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119 lines
4.3 KiB
Markdown
119 lines
4.3 KiB
Markdown
---
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slug: /en/engines/table-engines/special/keeper-map
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sidebar_position: 150
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sidebar_label: KeeperMap
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---
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# KeeperMap {#keepermap}
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This engine allows you to use Keeper/ZooKeeper cluster as consistent key-value store with linearizable writes and sequentially consistent reads.
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To enable KeeperMap storage engine, you need to define a ZooKeeper path where the tables will be stored using `<keeper_map_path_prefix>` config.
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For example:
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```xml
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<clickhouse>
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<keeper_map_path_prefix>/keeper_map_tables</keeper_map_path_prefix>
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</clickhouse>
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```
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where path can be any other valid ZooKeeper path.
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## Creating a Table {#creating-a-table}
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``` sql
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CREATE TABLE [IF NOT EXISTS] [db.]table_name [ON CLUSTER cluster]
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(
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name1 [type1] [DEFAULT|MATERIALIZED|ALIAS expr1],
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name2 [type2] [DEFAULT|MATERIALIZED|ALIAS expr2],
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...
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) ENGINE = KeeperMap(root_path, [keys_limit]) PRIMARY KEY(primary_key_name)
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```
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Engine parameters:
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- `root_path` - ZooKeeper path where the `table_name` will be stored.
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This path should not contain the prefix defined by `<keeper_map_path_prefix>` config because the prefix will be automatically appended to the `root_path`.
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Additionally, format of `auxiliary_zookeper_cluster_name:/some/path` is also supported where `auxiliary_zookeper_cluster` is a ZooKeeper cluster defined inside `<auxiliary_zookeepers>` config.
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By default, ZooKeeper cluster defined inside `<zookeeper>` config is used.
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- `keys_limit` - number of keys allowed inside the table.
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This limit is a soft limit and it can be possible that more keys will end up in the table for some edge cases.
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- `primary_key_name` – any column name in the column list.
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- `primary key` must be specified, it supports only one column in the primary key. The primary key will be serialized in binary as a `node name` inside ZooKeeper.
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- columns other than the primary key will be serialized to binary in corresponding order and stored as a value of the resulting node defined by the serialized key.
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- queries with key `equals` or `in` filtering will be optimized to multi keys lookup from `Keeper`, otherwise all values will be fetched.
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Example:
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``` sql
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CREATE TABLE keeper_map_table
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(
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`key` String,
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`v1` UInt32,
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`v2` String,
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`v3` Float32
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)
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ENGINE = KeeperMap(/keeper_map_table, 4)
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PRIMARY KEY key
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```
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with
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```xml
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<clickhouse>
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<keeper_map_path_prefix>/keeper_map_tables</keeper_map_path_prefix>
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</clickhouse>
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```
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Each value, which is binary serialization of `(v1, v2, v3)`, will be stored inside `/keeper_map_tables/keeper_map_table/data/serialized_key` in `Keeper`.
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Additionally, number of keys will have a soft limit of 4 for the number of keys.
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If multiple tables are created on the same ZooKeeper path, the values are persisted until there exists at least 1 table using it.
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As a result, it is possible to use `ON CLUSTER` clause when creating the table and sharing the data from multiple ClickHouse instances.
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Of course, it's possible to manually run `CREATE TABLE` with same path on unrelated ClickHouse instances to have same data sharing effect.
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## Supported operations {#supported-operations}
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### Inserts
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When new rows are inserted into `KeeperMap`, if the key does not exist, a new entry for the key is created.
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If the key exists, and setting `keeper_map_strict_mode` is set to `true`, an exception is thrown, otherwise, the value for the key is overwritten.
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Example:
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```sql
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INSERT INTO keeper_map_table VALUES ('some key', 1, 'value', 3.2);
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```
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### Deletes
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Rows can be deleted using `DELETE` query or `TRUNCATE`.
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If the key exists, and setting `keeper_map_strict_mode` is set to `true`, fetching and deleting data will succeed only if it can be executed atomically.
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```sql
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DELETE FROM keeper_map_table WHERE key LIKE 'some%' AND v1 > 1;
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```
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```sql
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ALTER TABLE keeper_map_table DELETE WHERE key LIKE 'some%' AND v1 > 1;
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```
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```sql
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TRUNCATE TABLE keeper_map_table;
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```
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### Updates
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Values can be updated using `ALTER TABLE` query. Primary key cannot be updated.
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If setting `keeper_map_strict_mode` is set to `true`, fetching and updating data will succeed only if it's executed atomically.
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```sql
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ALTER TABLE keeper_map_table UPDATE v1 = v1 * 10 + 2 WHERE key LIKE 'some%' AND v3 > 3.1;
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```
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## Related content
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- Blog: [Building a Real-time Analytics Apps with ClickHouse and Hex](https://clickhouse.com/blog/building-real-time-applications-with-clickhouse-and-hex-notebook-keeper-engine)
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