--- slug: /en/engines/table-engines/integrations/redis sidebar_position: 175 sidebar_label: Redis --- # Redis This engine allows integrating ClickHouse with [Redis](https://redis.io/). For Redis takes kv model, we strongly recommend you only query it in a point way, such as `where k=xx` or `where k in (xx, xx)`. ## Creating a Table {#creating-a-table} ``` sql CREATE TABLE [IF NOT EXISTS] [db.]table_name ( name1 [type1], name2 [type2], ... ) ENGINE = Redis({host:port[, db_index[, password[, pool_size]]] | named_collection[, option=value [,..]] }) PRIMARY KEY(primary_key_name); ``` **Engine Parameters** - `host:port` — Redis server address, you can ignore port and default Redis port 6379 will be used. - `db_index` — Redis db index range from 0 to 15, default is 0. - `password` — User password, default is blank string. - `pool_size` — Redis max connection pool size, default is 16. - `primary_key_name` - any column name in the column list. :::note Serialization `PRIMARY KEY` supports only one column. The primary key will be serialized in binary as a Redis key. Columns other than the primary key will be serialized in binary as Redis value in corresponding order. ::: Arguments also can be passed using [named collections](/docs/en/operations/named-collections.md). In this case `host` and `port` should be specified separately. This approach is recommended for production environment. At this moment, all parameters passed using named collections to redis are required. :::note Filtering Queries with `key equals` or `in filtering` will be optimized to multi keys lookup from Redis. If queries without filtering key full table scan will happen which is a heavy operation. ::: ## Usage Example {#usage-example} Create a table in ClickHouse using `Redis` engine with plain arguments: ``` sql CREATE TABLE redis_table ( `key` String, `v1` UInt32, `v2` String, `v3` Float32 ) ENGINE = Redis('redis1:6379') PRIMARY KEY(key); ``` Or using [named collections](/docs/en/operations/named-collections.md): ``` localhost 6379 **** 16 s0 ``` ```sql CREATE TABLE redis_table ( `key` String, `v1` UInt32, `v2` String, `v3` Float32 ) ENGINE = Redis(redis_creds) PRIMARY KEY(key); ``` Insert: ```sql INSERT INTO redis_table Values('1', 1, '1', 1.0), ('2', 2, '2', 2.0); ``` Query: ``` sql SELECT COUNT(*) FROM redis_table; ``` ``` text ┌─count()─┐ │ 2 │ └─────────┘ ``` ``` sql SELECT * FROM redis_table WHERE key='1'; ``` ```text ┌─key─┬─v1─┬─v2─┬─v3─┐ │ 1 │ 1 │ 1 │ 1 │ └─────┴────┴────┴────┘ ``` ``` sql SELECT * FROM redis_table WHERE v1=2; ``` ```text ┌─key─┬─v1─┬─v2─┬─v3─┐ │ 2 │ 2 │ 2 │ 2 │ └─────┴────┴────┴────┘ ``` Update: Note that the primary key cannot be updated. ```sql ALTER TABLE redis_table UPDATE v1=2 WHERE key='1'; ``` Delete: ```sql ALTER TABLE redis_table DELETE WHERE key='1'; ``` Truncate: Flush Redis db asynchronously. Also `Truncate` support SYNC mode. ```sql TRUNCATE TABLE redis_table SYNC; ``` Join: Join with other tables. ``` SELECT * FROM redis_table JOIN merge_tree_table ON merge_tree_table.key=redis_table.key; ``` ## Limitations {#limitations} Redis engine also supports scanning queries, such as `where k > xx`, but it has some limitations: 1. Scanning query may produce some duplicated keys in a very rare case when it is rehashing. See details in [Redis Scan](https://github.com/redis/redis/blob/e4d183afd33e0b2e6e8d1c79a832f678a04a7886/src/dict.c#L1186-L1269). 2. During the scanning, keys could be created and deleted, so the resulting dataset can not represent a valid point in time.