level=0.5` функция вычисляет [медиану](https://en.wikipedia.org/wiki/Median).
|
||||
- `expr` — Выражение над значениями столбца, которое возвращает данные [числовых типов](../../../sql-reference/data-types/index.md#data_types), [Date](../../../sql-reference/data-types/date.md) или [DateTime](../../../sql-reference/data-types/datetime.md).
|
||||
|
||||
**Возвращаемое значение**
|
||||
|
||||
- Квантиль заданного уровня.
|
||||
|
||||
Тип:
|
||||
|
||||
- [Float64](../../../sql-reference/data-types/float.md) для входных данных числового типа.
|
||||
- [Date](../../../sql-reference/data-types/date.md) если входные значения имеют тип `Date`.
|
||||
- [DateTime](../../../sql-reference/data-types/datetime.md) если входные значения имеют тип `DateTime`.
|
||||
|
||||
**Пример**
|
||||
|
||||
Запрос:
|
||||
|
||||
``` sql
|
||||
SELECT quantileExactLow(number) FROM numbers(10)
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
``` text
|
||||
┌─quantileExactLow(number)─┐
|
||||
│ 4 │
|
||||
└──────────────────────────┘
|
||||
```
|
||||
# quantileExactHigh {#quantileexacthigh}
|
||||
|
||||
Как и `quantileExact`, эта функция вычисляет точный [квантиль](https://en.wikipedia.org/wiki/Quantile) числовой последовательности данных.
|
||||
|
||||
Все переданные значения объединяются в массив, который затем сортируется, чтобы получить точное значение. Сложность [алгоритма сортировки](https://en.cppreference.com/w/cpp/algorithm/sort) равна `O(N·log(N))`, где `N = std::distance(first, last)`.
|
||||
|
||||
Возвращаемое значение зависит от уровня квантили и количества элементов в выборке, то есть если уровень 0,5, то функция возвращает верхнюю медиану при чётном количестве элементов и медиану при нечётном. Медиана вычисляется аналогично реализации [median_high](https://docs.python.org/3/library/statistics.html#statistics.median_high), которая используется в python. Для всех остальных уровней возвращается элемент с индексом, соответствующим значению `level * size_of_array`.
|
||||
|
||||
Эта реализация ведет себя точно так же, как `quantileExact`.
|
||||
|
||||
При использовании в запросе нескольких функций `quantile*` с разными уровнями, внутренние состояния не объединяются (то есть запрос работает менее эффективно). В этом случае используйте функцию [quantiles](../../../sql-reference/aggregate-functions/reference/quantiles.md#quantiles).
|
||||
|
||||
**Синтаксис**
|
||||
|
||||
``` sql
|
||||
quantileExactHigh(level)(expr)
|
||||
```
|
||||
|
||||
Алиас: `medianExactHigh`.
|
||||
|
||||
**Параметры**
|
||||
|
||||
- `level` — Уровень квантили. Опциональный параметр. Константное занчение с плавающей запятой от 0 до 1. Мы рекомендуем использовать значение `level` из диапазона `[0.01, 0.99]`. Значение по умолчанию: 0.5. При `level=0.5` функция вычисляет [медиану](https://en.wikipedia.org/wiki/Median).
|
||||
- `expr` — Выражение над значениями столбца, которое возвращает данные [числовых типов](../../../sql-reference/data-types/index.md#data_types), [Date](../../../sql-reference/data-types/date.md) или [DateTime](../../../sql-reference/data-types/datetime.md).
|
||||
|
||||
**Возвращаемое значение**
|
||||
|
||||
- Квантиль заданного уровня.
|
||||
|
||||
Тип:
|
||||
|
||||
- [Float64](../../../sql-reference/data-types/float.md) для входных данных числового типа.
|
||||
- [Date](../../../sql-reference/data-types/date.md) если входные значения имеют тип `Date`.
|
||||
- [DateTime](../../../sql-reference/data-types/datetime.md) если входные значения имеют тип `DateTime`.
|
||||
|
||||
**Пример**
|
||||
|
||||
Запрос:
|
||||
|
||||
``` sql
|
||||
SELECT quantileExactHigh(number) FROM numbers(10)
|
||||
```
|
||||
|
||||
Результат:
|
||||
|
||||
``` text
|
||||
┌─quantileExactHigh(number)─┐
|
||||
│ 5 │
|
||||
└───────────────────────────┘
|
||||
```
|
||||
|
||||
**Смотрите также**
|
||||
|
||||
- [median](../../../sql-reference/aggregate-functions/reference/median.md#median)
|
||||
|
||||
@ -54,6 +54,8 @@ LAYOUT(LAYOUT_TYPE(param value)) -- layout settings
|
||||
- [hashed](#dicts-external_dicts_dict_layout-hashed)
|
||||
- [sparse_hashed](#dicts-external_dicts_dict_layout-sparse_hashed)
|
||||
- [cache](#cache)
|
||||
- [ssd_cache](#ssd-cache)
|
||||
- [ssd_complex_key_cache](#complex-key-ssd-cache)
|
||||
- [direct](#direct)
|
||||
- [range_hashed](#range-hashed)
|
||||
- [complex_key_hashed](#complex-key-hashed)
|
||||
@ -299,6 +301,40 @@ LAYOUT(CACHE(SIZE_IN_CELLS 1000000000))
|
||||
|
||||
Тип размещения предназначен для использования с составными [ключами](external-dicts-dict-structure.md). Аналогичен `cache`.
|
||||
|
||||
### ssd_cache {#ssd-cache}
|
||||
|
||||
Похож на `cache`, но хранит данные на SSD и индекс в оперативной памяти.
|
||||
|
||||
``` xml
|
||||
<layout>
|
||||
<ssd_cache>
|
||||
<!-- Size of elementary read block in bytes. Recommended to be equal to SSD's page size. -->
|
||||
<block_size>4096</block_size>
|
||||
<!-- Max cache file size in bytes. -->
|
||||
<file_size>16777216</file_size>
|
||||
<!-- Size of RAM buffer in bytes for reading elements from SSD. -->
|
||||
<read_buffer_size>131072</read_buffer_size>
|
||||
<!-- Size of RAM buffer in bytes for aggregating elements before flushing to SSD. -->
|
||||
<write_buffer_size>1048576</write_buffer_size>
|
||||
<!-- Path where cache file will be stored. -->
|
||||
<path>/var/lib/clickhouse/clickhouse_dictionaries/test_dict</path>
|
||||
<!-- Max number on stored keys in the cache. Rounded up to a power of two. -->
|
||||
<max_stored_keys>1048576</max_stored_keys>
|
||||
</ssd_cache>
|
||||
</layout>
|
||||
```
|
||||
|
||||
или
|
||||
|
||||
``` sql
|
||||
LAYOUT(CACHE(BLOCK_SIZE 4096 FILE_SIZE 16777216 READ_BUFFER_SIZE 1048576
|
||||
PATH /var/lib/clickhouse/clickhouse_dictionaries/test_dict MAX_STORED_KEYS 1048576))
|
||||
```
|
||||
|
||||
### complex_key_ssd_cache {#complex-key-ssd-cache}
|
||||
|
||||
Тип размещения предназначен для использования с составными [ключами](../../../sql-reference/dictionaries/external-dictionaries/external-dicts-dict-structure.md). Похож на `ssd_cache`.
|
||||
|
||||
### direct {#direct}
|
||||
|
||||
Словарь не хранит данные локально и взаимодействует с источником непосредственно в момент запроса.
|
||||
|
||||
@ -1,4 +1,4 @@
|
||||
# Cловари полигонов {#slovari-polygonov}
|
||||
# Cловари полигонов {#polygon-dictionaries}
|
||||
|
||||
Словари полигонов позволяют эффективно искать полигон, в который попадают данные точки, среди множества полигонов.
|
||||
Для примера: определение района города по географическим координатам.
|
||||
|
||||
@ -927,6 +927,48 @@ SELECT defaultValueOfArgumentType( CAST(1 AS Nullable(Int8) ) )
|
||||
└───────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
## defaultValueOfTypeName {#defaultvalueoftypename}
|
||||
|
||||
Выводит значение по умолчанию для указанного типа данных.
|
||||
|
||||
Не включает значения по умолчанию для настраиваемых столбцов, установленных пользователем.
|
||||
|
||||
``` sql
|
||||
defaultValueOfTypeName(type)
|
||||
```
|
||||
|
||||
**Параметры:**
|
||||
|
||||
- `type` — тип данных.
|
||||
|
||||
**Возвращаемое значение**
|
||||
|
||||
- `0` для чисел;
|
||||
- Пустая строка для строк;
|
||||
- `ᴺᵁᴸᴸ` для [Nullable](../../sql-reference/data-types/nullable.md).
|
||||
|
||||
**Пример**
|
||||
|
||||
``` sql
|
||||
SELECT defaultValueOfTypeName('Int8')
|
||||
```
|
||||
|
||||
``` text
|
||||
┌─defaultValueOfTypeName('Int8')─┐
|
||||
│ 0 │
|
||||
└────────────────────────────────┘
|
||||
```
|
||||
|
||||
``` sql
|
||||
SELECT defaultValueOfTypeName('Nullable(Int8)')
|
||||
```
|
||||
|
||||
``` text
|
||||
┌─defaultValueOfTypeName('Nullable(Int8)')─┐
|
||||
│ ᴺᵁᴸᴸ │
|
||||
└──────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
## replicate {#other-functions-replicate}
|
||||
|
||||
Создает массив, заполненный одним значением.
