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Azure Machine Learning supports submission of standalone machine learning jobs, and creation of [machine learning pipelines](./concept-ml-pipelines.md), that involve multiple machine learning workflow steps. Azure Machine Learning handles both standalone Spark job creation, and creation of reusable Spark components that Azure Machine Learning pipelines can use. In this article, you'll learn how to submit Spark jobs using:
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### Submit a standalone Spark job from Azure Machine Learning studio UI
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To submit a standalone Spark job using the Azure Machine Learning studio UI:
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### Submit a standalone Spark job from Azure Machine Learning Studio UI
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To submit a standalone Spark job using the Azure Machine Learning Studio UI:
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:::image type="content" source="media/how-to-submit-spark-jobs/create_standalone_spark_job.png" alt-text="Screenshot showing creation of a new Spark job in Azure Machine Learning studio UI.":::
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:::image type="content" source="media/how-to-submit-spark-jobs/create_standalone_spark_job.png" alt-text="Screenshot showing creation of a new Spark job in Azure Machine Learning Studio UI.":::
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- In the left pane, select **+ New**.
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- Select **Spark job (preview)**.
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- On the **Compute** screen:
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:::image type="content" source="media/how-to-submit-spark-jobs/create_standalone_spark_job_compute.png" alt-text="Screenshot showing compute selection screen for a new Spark job in Azure Machine Learning studio UI.":::
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:::image type="content" source="media/how-to-submit-spark-jobs/create_standalone_spark_job_compute.png" alt-text="Screenshot showing compute selection screen for a new Spark job in Azure Machine Learning Studio UI.":::
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1. Under **Select compute type**, select **Spark automatic compute (Preview)** for Managed (Automatic) Spark compute, or **Attached compute** for an attached Synapse Spark pool.
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1. If you selected **Spark automatic compute (Preview)**:
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