Use Azure Toolkit for Eclipse to create Spark applications for an HDInsight cluster

Use HDInsight Tools in Azure Toolkit for Eclipse to develop Spark applications written in Scala and submit them to an Azure HDInsight Spark cluster, directly from the Eclipse IDE. You can use the HDInsight Tools plug-in in a few different ways:

  • To develop and submit a Scala Spark application on an HDInsight Spark cluster
  • To access your Azure HDInsight Spark cluster resources
  • To develop and run a Scala Spark application locally

This tool can be used to create and submit applications only for an HDInsight Spark cluster on Linux.


  • An Apache Spark cluster on HDInsight. For instructions, see Create Apache Spark clusters in Azure HDInsight.
  • Oracle Java Development Kit version 8, which is used for the Eclipse IDE runtime. You can download it from the Oracle website.
  • Eclipse IDE. This article uses Eclipse Neon. You can install it from the Eclipse website.
  • Scala IDE for Eclipse.

    • If you have the Eclipse IDE installed, you can add the Scala IDE plug-in by going to Help > Install New SoftWare, and add as the source to download the Scala plug-in for Eclipse.
    • If you do not have the Eclipse IDE installed, you can install the Scala IDE directly from the Scala website. Download the .zip file, extract it, browse to the /eclipse folder, and then run eclipse.exe file from there.


      The steps in this article are based on using the Eclipse IDE with the Scala plug-in installed.

  • Spark SDK. You can download it from GitHub.
  • e(fx)clipse. You can install it from the download page on the Eclipse website.

Install HDInsight Tools in Azure Toolkit for Eclipse

HDInsight Tools for Eclipse is available as part of Azure Toolkit for Eclipse. For installation instructions, see Installing Azure Toolkit for Eclipse.

Sign in to your Azure subscription

  1. Start the Eclipse IDE and open Azure Explorer. On the Window menu, click Show View, and then click Other. In the dialog box that opens, expand Azure, click Azure Explorer, and then click OK.

    Show View dialog box

  2. Right-click the Azure node, and then click Sign in.
  3. In the Azure Sign In dialog box, choose the authentication method, click Sign in, and enter your Azure credentials.

    Azure Sign In dialog box

  4. After you're signed in, the Select Subscriptions dialog box lists all the Azure subscriptions associated with the credentials. Click Select to close the dialog box.

    Select Subscriptions dialog box

  5. On the Azure Explorer tab, expand HDInsight to see the HDInsight Spark clusters under your subscription.

    HDInsight Spark clusters in Azure Explorer

  6. You can further expand a cluster name node to see the resources (for example, storage accounts) associated with the cluster.

    Expanding a cluster name to see resources

Set up a Spark Scala project for an HDInsight Spark cluster

  1. In the Eclipse IDE workspace, click File, click New, and then click Project.
  2. In the New Project wizard, expand HDInsight, select Spark on HDInsight (Scala), and then click Next.

    Selecting the Spark on HDInsight (Scala) project

  3. In the New HDInsight Scala Project dialog box, provide the following values, and then click Next:

    • Enter a name for the project.
    • In the JRE area, make sure that Use an execution environment JRE is set to JavaSE-1.7 or later.
    • Make sure that Spark SDK is set to the location where you downloaded the SDK. The link to the download location is included in the prerequisites earlier in this article. You can also download the SDK from the link included in the dialog box.

      New HDInsight Scala Project dialog box

  4. In the next dialog box, click the Libraries tab and keep the defaults, and then click Finish.

    Libraries tab

Run a Spark Scala application on an Azure Data Lake Store cluster

If you want to submit an application to Azure Data Lake Store, you must choose Interactive mode during the Azure sign-in process.

Interactive option at sign-in

Create a Scala application for an HDInsight Spark cluster

  1. In the Eclipse IDE, from Package Explorer, expand the project that you created earlier, right-click src, point to New, and then click Other.
  2. In the Select a wizard dialog box, expand Scala Wizards, click Scala Object, and then click Next.

    Select a wizard dialog box

  3. In the Create New File dialog box, enter a name for the object, and then click Finish.

    Create New File dialog box

  4. Paste the following code in the text editor:

     import org.apache.spark.SparkConf
     import org.apache.spark.SparkContext
     object MyClusterApp{
       def main (arg: Array[String]): Unit = {
         val conf = new SparkConf().setAppName("MyClusterApp")
         val sc = new SparkContext(conf)
         val rdd = sc.textFile("wasb:///HdiSamples/HdiSamples/SensorSampleData/hvac/HVAC.csv")
         //find the rows that have only one digit in the seventh column in the CSV
         val rdd1 =  rdd.filter(s => s.split(",")(6).length() == 1)
  5. Run the application on an HDInsight Spark cluster:

    1. From Package Explorer, right-click the project name, and then select Submit Spark Application to HDInsight.
    2. In the Spark Submission dialog box, provide the following values, and then click Submit:

      • For Cluster Name, select the HDInsight Spark cluster on which you want to run your application.
      • Select an artifact from the Eclipse project, or select one from a hard drive. The default value depends on the item you right-click from package explorer.
      • In the Main class name dropdownlist, submission wizard displays all object names from your selected project. Select or input one that you want to run. If you select artifact from hard disk, you need input main class name by yourself.
      • Because the application code in this example does not require any command-line arguments or reference JARs or files, you can leave the remaining text boxes empty.