|
||||
|
||||
@ -772,4 +772,43 @@ FROM numbers(3)
|
||||
│
|
||||
└──────────────────────────────────┘
|
||||
```
|
||||
|
||||
## formatRowNoNewline {#formatrownonewline}
|
||||
|
||||
Преобразует произвольные выражения в строку заданного формата. При этом удаляет лишние переводы строк `\n`, если они появились.
|
||||
|
||||
**Синтаксис**
|
||||
|
||||
``` sql
|
||||
formatRowNoNewline(format, x, y, ...)
|
||||
```
|
||||
|
||||
**Параметры**
|
||||
|
||||
- `format` — Текстовый формат. Например, [CSV](../../interfaces/formats.md#csv), [TSV](../../interfaces/formats.md#tabseparated).
|
||||
- `x`,`y`, ... — Выражения.
|
||||
|
||||
**Возвращаемое значение**
|
||||
|
||||
- Отформатированная строка (в текстовых форматах без завершающего перевода строки).
|
||||
|
||||
**Пример**
|
||||
|
||||
Запрос:
|
||||
|
||||
``` sql
|
||||
SELECT formatRowNoNewline('CSV', number, 'good')
|
||||
FROM numbers(3)
|
||||
```
|
||||
|
||||
Ответ:
|
||||
|
||||
``` text
|
||||
┌─formatRowNoNewline('CSV', number, 'good')─┐
|
||||
│ 0,"good" │
|
||||
│ 1,"good" │
|
||||
│ 2,"good" │
|
||||
└───────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
[Оригинальная статья](https://clickhouse.tech/docs/ru/query_language/functions/type_conversion_functions/) <!--hide-->
|
||||
|
||||
@ -59,6 +59,54 @@ SELECT toUUID('61f0c404-5cb3-11e7-907b-a6006ad3dba0') AS uuid
|
||||
└──────────────────────────────────────┘
|
||||
```
|
||||
|
||||
## toUUIDOrNull (x) {#touuidornull-x}
|
||||
|
||||
Принимает строку, и пытается преобразовать в тип UUID. При неудаче возвращает NULL.
|
||||
|
||||
``` sql
|
||||
toUUIDOrNull(String)
|
||||
```
|
||||
|
||||
**Возвращаемое значение**
|
||||
|
||||
Значение типа Nullable(UUID).
|
||||
|
||||
**Пример использования**
|
||||
|
||||
``` sql
|
||||
SELECT toUUIDOrNull('61f0c404-5cb3-11e7-907b-a6006ad3dba0T') AS uuid
|
||||
```
|
||||
|
||||
``` text
|
||||
┌─uuid─┐
|
||||
│ ᴺᵁᴸᴸ │
|
||||
└──────┘
|
||||
```
|
||||
|
||||
## toUUIDOrZero (x) {#touuidorzero-x}
|
||||
|
||||
Принимает строку, и пытается преобразовать в тип UUID. При неудаче возвращает нулевой UUID.
|
||||
|
||||
``` sql
|
||||
toUUIDOrZero(String)
|
||||
```
|
||||
|
||||
**Возвращаемое значение**
|
||||
|
||||
Значение типа UUID.
|
||||
|
||||
**Пример использования**
|
||||
|
||||
``` sql
|
||||
SELECT toUUIDOrZero('61f0c404-5cb3-11e7-907b-a6006ad3dba0T') AS uuid
|
||||
```
|
||||
|
||||
``` text
|
||||
┌─────────────────────────────────uuid─┐
|
||||
│ 00000000-0000-0000-0000-000000000000 │
|
||||
└──────────────────────────────────────┘
|
||||
```
|
||||
|
||||
## UUIDStringToNum {#uuidstringtonum}
|
||||
|
||||
Принимает строку, содержащую 36 символов в формате `xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx`, и возвращает в виде набора байт в [FixedString(16)](../../sql-reference/functions/uuid-functions.md).
|
||||
|
||||
@ -152,21 +152,43 @@ FROM test.Orders;
|
||||
- `QUARTER`
|
||||
- `YEAR`
|
||||
|
||||
В качестве значения оператора `INTERVAL` вы можете также использовать строковый литерал. Например, выражение `INTERVAL 1 HOUR` идентично выражению `INTERVAL '1 hour'` или `INTERVAL '1' hour`.
|
||||
|
||||
!!! warning "Внимание"
|
||||
Интервалы различных типов нельзя объединять. Нельзя использовать выражения вида `INTERVAL 4 DAY 1 HOUR`. Вместо этого интервалы можно выразить в единицах меньших или равных наименьшей единице интервала, Например, `INTERVAL 25 HOUR`. Также можно выполнять последовательные операции как показано в примере ниже.
|
||||
|
||||
Пример:
|
||||
Примеры:
|
||||
|
||||
``` sql
|
||||
SELECT now() AS current_date_time, current_date_time + INTERVAL 4 DAY + INTERVAL 3 HOUR
|
||||
SELECT now() AS current_date_time, current_date_time + INTERVAL 4 DAY + INTERVAL 3 HOUR;
|
||||
```
|
||||
|
||||
``` text
|
||||
┌───current_date_time─┬─plus(plus(now(), toIntervalDay(4)), toIntervalHour(3))─┐
|
||||
│ 2019-10-23 11:16:28 │ 2019-10-27 14:16:28 │
|
||||
│ 2020-11-03 22:09:50 │ 2020-11-08 01:09:50 │
|
||||
└─────────────────────┴────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
``` sql
|
||||
SELECT now() AS current_date_time, current_date_time + INTERVAL '4 day' + INTERVAL '3 hour';
|
||||
```
|
||||
|
||||
``` text
|
||||
┌───current_date_time─┬─plus(plus(now(), toIntervalDay(4)), toIntervalHour(3))─┐
|
||||
│ 2020-11-03 22:12:10 │ 2020-11-08 01:12:10 │
|
||||
└─────────────────────┴────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
``` sql
|
||||
SELECT now() AS current_date_time, current_date_time + INTERVAL '4' day + INTERVAL '3' hour;
|
||||
```
|
||||
|
||||
``` text
|
||||
┌───current_date_time─┬─plus(plus(now(), toIntervalDay('4')), toIntervalHour('3'))─┐
|
||||
│ 2020-11-03 22:33:19 │ 2020-11-08 01:33:19 │
|
||||
└─────────────────────┴────────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
**Смотрите также**
|
||||
|
||||
- Тип данных [Interval](../../sql-reference/operators/index.md)
|
||||
|
||||
@ -13,7 +13,7 @@ toc_title: "\u041f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u
|
||||
CREATE [OR REPLACE] VIEW [IF NOT EXISTS] [db.]table_name [ON CLUSTER] AS SELECT ...
|
||||
```
|
||||
|
||||
Normal views don’t store any data, they just perform a read from another table on each access. In other words, a normal view is nothing more than a saved query. When reading from a view, this saved query is used as a subquery in the [FROM](../../../sql-reference/statements/select/from.md) clause.
|
||||
Обычные представления не хранят никаких данных, они выполняют чтение данных из другой таблицы при каждом доступе. Другими словами, обычное представление - это не что иное, как сохраненный запрос. При чтении данных из представления этот сохраненный запрос используется как подзапрос в секции [FROM](../../../sql-reference/statements/select/from.md).
|
||||
|
||||
Для примера, пусть вы создали представление:
|
||||
|
||||
|
||||
@ -18,7 +18,7 @@ Markdown==3.3.2
|
||||
MarkupSafe==1.1.1
|
||||
mkdocs==1.1.2
|
||||
mkdocs-htmlproofer-plugin==0.0.3
|
||||
mkdocs-macros-plugin==0.4.17
|
||||
mkdocs-macros-plugin==0.4.20
|
||||
nltk==3.5
|
||||
nose==1.3.7
|
||||
protobuf==3.13.0
|
||||
|
||||
@ -19,7 +19,7 @@ $ sudo apt-get install git cmake python ninja-build
|
||||
|
||||
Veya eski sistemlerde cmake yerine cmake3.
|
||||
|
||||
## Gcc 9'u yükle {#install-gcc-9}
|
||||
## Gcc 10'u yükle {#install-gcc-10}
|
||||
|
||||
Bunu yapmak için çeşitli yollar vardır.
|
||||
|
||||
@ -29,18 +29,18 @@ Bunu yapmak için çeşitli yollar vardır.
|
||||
$ sudo apt-get install software-properties-common
|
||||
$ sudo apt-add-repository ppa:ubuntu-toolchain-r/test
|
||||
$ sudo apt-get update
|
||||
$ sudo apt-get install gcc-9 g++-9
|
||||
$ sudo apt-get install gcc-10 g++-10
|
||||
```
|
||||
|
||||
### Kaynaklardan yükleyin {#install-from-sources}
|
||||
|
||||
Bakmak [utils/ci/build-gcc-from-sources.sh](https://github.com/ClickHouse/ClickHouse/blob/master/utils/ci/build-gcc-from-sources.sh)
|
||||
|
||||
## Yapılar için GCC 9 kullanın {#use-gcc-9-for-builds}
|
||||
## Yapılar için GCC 10 kullanın {#use-gcc-10-for-builds}
|
||||
|
||||
``` bash
|
||||
$ export CC=gcc-9
|
||||
$ export CXX=g++-9
|
||||
$ export CC=gcc-10
|
||||
$ export CXX=g++-10
|
||||
```
|
||||
|
||||
## Checkout ClickHouse Kaynakları {#checkout-clickhouse-sources}
|
||||
@ -76,7 +76,7 @@ Yapı aşağıdaki bileşenleri gerektirir:
|
||||
- Git (yalnızca kaynakları kontrol etmek için kullanılır, yapı için gerekli değildir)
|
||||
- Cmake 3.10 veya daha yeni
|
||||
- Ninja (önerilir) veya yapmak
|
||||
- C ++ derleyici: gcc 9 veya clang 8 veya daha yeni
|
||||
- C ++ derleyici: gcc 10 veya clang 8 veya daha yeni
|
||||
- Linker :lld veya altın (klasik GNU ld çalışmaz)
|
||||
- Python (sadece LLVM yapısında kullanılır ve isteğe bağlıdır)
|
||||
|
||||
|
||||
@ -141,7 +141,7 @@ Resmi Yandex şu anda GCC'Yİ kullanıyor çünkü biraz daha iyi performansa sa
|
||||
|
||||
Ubuntu run GCC yüklemek için: `sudo apt install gcc g++`
|
||||
|
||||
Gcc sürümünü kontrol edin: `gcc --version`. 9'un altındaysa, buradaki talimatları izleyin: https://clickhouse.tech/docs/tr/development/build/#install-gcc-9.
