Mengirim tugas hasoop fs

Mengirim tugas Hadoop FS ke cluster Dataproc.

Contoh kode

Java

Sebelum mencoba contoh ini, ikuti petunjuk penyiapan Java di Panduan memulai Dataproc menggunakan library klien. Untuk mengetahui informasi selengkapnya, lihat dokumentasi referensi API Java Dataproc.

Untuk mengautentikasi ke Dataproc, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, baca Menyiapkan autentikasi untuk lingkungan pengembangan lokal.

import com.google.api.gax.longrunning.OperationFuture;
import com.google.cloud.dataproc.v1.HadoopJob;
import com.google.cloud.dataproc.v1.Job;
import com.google.cloud.dataproc.v1.JobControllerClient;
import com.google.cloud.dataproc.v1.JobControllerSettings;
import com.google.cloud.dataproc.v1.JobMetadata;
import com.google.cloud.dataproc.v1.JobPlacement;
import com.google.cloud.storage.Blob;
import com.google.cloud.storage.Storage;
import com.google.cloud.storage.StorageOptions;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.concurrent.ExecutionException;
import java.util.regex.Matcher;
import java.util.regex.Pattern;

public class SubmitHadoopFsJob {

  public static ArrayList<String> stringToList(String s) {
    return new ArrayList<>(Arrays.asList(s.split(" ")));
  }

  public static void submitHadoopFsJob() throws IOException, InterruptedException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "your-project-id";
    String region = "your-project-region";
    String clusterName = "your-cluster-name";
    String hadoopFsQuery = "your-hadoop-fs-query";
    submitHadoopFsJob(projectId, region, clusterName, hadoopFsQuery);
  }

  public static void submitHadoopFsJob(
      String projectId, String region, String clusterName, String hadoopFsQuery)
      throws IOException, InterruptedException {
    String myEndpoint = String.format("%s-dataproc.googleapis.com:443", region);

    // Configure the settings for the job controller client.
    JobControllerSettings jobControllerSettings =
        JobControllerSettings.newBuilder().setEndpoint(myEndpoint).build();

    // Create a job controller client with the configured settings. Using a try-with-resources
    // closes the client,
    // but this can also be done manually with the .close() method.
    try (JobControllerClient jobControllerClient =
        JobControllerClient.create(jobControllerSettings)) {

      // Configure cluster placement for the job.
      JobPlacement jobPlacement = JobPlacement.newBuilder().setClusterName(clusterName).build();

      // Configure Hadoop job settings. The HadoopFS query is set here.
      HadoopJob hadoopJob =
          HadoopJob.newBuilder()
              .setMainClass("org.apache.hadoop.fs.FsShell")
              .addAllArgs(stringToList(hadoopFsQuery))
              .build();

      Job job = Job.newBuilder().setPlacement(jobPlacement).setHadoopJob(hadoopJob).build();

      // Submit an asynchronous request to execute the job.
      OperationFuture<Job, JobMetadata> submitJobAsOperationAsyncRequest =
          jobControllerClient.submitJobAsOperationAsync(projectId, region, job);

      Job response = submitJobAsOperationAsyncRequest.get();

      // Print output from Google Cloud Storage.
      Matcher matches =
          Pattern.compile("gs://(.*?)/(.*)").matcher(response.getDriverOutputResourceUri());
      matches.matches();

      Storage storage = StorageOptions.getDefaultInstance().getService();
      Blob blob = storage.get(matches.group(1), String.format("%s.000000000", matches.group(2)));

      System.out.println(
          String.format("Job finished successfully: %s", new String(blob.getContent())));

    } catch (ExecutionException e) {
      // If the job does not complete successfully, print the error message.
      System.err.println(String.format("submitHadoopFSJob: %s ", e.getMessage()));
    }
  }
}

Langkah selanjutnya

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