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title: “Local Execution”

Local Execution/Debugging

Flink can run on a single machine, even in a single Java Virtual Machine. This allows users to test and debug Flink programs locally. This section gives an overview of the local execution mechanisms.

NOTE: Please also refer to the debugging section in the Java API documentation for a guide to testing and local debugging utilities in the Java API.

The local environments and executors allow you to run Flink programs in local Java Virtual Machine, or with within any JVM as part of existing programs. Most examples can be launched locally by simply hitting the “Run” button of your IDE.

If you are running Flink programs locally, you can also debug your program like any other Java program. You can either use System.out.println() to write out some internal variables or you can use the debugger. It is possible to set breakpoints within map(), reduce() and all the other methods.

The JobExecutionResult object, which is returned after the execution finished, contains the program runtime and the accumulator results.

Note: The local execution environments do not start any web frontend to monitor the execution.

Maven Dependency

If you are developing your program in a Maven project, you have to add the flink-clients module using this dependency:

<dependency>
  <groupId>org.apache.flink</groupId>
  <artifactId>flink-clients</artifactId>
  <version>{{site.FLINK_VERSION_STABLE}}</version>
</dependency>

Local Environment

The LocalEnvironment is a handle to local execution for Flink programs. Use it to run a program within a local JVM - standalone or embedded in other programs.

The local environment is instantiated via the method ExecutionEnvironment.createLocalEnvironment(). By default, it will use as many local threads for execution as your machine has CPU cores (hardware contexts). You can alternatively specify the desired parallelism. The local environment can be configured to log to the console using enableLogging()/disableLogging().

In most cases, calling ExecutionEnvironment.getExecutionEnvironment() is the even better way to go. That method returns a LocalEnvironment when the program is started locally (outside the command line interface), and it returns a pre-configured environment for cluster execution, when the program is invoked by the command line interface.

public static void main(String[] args) throws Exception {
    ExecutionEnvironment env = ExecutionEnvironment.createLocalEnvironment();

    DataSet<String> data = env.readTextFile("file:///path/to/file");

    data
        .filter(new FilterFunction<String>() {
            public boolean filter(String value) {
                return value.startsWith("http://");
            }
        })
        .writeAsText("file:///path/to/result");

    env.execute();
}

Local Executor

The LocalExecutor is similar to the local environment, but it takes a Plan object, which describes the program as a single executable unit. The LocalExecutor is typically used with the Scala API.

The following code shows how you would use the LocalExecutor with the Wordcount example for Scala Programs:

public static void main(String[] args) throws Exception {
    val input = TextFile("hdfs://path/to/file")

    val words = input flatMap { _.toLowerCase().split("""\W+""") filter { _ != "" } }
    val counts = words groupBy { x => x } count()

    val output = counts.write(wordsOutput, CsvOutputFormat())
  
    val plan = new ScalaPlan(Seq(output), "Word Count")
    LocalExecutor.executePlan(p);
}

LocalDistributedExecutor

Flink also offers a LocalDistributedExecutor which starts multiple TaskManagers within one JVM. The standard LocalExecutor starts one JobManager and one TaskManager in one JVM. With the LocalDistributedExecutor you can define the number of TaskManagers to start. This is useful for debugging network related code and more of a developer tool than a user tool.

public static void main(String[] args) throws Exception {
    ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();

    DataSet<String> data = env.readTextFile("hdfs://path/to/file");

    data
        .filter(new FilterFunction<String>() {
            public boolean filter(String value) {
                return value.startsWith("http://");
            }
        })
        .writeAsText("hdfs://path/to/result");

    Plan p = env.createProgramPlan();
    LocalDistributedExecutor lde = new LocalDistributedExecutor();
    lde.startNephele(2); // start two TaskManagers
    lde.run(p);
}