|
||||
Gcc sürümünü kontrol edin: `gcc --version`. 10'un altındaysa, buradaki talimatları izleyin: https://clickhouse.tech/docs/tr/development/build/#install-gcc-10.
|
||||
|
||||
Mac OS X build sadece Clang için desteklenir. Sadece koş `brew install llvm`
|
||||
|
||||
@ -160,7 +160,7 @@ Birkaç farklı dizine (build_release, build_debug, vb.) sahip olabilirsiniz.) f
|
||||
|
||||
Linux:
|
||||
|
||||
export CC=gcc-9 CXX=g++-9
|
||||
export CC=gcc-10 CXX=g++-10
|
||||
cmake ..
|
||||
|
||||
Mac OS X:
|
||||
|
||||
@ -1,262 +0,0 @@
|
||||
---
|
||||
machine_translated: true
|
||||
machine_translated_rev: 72537a2d527c63c07aa5d2361a8829f3895cf2bd
|
||||
toc_priority: 69
|
||||
toc_title: "ClickHouse testleri nas\u0131l \xE7al\u0131\u015Ft\u0131r\u0131l\u0131\
|
||||
r"
|
||||
---
|
||||
|
||||
# ClickHouse Testi {#clickhouse-testing}
|
||||
|
||||
## Fonksiyonel Testler {#functional-tests}
|
||||
|
||||
Fonksiyonel testler en basit ve kullanımı kolay olanlardır. ClickHouse özelliklerinin çoğu fonksiyonel testlerle test edilebilir ve bu şekilde test edilebilecek ClickHouse kodundaki her değişiklik için kullanılması zorunludur.
|
||||
|
||||
Her işlevsel test, çalışan ClickHouse sunucusuna bir veya birden çok sorgu gönderir ve sonucu referansla karşılaştırır.
|
||||
|
||||
Testler bulunur `queries` dizin. İki alt dizin var: `stateless` ve `stateful`. Durumsuz testler, önceden yüklenmiş test verileri olmadan sorguları çalıştırır - genellikle testin kendisinde anında küçük sentetik veri kümeleri oluştururlar. Durum bilgisi testleri, Yandex'ten önceden yüklenmiş test verileri gerektirir.Metrica ve halka açık değil. Biz sadece kullanmak eğilimindedir `stateless` testler ve yeni eklemekten kaçının `stateful` testler.
|
||||
|
||||
Her test iki tipten biri olabilir: `.sql` ve `.sh`. `.sql` test için borulu basit SQL komut dosyasıdır `clickhouse-client --multiquery --testmode`. `.sh` test kendisi tarafından çalıştırılan bir komut dosyasıdır.
|
||||
|
||||
Tüm testleri çalıştırmak için şunları kullanın `clickhouse-test` aracı. Bak `--help` Olası seçeneklerin listesi için. Sadece tüm testleri çalıştırmak veya test adı alt dize tarafından süzülmüş testlerin alt kümesini çalıştırabilirsiniz: `./clickhouse-test substring`.
|
||||
|
||||
Fonksiyonel testleri çağırmanın en basit yolu kopyalamaktır `clickhouse-client` -e doğru `/usr/bin/`, çalıştırmak `clickhouse-server` ve sonra koş `./clickhouse-test` kendi dizininden.
|
||||
|
||||
Yeni test eklemek için, bir `.sql` veya `.sh` dosya içinde `queries/0_stateless` dizin, elle kontrol edin ve sonra oluşturun `.reference` aşağıdaki şekilde dosya: `clickhouse-client -n --testmode < 00000_test.sql > 00000_test.reference` veya `./00000_test.sh > ./00000_test.reference`.
|
||||
|
||||
Testler yalnızca tabloları (create, drop, vb.) kullanmalıdır `test` önceden oluşturulduğu varsayılır veritabanı; ayrıca testler geçici tablolar kullanabilirsiniz.
|
||||
|
||||
İşlevsel testlerde dağıtılmış sorgular kullanmak istiyorsanız, kaldıraç `remote` tablo fonksiyonu ile `127.0.0.{1..2}` sunucunun kendisini sorgulaması için adresler; veya sunucu yapılandırma dosyasında önceden tanımlanmış test kümelerini kullanabilirsiniz `test_shard_localhost`.
|
||||
|
||||
Bazı testler ile işaretlenir `zookeeper`, `shard` veya `long` kendi adlarına.
|
||||
`zookeeper` ZooKeeper kullanan testler içindir. `shard` testler içindir
|
||||
dinlemek için sunucu gerektirir `127.0.0.*`; `distributed` veya `global` aynı var
|
||||
anlama. `long` bir saniye biraz daha uzun süren testler içindir. Yapabilirsin
|
||||
kullanarak bu test gruplarını devre dışı bırakın `--no-zookeeper`, `--no-shard` ve
|
||||
`--no-long` sırasıyla seçenekler.
|
||||
|
||||
## Bilinen Hatalar {#known-bugs}
|
||||
|
||||
Fonksiyonel testlerle kolayca çoğaltılabilen bazı hatalar biliyorsak, hazırlanmış fonksiyonel testleri `tests/queries/bugs` dizin. Bu testler taşınacaktır `tests/queries/0_stateless` hatalar düzeltildiğinde.
|
||||
|
||||
## Entegrasyon Testleri {#integration-tests}
|
||||
|
||||
Entegrasyon testleri, kümelenmiş konfigürasyonda Clickhouse'u ve MySQL, Postgres, MongoDB gibi diğer sunucularla ClickHouse etkileşimini test etmeyi sağlar. Ağ bölmelerini, paket damlalarını vb. taklit etmek için kullanışlıdırlar. Bu testler Docker altında çalıştırılır ve çeşitli yazılımlarla birden fazla konteyner oluşturur.
|
||||
|
||||
Görmek `tests/integration/README.md` bu testlerin nasıl çalıştırılacağı hakkında.
|
||||
|
||||
Clickhouse'un üçüncü taraf sürücülerle entegrasyonunun sınanmadığını unutmayın. Ayrıca şu anda JDBC ve ODBC sürücülerimizle entegrasyon testlerimiz yok.
|
||||
|
||||
## Ünite Testleri {#unit-tests}
|
||||
|
||||
Birim testleri, Clickhouse'u bir bütün olarak değil, tek bir yalıtılmış kitaplık veya sınıfı test etmek istediğinizde kullanışlıdır. Etkinleştirebilir veya devre dışı bırakma ile testlerin yapı `ENABLE_TESTS` Cmake seçeneği. Birim testleri (ve diğer test programları) bulunur `tests` kodun alt dizinleri. Birim testlerini çalıştırmak için şunları yazın `ninja test`. Bazı testler kullanın `gtest`, ancak bazıları test başarısızlığında sıfır olmayan çıkış kodunu döndüren programlardır.
|
||||
|
||||
Kodun zaten işlevsel testler tarafından kapsanması durumunda birim testlerine sahip olmak zorunlu değildir (ve işlevsel testler genellikle kullanımı çok daha basittir).
|
||||
|
||||
## Performans Testleri {#performance-tests}
|
||||
|
||||
Performans testleri ölçmek ve sentetik sorguları ClickHouse bazı izole kısmının performansını karşılaştırmak için izin verir. Testler bulunur `tests/performance`. Her test ile temsil edilir `.xml` test durumunun açıklaması ile dosya. Testler ile çalıştırılır `clickhouse performance-test` Aracı (Bu gömülü `clickhouse` ikilik). Görmek `--help` çağırma için.
|
||||
|
||||
Her test, durdurma için bazı koşullarla (örneğin, bir döngüde bir veya birden fazla sorgu (muhtemelen parametre kombinasyonlarıyla) çalıştırır “maximum execution speed is not changing in three seconds”) ve sorgu performansı ile ilgili bazı metrikleri ölçün (örneğin “maximum execution speed”). Bazı testler önceden yüklenmiş test veri kümesinde Önkoşullar içerebilir.
|
||||
|
||||
Bazı senaryoda Clickhouse'un performansını artırmak istiyorsanız ve basit sorgularda iyileştirmeler gözlemlenebiliyorsa, bir performans testi yazmanız önerilir. Her zaman kullanmak mantıklı `perf top` testleriniz sırasında veya diğer perf araçları.
|
||||
|
||||
## Test araçları ve komut dosyaları {#test-tools-and-scripts}
|
||||
|
||||
Bazı programlar `tests` dizin testleri hazırlanmış değil, ancak test araçlarıdır. Örneğin, için `Lexer` bir araç var `src/Parsers/tests/lexer` bu sadece stdin'in tokenizasyonunu yapar ve renklendirilmiş sonucu stdout'a yazar. Bu tür araçları kod örnekleri olarak ve keşif ve manuel test için kullanabilirsiniz.
