# Step 2: Configure the Amazon Glue job that exports the Amazon Keyspaces table
Step 2: Configure the Amazon Glue job

In the second step of the tutorial you use the script `setup-export.sh` available on [Github](https://github.com/aws-samples/amazon-keyspaces-examples/blob/main/scala/datastax-v4/aws-glue/export-to-s3/setup-export.sh) to create and configure the Amazon Glue job that connects to Amazon Keyspaces using the SigV4 plugin and then exports the specified table to your Amazon S3 bucket created in the previous step. Using the script allows you to export data from Amazon Keyspaces without setting up an Apache Spark cluster.

**Create an Amazon Glue job to export an Amazon Keyspaces table to an Amazon S3 bucket.**
+ In this step, you run the `setup-export.sh` shell script located in the `export-to-s3/` directory to use Amazon CloudFormation to create and configure the Amazon Glue export job. The script takes the following parameters.

  ```
  PARENT_STACK_NAME, EXPORT_STACK_NAME, KEYSPACE_NAME, TABLE_NAME, S3_URI, FORMAT
  ```
  + `PARENT_STACK_NAME` – The name of the Amazon CloudFormation stack created in the previous step.
  + `EXPORT_STACK_NAME` – The name of the Amazon CloudFormation stack that creates the Amazon Glue export job.
  + `KEYSPACE_NAME` and `TABLE_NAME` – The fully qualified name of the keyspace and table to be exported. For this tutorial, we use `catalog.book_awards`, but you can replace this with your own fully qualified table name.
  + `S3URI` – The optional URI of the Amazon S3 bucket. The default is the Amazon S3 bucket from the parent stack.
  + `FORMAT` – The optional data format. The default value is `parquet`. For this tutorial, to make data load and transformation easier, we use the default.

  You can use the following command as an example.

  ```
  setup-export.sh cfn-setup cfn-glue catalog book_awards
  ```

  To confirm that the job has been created, you can use the following statement.

  ```
  aws glue list-jobs
  ```

  The output of the statement should look similar to this.

  ```
  {
      "JobNames": [
          "AmazonKeyspacesExportToS3-cfn-setup-cfn-glue"
      ]
  }
  ```

  To see the details of the job, you can use the following command.

  ```
  aws glue get-job --job-name AmazonKeyspacesExportToS3-cfn-setup-cfn-glue
  ```

  The output of the command shows all the details of the job. This includes the default arguments that you can override when running the job.

  ```
  {
      "Job": {
          "Name": "AmazonKeyspacesExportToS3-cfn-setup-cfn-glue",
          "JobMode": "SCRIPT",
          "JobRunQueuingEnabled": false,
          "Description": "export to s3",
          "Role": "iam-export-role",
          "CreatedOn": "2025-01-30T15:53:30.765000+00:00",
          "LastModifiedOn": "2025-01-30T15:53:30.765000+00:00",
          "ExecutionProperty": {
              "MaxConcurrentRuns": 1
          },
          "Command": {
              "Name": "glueetl",
              "ScriptLocation": "s3://s3-keyspaces/scripts/cfn-setup-cfn-glue-export.scala",
              "PythonVersion": "3"
          },
          "DefaultArguments": {
              "--write-shuffle-spills-to-s3": "true",
              "--S3_URI": "s3://s3-keyspaces",
              "--TempDir": "s3://s3-keyspaces/shuffle-space/export-sample/",
              "--extra-jars": "s3://s3-keyspaces/jars/spark-cassandra-connector-assembly_2.12-3.1.0.jar,s3://s3-keyspaces/jars/aws-sigv4-auth-cassandra-java-driver-plugin-4.0.9-shaded.jar,s3://s3-keyspaces/jars/spark-extension_2.12-2.8.0-3.4.jar,s3://s3-keyspaces/jars/amazon-keyspaces-helpers-1.0-SNAPSHOT.jar",
              "--class": "GlueApp",
              "--user-jars-first": "true",
              "--enable-metrics": "true",
              "--enable-spark-ui": "true",
              "--KEYSPACE_NAME": "catalog",
              "--spark-event-logs-path": "s3://s3-keyspaces/spark-logs/",
              "--enable-continuous-cloudwatch-log": "true",
              "--write-shuffle-files-to-s3": "true",
              "--FORMAT": "parquet",
              "--TABLE_NAME": "book_awards",
              "--job-language": "scala",
              "--extra-files": "s3://s3-keyspaces/conf/keyspaces-application.conf",
              "--DRIVER_CONF": "keyspaces-application.conf"
          },
          "MaxRetries": 0,
          "AllocatedCapacity": 4,
          "Timeout": 2880,
          "MaxCapacity": 4.0,
          "WorkerType": "G.2X",
          "NumberOfWorkers": 2,
          "GlueVersion": "3.0"
      }
  }
  ```

If the Amazon CloudFormation stack process fails, you can review the errors for the failed stack in the Amazon CloudFormation console. You can review the details of the export job in the Amazon Glue console by choosing **ETL jobs** on the left-side menu.

After you have confirmed the details of the Amazon Glue export job, proceed to [Step 3: Run the Amazon Glue job to export the Amazon Keyspaces table to the Amazon S3 bucket from the Amazon CLI](S3-tutorial-step3.md) to run the job to export the data from your Amazon Keyspaces table.