feat: dataproc quickstart and createcluster #1908
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| /* | ||
| * Copyright 2019 Google LLC | ||
| * | ||
| * Licensed under the Apache License, Version 2.0 (the "License"); | ||
| * you may not use this file except in compliance with the License. | ||
| * You may obtain a copy of the License at | ||
| * | ||
| * http://www.apache.org/licenses/LICENSE-2.0 | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, software | ||
| * distributed under the License is distributed on an "AS IS" BASIS, | ||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| * See the License for the specific language governing permissions and | ||
| * limitations under the License. | ||
| */ | ||
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| // [START dataproc_quickstart] | ||
| import com.google.api.gax.longrunning.OperationFuture; | ||
| import com.google.cloud.dataproc.v1.Cluster; | ||
| import com.google.cloud.dataproc.v1.ClusterConfig; | ||
| import com.google.cloud.dataproc.v1.ClusterControllerClient; | ||
| import com.google.cloud.dataproc.v1.ClusterControllerSettings; | ||
| import com.google.cloud.dataproc.v1.ClusterOperationMetadata; | ||
| import com.google.cloud.dataproc.v1.InstanceGroupConfig; | ||
| 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.JobPlacement; | ||
| import com.google.cloud.dataproc.v1.PySparkJob; | ||
| import com.google.cloud.storage.Blob; | ||
| import com.google.cloud.storage.Storage; | ||
| import com.google.cloud.storage.StorageOptions; | ||
| import com.google.protobuf.Empty; | ||
| import java.io.IOException; | ||
| import java.util.concurrent.CompletableFuture; | ||
| import java.util.concurrent.ExecutionException; | ||
| import java.util.concurrent.TimeUnit; | ||
| import java.util.concurrent.TimeoutException; | ||
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| public class Quickstart { | ||
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| public static Job waitForJobCompletion( | ||
| JobControllerClient jobControllerClient, String projectId, String region, String jobId) { | ||
| while (true) { | ||
| // Poll the service periodically until the Job is in a finished state. | ||
| Job jobInfo = jobControllerClient.getJob(projectId, region, jobId); | ||
| switch (jobInfo.getStatus().getState()) { | ||
| case DONE: | ||
| case CANCELLED: | ||
| case ERROR: | ||
| return jobInfo; | ||
| default: | ||
| try { | ||
| // Wait a second in between polling attempts. | ||
| TimeUnit.SECONDS.sleep(1); | ||
| } catch (InterruptedException e) { | ||
| throw new RuntimeException(e); | ||
| } | ||
| } | ||
| } | ||
| } | ||
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| public static void quickstart() 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 jobFilePath = "your-job-file-path"; | ||
| quickstart(projectId, region, clusterName, jobFilePath); | ||
| } | ||
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| public static void quickstart( | ||
| String projectId, String region, String clusterName, String jobFilePath) | ||
| throws IOException, InterruptedException { | ||
| String myEndpoint = String.format("%s-dataproc.googleapis.com:443", region); | ||
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| // Configure the settings for the cluster controller client. | ||
| ClusterControllerSettings clusterControllerSettings = | ||
| ClusterControllerSettings.newBuilder().setEndpoint(myEndpoint).build(); | ||
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| // Configure the settings for the job controller client. | ||
| JobControllerSettings jobControllerSettings = | ||
| JobControllerSettings.newBuilder().setEndpoint(myEndpoint).build(); | ||
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| // Create both a cluster controller client and job controller client with the configured | ||
| // settings. The client only needs to be created once and can be reused for multiple requests. | ||
| // Using a try-with-resources closes the client, but this can also be done manually with | ||
| // the .close() method. | ||
| try (ClusterControllerClient clusterControllerClient = | ||
| ClusterControllerClient.create(clusterControllerSettings); | ||
| JobControllerClient jobControllerClient = | ||
| JobControllerClient.create(jobControllerSettings)) { | ||
| // Configure the settings for our cluster. | ||