|
||||
|
||||
Ayrıca Çift Dosya yerleştirebilirsiniz `.sh` ve `.reference` aracı ile birlikte bazı önceden tanımlanmış giriş üzerinde çalıştırmak için-daha sonra komut sonucu karşılaştırılabilir `.reference` Dosya. Bu tür testler otomatik değildir.
|
||||
|
||||
## Çeşitli Testler {#miscellaneous-tests}
|
||||
|
||||
Bulunan dış sözlükler için testler vardır `tests/external_dictionaries` ve makine öğrenilen modeller için `tests/external_models`. Bu testler güncelleştirilmez ve tümleştirme testlerine aktarılmalıdır.
|
||||
|
||||
Çekirdek ekler için ayrı bir test var. Bu test, ayrı sunucularda ClickHouse kümesini çalıştırır ve çeşitli arıza durumlarını taklit eder: ağ bölünmesi, paket bırakma (ClickHouse düğümleri arasında, ClickHouse ve ZooKeeper arasında, ClickHouse sunucusu ve istemci arasında, vb.), `kill -9`, `kill -STOP` ve `kill -CONT` , istemek [Jepsen](https://aphyr.com/tags/Jepsen). Daha sonra test, kabul edilen tüm eklerin yazıldığını ve reddedilen tüm eklerin olmadığını kontrol eder.
|
||||
|
||||
Clickhouse açık kaynaklı önce çekirdek testi ayrı ekip tarafından yazılmıştır. Bu takım artık ClickHouse ile çalışmıyor. Test yanlışlıkla Java ile yazılmıştır. Bu nedenlerden dolayı, çekirdek testi yeniden yazılmalı ve entegrasyon testlerine taşınmalıdır.
|
||||
|
||||
## Manuel Test {#manual-testing}
|
||||
|
||||
Yeni bir özellik geliştirdiğinizde, el ile de test etmek mantıklıdır. Bunu aşağıdaki adımlarla yapabilirsiniz:
|
||||
|
||||
ClickHouse Oluşturun. Terminalden Clickhouse'u çalıştırın: dizini değiştir `programs/clickhouse-server` ve ile çalıştırın `./clickhouse-server`. Bu yapılandırma kullanacak (`config.xml`, `users.xml` ve içindeki dosyalar `config.d` ve `users.d` dizinler) geçerli dizinden varsayılan olarak. ClickHouse sunucusuna bağlanmak için, çalıştırın `programs/clickhouse-client/clickhouse-client`.
|
||||
|
||||
Tüm clickhouse araçlarının (sunucu, istemci, vb.) sadece tek bir ikili için symlinks olduğunu unutmayın `clickhouse`. Bu ikili bulabilirsiniz `programs/clickhouse`. Tüm araçlar olarak da çağrılabilir `clickhouse tool` yerine `clickhouse-tool`.
|
||||
|
||||
Alternatif olarak ClickHouse paketini yükleyebilirsiniz: Yandex deposundan kararlı sürüm veya kendiniz için paket oluşturabilirsiniz `./release` ClickHouse kaynakları kökünde. Ardından sunucuyu şu şekilde başlatın `sudo service clickhouse-server start` (veya sunucuyu durdurmak için durdurun). Günlükleri arayın `/etc/clickhouse-server/clickhouse-server.log`.
|
||||
|
||||
ClickHouse sisteminizde zaten yüklü olduğunda, yeni bir `clickhouse` ikili ve mevcut ikili değiştirin:
|
||||
|
||||
``` bash
|
||||
$ sudo service clickhouse-server stop
|
||||
$ sudo cp ./clickhouse /usr/bin/
|
||||
$ sudo service clickhouse-server start
|
||||
```
|
||||
|
||||
Ayrıca sistem clickhouse-server durdurmak ve aynı yapılandırma ile ancak terminale günlüğü ile kendi çalıştırabilirsiniz:
|
||||
|
||||
``` bash
|
||||
$ sudo service clickhouse-server stop
|
||||
$ sudo -u clickhouse /usr/bin/clickhouse server --config-file /etc/clickhouse-server/config.xml
|
||||
```
|
||||
|
||||
Gdb ile örnek:
|
||||
|
||||
``` bash
|
||||
$ sudo -u clickhouse gdb --args /usr/bin/clickhouse server --config-file /etc/clickhouse-server/config.xml
|
||||
```
|
||||
|
||||
Sistem clickhouse-sunucu zaten çalışıyorsa ve bunu durdurmak istemiyorsanız, sizin port numaralarını değiştirebilirsiniz `config.xml` (veya bunları bir dosyada geçersiz kılma `config.d` dizin), uygun veri yolu sağlayın ve çalıştırın.
|
||||
|
||||
`clickhouse` ikili neredeyse hiçbir bağımlılıkları vardır ve Linux dağıtımları geniş genelinde çalışır. Hızlı ve kirli bir sunucuda değişikliklerinizi test etmek için, sadece yapabilirsiniz `scp` taze inşa `clickhouse` sunucunuza ikili ve daha sonra yukarıdaki örneklerde olduğu gibi çalıştırın.
|
||||
|
||||
## Test Ortamı {#testing-environment}
|
||||
|
||||
Kararlı olarak yayınlamadan önce test ortamında dağıtın. Test ortamı, 1/39 bölümünü işleyen bir kümedir [Üye.Metrica](https://metrica.yandex.com/) veriler. Test ortamımızı Yandex ile paylaşıyoruz.Metrica takımı. ClickHouse mevcut verilerin üstünde kesinti olmadan yükseltilir. İlk önce verilerin gerçek zamanlı olarak gecikmeden başarıyla işlendiğine bakıyoruz, çoğaltma çalışmaya devam ediyor ve Yandex tarafından görülebilen herhangi bir sorun yok.Metrica takımı. İlk kontrol aşağıdaki şekilde yapılabilir:
|
||||
|
||||
``` sql
|
||||
SELECT hostName() AS h, any(version()), any(uptime()), max(UTCEventTime), count() FROM remote('example01-01-{1..3}t', merge, hits) WHERE EventDate >= today() - 2 GROUP BY h ORDER BY h;
|
||||
```
|
||||
|
||||
Bazı durumlarda yandex'teki arkadaş ekiplerimizin test ortamına da dağıtım yapıyoruz: Pazar, Bulut, vb. Ayrıca geliştirme amacıyla kullanılan bazı donanım sunucularımız var.
|
||||
|
||||
## Yük Testi {#load-testing}
|
||||
|
||||
Test ortamına dağıtıldıktan sonra, üretim kümesinden gelen sorgularla yük testini çalıştırıyoruz. Bu elle yapılır.
|
||||
|
||||
Etkinleştirdiğinizden emin olun `query_log` üretim kümenizde.
|
||||
|
||||
Bir gün veya daha fazla sorgu günlüğü toplayın:
|
||||
|
||||
``` bash
|
||||
$ clickhouse-client --query="SELECT DISTINCT query FROM system.query_log WHERE event_date = today() AND query LIKE '%ym:%' AND query NOT LIKE '%system.query_log%' AND type = 2 AND is_initial_query" > queries.tsv
|
||||
```
|
||||
|
||||
Bu şekilde karmaşık bir örnektir. `type = 2` başarıyla yürütülen sorguları süzer. `query LIKE '%ym:%'` yandex'ten ilgili sorguları seçmektir.Metrica. `is_initial_query` yalnızca istemci tarafından başlatılan sorguları seçmektir, Clickhouse'un kendisi tarafından değil (dağıtılmış sorgu işlemenin parçaları olarak).
|
||||
|
||||
`scp` bu test kümenize günlük ve aşağıdaki gibi çalıştırın:
|
||||
|
||||
``` bash
|
||||
$ clickhouse benchmark --concurrency 16 < queries.tsv
|
||||
```
|
||||
|
||||
(muhtemelen de belirtmek istiyorum `--user`)
|
||||
|
||||
Sonra bir gece ya da hafta sonu için bırakın ve dinlenin.
|
||||
|
||||
Kontrol etmelisiniz `clickhouse-server` çökmez, bellek ayak izi sınırlıdır ve performans zamanla aşağılayıcı değildir.
|
||||
|
||||
Kesin sorgu yürütme zamanlamaları kaydedilmez ve sorguların ve ortamın yüksek değişkenliği nedeniyle karşılaştırılmaz.
|
||||
|
||||
## Yapı Testleri {#build-tests}
|
||||
|
||||
Yapı testleri, yapının çeşitli alternatif konfigürasyonlarda ve bazı yabancı sistemlerde bozulmadığını kontrol etmeyi sağlar. Testler bulunur `ci` dizin. Docker, Vagrant ve bazen de `qemu-user-static` Docker'ın içinde. Bu testler geliştirme aşamasındadır ve test çalıştırmaları otomatik değildir.
|
||||
|
||||
Motivasyon:
|
||||
|
||||
Normalde tüm testleri ClickHouse yapısının tek bir varyantında serbest bırakırız ve çalıştırırız. Ancak, iyice test edilmeyen alternatif yapı varyantları vardır. Örnekler:
|
||||
|
||||
- FreeBSD üzerine inşa;
|
||||
- sistem paketlerinden kütüphaneler ile Debian üzerine inşa;
|
||||
- kütüphanelerin paylaşılan bağlantısı ile oluşturun;
|
||||
- AArch64 platformunda oluşturun;
|
||||
- PowerPc platformunda oluşturun.
