Use StartJobRun with an Amazon SDK or CLI - Amazon Glue
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Use StartJobRun with an Amazon SDK or CLI

The following code examples show how to use StartJobRun.

Action examples are code excerpts from larger programs and must be run in context. You can see this action in context in the following code example:

.NET
Amazon SDK for .NET
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the Amazon Code Examples Repository.

/// <summary> /// Start an AWS Glue job run. /// </summary> /// <param name="jobName">The name of the job.</param> /// <returns>A string representing the job run Id.</returns> public async Task<string> StartJobRunAsync( string jobName, string inputDatabase, string inputTable, string bucketName) { var request = new StartJobRunRequest { JobName = jobName, Arguments = new Dictionary<string, string> { {"--input_database", inputDatabase}, {"--input_table", inputTable}, {"--output_bucket_url", $"s3://{bucketName}/"} } }; var response = await _amazonGlue.StartJobRunAsync(request); return response.JobRunId; }
  • For API details, see StartJobRun in Amazon SDK for .NET API Reference.

C++
SDK for C++
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the Amazon Code Examples Repository.

Aws::Client::ClientConfiguration clientConfig; // Optional: Set to the AWS Region in which the bucket was created (overrides config file). // clientConfig.region = "us-east-1"; Aws::Glue::GlueClient client(clientConfig); Aws::Glue::Model::StartJobRunRequest request; request.SetJobName(JOB_NAME); Aws::Map<Aws::String, Aws::String> arguments; arguments["--input_database"] = CRAWLER_DATABASE_NAME; arguments["--input_table"] = tableName; arguments["--output_bucket_url"] = Aws::String("s3://") + bucketName + "/"; request.SetArguments(arguments); Aws::Glue::Model::StartJobRunOutcome outcome = client.StartJobRun(request); if (outcome.IsSuccess()) { std::cout << "Successfully started the job." << std::endl; Aws::String jobRunId = outcome.GetResult().GetJobRunId(); int iterator = 0; bool done = false; while (!done) { ++iterator; std::this_thread::sleep_for(std::chrono::seconds(1)); Aws::Glue::Model::GetJobRunRequest jobRunRequest; jobRunRequest.SetJobName(JOB_NAME); jobRunRequest.SetRunId(jobRunId); Aws::Glue::Model::GetJobRunOutcome jobRunOutcome = client.GetJobRun( jobRunRequest); if (jobRunOutcome.IsSuccess()) { const Aws::Glue::Model::JobRun &jobRun = jobRunOutcome.GetResult().GetJobRun(); Aws::Glue::Model::JobRunState jobRunState = jobRun.GetJobRunState(); if ((jobRunState == Aws::Glue::Model::JobRunState::STOPPED) || (jobRunState == Aws::Glue::Model::JobRunState::FAILED) || (jobRunState == Aws::Glue::Model::JobRunState::TIMEOUT)) { std::cerr << "Error running job. " << jobRun.GetErrorMessage() << std::endl; deleteAssets(CRAWLER_NAME, CRAWLER_DATABASE_NAME, JOB_NAME, bucketName, clientConfig); return false; } else if (jobRunState == Aws::Glue::Model::JobRunState::SUCCEEDED) { std::cout << "Job run succeeded after " << iterator << " seconds elapsed." << std::endl; done = true; } else if ((iterator % 10) == 0) { // Log status every 10 seconds. std::cout << "Job run status " << Aws::Glue::Model::JobRunStateMapper::GetNameForJobRunState( jobRunState) << ". " << iterator << " seconds elapsed." << std::endl; } } else { std::cerr << "Error retrieving job run state. " << jobRunOutcome.GetError().GetMessage() << std::endl; deleteAssets(CRAWLER_NAME, CRAWLER_DATABASE_NAME, JOB_NAME, bucketName, clientConfig); return false; } } } else { std::cerr << "Error starting a job. " << outcome.GetError().GetMessage() << std::endl; deleteAssets(CRAWLER_NAME, CRAWLER_DATABASE_NAME, JOB_NAME, bucketName, clientConfig); return false; }
  • For API details, see StartJobRun in Amazon SDK for C++ API Reference.

CLI
Amazon CLI

To start running a job

The following start-job-run example starts a job.

aws glue start-job-run \ --job-name my-job

Output:

{ "JobRunId": "jr_22208b1f44eb5376a60569d4b21dd20fcb8621e1a366b4e7b2494af764b82ded" }

For more information, see Authoring Jobs in the Amazon Glue Developer Guide.

  • For API details, see StartJobRun in Amazon CLI Command Reference.

