Verwendung von CreateJob mit einem AWS-SDK oder CLI

    /// <summary>
    /// Create an AWS Glue job.
    /// </summary>
    /// <param name="jobName">The name of the job.</param>
    /// <param name="roleName">The name of the IAM role to be assumed by
    /// the job.</param>
    /// <param name="description">A description of the job.</param>
    /// <param name="scriptUrl">The URL to the script.</param>
    /// <returns>A Boolean value indicating the success of the action.</returns>
    public async Task<bool> CreateJobAsync(string dbName, string tableName, string bucketUrl, string jobName, string roleName, string description, string scriptUrl)
    {
        var command = new JobCommand
        {
            PythonVersion = "3",
            Name = "glueetl",
            ScriptLocation = scriptUrl,
        };

        var arguments = new Dictionary<string, string>
        {
            { "--input_database", dbName },
            { "--input_table", tableName },
            { "--output_bucket_url", bucketUrl }
        };

        var request = new CreateJobRequest
        {
            Command = command,
            DefaultArguments = arguments,
            Description = description,
            GlueVersion = "3.0",
            Name = jobName,
            NumberOfWorkers = 10,
            Role = roleName,
            WorkerType = "G.1X"
        };

        var response = await _amazonGlue.CreateJobAsync(request);
        return response.HttpStatusCode == HttpStatusCode.OK;
    }

        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::CreateJobRequest request;
        request.SetName(JOB_NAME);
        request.SetRole(roleArn);
        request.SetGlueVersion(GLUE_VERSION);

        Aws::Glue::Model::JobCommand command;
        command.SetName(JOB_COMMAND_NAME);
        command.SetPythonVersion(JOB_PYTHON_VERSION);
        command.SetScriptLocation(
                Aws::String("s3://") + bucketName + "/" + PYTHON_SCRIPT);
        request.SetCommand(command);

        Aws::Glue::Model::CreateJobOutcome outcome = client.CreateJob(request);

        if (outcome.IsSuccess()) {
            std::cout << "Successfully created the job." << std::endl;
        }
        else {
            std::cerr << "Error creating the job. " << outcome.GetError().GetMessage()
                      << std::endl;
            deleteAssets(CRAWLER_NAME, CRAWLER_DATABASE_NAME, "", bucketName,
                         clientConfig);
            return false;
        }

Einen Auftrag zur Datentransformation erstellen

Im folgenden Beispiel für create-job wird ein Streaming-Job erstellt, der ein in S3 gespeichertes Skript ausführt.

aws glue create-job \
    --name my-testing-job \
    --role AWSGlueServiceRoleDefault \
    --command '{ \
        "Name": "gluestreaming", \
        "ScriptLocation": "s3://amzn-s3-demo-bucket/folder/" \
    }' \
    --region us-east-1 \
    --output json \
    --default-arguments '{ \
        "--job-language":"scala", \
        "--class":"GlueApp" \
    }' \
    --profile my-profile \
    --endpoint https://glue.us-east-1.amazonaws.com

Inhalt von test_script.scala:

import com.amazonaws.services.glue.ChoiceOption
import com.amazonaws.services.glue.GlueContext
import com.amazonaws.services.glue.MappingSpec
import com.amazonaws.services.glue.ResolveSpec
import com.amazonaws.services.glue.errors.CallSite
import com.amazonaws.services.glue.util.GlueArgParser
import com.amazonaws.services.glue.util.Job
import com.amazonaws.services.glue.util.JsonOptions
import org.apache.spark.SparkContext
import scala.collection.JavaConverters._