|
||||
|
||||
Örneğin, sistem paketleri ile oluştur kötü bir uygulamadır, çünkü bir sistemin hangi paketlerin tam sürümüne sahip olacağını garanti edemeyiz. Ancak bu gerçekten Debian bakıcılarına ihtiyaç duyuyor. Bu nedenle en azından bu yapı varyantını desteklemeliyiz. Başka bir örnek: paylaşılan bağlantı ortak bir sorun kaynağıdır, ancak bazı Meraklılar için gereklidir.
|
||||
|
||||
Tüm yapı varyantlarında tüm testleri çalıştıramasak da, en azından çeşitli yapı varyantlarının bozulmadığını kontrol etmek istiyoruz. Bu amaçla yapı testlerini kullanıyoruz.
|
||||
|
||||
## Protokol uyumluluğu testi {#testing-for-protocol-compatibility}
|
||||
|
||||
ClickHouse ağ protokolünü genişlettiğimizde, eski clickhouse istemcisinin yeni clickhouse sunucusu ile çalıştığını ve yeni clickhouse istemcisinin eski clickhouse sunucusu ile çalıştığını (sadece ilgili paketlerden ikili dosyaları çalıştırarak) manuel olarak test ediyoruz.
|
||||
|
||||
## Derleyiciden yardım {#help-from-the-compiler}
|
||||
|
||||
Ana ClickHouse kodu (bu `dbms` dizin) ile inşa edilmiştir `-Wall -Wextra -Werror` ve bazı ek etkin uyarılar ile. Bu seçenekler üçüncü taraf kitaplıkları için etkin olmasa da.
|
||||
|
||||
Clang daha yararlı uyarılar vardır-Sen ile onları arayabilirsiniz `-Weverything` ve varsayılan oluşturmak için bir şey seçin.
|
||||
|
||||
Üretim yapıları için gcc kullanılır (hala clang'dan biraz daha verimli kod üretir). Geliştirme için, clang genellikle kullanımı daha uygundur. Hata ayıklama modu ile kendi makinenizde inşa edebilirsiniz (dizüstü bilgisayarınızın pilinden tasarruf etmek için), ancak derleyicinin daha fazla uyarı üretebileceğini lütfen unutmayın `-O3` daha iyi kontrol akışı ve prosedürler arası analiz nedeniyle. Clang ile inşa ederken ayıklama modu ile oluştururken, hata ayıklama sürümü `libc++` çalışma zamanında daha fazla hata yakalamak için izin verir kullanılır.
|
||||
|
||||
## Dezenfektanlar {#sanitizers}
|
||||
|
||||
**Adres dezenfektanı**.
|
||||
Biz başına taahhüt bazında ASan altında fonksiyonel ve entegrasyon testleri çalıştırın.
|
||||
|
||||
**Valgrind (Memcheck)**.
|
||||
Bir gecede valgrind altında fonksiyonel testler yapıyoruz. Birden fazla saat sürer. Şu anda bilinen bir yanlış pozitif var `re2` kütüphane, bkz [bu makale](https://research.swtch.com/sparse).
|
||||
|
||||
**Tanımsız davranış dezenfektanı.**
|
||||
Biz başına taahhüt bazında ASan altında fonksiyonel ve entegrasyon testleri çalıştırın.
|
||||
|
||||
**İplik dezenfektanı**.
|
||||
Biz başına taahhüt bazında tsan altında fonksiyonel testler çalıştırın. Tsan altında hala taahhüt bazında entegrasyon testleri yapmıyoruz.
|
||||
|
||||
**Bellek temizleyici**.
|
||||
Şu anda hala MSan kullanmıyoruz.
|
||||
|
||||
**Hata ayıklama ayırıcısı.**
|
||||
Hata ayıklama sürümü `jemalloc` hata ayıklama oluşturmak için kullanılır.
|
||||
|
||||
## Fuzzing {#fuzzing}
|
||||
|
||||
ClickHouse fuzzing hem kullanılarak uygulanmaktadır [libFuzzer](https://llvm.org/docs/LibFuzzer.html) ve rastgele SQL sorguları.
|
||||
Tüm fuzz testleri sanitizers (Adres ve tanımsız) ile yapılmalıdır.
|
||||
|
||||
LibFuzzer kütüphane kodu izole fuzz testi için kullanılır. Fuzzers test kodunun bir parçası olarak uygulanır ve “_fuzzer” adı postfixes.
|
||||
Fuzzer örneği bulunabilir `src/Parsers/tests/lexer_fuzzer.cpp`. LibFuzzer özgü yapılandırmalar, sözlükler ve corpus saklanır `tests/fuzz`.
|
||||
Kullanıcı girişini işleyen her işlevsellik için fuzz testleri yazmanızı öneririz.
|
||||
|
||||
Fuzzers varsayılan olarak oluşturulmaz. Hem fuzzers inşa etmek `-DENABLE_FUZZING=1` ve `-DENABLE_TESTS=1` seçenekler ayarlanmalıdır.
|
||||
Fuzzers oluştururken Jemalloc'u devre dışı bırakmanızı öneririz. ClickHouse fuzzing'i entegre etmek için kullanılan yapılandırma
|
||||
Google OSS-Fuzz bulunabilir `docker/fuzz`.
|
||||
|
||||
Ayrıca rastgele SQL sorguları oluşturmak ve sunucunun bunları çalıştırarak ölmediğini kontrol etmek için basit fuzz testi kullanıyoruz.
|
||||
İçinde bulabilirsiniz `00746_sql_fuzzy.pl`. Bu test sürekli olarak (gece ve daha uzun) çalıştırılmalıdır.
|
||||
|
||||
## Güvenlik Denetimi {#security-audit}
|
||||
|
||||
Yandex Güvenlik ekibinden insanlar güvenlik açısından ClickHouse yetenekleri bazı temel bakış yapmak.
|
||||
|
||||
## Statik Analizörler {#static-analyzers}
|
||||
|
||||
Koş weuyoruz `PVS-Studio` taahhüt bazında. Değerlendir havedik `clang-tidy`, `Coverity`, `cppcheck`, `PVS-Studio`, `tscancode`. Sen kullanım talimatları bulacaksınız `tests/instructions/` dizin. Ayrıca okuyabilirsiniz [Rusça makale](https://habr.com/company/yandex/blog/342018/).
|
||||
|
||||
Kullanıyorsanız `CLion` bir IDE olarak, bazı kaldıraç `clang-tidy` kutudan kontrol eder.
|
||||
|
||||
## Sertleşme {#hardening}
|
||||
|
||||
`FORTIFY_SOURCE` varsayılan olarak kullanılır. Neredeyse işe yaramaz, ancak nadir durumlarda hala mantıklı ve bunu devre dışı bırakmıyoruz.
|
||||
|
||||
## Kod Stili {#code-style}
|
||||
|
||||
Kod stili kuralları açıklanmıştır [burada](https://clickhouse.tech/docs/en/development/style/).
|
||||
|
||||
Bazı ortak stil ihlallerini kontrol etmek için şunları kullanabilirsiniz `utils/check-style` komut.
|
||||
|
||||
Kodunuzun uygun stilini zorlamak için şunları kullanabilirsiniz `clang-format`. Dosya `.clang-format` kaynak rootlarında yer almaktadır. Çoğunlukla gerçek kod stilimizle karşılık gelir. Ancak uygulanması tavsiye edilmez `clang-format` varolan dosyalara biçimlendirmeyi daha da kötüleştirdiği için. Kullanabilirsiniz `clang-format-diff` eğer clang kaynak deposunda bulabilirsiniz aracı.
|
||||
|
||||
Alternatif olarak deneyebilirsiniz `uncrustify` kodunuzu yeniden biçimlendirmek için bir araç. Yapılandırma içinde `uncrustify.cfg` kaynaklarda kök. Daha az test edilmiştir `clang-format`.
|
||||
|
||||
`CLion` kod stilimiz için ayarlanması gereken kendi kod biçimlendiricisine sahiptir.
|
||||
|
||||
## Metrica B2B testleri {#metrica-b2b-tests}
|
||||
|
||||
Her ClickHouse sürümü Yandex Metrica ve AppMetrica motorları ile test edilir. Clickhouse'un Test ve kararlı sürümleri Vm'lerde dağıtılır ve Giriş verilerinin sabit örneğini işleyen Metrica motorunun küçük bir kopyasıyla çalışır. Daha sonra Metrica motorunun iki örneğinin sonuçları birlikte karşılaştırılır.
|
||||
|
||||
Bu testler ayrı ekip tarafından otomatikleştirilir. Yüksek sayıda hareketli parça nedeniyle, testler çoğu zaman tamamen ilgisiz nedenlerle başarısız olur, bu da anlaşılması çok zordur. Büyük olasılıkla bu testlerin bizim için negatif değeri var. Bununla birlikte, bu testlerin yüzlerce kişiden yaklaşık bir veya iki kez yararlı olduğu kanıtlanmıştır.
|
||||
|
||||
## Test Kapsamı {#test-coverage}
|
||||
|
||||
Temmuz 2018 itibariyle test kapsamını takip etmiyoruz.
|
||||
|
||||
## Test Otomasyonu {#test-automation}
|
||||
|
||||
Yandex dahili CI ve iş otomasyon sistemi ile testler yapıyoruz “Sandbox”.