JavaScript
SDK for JavaScript (v3)
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the Amazon Code Examples Repository.

const startJobRun = (jobName, dbName, tableName, bucketName) => { const client = new GlueClient({}); const command = new StartJobRunCommand({ JobName: jobName, Arguments: { "--input_database": dbName, "--input_table": tableName, "--output_bucket_url": `s3://${bucketName}/`, }, }); return client.send(command); };
  • For API details, see StartJobRun in Amazon SDK for JavaScript API Reference.

PHP
SDK for PHP
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the Amazon Code Examples Repository.

$jobName = 'test-job-' . $uniqid; $databaseName = "doc-example-database-$uniqid"; $tables = $glueService->getTables($databaseName); $outputBucketUrl = "s3://$bucketName"; $runId = $glueService->startJobRun($jobName, $databaseName, $tables, $outputBucketUrl)['JobRunId']; public function startJobRun($jobName, $databaseName, $tables, $outputBucketUrl): Result { return $this->glueClient->startJobRun([ 'JobName' => $jobName, 'Arguments' => [ 'input_database' => $databaseName, 'input_table' => $tables['TableList'][0]['Name'], 'output_bucket_url' => $outputBucketUrl, '--input_database' => $databaseName, '--input_table' => $tables['TableList'][0]['Name'], '--output_bucket_url' => $outputBucketUrl, ], ]); }
  • For API details, see StartJobRun in Amazon SDK for PHP API Reference.

Python
SDK for Python (Boto3)
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the Amazon Code Examples Repository.

class GlueWrapper: """Encapsulates AWS Glue actions.""" def __init__(self, glue_client): """ :param glue_client: A Boto3 Glue client. """ self.glue_client = glue_client def start_job_run(self, name, input_database, input_table, output_bucket_name): """ Starts a job run. A job run extracts data from the source, transforms it, and loads it to the output bucket. :param name: The name of the job definition. :param input_database: The name of the metadata database that contains tables that describe the source data. This is typically created by a crawler. :param input_table: The name of the table in the metadata database that describes the source data. :param output_bucket_name: The S3 bucket where the output is written. :return: The ID of the job run. """ try: # The custom Arguments that are passed to this function are used by the # Python ETL script to determine the location of input and output data. response = self.glue_client.start_job_run( JobName=name, Arguments={ "--input_database": input_database, "--input_table": input_table, "--output_bucket_url": f"s3://{output_bucket_name}/", }, ) except ClientError as err: logger.error( "Couldn't start job run %s. Here's why: %s: %s", name, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return response["JobRunId"]
  • For API details, see StartJobRun in Amazon SDK for Python (Boto3) API Reference.

Ruby
SDK for Ruby
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the Amazon Code Examples Repository.

# The `GlueWrapper` class serves as a wrapper around the AWS Glue API, providing a simplified interface for common operations. # It encapsulates the functionality of the AWS SDK for Glue and provides methods for interacting with Glue crawlers, databases, tables, jobs, and S3 resources. # The class initializes with a Glue client and a logger, allowing it to make API calls and log any errors or informational messages. class GlueWrapper def initialize(glue_client, logger) @glue_client = glue_client @logger = logger end # Starts a job run for the specified job. # # @param name [String] The name of the job to start the run for. # @param input_database [String] The name of the input database for the job. # @param input_table [String] The name of the input table for the job. # @param output_bucket_name [String] The name of the output S3 bucket for the job. # @return [String] The ID of the started job run. def start_job_run(name, input_database, input_table, output_bucket_name) response = @glue_client.start_job_run( job_name: name, arguments: { '--input_database': input_database, '--input_table': input_table, '--output_bucket_url': "s3://#{output_bucket_name}/" } ) response.job_run_id rescue Aws::Glue::Errors::GlueException => e @logger.error("Glue could not start job run #{name}: \n#{e.message}") raise end
  • For API details, see StartJobRun in Amazon SDK for Ruby API Reference.

Rust
SDK for Rust
Note

There's more on GitHub. Find the complete example and learn how to set up and run in the Amazon Code Examples Repository.

let job_run_output = glue .start_job_run() .job_name(self.job()) .arguments("--input_database", self.database()) .arguments( "--input_table", self.tables .first() .ok_or_else(|| GlueMvpError::Unknown("Missing crawler table".into()))? .name(), ) .arguments("--output_bucket_url", self.bucket()) .send() .await .map_err(GlueMvpError::from_glue_sdk)?; let job = job_run_output .job_run_id() .ok_or_else(|| GlueMvpError::Unknown("Missing run id from just started job".into()))? .to_string();
  • For API details, see StartJobRun in Amazon SDK for Rust API reference.

For a complete list of Amazon SDK developer guides and code examples, see Using this service with an Amazon SDK. This topic also includes information about getting started and details about previous SDK versions.