Flink Table API/SQL 多分支sink

背景

在某个场景中,需要从Kafka中获取数据,经过转换处理后,需要同时sink到多个输出源中(kafka、mysql、hologres)等。两次调用execute, 阿里云Flink vvr引擎报错:

java 复制代码
public static void main(String[] args) {
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        StreamTableEnvironment tEnv = StreamTableEnvironment.create(env);
        StreamStatementSet streamStatementSet = tEnv.createStatementSet();

        String s = LocalDateTimeUtils.getDateTime(System.currentTimeMillis());

        DataStream<String> dataStream = env.fromElements(s, LocalDateTimeUtils.getDateTime(System.currentTimeMillis()));

        tEnv.executeSql(KAFKA_TABLE_SQL);
        tEnv.executeSql(KAFKA_TABLE_SQL_1);


        Table table = tEnv.fromDataStream(dataStream);
        table.insertInto("kafka_sink").execute();
        table.insertInto("kafka_sink_1").execute();

        streamStatementSet.execute();
    }
java 复制代码
Caused by: org.apache.flink.util.FlinkRuntimeException: Cannot have more than one execute() or executeAsync() call in a single environment.
	at org.apache.flink.client.program.StreamContextEnvironment.validateAllowedExecution(StreamContextEnvironment.java:199) ~[flink-dist-1.15-vvr-6.0.7-1-SNAPSHOT.jar:1.15-vvr-6.0.7-1-SNAPSHOT]
	at org.apache.flink.client.program.StreamContextEnvironment.executeAsync(StreamContextEnvironment.java:187) ~[flink-dist-1.15-vvr-6.0.7-1-SNAPSHOT.jar:1.15-vvr-6.0.7-1-SNAPSHOT]
	at org.apache.flink.table.planner.delegation.DefaultExecutor.executeAsync(DefaultExecutor.java:110) ~[?:?]
	at org.apache.flink.table.api.internal.TableEnvironmentImpl.executeInternal(TableEnvironmentImpl.java:877) ~[flink-table-api-java-uber-1.15-vvr-6.0.7-1-SNAPSHOT.jar:1.15-vvr-6.0.7-1-SNAPSHOT]
	at org.apache.flink.table.api.internal.TableEnvironmentImpl.executeInternal(TableEnvironmentImpl.java:756) ~[flink-table-api-java-uber-1.15-vvr-6.0.7-1-SNAPSHOT.jar:1.15-vvr-6.0.7-1-SNAPSHOT]
	at org.apache.flink.table.api.internal.TableEnvironmentImpl.executeInternal(TableEnvironmentImpl.java:955) ~[flink-table-api-java-uber-1.15-vvr-6.0.7-1-SNAPSHOT.jar:1.15-vvr-6.0.7-1-SNAPSHOT]
	at org.apache.flink.table.api.internal.TablePipelineImpl.execute(TablePipelineImpl.java:57) ~[flink-table-api-java-uber-1.15-vvr-6.0.7-1-SNAPSHOT.jar:1.15-vvr-6.0.7-1-SNAPSHOT]

解决

使用 StreamStatementSet. 具体参考官网:

https://nightlies.apache.org/flink/flink-docs-release-1.15/zh/docs/dev/table/data_stream_api/#converting-between-datastream-and-table

改良后的代码:

java 复制代码
public static void main(String[] args) {
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        StreamTableEnvironment tEnv = StreamTableEnvironment.create(env);
        StreamStatementSet streamStatementSet = tEnv.createStatementSet();

        String s = LocalDateTimeUtils.getDateTime(System.currentTimeMillis());

        DataStream<String> dataStream = env.fromElements(s, LocalDateTimeUtils.getDateTime(System.currentTimeMillis()));

        tEnv.executeSql(KAFKA_TABLE_SQL);
        tEnv.executeSql(KAFKA_TABLE_SQL_1);


        Table table = tEnv.fromDataStream(dataStream);

        streamStatementSet.addInsert("kafka_sink", table);
        streamStatementSet.addInsert("kafka_sink_1", table);

        streamStatementSet.execute();
    }
相关推荐
D愿你归来仍是少年6 小时前
Apache Flink Checkpoint 与 Chandy-Lamport 算法深度解析
算法·flink·apache
docsz6 小时前
Flink-1.20集群部署
linux·服务器·flink
念陌曦2 天前
Flink总结
大数据·flink
岁岁种桃花儿3 天前
Flink从入门到上天系列第二十五篇:Flink和Kafka连接时的精准一次性
大数据·flink·kafka
岁岁种桃花儿4 天前
Flink从入门到上天系列第二十四篇:Flink中的保存点
大数据·flink
yumgpkpm4 天前
华为昇腾910B 开源软件GPUStack的介绍(Cloudera CDH、CDP)
人工智能·hadoop·elasticsearch·flink·kafka·企业微信·big data
岁岁种桃花儿5 天前
Flink从入门到上天系列第二十二篇:Flink中通过UI查看检查点
大数据·ui·flink
D愿你归来仍是少年5 天前
Apache Flink 算子(Operator)深度解析
大数据·flink·apache
岁岁种桃花儿5 天前
Flink从入门到上天系列第二十一篇:Flink当中的检查点配置
大数据·flink
岁岁种桃花儿5 天前
Flink从入门到上天系列第二十三篇:Flink中增量检查点和最终检查点
大数据·flink