|
||||
|
||||
Yapı işleri ve testler, taahhüt bazında sanal alanda çalıştırılır. Ortaya çıkan paketler ve test sonuçları Github'da yayınlanır ve doğrudan bağlantılar tarafından indirilebilir. Eserler sonsuza dek saklanır. Eğer GitHub bir çekme isteği gönderdiğinizde, biz olarak etiketlemek “can be tested” ve bizim CI sistemi sizin için ClickHouse paketleri (yayın, hata ayıklama, Adres dezenfektanı ile, vb) inşa edecek.
|
||||
|
||||
Travis CI, zaman ve hesaplama gücü sınırı nedeniyle kullanmıyoruz.
|
||||
Jenkins'i kullanmayız. Daha önce kullanıldı ve şimdi Jenkins kullanmadığımız için mutluyuz.
|
||||
|
||||
[Orijinal makale](https://clickhouse.tech/docs/en/development/tests/) <!--hide-->
|
||||
1
docs/tr/development/tests.md
Symbolic link
1
docs/tr/development/tests.md
Symbolic link
@ -0,0 +1 @@
|
||||
../../en/development/tests.md
|
||||
@ -35,7 +35,7 @@ sudo apt-get install git cmake ninja-build
|
||||
或cmake3而不是旧系统上的cmake。
|
||||
或者在早期版本的系统中用 cmake3 替代 cmake
|
||||
|
||||
## 安装 GCC 9 {#an-zhuang-gcc-9}
|
||||
## 安装 GCC 10 {#an-zhuang-gcc-10}
|
||||
|
||||
有几种方法可以做到这一点。
|
||||
|
||||
@ -45,18 +45,18 @@ sudo apt-get install git cmake ninja-build
|
||||
sudo apt-get install software-properties-common
|
||||
sudo apt-add-repository ppa:ubuntu-toolchain-r/test
|
||||
sudo apt-get update
|
||||
sudo apt-get install gcc-9 g++-9
|
||||
sudo apt-get install gcc-10 g++-10
|
||||
```
|
||||
|
||||
### 源码安装 gcc {#yuan-ma-an-zhuang-gcc}
|
||||
|
||||
请查看 [utils/ci/build-gcc-from-sources.sh](https://github.com/ClickHouse/ClickHouse/blob/master/utils/ci/build-gcc-from-sources.sh)
|
||||
|
||||
## 使用 GCC 9 来编译 {#shi-yong-gcc-9-lai-bian-yi}
|
||||
## 使用 GCC 10 来编译 {#shi-yong-gcc-10-lai-bian-yi}
|
||||
|
||||
``` bash
|
||||
export CC=gcc-9
|
||||
export CXX=g++-9
|
||||
export CC=gcc-10
|
||||
export CXX=g++-10
|
||||
```
|
||||
|
||||
## 拉取 ClickHouse 源码 {#la-qu-clickhouse-yuan-ma-1}
|
||||
|
||||
@ -129,7 +129,7 @@ Yandex官方当前使用GCC构建ClickHouse，因为它生成的机器代码性
|
||||
|
||||
在Ubuntu上安装GCC，请执行：`sudo apt install gcc g++`
|
||||
|
||||
请使用`gcc --version`查看gcc的版本。如果gcc版本低于9，请参考此处的指示：https://clickhouse.tech/docs/zh/development/build/#an-zhuang-gcc-9 。
|
||||
请使用`gcc --version`查看gcc的版本。如果gcc版本低于9，请参考此处的指示：https://clickhouse.tech/docs/zh/development/build/#an-zhuang-gcc-10 。
|
||||
|
||||
在Mac OS X上安装GCC，请执行：`brew install gcc`
|
||||
|
||||
@ -146,7 +146,7 @@ Yandex官方当前使用GCC构建ClickHouse，因为它生成的机器代码性
|
||||
|
||||
在`build`目录下，通过运行CMake配置构建。 在第一次运行之前，请定义用于指定编译器的环境变量（本示例中为gcc 9 编译器）。
|
||||
|
||||
export CC=gcc-9 CXX=g++-9
|
||||
export CC=gcc-10 CXX=g++-10
|
||||
cmake ..
|
||||
|
||||
`CC`变量指代C的编译器（C Compiler的缩写），而`CXX`变量指代要使用哪个C++编译器进行编译。
|
||||
|
||||
@ -1,237 +0,0 @@
|
||||
# ClickHouse 测试 {#clickhouse-ce-shi}
|
||||
|
||||
## 功能性测试 {#gong-neng-xing-ce-shi}
|
||||
|
||||
功能性测试是最简便使用的。绝大部分 ClickHouse 的功能可以通过功能性测试来测试，任何代码的更改都必须通过该测试。
|
||||
|
||||
每个功能测试会向正在运行的 ClickHouse服务器发送一个或多个查询，并将结果与预期结果进行比较。
|
||||
|
||||
测试用例在 `tests/queries` 目录中。这里有两个子目录：`stateless` 和 `stateful`目录。无状态的测试无需预加载测试数据集 - 通常是在测试运行期间动态创建小量的数据集。有状态测试需要来自 Yandex.Metrica 的预加载测试数据，而不向一般公众提供。我们倾向于仅使用«无状态»测试并避免添加新的«有状态»测试。
|
||||
|
||||
每个测试用例可以是两种类型之一：`.sql` 和 `.sh`。`.sql` 测试文件是用于管理`clickhouse-client --multiquery --testmode`的简单SQL脚本。`.sh` 测试文件是一个可以自己运行的脚本。
|
||||
|
||||
要运行所有测试，请使用 `tests/clickhouse-test` 工具，用 `--help` 可以获取所有的选项列表。您可以简单地运行所有测试或运行测试名称中的子字符串过滤的测试子集：`./clickhouse-test substring`。
|
||||
|
||||
调用功能测试最简单的方法是将 `clickhouse-client` 复制到`/usr/bin/`，运行`clickhouse-server`，然后从自己的目录运行`./ clickhouse-test`。
|
||||
|
||||
要添加新测试，请在 `tests/queries/0_stateless` 目录内添加新的 `.sql` 或 `.sh` 文件，手动检查，然后按以下方式生成 `.reference` 文件： `clickhouse-client -n --testmode < 00000_test.sql > 00000_test.reference` 或 `./00000_test.sh > ./00000_test.reference`。
|
||||
|
||||
测试应该只使用（创建，删除等）`test` 数据库中的表，这些表假定是事先创建的; 测试也可以使用临时表。
|
||||
|
||||
如果要在功能测试中使用分布式查询，可以利用 `remote` 表函数和 `127.0.0.{1..2}` 地址为服务器查询自身; 或者您可以在服务器配置文件中使用预定义的测试集群，例如`test_shard_localhost`。
|
||||
|
||||
有些测试在名称中标有 `zookeeper`，`shard` 或 `long`。`zookeeper` 用于使用ZooKeeper的测试; `shard` 用于需要服务器监听`127.0.0.*`的测试。`long` 适用于运行时间稍长一秒的测试。
|
||||
|
||||
## 已知的bug {#yi-zhi-de-bug}
|
||||
|
||||
如果我们知道一些可以通过功能测试轻松复制的错误，我们将准备好的功能测试放在 `tests/queries/bugs` 目录中。当修复错误时，这些测试将被移动到 `tests/queries/0_stateless` 目录中。
|
||||
|
||||
## 集成测试 {#ji-cheng-ce-shi}
|
||||
|
||||
集成测试允许在集群配置中测试 ClickHouse，并与其他服务器（如MySQL，Postgres，MongoDB）进行 ClickHouse 交互。它们可用于模拟网络拆分，数据包丢弃等。这些测试在Docker下运行，并使用各种软件创建多个容器。
|
||||
|
||||
参考 `tests/integration/README.md` 文档关于如何使用集成测试。
|
||||
|
||||
请注意，ClickHouse 与第三方驱动程序的集成未经过测试。此外，我们目前还没有与 JDBC 和ODBC 驱动程序进行集成测试。
|
||||
|
||||
## 单元测试 {#dan-yuan-ce-shi}
|
||||
|
||||
当您想要测试整个 ClickHouse，而不是单个独立的库或类时，单元测试非常有用。您可以使用`ENABLE_TESTS` CMake 选项启用或禁用测试构建。单元测试（和其他测试程序）位于代码中的`tests` 子目录中。要运行单元测试，请键入 `ninja test`。有些测试使用 `gtest`，但有些只是在测试失败时返回非零状态码。
|
||||
|
||||
如果代码已经被功能测试覆盖（并且功能测试通常使用起来要简单得多），则不一定要进行单元测试。
|
||||
|
||||
## 性能测试 {#xing-neng-ce-shi}
|
||||
|
||||
性能测试允许测量和比较综合查询中 ClickHouse 的某些独立部分的性能。测试位于`tests/performance` 目录中。每个测试都由 `.xml` 文件表示，并附有测试用例的描述。使用 `clickhouse performance-test` 工具（嵌入在 `clickhouse` 二进制文件中）运行测试。请参阅 `--help` 以进行调用。
|
||||
|
||||
每个测试在循环中运行一个或多个查询（可能带有参数组合），并具有一些停止条件（如«最大执行速度不会在三秒内更改»）并测量一些有关查询性能的指标（如«最大执行速度»））。某些测试可以包含预加载的测试数据集的前提条件。
|
||||
|
||||
如果要在某些情况下提高 ClickHouse 的性能，并且如果可以在简单查询上观察到改进，则强烈建议编写性能测试。在测试过程中使用 `perf top` 或其他 perf 工具总是有意义的。
|
||||
|
||||
性能测试不是基于每个提交运行的。不收集性能测试结果，我们手动比较它们。
|
||||
|
||||
## 测试工具和脚本 {#ce-shi-gong-ju-he-jiao-ben}
|
||||
|
||||
`tests`目录中的一些程序不是准备测试，而是测试工具。例如，对于`Lexer`，有一个工具`src/Parsers/tests/lexer` 标准输出。您可以使用这些工具作为代码示例以及探索和手动测试。
|
||||
|
||||
您还可以将一对文件 `.sh` 和 `.reference` 与工具放在一些预定义的输入上运行它 - 然后可以将脚本结果与 `.reference` 文件进行比较。这些测试不是自动化的。
|
||||
|
||||
## 杂项测试 {#za-xiang-ce-shi}
|
||||
|
||||
有一些外部字典的测试位于 `tests/external_dictionaries`，机器学习模型在`tests/external_models`目录。这些测试未更新，必须转移到集成测试。
|
||||
|
||||