        Spark Submission dialog box

    3. The Spark Submission tab should start displaying the progress. You can stop the application by clicking the red button in the Spark Submission window. You can also view the logs for this specific application run by clicking the globe icon (denoted by the blue box in the image).

      Spark Submission window

Access and manage HDInsight Spark clusters by using HDInsight Tools in Azure Toolkit for Eclipse

You can perform various operations by using HDInsight Tools, including accessing the job output.

Access the job view

  1. In Azure Explorer, expand HDInsight, expand the Spark cluster name, and then click Jobs.
    Job view node
  2. In the right pane, the Spark Job View tab displays all the applications that were run on the cluster. Click the name of the application for which you want to see more details. Application details
  3. Hover on job graph, it displays basic running job info. Click on job graph, you can see the stages graph and info which every job generates. Job stage details

  4. Frequently-used log including Driver Stderr, Driver Stdout, Directory Info are listed in Log tab. Log details

  5. You can also open the Spark history UI and the YARN UI (at the application level) by clicking the respective hyperlink at the top of the window.

Access the storage container for the cluster

  1. In Azure Explorer, expand the HDInsight root node to see a list of HDInsight Spark clusters that are available.
  2. Expand the cluster name to see the storage account and the default storage container for the cluster.

    Storage account and default storage container

  3. Click the storage container name associated with the cluster. In the right pane, double-click the HVACOut folder. Open one of the part- files to see the output of the application.

Access the Spark history server

  1. In Azure Explorer, right-click your Spark cluster name, and then select Open Spark History UI. When you're prompted, enter the admin credentials for the cluster. You must have specified these while provisioning the cluster.
  2. In the Spark history server dashboard, you use the application name to look for the application that you just finished running. In the preceding code, you set the application name by using val conf = new SparkConf().setAppName("MyClusterApp"). Hence, your Spark application name was MyClusterApp.

Start the Ambari portal

  1. In Azure Explorer, right-click your Spark cluster name, and then select Open Cluster Management Portal (Ambari).
  2. When you're prompted, enter the admin credentials for the cluster. You must have specified these while provisioning the cluster.

Manage Azure subscriptions

By default, HDInsight Tools in Azure Toolkit for Eclipse lists the Spark clusters from all your Azure subscriptions. If necessary, you can specify the subscriptions for which you want to access the cluster.

  1. In Azure Explorer, right-click the Azure root node, and then click Manage Subscriptions.
  2. In the dialog box, clear the check boxes for the subscription that you don't want to access, and then click Close. You can also click Sign Out if you want to sign out of your Azure subscription.

Run a Spark Scala application locally

You can use HDInsight Tools in Azure Toolkit for Eclipse to run Spark Scala applications locally on your workstation. Typically, these applications don't need access to cluster resources such as a storage container, and you can run and test them locally.


While you're running the local Spark Scala application on a Windows computer, you might get an exception as explained in SPARK-2356. This exception occurs because WinUtils.exe is missing in Windows.

To resolve this error, you must download the executable to a location like C:\WinUtils\bin. You must then add the environment variable HADOOP_HOME and set the value of the variable to C\WinUtils.

Run a local Spark Scala application

  1. Start Eclipse and create a project. In the New Project dialog box, make the following choices, and then click Next.

    • In the left pane, select HDInsight.
    • In the right pane, select Spark on HDInsight Local Run Sample (Scala).

      New Project dialog box

  2. To provide the project details, follow steps 3 through 6 from the earlier section Set up a Spark Scala project for an HDInsight Spark cluster.
  3. The template adds a sample code (LogQuery) under the src folder that you can run locally on your computer.

    Location of LogQuery

  4. Right-click the LogQuery application, point to Run As, and then click 1 Scala Application. You will see an output like this in the Console tab at the bottom:

    Spark Application local run result

Feedback and known issues

Currently, viewing Spark outputs directly is not supported.

If you have any suggestions or feedback, or if you encounter any problems when using this tool, feel free to send us an email at

See also


Creating and running applications

Tools and extensions

Managing resources