| InstanceGroupConfig masterConfig = | ||
| InstanceGroupConfig.newBuilder() | ||
| .setMachineTypeUri("n1-standard-1") | ||
| .setNumInstances(1) | ||
| .build(); | ||
| InstanceGroupConfig workerConfig = | ||
| InstanceGroupConfig.newBuilder() | ||
| .setMachineTypeUri("n1-standard-1") | ||
| .setNumInstances(2) | ||
| .build(); | ||
| ClusterConfig clusterConfig = | ||
| ClusterConfig.newBuilder() | ||
| .setMasterConfig(masterConfig) | ||
| .setWorkerConfig(workerConfig) | ||
| .build(); | ||
| // Create the cluster object with the desired cluster config. | ||
| Cluster cluster = | ||
| Cluster.newBuilder().setClusterName(clusterName).setConfig(clusterConfig).build(); | ||
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||
| // Create the Cloud Dataproc cluster. | ||
| OperationFuture<Cluster, ClusterOperationMetadata> createClusterAsyncRequest = | ||
| clusterControllerClient.createClusterAsync(projectId, region, cluster); | ||
| Cluster response = createClusterAsyncRequest.get(); | ||
| System.out.printf("Cluster created successfully: %s", response.getClusterName()); | ||
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| // Configure the settings for our job. | ||
| JobPlacement jobPlacement = JobPlacement.newBuilder().setClusterName(clusterName).build(); | ||
| PySparkJob pySparkJob = PySparkJob.newBuilder().setMainPythonFileUri(jobFilePath).build(); | ||
| Job job = Job.newBuilder().setPlacement(jobPlacement).setPysparkJob(pySparkJob).build(); | ||
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| // Submit an asynchronous request to execute the job. | ||
| Job request = jobControllerClient.submitJob(projectId, region, job); | ||
| String jobId = request.getReference().getJobId(); | ||
| System.out.println(String.format("Submitted job \"%s\"", jobId)); | ||
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| // Wait for the job to finish. | ||
| CompletableFuture<Job> finishedJobFuture = | ||
| CompletableFuture.supplyAsync( | ||
| () -> waitForJobCompletion(jobControllerClient, projectId, region, jobId)); | ||
| int timeout = 10; | ||
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|
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| try { | ||
| Job jobInfo = finishedJobFuture.get(timeout, TimeUnit.MINUTES); | ||
| System.out.printf("Job %s finished successfully.", jobId); | ||
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| // Cloud Dataproc job output gets saved to a GCS bucket allocated to it. | ||
| Cluster clusterInfo = clusterControllerClient.getCluster(projectId, region, clusterName); | ||
| Storage storage = StorageOptions.getDefaultInstance().getService(); | ||
| Blob blob = | ||
| storage.get( | ||
| clusterInfo.getConfig().getConfigBucket(), | ||
| String.format( | ||
| "google-cloud-dataproc-metainfo/%s/jobs/%s/driveroutput.000000000", | ||
| clusterInfo.getClusterUuid(), jobId)); | ||
| System.out.println( | ||
| String.format( | ||
| "Job \"%s\" finished with state %s:\n%s", | ||
| jobId, jobInfo.getStatus().getState(), new String(blob.getContent()))); | ||
| } catch (TimeoutException e) { | ||
| System.err.println( | ||
| String.format("Job timed out after %d minutes: %s", timeout, e.getMessage())); | ||
| } | ||
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| // Delete the cluster. | ||
| OperationFuture<Empty, ClusterOperationMetadata> deleteClusterAsyncRequest = | ||
| clusterControllerClient.deleteClusterAsync(projectId, region, clusterName); | ||
| deleteClusterAsyncRequest.get(); | ||
| System.out.println(String.format("Cluster \"%s\" successfully deleted.", clusterName)); | ||
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| } catch (ExecutionException e) { | ||
|
There was a problem hiding this comment. If If it's not from the API, please let it bubble up (and be consistent with the other samples - it's bubbled up in a few other places). There was a problem hiding this comment. Ahh yes, I see what you're saying. Errors caused by our API bubble up to be an Execution Exception, so I think it should definitely be caught. I'll add it to the other sample. |
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| System.err.println(String.format("Error executing quickstart: %s ", e.getMessage())); | ||
| } | ||
| } | ||
| } | ||
| // [END dataproc_quickstart] | ||
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