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translate docs/zh/operations/table_engines/custom_partitioning_key.md (#5134)
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Ivan Blinkov
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# 自定义分区键
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# Custom Partitioning Key
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[MergeTree](mergetree.md) 系列的表（包括 [可复制表](replication.md) ）可以使用分区。基于 MergeTree 表的 [物化视图](materializedview.md) 也支持分区。
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Starting with version 1.1.54310, you can create tables in the MergeTree family with any partitioning expression (not only partitioning by month).
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一个分区是指按指定规则逻辑组合一起的表的记录集。可以按任意标准进行分区，如按月，按日或按事件类型。为了减少需要操作的数据，每个分区都是分开存储的。访问数据时，ClickHouse 尽量使用这些分区的最小子集。
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The partition key can be an expression from the table columns, or a tuple of such expressions (similar to the primary key). The partition key can be omitted. When creating a table, specify the partition key in the ENGINE description with the new syntax:
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分区是在 [建表](mergetree.md#table_engine-mergetree-creating-a-table) 的 `PARTITION BY expr` 子句中指定。分区键可以是关于列的任何表达式。例如，指定按月分区，表达式为 `toYYYYMM(date_column)`：
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```
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ENGINE [=] Name(...) [PARTITION BY expr] [ORDER BY expr] [SAMPLE BY expr] [SETTINGS name=value, ...]
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``` sql
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CREATE TABLE visits
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(
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VisitDate Date,
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Hour UInt8,
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ClientID UUID
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)
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ENGINE = MergeTree()
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PARTITION BY toYYYYMM(VisitDate)
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ORDER BY Hour;
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```
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For MergeTree tables, the partition expression is specified after `PARTITION BY`, the primary key after `ORDER BY`, the sampling key after `SAMPLE BY`, and `SETTINGS` can specify `index_granularity` (optional; the default value is 8192), as well as other settings from [MergeTreeSettings.h](https://github.com/yandex/ClickHouse/blob/master/dbms/src/Storages/MergeTree/MergeTreeSettings.h). The other engine parameters are specified in parentheses after the engine name, as previously. Example:
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分区键也可以是表达式元组（类似 [主键](mergetree.md#primary-keys-and-indexes-in-queries) ）。例如：
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``` sql
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ENGINE = ReplicatedCollapsingMergeTree('/clickhouse/tables/name', 'replica1', Sign)
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PARTITION BY (toMonday(StartDate), EventType)
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ORDER BY (CounterID, StartDate, intHash32(UserID))
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SAMPLE BY intHash32(UserID)
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PARTITION BY (toMonday(StartDate), EventType)
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ORDER BY (CounterID, StartDate, intHash32(UserID));
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```
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The traditional partitioning by month is expressed as `toYYYYMM(date_column)`.
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上例中，我们设置按一周内的事件类型分区。
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You can't convert an old-style table to a table with custom partitions (only via INSERT SELECT).
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新数据插入到表中时，这些数据会存储为按主键排序的新片段（块）。插入后 10-15 分钟，同一分区的各个片段会合并为一整个片段。
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After this table is created, merge will only work for data parts that have the same value for the partitioning expression. Note: This means that you shouldn't make overly granular partitions (more than about a thousand partitions), or SELECT will perform poorly.
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!!! 注意
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那些有相同分区表达式值的数据片段才会合并。这意味着 **你不应该用太精细的分区方案**（超过一千个分区）。否则，会因为文件系统中的文件数量和需要找开的文件描述符过多，导致 `SELECT` 查询效率不佳。
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To specify a partition in ALTER PARTITION commands, specify the value of the partition expression (or a tuple). Constants and constant expressions are supported. Example:
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可以通过 [system.parts](../system_tables.md#system_tables-parts) 表查看表片段和分区信息。例如，假设我们有一个 `visits` 表，按月分区。对 `system.parts` 表执行 `SELECT`：
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``` sql
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ALTER TABLE table DROP PARTITION (toMonday(today()), 1)
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SELECT
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partition,
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name,
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active
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FROM system.parts
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WHERE table = 'visits'
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```
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Deletes the partition for the current week with event type 1. The same is true for the OPTIMIZE query. To specify the only partition in a non-partitioned table, specify `PARTITION tuple()`.
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```
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┌─partition─┬─name───────────┬─active─┐
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│ 201901 │ 201901_1_3_1 │ 0 │
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│ 201901 │ 201901_1_9_2 │ 1 │
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│ 201901 │ 201901_8_8_0 │ 0 │
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│ 201901 │ 201901_9_9_0 │ 0 │
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│ 201902 │ 201902_4_6_1 │ 1 │
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│ 201902 │ 201902_10_10_0 │ 1 │
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│ 201902 │ 201902_11_11_0 │ 1 │
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└───────────┴────────────────┴────────┘
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```
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Note: For old-style tables, the partition can be specified either as a number `201710` or a string `'201710'`. The syntax for the new style of tables is stricter with types (similar to the parser for the VALUES input format). In addition, ALTER TABLE FREEZE PARTITION uses exact match for new-style tables (not prefix match).
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`partition` 列存储分区的名称。此示例中有两个分区：`201901` 和 `201902`。在 [ALTER ... PARTITION](#alter_manipulations-with-partitions) 语句中你可以使用该列值来指定分区名称。
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In the `system.parts` table, the `partition` column specifies the value of the partition expression to use in ALTER queries (if quotas are removed). The `name` column should specify the name of the data part that has a new format.