object GlueApp {
    def main(sysArgs: Array[String]) {
        val spark: SparkContext = new SparkContext()
        val glueContext: GlueContext = new GlueContext(spark)
        // @params: [JOB_NAME]
        val args = GlueArgParser.getResolvedOptions(sysArgs, Seq("JOB_NAME").toArray)
        Job.init(args("JOB_NAME"), glueContext, args.asJava)
        // @type: DataSource
        // @args: [database = "tempdb", table_name = "s3-source", transformation_ctx = "datasource0"]
        // @return: datasource0
        // @inputs: []
        val datasource0 = glueContext.getCatalogSource(database = "tempdb", tableName = "s3-source", redshiftTmpDir = "", transformationContext = "datasource0").getDynamicFrame()
        // @type: ApplyMapping
        // @args: [mapping = [("sensorid", "int", "sensorid", "int"), ("currenttemperature", "int", "currenttemperature", "int"), ("status", "string", "status", "string")], transformation_ctx = "applymapping1"]
        // @return: applymapping1
        // @inputs: [frame = datasource0]
        val applymapping1 = datasource0.applyMapping(mappings = Seq(("sensorid", "int", "sensorid", "int"), ("currenttemperature", "int", "currenttemperature", "int"), ("status", "string", "status", "string")), caseSensitive = false, transformationContext = "applymapping1")
        // @type: SelectFields
        // @args: [paths = ["sensorid", "currenttemperature", "status"], transformation_ctx = "selectfields2"]
        // @return: selectfields2
        // @inputs: [frame = applymapping1]
        val selectfields2 = applymapping1.selectFields(paths = Seq("sensorid", "currenttemperature", "status"), transformationContext = "selectfields2")
        // @type: ResolveChoice
        // @args: [choice = "MATCH_CATALOG", database = "tempdb", table_name = "my-s3-sink", transformation_ctx = "resolvechoice3"]
        // @return: resolvechoice3
        // @inputs: [frame = selectfields2]
        val resolvechoice3 = selectfields2.resolveChoice(choiceOption = Some(ChoiceOption("MATCH_CATALOG")), database = Some("tempdb"), tableName = Some("my-s3-sink"), transformationContext = "resolvechoice3")
        // @type: DataSink
        // @args: [database = "tempdb", table_name = "my-s3-sink", transformation_ctx = "datasink4"]
        // @return: datasink4
        // @inputs: [frame = resolvechoice3]
        val datasink4 = glueContext.getCatalogSink(database = "tempdb", tableName = "my-s3-sink", redshiftTmpDir = "", transformationContext = "datasink4").writeDynamicFrame(resolvechoice3)
        Job.commit()
    }
}

Ausgabe:

{
    "Name": "my-testing-job"
}

Weitere Informationen finden Sie unter Autorisieren von Aufträgen in AWS Glue im Entwicklerhandbuch für AWS Glue.

    /**
     * Creates a new AWS Glue job.
     *
     * @param glueClient     the AWS Glue client to use for the operation
     * @param jobName        the name of the job to create
     * @param iam            the IAM role to associate with the job
     * @param scriptLocation the location of the script to be used by the job
     * @throws GlueException if there is an error creating the job
     */
    public static void createJob(GlueClient glueClient, String jobName, String iam, String scriptLocation) {
        try {
            JobCommand command = JobCommand.builder()
                .pythonVersion("3")
                .name("glueetl")
                .scriptLocation(scriptLocation)
                .build();

            CreateJobRequest jobRequest = CreateJobRequest.builder()
                .description("A Job created by using the AWS SDK for Java V2")
                .glueVersion("2.0")
                .workerType(WorkerType.G_1_X)
                .numberOfWorkers(10)
                .name(jobName)
                .role(iam)
                .command(command)
                .build();

            glueClient.createJob(jobRequest);
            System.out.println(jobName + " was successfully created.");

        } catch (GlueException e) {
            throw e;
        }
    }

const createJob = (name, role, scriptBucketName, scriptKey) => {
  const client = new GlueClient({});

  const command = new CreateJobCommand({
    Name: name,
    Role: role,
    Command: {
      Name: "glueetl",
      PythonVersion: "3",
      ScriptLocation: `s3://${scriptBucketName}/${scriptKey}`,
    },
    GlueVersion: "3.0",
  });

  return client.send(command);
};

        $role = $iamService->getRole("AWSGlueServiceRole-DocExample");

        $jobName = 'test-job-' . $uniqid;

