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:
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();
}
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:
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();
}