Run a pipeline against an existing Dataproc cluster

This page describes how to run a pipeline in Cloud Data Fusion against an existing Dataproc cluster.

By default, Cloud Data Fusion creates ephemeral clusters for each pipeline: it creates a cluster at the beginning of the pipeline run, and then deletes it after the pipeline run completes. While this behavior saves costs by ensuring that resources are only created when required, this default behavior might not be desirable in the following scenarios:

• If the time it takes to create a new cluster for every pipeline is prohibitive for your use case.

• If your organization requires cluster creation to be managed centrally; for example, when you want to enforce certain policies for all Dataproc clusters.

For these scenarios, you instead run pipelines against an existing cluster with the following steps. The steps are simplified in versions 6.2.1 and later.

Before you begin

You need the following:

• A Cloud Data Fusion instance.

  Create a Cloud Data Fusion instance

• An existing Dataproc cluster.

  Create a Dataproc cluster

• If you run your pipelines in Cloud Data Fusion version 6.2, use an older Dataproc image that runs with Hadoop 2.x (for example, 1.5-debian10), or upgrade to the latest Cloud Data Fusion version.

Versions 6.2.1 and later

Connect to the existing cluster

In Cloud Data Fusion versions 6.2.1 and later, you can connect to an existing Dataproc cluster when you create a new Compute Engine profile.

1. Go to your instance:

   1. In the Google Cloud console, go to the Cloud Data Fusion page.

   2. To open the instance in the Cloud Data Fusion web interface, click Instances, and then click View instance.

      Go to Instances

2. Click System Admin.

3. Click the Configuration tab.

4. Expand the System Compute Profiles field.

5. Click Create New Profile. A page of provisioners opens.

6. Click Existing Dataproc.

7. Enter your desired profile, cluster, and monitoring information.

8. Click Create.

Configure your pipeline to use the custom profile

1. In the Pipeline Studio, click Configure.

2. Click Compute config.

3. Click the profile that you created.

   

4. Run the pipeline. It now runs against your existing Dataproc cluster.

Versions before 6.2.1

Note: The following advice applies only if you're using Cloud Data Fusion the Enterprise edition in version 6.1.

Set up SSH on a Dataproc cluster

1. In the Google Cloud console, go to the Dataproc Clusters page.

   Go to Clusters

2. Click the cluster name. A page with cluster details opens.

3. Click the VM Instances tab, and then click the SSH button to connect to the Dataproc Master VM.

4. Create a new SSH key by running the following command:

   ssh-keygen -m PEM -t rsa -b 4096 -f ~/.ssh/KEY_FILENAME -C USERNAME
   

   The following two files are created:

   • ~/.ssh/KEY_FILENAME (Private key)
   • ~/.ssh/KEY_FILENAME.pub (Public key)

5. Copy the entire SSH public key. To view the key in a readable format, run the following command:

   cat  ~/.ssh/KEY_FILENAME.pub
   

6. Open the Compute Engine Metadata page, select the SSH Keys tab, and then click Edit.

7. Click Add item.

8. In the text box that appears, paste the public key that you previously copied.

9. Click Save.

Create a custom system compute profile for the instance

1. Go to your instance:

   1. In the Google Cloud console, go to the Cloud Data Fusion page.

   2. To open the instance in the Cloud Data Fusion web interface, click Instances, and then click View instance.

      Go to Instances

2. Click System Admin.

3. Click the Configuration tab.

4. Expand the System Compute Profiles box.

5. Click Create New Profile. A page of provisioners opens.

6. Click Remote Hadoop Provisioner.

7. On the Create a profile for Remote Hadoop Provisioner page, enter the profile information, including the SSH information:

   • Host: You can find the SSH host IP information for the Master Node in the Compute Engine VM instance page details.
   Note: If the instance is private, use the master's internal IP address, instead of the external IP address.

   

   • User: The username that you specified when creating the SSH keys.
   • SSH private key: Paste in the SSH private key that you created previously. To view the key content in a readable format, use the following command:

      cat  ~/.ssh/KEY_FILENAME 

   Include the beginning and ending comments in your copy.

8. Click Create.

Configure your pipeline to use the custom profile

1. In the Pipeline Studio, click Configure.

2. Click Compute config.

3. Click the profile that you created.

4. Run the pipeline. It now runs against your existing Dataproc cluster.

Troubleshooting

• If the pipeline fails on connection timeout, check that the SSH key and the firewall rules are configured correctly.

• If you get an invalid privatekey error while running the pipeline, check if the first line of your private key is as follows: ----BEGIN OPENSSH PRIVATE KEY-----. If it is, try generating a key pair with RSA type:

  ssh-keygen -m PEM -t rsa -b 4096 -f ~/.ssh/KEY_FILENAME -C USERNAME
  

• If you receive the following error from your pipeline, java.io.IOException:com.jcraft.jsch.JSchException: Auth fail, follow these steps:

  • Validate the SSH key by manually connecting to the target Dataproc node using the SSH key.
  • If you're manually connecting to the VM by using SSH from the command line, and a private key works, but the same setup results in an Auth failed exception from JSch, then verify that OS login is not enabled. From the Compute Engine UI, click Metadata in the menu on the left, and then click the Metadata tab. Either delete the osLogin key, or set it to FALSE.