        $scriptLocation = "s3://$bucketName/run_job.py";
        $job = $glueService->createJob($jobName, $role['Role']['Arn'], $scriptLocation);

    public function createJob($jobName, $role, $scriptLocation, $pythonVersion = '3', $glueVersion = '3.0'): Result
    {
        return $this->glueClient->createJob([
            'Name' => $jobName,
            'Role' => $role,
            'Command' => [
                'Name' => 'glueetl',
                'ScriptLocation' => $scriptLocation,
                'PythonVersion' => $pythonVersion,
            ],
            'GlueVersion' => $glueVersion,
        ]);
    }

Beispiel 1: In diesem Beispiel wird ein neuer Auftrag in AWS Glue erstellt. Der Wert des Befehlsnamens ist immer glueetl. AWS Glue unterstützt das Ausführen von Auftragsskripts, die in Python oder Scala geschrieben sind. In diesem Beispiel ist das Auftragsskript (MyTestGlueJob.py) in Python geschrieben. Python-Parameter werden in der $DefArgs-Variablen angegeben und dann an den PowerShell-Befehl im DefaultArguments-Parameter übergeben, der eine Hashtabelle akzeptiert. Die Parameter in der $JobParams-Variablen stammen aus der CreateJob-API, die im Thema „Aufträge“ (https://docs.aws.amazon.com/glue/latest/dg/aws-glue-api-jobs-job.html) der API-Referenz für AWS Glue dokumentiert ist.

$Command = New-Object Amazon.Glue.Model.JobCommand
$Command.Name = 'glueetl'
$Command.ScriptLocation = 's3://amzn-s3-demo-source-bucket/admin/MyTestGlueJob.py'
$Command

$Source = "source_test_table"
$Target = "target_test_table"
$Connections = $Source, $Target

$DefArgs = @{
     '--TempDir' = 's3://amzn-s3-demo-bucket/admin'
     '--job-bookmark-option' = 'job-bookmark-disable'
     '--job-language' = 'python'
     }
$DefArgs

$ExecutionProp = New-Object Amazon.Glue.Model.ExecutionProperty
$ExecutionProp.MaxConcurrentRuns = 1
$ExecutionProp

$JobParams = @{
    "AllocatedCapacity"    = "5"
    "Command"              = $Command
    "Connections_Connection" = $Connections
    "DefaultArguments"  = $DefArgs
    "Description"       = "This is a test"
    "ExecutionProperty" = $ExecutionProp
    "MaxRetries"        = "1"
    "Name"              = "MyOregonTestGlueJob"
    "Role"              = "Amazon-GlueServiceRoleForSSM"
    "Timeout"           = "20"
     }

New-GlueJob @JobParams

Beispiel 1: In diesem Beispiel wird ein neuer Auftrag in AWS Glue erstellt. Der Wert des Befehlsnamens ist immer glueetl. AWS Glue unterstützt das Ausführen von Auftragsskripts, die in Python oder Scala geschrieben sind. In diesem Beispiel ist das Auftragsskript (MyTestGlueJob.py) in Python geschrieben. Python-Parameter werden in der $DefArgs-Variablen angegeben und dann an den PowerShell-Befehl im DefaultArguments-Parameter übergeben, der eine Hashtabelle akzeptiert. Die Parameter in der $JobParams-Variablen stammen aus der CreateJob-API, die im Thema „Aufträge“ (https://docs.aws.amazon.com/glue/latest/dg/aws-glue-api-jobs-job.html) der API-Referenz für AWS Glue dokumentiert ist.

$Command = New-Object Amazon.Glue.Model.JobCommand
$Command.Name = 'glueetl'
$Command.ScriptLocation = 's3://amzn-s3-demo-source-bucket/admin/MyTestGlueJob.py'
$Command

$Source = "source_test_table"
$Target = "target_test_table"
$Connections = $Source, $Target

$DefArgs = @{
     '--TempDir' = 's3://amzn-s3-demo-bucket/admin'
     '--job-bookmark-option' = 'job-bookmark-disable'
     '--job-language' = 'python'
     }
$DefArgs

$ExecutionProp = New-Object Amazon.Glue.Model.ExecutionProperty
$ExecutionProp.MaxConcurrentRuns = 1
$ExecutionProp

