Help Center/ Data Lake Insight/ Flink SQL Syntax Reference/ Flink Opensource SQL 1.10 Syntax Reference/ Data Definition Language (DDL)/ Creating a Result Table/ Redis Result Table
Updated on 2024-09-29 GMT+08:00
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Redis Result Table

Function

DLI exports the output data of the Flink job to Redis. Redis is a storage system that supports multiple types of data structures such as key-value. It can be used in scenarios such as caching, event pub/sub, and high-speed queuing. Redis supports direct read/write of strings, hashes, lists, queues, and sets. Redis works with in-memory dataset and provides persistence. For more information about Redis, visit https://redis.io/.

Prerequisites

An enhanced datasource connection with Redis has been established, so that you can configure security group rules as required.

Syntax

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create table dwsSink (
  attr_name attr_type 
  (',' attr_name attr_type)* 
  (','PRIMARY KEY (attr_name, ...) NOT ENFORCED)
)
with (
'connector.type' = 'redis',
  'connector.host' = '',
  'connector.port' = '',
  'connector.password' = '',
  'connector.table-name' = '',
  'connector.key-column' = ''
);

Parameters

Table 1 Parameter description

Parameter

Mandatory

Description

connector.type

Yes

Connector type. Set this parameter to redis.

connector.host

Yes

Redis connector address

connector.port

Yes

Redis connector port

connector.password

No

Redis authentication password

connector.deploy-mode

No

Redis deployment mode. The value can be standalone or cluster. The default value is standalone.

connector.table-name

No

Name of the table stored in the Redis. This parameter is mandatory in the Redis Hashmap storage pattern. In this pattern, data is stored to Redis in hashmaps. The hash key is ${table-name}:${ext-key}, and the field name is the column name.

NOTE:

Table storage pattern: connector.table-name and connector.key-column are used as Redis keys. For the Redis hash type, each key corresponds to a hashmap. A hash key is a field name of the source table, and a hash value is a field value of the source table.

connector.key-column

No

This parameter is optional in table storage pattern. The value is used as the value of ext-key in the Redis. If this parameter is not set, the value of ext-key is the generated UUID.

connector.write-schema

No

Whether to write the current schema to the Redis. This parameter is available in table storage pattern. The default value is false.

connector.data-type

No

Data types for storage. This parameter is mandatory for a custom storage pattern. Supported values include string, list, hash, and set. In a string, list or set, the number of schema fields must be 2, and the number of hash fields must be 3.

connector.ignore-retraction

No

Whether to ignore the retraction message. The default value is false.

Precautions

Either connector.table-name or connector.data-type must be set.

Example

  • Configure the table storage pattern when you configure connector.table-name.
    In table storage pattern, data is stored in hash mode, which is different from the basic hash pattern in which the three fields of a table are used as the key, hash_key, and hash_value. The key in table pattern can be specified by connector.table-name and connector.key-column parameters, all field names in the table are used as hash_key, and the field values are written to the hash table as hash_value. 
    create table redisSink(
  car_id STRING,
  car_owner STRING,
  car_brand STRING,
  car_speed INT
) with (
  'connector.type' = 'redis',
  'connector.host' = 'xx.xx.xx.xx',
  'connector.port' = '6379',
  'connector.password' = 'xx',
  'connector.table-name'='car_info',
  'connector.key-column'='car_id'
);

insert into redisSink
  (car_id,car_owner,car_brand,car_speed)
  VALUES
  ("A1234","OwnA","A1234",30);
  • The following example shows how to create a table when connector.data-type is set to string, list, hash, or set, respectively.
    • String type
      The table contains two columns: key and value. 
      create table redisSink(
  attr1 STRING,
  attr2 STRING
) with (
  'connector.type' = 'redis',
  'connector.host' = 'xx.xx.xx.xx',
  'connector.port' = '6379',
  'connector.password' = 'xx',
  'connector.data-type' = 'string'
);

insert into redisSink
  (attr1,attr2)
  VALUES
  ("car_id","A1234");
    • List type
      The table contains two columns: key and value. 
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      create table redisSink(
  attr1 STRING,
  attr2 STRING
) with (
  'connector.type' = 'redis',
  'connector.host' = 'xx.xx.xx.xx',
  'connector.port' = '6379',
  'connector.password' = 'xx',
  'connector.data-type' = 'list'
);

insert into redisSink
  (attr1,attr2)
  VALUES
  ("car_id","A1234");
    • Set type
      The table contains two columns: key and value. 
      create table redisSink(
  attr1 STRING,
  attr2 STRING
) with (
  'connector.type' = 'redis',
  'connector.host' = 'xx.xx.xx.xx',
  'connector.port' = '6379',
  'connector.password' = 'xx',
  'connector.data-type' = 'set'
);

insert into redisSink
  (attr1,attr2)
  VALUES
  ("car_id","A1234");
    • Hash type
      The table contains three columns: key, hash_key, and hash_value. 
      create table redisSink(
  attr1 STRING,
  attr2 STRING,
  attr3 STRING
) with (
  'connector.type' = 'redis',
  'connector.host' = 'xx.xx.xx.xx',
  'connector.port' = '6379',
  'connector.password' = 'xx',
  'connector.data-type' = 'hash'
);

insert into redisSink
  (attr1,attr2,attr3)
  VALUES
  ("car_info","car_id","A1234");
Parent topic: Creating a Result Table