How to use

createRemoteEnvironment

method

in

org.apache.flink.streaming.api.environment.StreamExecutionEnvironment

/**
 * A thin wrapper layer over {@link StreamExecutionEnvironment#createRemoteEnvironment(String, int, String...)}.
 *
 * @param host The host name or address of the master (JobManager), where the
 * program should be executed.
 * @param port The port of the master (JobManager), where the program should
 * be executed.
 * @param jar_files The JAR files with code that needs to be shipped to the
 * cluster. If the program uses user-defined functions,
 * user-defined input formats, or any libraries, those must be
 * provided in the JAR files.
 * @return A remote environment that executes the program on a cluster.
 */
public PythonStreamExecutionEnvironment create_remote_execution_environment(
  String host, int port, String... jar_files) {
  return new PythonStreamExecutionEnvironment(
    StreamExecutionEnvironment.createRemoteEnvironment(host, port, jar_files), new Path(localTmpPath), scriptName);
}

/**
 * A thin wrapper layer over {@link StreamExecutionEnvironment#createRemoteEnvironment(
 *String, int, Configuration, String...)}.
 *
 * @param host The host name or address of the master (JobManager), where the
 * program should be executed.
 * @param port The port of the master (JobManager), where the program should
 * be executed.
 * @param config The configuration used by the client that connects to the remote cluster.
 * @param jar_files The JAR files with code that needs to be shipped to the
 * cluster. If the program uses user-defined functions,
 * user-defined input formats, or any libraries, those must be
 * provided in the JAR files.
 * @return A remote environment that executes the program on a cluster.
 */
public PythonStreamExecutionEnvironment create_remote_execution_environment(
  String host, int port, Configuration config, String... jar_files) {
  return new PythonStreamExecutionEnvironment(
    StreamExecutionEnvironment.createRemoteEnvironment(host, port, config, jar_files), new Path(localTmpPath), scriptName);
}

  /**
   * A thin wrapper layer over {@link StreamExecutionEnvironment#createRemoteEnvironment(
   *String, int, int, String...)}.
   *
   * @param host The host name or address of the master (JobManager), where the
   * program should be executed.
   * @param port The port of the master (JobManager), where the program should
   * be executed.
   * @param parallelism The parallelism to use during the execution.
   * @param jar_files The JAR files with code that needs to be shipped to the
   * cluster. If the program uses user-defined functions,
   * user-defined input formats, or any libraries, those must be
   * provided in the JAR files.
   * @return A remote environment that executes the program on a cluster.
   */
  public PythonStreamExecutionEnvironment create_remote_execution_environment(
    String host, int port, int parallelism, String... jar_files) {
    return new PythonStreamExecutionEnvironment(
      StreamExecutionEnvironment.createRemoteEnvironment(host, port, parallelism, jar_files), new Path(localTmpPath), scriptName);
  }
}

/**
 * Verifies that the port passed to the RemoteStreamEnvironment is used for connecting to the cluster.
 */
@Test
public void testPortForwarding() throws Exception {
  String host = "fakeHost";
  int port = 99;
  JobExecutionResult expectedResult = new JobExecutionResult(null, 0, null);
  RestClusterClient mockedClient = Mockito.mock(RestClusterClient.class);
  when(mockedClient.run(Mockito.any(), Mockito.any(), Mockito.any(), Mockito.any(), Mockito.any()))
    .thenReturn(expectedResult);
  PowerMockito.whenNew(RestClusterClient.class).withAnyArguments().thenAnswer((invocation) -> {
      Object[] args = invocation.getArguments();
      Configuration config = (Configuration) args[0];
      Assert.assertEquals(host, config.getString(RestOptions.ADDRESS));
      Assert.assertEquals(port, config.getInteger(RestOptions.PORT));
      return mockedClient;
    }
  );
  final Configuration clientConfiguration = new Configuration();
  final StreamExecutionEnvironment env = StreamExecutionEnvironment.createRemoteEnvironment(
    host, port, clientConfiguration);
  env.fromElements(1).map(x -> x * 2);
  JobExecutionResult actualResult = env.execute("fakeJobName");
  Assert.assertEquals(expectedResult, actualResult);
}

StreamExecutionEnvironment env = StreamExecutionEnvironment.createRemoteEnvironment(
  "localhost",
  1337, // not needed since we use ZooKeeper

  String[] parts = masterUrl.split(":");
  List<String> stagingFiles = options.getFilesToStage();
  this.flinkStreamEnv = StreamExecutionEnvironment.createRemoteEnvironment(parts[0],
      Integer.parseInt(parts[1]), stagingFiles.toArray(new String[stagingFiles.size()]));
} else {

 String[] parts = masterUrl.split(":");
 List<String> stagingFiles = options.getFilesToStage();
 flinkStreamEnv = StreamExecutionEnvironment.createRemoteEnvironment(parts[0],
   Integer.parseInt(parts[1]), stagingFiles.toArray(new String[stagingFiles.size()]));
} else {

clientConfig.setInteger(RestOptions.PORT, Integer.parseInt(parts.get(1)));
flinkStreamEnv =
  StreamExecutionEnvironment.createRemoteEnvironment(
    parts.get(0),
    Integer.parseInt(parts.get(1)),

@Override
public void prepareRuntime() throws SpRuntimeException {
 if (debug) {
  this.env = StreamExecutionEnvironment.createLocalEnvironment();
 } else {
  this.env = StreamExecutionEnvironment
      .createRemoteEnvironment(config.getHost(), config.getPort(), config.getJarFile());
 }
 appendEnvironmentConfig(this.env);
 // Add the first source to the topology
 DataStream<Map<String, Object>> messageStream1;
 SourceFunction<String> source1 = getStream1Source();
 if (source1 != null) {
  messageStream1 = env
      .addSource(source1).flatMap(new JsonToMapFormat()).flatMap(new StatisticLogger(getGraph()));
 } else {
  throw new SpRuntimeException("At least one source must be defined for a flink sepa");
 }
 DataStream<Map<String, Object>> messageStream2;
 SourceFunction<String> source2 = getStream2Source();
 if (source2 != null) {
  messageStream2 = env
      .addSource(source2).flatMap(new JsonToMapFormat()).flatMap(new StatisticLogger(getGraph()));
  appendExecutionConfig(messageStream1, messageStream2);
 } else {
  appendExecutionConfig(messageStream1);
 }
}