对于分布式数据的插入，有单独的测试。此测试在单独的服务器上运行 ClickHouse 集群并模拟各种故障情况：网络拆分，数据包丢弃（ClickHouse 节点之间，ClickHouse 和 ZooKeeper之间，ClickHouse 服务器和客户端之间等），进行 `kill -9`，`kill -STOP` 和`kill -CONT` 等操作，类似[Jepsen](https://aphyr.com/tags/Jepsen)。然后，测试检查是否已写入所有已确认的插入，并且所有已拒绝的插入都未写入。
|
||||
|
||||
在 ClickHouse 开源之前，分布式测试是由单独的团队编写的，但该团队不再使用 ClickHouse，测试是在 Java 中意外编写的。由于这些原因，必须重写分布式测试并将其移至集成测试。
|
||||
|
||||
## 手动测试 {#shou-dong-ce-shi}
|
||||
|
||||
当您开发了新的功能，做手动测试也是合理的。可以按照以下步骤来进行：
|
||||
|
||||
编译 ClickHouse。在命令行中运行 ClickHouse：进入 `programs/clickhouse-server` 目录并运行 `./clickhouse-server`。它会默认使用当前目录的配置文件 (`config.xml`， `users.xml` 以及在 `config.d` 和 `users.d` 目录的文件)。可以使用 `programs/clickhouse-client/clickhouse-client` 来连接数据库。
|
||||
|
||||
或者，您可以安装 ClickHouse 软件包：从 Yandex 存储库中获得稳定版本，或者您可以在ClickHouse源根目录中使用 `./release` 构建自己的软件包。然后使用 `sudo service clickhouse-server start` 启动服务器（或停止服务器）。在 `/etc/clickhouse-server/clickhouse-server.log` 中查找日志。
|
||||
|
||||
当您的系统上已经安装了 ClickHouse 时，您可以构建一个新的 `clickhouse` 二进制文件并替换现有的二进制文件：
|
||||
|
||||
sudo service clickhouse-server stop
|
||||
sudo cp ./clickhouse /usr/bin/
|
||||
sudo service clickhouse-server start
|
||||
|
||||
您也可以停止 clickhouse-server 并使用相同的配置运行您自己的服务器，日志打印到终端：
|
||||
|
||||
sudo service clickhouse-server stop
|
||||
sudo -u clickhouse /usr/bin/clickhouse server --config-file /etc/clickhouse-server/config.xml
|
||||
|
||||
使用 gdb 的一个示例:
|
||||
|
||||
sudo -u clickhouse gdb --args /usr/bin/clickhouse server --config-file /etc/clickhouse-server/config.xml
|
||||
|
||||
如果 clickhouse-server 已经运行并且您不想停止它，您可以更改 `config.xml` 中的端口号（或在 `config.d` 目录中的文件中覆盖它们），配置适当的数据路径，然后运行它。
|
||||
|
||||
`clickhouse` 二进制文件几乎没有依赖关系，适用于各种 Linux 发行版。要快速地测试服务器上的更改，您可以简单地将新建的 `clickhouse` 二进制文件 `scp` 到其他服务器，然后按照上面的示例运行它。
|
||||
|
||||
## 测试环境 {#ce-shi-huan-jing}
|
||||
|
||||
在将版本发布为稳定之前，我们将其部署在测试环境中测试环境是一个处理\[Yandex.Metrica\]（https://metrica.yandex.com/）总数据的1/39部分大小的集群。我们与 Yandex.Metrica 团队公用我们的测试环境。ClickHouse 在现有数据的基础上无需停机即可升级。我们首先看到数据处理成功而不会实时滞后，复制继续工作，并且 Yandex.Metrica 团队无法看到问题。首先的检查可以通过以下方式完成：
|
||||
|
||||
SELECT hostName() AS h, any(version()), any(uptime()), max(UTCEventTime), count() FROM remote('example01-01-{1..3}t', merge, hits) WHERE EventDate >= today() - 2 GROUP BY h ORDER BY h;
|
||||
|
||||
在某些情况下，我们还部署到 Yandex 的合作团队的测试环境：市场，云等。此外，我们还有一些用于开发目的的硬件服务器。
|
||||
|
||||
## 负载测试 {#fu-zai-ce-shi}
|
||||
|
||||
部署到测试环境后，我们使用生产群集中的查询运行负载测试。这是手动完成的。
|
||||
|
||||
确保在生产集群中开启了 `query_log` 选项。
|
||||
|
||||
收集一天或更多的查询日志：
|
||||
|
||||
clickhouse-client --query="SELECT DISTINCT query FROM system.query_log WHERE event_date = today() AND query LIKE '%ym:%' AND query NOT LIKE '%system.query_log%' AND type = 2 AND is_initial_query" > queries.tsv
|
||||
|
||||
这是一个复杂的例子。`type = 2` 将过滤成功执行的查询。`query LIKE'％ym：％'` 用于从 Yandex.Metrica 中选择相关查询。`is_initial_query` 是仅选择由客户端发起的查询，而不是由 ClickHouse 本身（作为分布式查询处理的一部分）。
|
||||
|
||||
`scp` 这份日志到测试机器，并运行以下操作：
|
||||
|
||||
clickhouse benchmark --concurrency 16 < queries.tsv
|
||||
|
||||
(可能你需要指定运行的用户 `--user`)
|
||||
|
||||
然后离开它一晚或周末休息一下。
|
||||
|
||||
你要检查下 `clickhouse-server` 是否崩溃，内存占用是否合理，性能也不会随着时间的推移而降低。
|
||||
|
||||
由于查询和环境的高度可变性，不会记录精确的查询执行时序并且不进行比较。
|
||||
|
||||
## 编译测试 {#bian-yi-ce-shi}
|
||||
|
||||
构建测试允许检查构建在各种替代配置和某些外部系统上是否被破坏。测试位于`ci`目录。它们从 Docker，Vagrant 中的源代码运行构建，有时在 Docker 中运行 `qemu-user-static`。这些测试正在开发中，测试运行不是自动化的。
|
||||
|
||||
动机：
|
||||
|
||||
通常我们会在 ClickHouse 构建的单个版本上发布并运行所有测试。但是有一些未经过彻底测试的替代构建版本。例子：
|
||||
|
||||
- 在 FreeBSD 中的构建；
|
||||
- 在 Debian 中使用系统包中的库进行构建；
|
||||
- 使用库的共享链接构建；
|
||||
- 在 AArch64 平台进行构建。
|
||||
|
||||
例如，使用系统包构建是不好的做法，因为我们无法保证系统具有的确切版本的软件包。但 Debian 维护者确实需要这样做。出于这个原因，我们至少必须支持这种构建。另一个例子：共享链接是一个常见的麻烦来源，但是对于一些爱好者来说需要它。
|
||||
|
||||
虽然我们无法对所有构建版本运行所有测试，但我们想要检查至少不会破坏各种构建变体。为此，我们使用构建测试。
|
||||
|
||||
## 测试协议兼容性 {#ce-shi-xie-yi-jian-rong-xing}
|
||||
|
||||
当我们扩展 ClickHouse 网络协议时，我们手动测试旧的 clickhouse-client 与新的 clickhouse-server 和新的clickhouse-client 一起使用旧的 clickhouse-server (只需从相应的包中运行二进制文件)
|
||||
|
||||
## 来自编译器的提示 {#lai-zi-bian-yi-qi-de-ti-shi}
|
||||
|
||||
ClickHouse 主要的代码 (位于`dbms`目录中) 使用 `-Wall -Wextra -Werror` 构建，并带有一些其他已启用的警告。 虽然没有为第三方库启用这些选项。
|
||||
|
||||
Clang 有更多有用的警告 - 您可以使用 `-Weverything` 查找它们并选择默认构建的东西。
|
||||
|
||||
对于生产构建，使用 gcc（它仍然生成比 clang 稍高效的代码）。对于开发来说，clang 通常更方便使用。您可以使用调试模式在自己的机器上构建（以节省笔记本电脑的电量），但请注意，由于更好的控制流程和过程分析，编译器使用 `-O3` 会生成更多警告。 当使用 clang 构建时，使用 `libc++` 而不是 `libstdc++`，并且在使用调试模式构建时，使用调试版本的 `libc++`，它允许在运行时捕获更多错误。
|
||||
|
||||
## Sanitizers {#sanitizers}
|
||||
|
||||
### Address sanitizer
|
||||
我们使用Asan对每个提交进行功能和集成测试。
|
||||
|
||||
### Valgrind (Memcheck)
|
||||
我们在夜间使用Valgrind进行功能测试。这需要几个小时。目前在 `re2` 库中有一个已知的误报，请参阅[文章](https://research.swtch.com/sparse)。
|
||||
|
||||
### Undefined behaviour sanitizer
|
||||
我们使用Asan对每个提交进行功能和集成测试。
|
||||
|
||||
### Thread sanitizer
|
||||
我们使用TSan对每个提交进行功能测试。目前不使用TSan对每个提交进行集成测试。
|
||||
|
||||
### Memory sanitizer
|
||||
目前我们不使用 MSan。
|
||||
|
||||
### Debug allocator
|
||||
您可以使用 `DEBUG_TCMALLOC` CMake 选项启用 `tcmalloc` 的调试版本。我们在每次提交的基础上使用调试分配器运行测试。
|
||||
|
||||
更多请参阅 `tests/instructions/sanitizers.txt`。
|
||||
|
||||
## 模糊测试 {#mo-hu-ce-shi}
|
||||
|
||||
ClickHouse模糊测试可以通过[libFuzzer](https://llvm.org/docs/LibFuzzer.html)和随机SQL查询实现。
|
||||
所有的模糊测试都应使用sanitizers（Address及Undefined）。
|
||||
|
||||
LibFuzzer用于对库代码进行独立的模糊测试。模糊器作为测试代码的一部分实现，并具有“_fuzzer”名称后缀。
|
||||
模糊测试示例在`src/Parsers/tests/lexer_fuzzer.cpp`。LibFuzzer配置、字典及语料库存放在`tests/fuzz`。
|
||||
我们鼓励您为每个处理用户输入的功能编写模糊测试。
|
||||
|
||||
默认情况下不构建模糊器。可通过设置`-DENABLE_FUZZING=1`和`-DENABLE_TESTS=1`来构建模糊器。 我们建议在构建模糊器时关闭Jemalloc。
|
||||
用于将ClickHouse模糊测试集成到的Google OSS-Fuzz的配置文件位于`docker/fuzz`。
|
||||
|
||||
此外，我们使用简单的模糊测试来生成随机SQL查询并检查服务器是否正常。你可以在`00746_sql_fuzzy.pl` 找到它。测试应连续进行（过夜和更长时间）。
|
||||
|
||||
## 安全审计 {#an-quan-shen-ji}
|
||||
|
||||
Yandex Cloud 部门的人员从安全角度对 ClickHouse 功能进行了一些基本概述。
|
||||
|
||||
## 静态分析 {#jing-tai-fen-xi}
|
||||
|
||||
我们偶尔使用静态分析。我们已经评估过 `clang-tidy`， `Coverity`， `cppcheck`， `PVS-Studio`， `tscancode`。您将在 `tests/instructions/` 目录中找到使用说明。你也可以阅读[俄文文章](https://habr.com/company/yandex/blog/342018/).
