Flink（八）Flink的Parallelism并行度

一、Flink的Parallel Execution

实例

1.Operator Level

final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
​
DataStream<String> text = [...]
DataStream<Tuple2<String, Integer>> wordCounts = text
    .flatMap(new LineSplitter())
    .keyBy(0)
    .timeWindow(Time.seconds(5))
    .sum(1).setParallelism(5);
​
wordCounts.print();
​
env.execute("Word Count Example");

operators、data sources、data sinks都可以调用setParallelism()方法来设置parallelism

2.Execution Environment Level

final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
env.setParallelism(3);
​
DataStream<String> text = [...]
DataStream<Tuple2<String, Integer>> wordCounts = [...]
wordCounts.print();
​
env.execute("Word Count Example");

在ExecutionEnvironment里头可以通过setParallelism来给operators、data sources、data sinks设置默认的parallelism；如果operators、data sources、data sinks自己有设置parallelism则会覆盖ExecutionEnvironment设置的parallelism

3.Client Level

./bin/flink run -p 10 ../examples/*WordCount-java*.jar

或者

try {
    PackagedProgram program = new PackagedProgram(file, args);
    InetSocketAddress jobManagerAddress = RemoteExecutor.getInetFromHostport("localhost:6123");
    Configuration config = new Configuration();
​
    Client client = new Client(jobManagerAddress, config, program.getUserCodeClassLoader());
​
    // set the parallelism to 10 here
    client.run(program, 10, true);
​
} catch (ProgramInvocationException e) {
    e.printStackTrace();
}

使用CLI client，可以在命令行调用是用-p来指定，或者Java/Scala调用时在Client.run的参数中指定parallelism

4.System Level

# The parallelism used for programs that did not specify and other parallelism.
​
parallelism.default: 1

可以在flink-conf.yaml中通过parallelism.default配置项给所有execution environments指定系统级的默认parallelism

小结

Flink可以设置好几个level的parallelism，其中包括Operator Level、Execution Environment Level、Client Level、System Level 在flink-conf.yaml中通过parallelism.default配置项给所有execution environments指定系统级的默认parallelism；在ExecutionEnvironment里头可以通过setParallelism来给operators、data sources、data sinks设置默认的parallelism；如果operators、data sources、data sinks自己有设置parallelism则会覆盖ExecutionEnvironment设置的parallelism