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`name` 列为分区中数据片段的名称。在 [ALTER ATTACH PART](#alter_attach-partition) 语句中你可以使用此列值中来指定片段名称。
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Old: `20140317_20140323_2_2_0` (minimum date - maximum date - minimum block number - maximum block number - level).
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这里我们拆解下第一部分的名称：`201901_1_3_1`：
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Now: `201403_2_2_0` (partition ID - minimum block number - maximum block number - level).
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- `201901` 是分区名称。
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- `1` 是数据块的最小编号。
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- `3` 是数据块的最大编号。
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- `1` 是块级别（即在由块组成的合并树中，该块在树中的深度）。
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The partition ID is its string identifier (human-readable, if possible) that is used for the names of data parts in the file system and in ZooKeeper. You can specify it in ALTER queries in place of the partition key. Example: Partition key `toYYYYMM(EventDate)`; ALTER can specify either `PARTITION 201710` or `PARTITION ID '201710'`.
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!!! 注意
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旧类型表的片段名称为：`20190117_20190123_2_2_0`（最小日期 - 最大日期 - 最小块编号 - 最大块编号 - 块级别）。
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For more examples, see the tests [`00502_custom_partitioning_local`](https://github.com/yandex/ClickHouse/blob/master/dbms/tests/queries/0_stateless/00502_custom_partitioning_local.sql) and [`00502_custom_partitioning_replicated_zookeeper`](https://github.com/yandex/ClickHouse/blob/master/dbms/tests/queries/0_stateless/00502_custom_partitioning_replicated_zookeeper.sql).
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`active` 列为片段状态。`1` 激活状态；`0` 非激活状态。非激活片段是那些在合并到较大片段之后剩余的源数据片段。损坏的数据片段也表示为非活动状态。
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正如在示例中所看到的，同一分区中有几个独立的片段（例如，`201901_1_3_1`和`201901_1_9_2`）。这意味着这些片段尚未合并。ClickHouse 大约在插入后15分钟定期报告合并操作，合并插入的数据片段。此外，你也可以使用 [OPTIMIZE](../../query_language/misc.md#misc_operations-optimize) 语句直接执行合并。例：
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[Original article](https://clickhouse.yandex/docs/en/operations/table_engines/custom_partitioning_key/) <!--hide-->
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``` sql
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OPTIMIZE TABLE visits PARTITION 201902;
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```
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```
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┌─partition─┬─name───────────┬─active─┐
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│ 201901 │ 201901_1_3_1 │ 0 │
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│ 201901 │ 201901_1_9_2 │ 1 │
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│ 201901 │ 201901_8_8_0 │ 0 │
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│ 201901 │ 201901_9_9_0 │ 0 │
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│ 201902 │ 201902_4_6_1 │ 0 │
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│ 201902 │ 201902_4_11_2 │ 1 │
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│ 201902 │ 201902_10_10_0 │ 0 │
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│ 201902 │ 201902_11_11_0 │ 0 │
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└───────────┴────────────────┴────────┘
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```
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非激活片段会在合并后的10分钟左右删除。
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查看片段和分区信息的另一种方法是进入表的目录：`/var/lib/clickhouse/data/<database>/<table>/`。例如：
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```bash
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dev:/var/lib/clickhouse/data/default/visits$ ls -l
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total 40
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drwxr-xr-x 2 clickhouse clickhouse 4096 Feb 1 16:48 201901_1_3_1
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drwxr-xr-x 2 clickhouse clickhouse 4096 Feb 5 16:17 201901_1_9_2
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drwxr-xr-x 2 clickhouse clickhouse 4096 Feb 5 15:52 201901_8_8_0
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drwxr-xr-x 2 clickhouse clickhouse 4096 Feb 5 15:52 201901_9_9_0
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drwxr-xr-x 2 clickhouse clickhouse 4096 Feb 5 16:17 201902_10_10_0
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drwxr-xr-x 2 clickhouse clickhouse 4096 Feb 5 16:17 201902_11_11_0
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drwxr-xr-x 2 clickhouse clickhouse 4096 Feb 5 16:19 201902_4_11_2
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drwxr-xr-x 2 clickhouse clickhouse 4096 Feb 5 12:09 201902_4_6_1
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drwxr-xr-x 2 clickhouse clickhouse 4096 Feb 1 16:48 detached
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```
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文件夹 '201901_1_1_0'，'201901_1_7_1' 等是片段的目录。每个片段都与一个对应的分区相关，并且只包含这个月的数据（本例中的表按月分区）。
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`detached` 目录存放着使用 [DETACH](#alter_detach-partition) 语句从表中分离的片段。损坏的片段也会移到该目录，而不是删除。服务器不使用`detached`目录中的片段。可以随时添加，删除或修改此目录中的数据 – 在运行 [ATTACH](../../query_language/alter.md#alter_attach-partition) 语句前，服务器不会感知到。
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注意，在操作服务器时，你不能手动更改文件系统上的片段集或其数据，因为服务器不会感知到这些修改。对于非复制表，可以在服务器停止时执行这些操作，但不建议这样做。对于复制表，在任何情况下都不要更改片段文件。
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ClickHouse 支持对分区执行这些操作：删除分区，从一个表复制到另一个表，或创建备份。了解分区的所有操作，请参阅 [分区和片段的操作](../../query_language/alter.md#alter_manipulations-with-partitions) 一节。
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[来源文章](https://clickhouse.yandex/docs/en/operations/table_engines/custom_partitioning_key/) <!--hide-->
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