|
||||
|
||||
如果您使用 `CLion` 作为 IDE，您可以开箱即用一些 `clang-tidy` 检查。
|
||||
|
||||
## 其他强化 {#qi-ta-qiang-hua}
|
||||
|
||||
默认情况下使用 `FORTIFY_SOURCE`。它几乎没用，但在极少数情况下仍然有意义，我们不会禁用它。
|
||||
|
||||
## 代码风格 {#dai-ma-feng-ge}
|
||||
|
||||
代码风格在[这里](https://clickhouse.tech/docs/en/development/style/) 有说明。
|
||||
|
||||
要检查一些常见的样式冲突，您可以使用 `utils/check-style` 脚本。
|
||||
|
||||
为了强制你的代码的正确风格，你可以使用 `clang-format` 文件。`.clang-format` 位于源代码根目录， 它主要与我们的实际代码风格对应。但不建议将 `clang-format` 应用于现有文件，因为它会使格式变得更糟。您可以使用 `clang-format-diff` 工具，您可以在 clang 源代码库中找到
|
||||
|
||||
或者，您可以尝试`uncrustify` 工具来格式化您的代码。配置文件在源代码的根目录中的`uncrustify.cfg`。它比 `clang-format` 经过更少的测试。
|
||||
|
||||
`CLion` 有自己的代码格式化程序，必须调整为我们的代码风格。
|
||||
|
||||
## Metrica B2B 测试 {#metrica-b2b-ce-shi}
|
||||
|
||||
每个 ClickHouse 版本都经过 Yandex Metrica 和 AppMetrica 引擎的测试。测试和稳定版本的 ClickHouse 部署在虚拟机上，并使用处理输入数据固定样本的度量引擎的小副本运行。将度量引擎的两个实例的结果一起进行比较
|
||||
|
||||
这些测试是由单独的团队自动完成的。由于移动部件的数量很多，大部分时间的测试都是完全无关的，很难弄清楚。很可能这些测试对我们来说是负值。然而，这些测试被证明是有用的大约一个或两个倍的数百。
|
||||
|
||||
## 测试覆盖率 {#ce-shi-fu-gai-lu}
|
||||
|
||||
截至2018年7月，我们不会跟踪测试复盖率。
|
||||
|
||||
## 自动化测试 {#zi-dong-hua-ce-shi}
|
||||
|
||||
我们使用 Yandex 内部 CI 和名为«沙箱»的作业自动化系统运行测试。我们还继续使用 Jenkins（可在Yandex内部使用）。
|
||||
|
||||
构建作业和测试在沙箱中按每次提交的基础上运行。结果包和测试结果发布在 GitHub 上，可以通过直接链接下载，结果会被永久存储。当您在 GitHub 上发送拉取请求时，我们将其标记为«可以测试»，我们的 CI 系统将为您构建 ClickHouse 包（发布，调试，地址消除等）。
|
||||
|
||||
由于时间和计算能力的限制，我们不使用 Travis CI。
|
||||
|
||||
在 Jenkins，我们运行字典测试，指标B2B测试。我们使用 Jenkins 来准备和发布版本。Jenkins是一种传统的技术，所有的工作将被转移到沙箱中。
|
||||
|
||||
[来源文章](https://clickhouse.tech/docs/zh/development/tests/) <!--hide-->
|
||||
@ -3,7 +3,7 @@ machine_translated: true
|
||||
machine_translated_rev: 5decc73b5dc60054f19087d3690c4eb99446a6c3
|
||||
---
|
||||
|
||||
# 系统。query_log {#system_tables-query_log}
|
||||
# system.query_log {#system_tables-query_log}
|
||||
|
||||
包含有关已执行查询的信息，例如，开始时间、处理持续时间、错误消息。
|
||||
|
||||
@ -140,4 +140,4 @@ Settings.Values: ['0','random','1','10000000000']
|
||||
|
||||
**另请参阅**
|
||||
|
||||
- [系统。query_thread_log](../../operations/system-tables/query_thread_log.md#system_tables-query_thread_log) — This table contains information about each query execution thread.
|
||||
- [system.query_thread_log](../../operations/system-tables/query_thread_log.md#system_tables-query_thread_log) — This table contains information about each query execution thread.
|
||||
|
||||
@ -227,9 +227,6 @@ else ()
|
||||
install (FILES ${CMAKE_CURRENT_BINARY_DIR}/clickhouse-git-import DESTINATION ${CMAKE_INSTALL_BINDIR} COMPONENT clickhouse)
|
||||
list(APPEND CLICKHOUSE_BUNDLE clickhouse-git-import)
|
||||
endif ()
|
||||
if(ENABLE_CLICKHOUSE_ODBC_BRIDGE)
|
||||
list(APPEND CLICKHOUSE_BUNDLE clickhouse-odbc-bridge)
|
||||
endif()
|
||||
|
||||
install (TARGETS clickhouse RUNTIME DESTINATION ${CMAKE_INSTALL_BINDIR} COMPONENT clickhouse)
|
||||
|
||||
|
||||
@ -75,6 +75,7 @@
|
||||
#include <Common/InterruptListener.h>
|
||||
#include <Functions/registerFunctions.h>
|
||||
#include <AggregateFunctions/registerAggregateFunctions.h>
|
||||
#include <Formats/registerFormats.h>
|
||||
#include <Common/Config/configReadClient.h>
|
||||
#include <Storages/ColumnsDescription.h>
|
||||
#include <common/argsToConfig.h>
|
||||
@ -463,6 +464,7 @@ private:
|
||||
{
|
||||
UseSSL use_ssl;
|
||||
|
||||
registerFormats();
|
||||
registerFunctions();
|
||||
registerAggregateFunctions();
|
||||
|
||||
|
||||
@ -1,6 +1,7 @@
|
||||
#include "ClusterCopierApp.h"
|
||||
#include <Common/StatusFile.h>
|
||||
#include <Common/TerminalSize.h>
|
||||
#include <Formats/registerFormats.h>
|
||||
#include <unistd.h>
|
||||
|
||||
|
||||
@ -122,6 +123,7 @@ void ClusterCopierApp::mainImpl()
|
||||
registerStorages();
|
||||
registerDictionaries();
|
||||
registerDisks();
|
||||
registerFormats();
|
||||
|
||||
static const std::string default_database = "_local";
|
||||
DatabaseCatalog::instance().attachDatabase(default_database, std::make_shared<DatabaseMemory>(default_database, *context));
|
||||
|
||||
@ -33,6 +33,7 @@
|
||||
#include <Storages/registerStorages.h>
|
||||
#include <Dictionaries/registerDictionaries.h>
|
||||
#include <Disks/registerDisks.h>
|
||||
#include <Formats/registerFormats.h>
|
||||
#include <boost/program_options/options_description.hpp>
|
||||
#include <boost/program_options.hpp>
|
||||
#include <common/argsToConfig.h>
|
||||
@ -224,6 +225,7 @@ try
|
||||
registerStorages();
|
||||
registerDictionaries();
|
||||
registerDisks();
|
||||
registerFormats();
|
||||
|
||||
/// Maybe useless
|
||||
if (config().has("macros"))
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Loading…
Reference in New Issue
Block a user