$JobParams = @{
    "AllocatedCapacity"    = "5"
    "Command"              = $Command
    "Connections_Connection" = $Connections
    "DefaultArguments"  = $DefArgs
    "Description"       = "This is a test"
    "ExecutionProperty" = $ExecutionProp
    "MaxRetries"        = "1"
    "Name"              = "MyOregonTestGlueJob"
    "Role"              = "Amazon-GlueServiceRoleForSSM"
    "Timeout"           = "20"
     }

New-GlueJob @JobParams

class GlueWrapper:
    """Encapsulates AWS Glue actions."""

    def __init__(self, glue_client):
        """
        :param glue_client: A Boto3 Glue client.
        """
        self.glue_client = glue_client


    def create_job(self, name, description, role_arn, script_location):
        """
        Creates a job definition for an extract, transform, and load (ETL) job that can
        be run by AWS Glue.

        :param name: The name of the job definition.
        :param description: The description of the job definition.
        :param role_arn: The ARN of an IAM role that grants AWS Glue the permissions
                         it requires to run the job.
        :param script_location: The Amazon S3 URL of a Python ETL script that is run as
                                part of the job. The script defines how the data is
                                transformed.
        """
        try:
            self.glue_client.create_job(
                Name=name,
                Description=description,
                Role=role_arn,
                Command={
                    "Name": "glueetl",
                    "ScriptLocation": script_location,
                    "PythonVersion": "3",
                },
                GlueVersion="3.0",
            )
        except ClientError as err:
            logger.error(
                "Couldn't create job %s. Here's why: %s: %s",
                name,
                err.response["Error"]["Code"],
                err.response["Error"]["Message"],
            )
            raise

# 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

  # Creates a new job with the specified configuration.
  #
  # @param name [String] The name of the job.
  # @param description [String] The description of the job.
  # @param role_arn [String] The ARN of the IAM role to be used by the job.
  # @param script_location [String] The location of the ETL script for the job.
  # @return [void]
  def create_job(name, description, role_arn, script_location)
    @glue_client.create_job(
      name: name,
      description: description,
      role: role_arn,
      command: {
        name: 'glueetl',
        script_location: script_location,
        python_version: '3'
      },
      glue_version: '3.0'
    )
  rescue Aws::Glue::Errors::GlueException => e
    @logger.error("Glue could not create job #{name}: \n#{e.message}")
    raise
  end

        let create_job = glue
            .create_job()
            .name(self.job())
            .role(self.iam_role.expose_secret())
            .command(
                JobCommand::builder()
                    .name("glueetl")
                    .python_version("3")
                    .script_location(format!("s3://{}/job.py", self.bucket()))
                    .build(),
            )
            .glue_version("3.0")
            .send()
            .await
            .map_err(GlueMvpError::from_glue_sdk)?;

        let job_name = create_job.name().ok_or_else(|| {
            GlueMvpError::Unknown("Did not get job name after creating job".into())
        })?;

import AWSClientRuntime
import AWSGlue

    /// Create a new AWS Glue job.
    /// 
    /// - Parameters:
    ///   - glueClient: The AWS Glue client to use.
    ///   - jobName: The name to give the new job.
    ///   - role: The IAM role for the job to use when accessing AWS services.
    ///   - scriptLocation: The AWS S3 URI of the script to be run by the job.
    /// 
    /// - Returns: `true` if the job is created successfully, otherwise `false`.
    func createJob(glueClient: GlueClient, name jobName: String, role: String,
                   scriptLocation: String) async -> Bool {
        let command = GlueClientTypes.JobCommand(
            name: "glueetl",
            pythonVersion: "3",
            scriptLocation: scriptLocation
        )

        do {
            _ = try await glueClient.createJob(
                input: CreateJobInput(
                    command: command,
                    description: "Created by the AWS SDK for Swift Glue basic scenario example.",
                    glueVersion: "3.0",
                    name: jobName,
                    numberOfWorkers: 10,
                    role: role,
                    workerType: .g1x
                )
            )
        } catch {
            return false
        }
        return true
    }