flink1.12 sql向redis实时写数据

插件名称：flink-connector-redis

插件地址：https://github.com/jeff-zou/flink-connector-redis.git

项目介绍

基于bahir-flink二次开发，使它支持SQL直接定义写入redis,用户通过DDL指定自己需要保存的字段。

使用方法:

命令行执行 mvn package -DskipTests=true打包后，将生成的包flink-connector-redis_2.12-1.11.1.jar引入flink lib中即可，无需其它设置。

重构介绍：

相对上一个版本简化了参数设置，思路更清晰，上一版本字段的值会根据主键等条件来自动生成，这要求使用者需要了解相关规则，有一定的学习成本并且容易埋坑，重构后字段的值由用户在DDL中显示地指定，如下：

  'key-column'='username','value-column'='passport',' //直接指定字段名

取消了必须有主键的限制，使用更简单，如果有多个字段组合成key或者value,需要用户在DML中使用concat_ws等方式组装，不再是插件在后台用不可见字符拼装。

使用示例:

• 1.SQL方式
  
  示例代码路径: src/test/java/org.apache.flink.streaming.connectors.redis.table.SQLInsertTest.java
  
  set示例，相当于redis命令： set test test11

       StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        EnvironmentSettings environmentSettings = EnvironmentSettings.newInstance().useBlinkPlanner().inStreamingMode().build();
        StreamTableEnvironment tEnv = StreamTableEnvironment.create(env, environmentSettings);

        String ddl = "create table sink_redis(username VARCHAR, passport VARCHAR) with ( 'connector'='redis', " +
                "'host'='10.11.80.147','port'='7001', 'redis-mode'='single','password'='******','key-column'='username','value-column'='passport','command'='set')" ;

        tEnv.executeSql(ddl);
        String sql = " insert into sink_redis select * from (values ('test', 'test11'))";
        TableResult tableResult = tEnv.executeSql(sql);
        tableResult.getJobClient().get()
                .getJobExecutionResult()
                .get();

• 2.DataStream方式
  
  示例代码路径:
  src/test/java/org.apache.flink.streaming.connectors.redis.datastream.DataStreamInsertTest.java
  
  hset示例，相当于redis命令：hset tom math 150

        Configuration configuration = new Configuration();
        configuration.setString(RedisOptions.KEY_COLUMN, "name");
        configuration.setString(RedisOptions.FIELD_COLUMN, "subject"); //对应hash的field、 sorted set的score
        configuration.setString(RedisOptions.VALUE_COLUMN, "score");
        configuration.setString(REDIS_MODE, REDIS_CLUSTER);
        configuration.setString(REDIS_COMMAND, RedisCommand.HSET.name());

        RedisMapper redisMapper = RedisHandlerServices
                .findRedisHandler(RedisMapperHandler.class, configuration.toMap())
                .createRedisMapper(configuration);

        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        GenericRowData genericRowData = new GenericRowData(3);
        genericRowData.setField(0, "tom");
        genericRowData.setField(1, "math");
        genericRowData.setField(2, "150");
        DataStream<GenericRowData> dataStream = env.fromElements(genericRowData);

        TableSchema tableSchema =  new TableSchema.Builder() .field("name", DataTypes.STRING().notNull()).field("subject", DataTypes.STRING()).field("score", DataTypes.INT()).build();

        FlinkJedisConfigBase conf = getLocalRedisClusterConfig();
        RedisSink redisSink = new RedisSink<>(conf, redisMapper, tableSchema);

        dataStream.addSink(redisSink);
        env.execute("RedisSinkTest");