Flink Databend Connector

Flink SQL connector for Databend database, this project Powered by Databend JDBC.

Currently, the project supports Sink Table.
Please create issues if you encounter bugs and any help for the project is greatly appreciated.

Connector Options

NOTE: sink.ignore-delete default value is true so this connector doesn't support DELETE default. If you make sink.ignore-delete=false make sure the source database has an Integer or String type primary key.

Upsert Data Considerations:

Data Type Mapping

Maven Dependency

The project isn't published to the maven central repository, we need to deploy/install to our own repository before use it, step as follows:

# clone the project
git clone https://github.com/databendcloud/flink-connector-databend.git

# enter the project directory
cd flink-connector-databend/

# display remote branches
git branch -r

# checkout the branch you need
git checkout $branch_name

# install or deploy the project to our own repository
mvn clean install -DskipTests
mvn clean deploy -DskipTests

<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-connector-databend</artifactId>
    <version>1.0.0-SNAPSHOT</version>
</dependency>

How to use

Create and read/write table

-- register a databend table `t_user` in flink sql.
CREATE TABLE t_user
(
    `user_id`   BIGINT,
    `user_type` INTEGER,
    `language`  STRING,
    `country`   STRING,
    `gender`    STRING,
    `score`     DOUBLE,
    `list`      ARRAY<STRING>,
    `map`       Map<STRING,
    BIGINT>,
    PRIMARY KEY (user_id)
) WITH (
      'connector' = 'databend',
      'url' = 'databend://{ip}:{port}',
      'database-name' = 'default',
      'table-name' = 'users',
      'sink.batch-size' = '500',
      'sink.flush-interval' = '1000',
      'sink.ignore-delete' = 'false',
      'sink.max-retries' = '3'
      );

-- read data from databend 
SELECT user_id, user_type
from t_user;

-- write data into the databend table from the table `T`
INSERT INTO t_user
SELECT cast(`user_id` as BIGINT),
       `user_type`,
       `lang`,
       `country`,
       `gender`,
       `score`,
       ARRAY['CODER',
       'SPORTSMAN'], CAST(MAP['BABA', cast(10 as BIGINT), 'NIO', cast(8 as BIGINT)] AS MAP<STRING, BIGINT>)
FROM T;

Create and use DatabendCatalog

Scala

val tEnv = TableEnvironment.create(setting)

val props = new util.HashMap[String, String]()
props.put(DatabendConfig.DATABASE_NAME, "default")
props.put(DatabendConfig.URL, "databend://127.0.0.1:8000")
props.put(DatabendConfig.USERNAME, "username")
props.put(DatabendConfig.PASSWORD, "password")
props.put(DatabendConfig.SINK_FLUSH_INTERVAL, "30s")
val cHcatalog = new DatabendConfig("databend", props)
tEnv.registerCatalog("databend", datbendcatalog)
tEnv.useCatalog("databend")

tEnv.executeSql("insert into `databend`.`default`.`t_table` select...");

Java

TableEnvironment tEnv=TableEnvironment.create(setting);

        Map<String, String> props=new HashMap<>();
        props.put(DatabendConfig.DATABASE_NAME,"default")
        props.put(DatabendConfig.URL,"databend://127.0.0.1:8000")
        props.put(DatabendConfig.USERNAME,"username")
        props.put(DatabendConfig.PASSWORD,"password")
        props.put(DatabendConfig.SINK_FLUSH_INTERVAL,"30s");
        Catalog cHcatalog=new DatabendConfig("databend",props);
        tEnv.registerCatalog("databend",databendcatalog);
        tEnv.useCatalog("databend");

        tEnv.executeSql("insert into `databend`.`default`.`t_table` select...");

Roadmap

• [x] Implement the Flink SQL Sink function.
• [x] Support DatabendCatalog.
• [x] Implement the Flink SQL Source function.