}

tensorflow::ServerDef GetServerDef(const string& job_name, int num_tasks) {
  tensorflow::ServerDef server_def;
  server_def.set_protocol("grpc");
  server_def.set_job_name(job_name);
  server_def.set_task_index(0);
  tensorflow::ClusterDef* cluster_def = server_def.mutable_cluster();
  tensorflow::JobDef* job_def = cluster_def->add_job();
  job_def->set_name(job_name);
  for (int i = 0; i < num_tasks; i++) {

          "type": "prometheus",
          "uid": "${DS_PROMETHEUS}"
        },
        "definition": "label_values(job)",
        "hide": 0,
        "includeAll": false,
        "multi": false,
        "name": "scrape_jobs",
        "options": [],
        "query": {
          "query": "label_values(job)",
          "refId": "StandardVariableQuery"
        },
        "refresh": 1,
        "regex": "",

errors.docid_not_found=Not found Doc ID:{0}
errors.document_not_found=Not found URL of Doc ID:{0}
errors.not_load_from_server=Could not load from this server: {0}
errors.failed_to_start_job=Failed to start job {0}.
errors.failed_to_stop_job=Failed to stop job {0}.
errors.failed_to_download_synonym_file=Failed to download the Synonym file.
errors.failed_to_upload_synonym_file=Failed to upload the Synonym file.

    examples/jars/spark-examples*.jar 10
```

The job should produce an output as shown below. Note the value of pi in the output.

```
17/03/22 23:21:10 INFO DAGScheduler: Job 0 finished: reduce at SparkPi.scala:38, took 1.302805 s
Pi is roughly 3.1445191445191445
```

Job status can also be viewed in a browser by navigating to the YARN ResourceManager Web UI and clicking on job history server information.

### **4.2 WordCount**

      TFE_NewContext(opts.get(), status.get()), TFE_DeleteContext);
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());

  std::vector<std::string> devices{
      "/job:localhost/replica:0/task:0/device:CPU:0",
      "/job:localhost/replica:0/task:0/device:CPU:1"};
  ParallelDevice parallel_device(std::move(devices));
  std::unique_ptr<TFE_Op, decltype(&TFE_DeleteOp)> handle_op(

        return getComponent(EXTRACTOR_FACTORY);
    }

    public static JobExecutor getJobExecutor(final String name) {
        if (name.endsWith(JOB_EXECUTOR_SUFFIX)) {
            return getComponent(name);
        }
        return getComponent("script" + JOB_EXECUTOR_SUFFIX);
    }

    public static FileTypeHelper getFileTypeHelper() {
        return getComponent(FILE_TYPE_HELPER);
    }

errors.docid_not_found=Not found Doc ID:{0}
errors.document_not_found=Not found URL of Doc ID:{0}
errors.not_load_from_server=Could not load from this server: {0}
errors.failed_to_start_job=Failed to start job {0}.
errors.failed_to_stop_job=Failed to stop job {0}.
errors.failed_to_download_synonym_file=Failed to download the Synonym file.
errors.failed_to_upload_synonym_file=Failed to upload the Synonym file.

  EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);

  const char task0_name[] = "/job:localhost/replica:0/task:0/device:CPU:0";
  const char task1_name[] = "/job:localhost/replica:0/task:1/device:CPU:0";
  const char task2_name[] = "/job:localhost/replica:0/task:2/device:CPU:0";

  // Create one variable per task.
  TFE_TensorHandle* h0 = TestVariable(ctx, 1.0, task1_name);

#-Xdebug\n\
#-Xrunjdwp:transport=dt_socket,server=y,suspend=y,address=127.0.0.1:8000\n\

# job
job.system.job.ids=default_crawler
job.template.title.web=Web Crawler - {0}
job.template.title.file=File Crawler - {0}
job.template.title.data=Data Crawler - {0}

  TFE_OpReset(reused_op.get(), "Identity",
              "/job:localhost/replica:0/task:0/device:CPU:0", status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  ASSERT_EQ(tensorflow::string(TFE_OpGetDevice(reused_op.get(), status.get())),
            tensorflow::string("/job:localhost/replica:0/task:0/device:CPU:0"));