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Hitachi Vantara Lumada and Pentaho Documentation

Connect to Azure HDInsight

This article explains how to connect the Pentaho Server to a Microsoft Azure HDInsight cluster. Pentaho supports both the HDFS file system and the WASB (Windows Azure Storage BLOB) extension for Azure HDInsight. The WASB file system is the default file system for Azure HDInsight. 

The following tasks make up the process for connecting an Azure HDInsight Hadoop cluster to the Pentaho Server:

  1. Edit Cluster Configuration Files
  2. Configure Pentaho Components Shim
  3. Connect to a Hadoop Cluster with the PDI Client

After creating a connection, we suggest that you test it. If you are not able to connect, refer to the Troubleshooting section. To ensure a good connection, we recommend performing a few tasks before you begin the connection process.

Before You Begin 

Before you begin, you will need to perform the following tasks:

  1. Verify Support
    Check the Components Reference to verify that your Pentaho version supports your version of the Azure HDInsight cluster.

  2. Set Up an Azure HDInsight cluster
    Pentaho can connect to secured and unsecured Azure HDInsight clusters:
    1. Configure an Azure HDInsight cluster. See the Microsoft Azure documentation if you need help.
    2. Install any required services and service client tools.
    3. Test the cluster.

  3. Get Connection Information
    Ask your Hadoop Administrator for connection information to the cluster and related services. This information may also be available in your cluster management tools or Ambari.

  4. Add a YARN User to the Superuser Group
    Add the YARN user on the cluster to the group defined by the dfs.permissions.superusergroup property. This property is located in the hdfs-site.xml file on your cluster or in the cluster management application.

Edit Cluster Configuration Files

Although Pentaho often supports more than one version of a Hadoop distribution, the shim for Azure HDInsight is not included in the Pentaho Suite download, and must be downloaded separately from the Pentaho Customer Support Portal. You will need to sign in to view the available downloads.

The Oozie user runs Oozie jobs by default. But if you use PDI to start an Oozie job, you must add the PDI user to the oozie-site.xml file on the cluster so that the PDI user can execute the program by proxy. To use the Oozie service complete the following instructions:

  1. Open the oozie-site.xml file on the cluster.
  2. Add the following lines of the code to the oozie-site.xml file on cluster, substituting <your_pdi_user_name> with the PDI User username, such as jdoe.
  1. Save and close the file.
  2. Create or edit an existing file to point to your hostnames and folders in the cluster. Here is an example:
nameNode=wasb://<Your server name> queueName=default examplesRoot=examples<Cluster folder name>/oozie/examples/apps/map-reduce outputDir=<Your working directory>/oozie/output

Configure Pentaho Component Shims 

You must configure the shim in each of the following Pentaho components and on each computer from which Pentaho will be used to connect to the cluster:

  • PDI client (Spoon)
  • Pentaho Server

As a best practice, configure the shim in the PDI client first. The PDI client has features that will help you test your configuration. Then, copy the tested PDI client configuration files to other components, making changes if necessary. 

You can also opt to go through these instructions for each Pentaho component, and not copy the shim files from the PDI client. If you do not plan to connect to the cluster from the PDI client, you can configure the shim in another component first.

Perform the following steps to configure the shim on each component:

  1. Locate the Pentaho Big Data Plugin and Shim Directories.
  2. Select the Correct Shim.
  3. Copy the Configuration Files from Cluster to Shim.
  4. Edit the Shim Configuration Files.

Step 1: Locate the Pentaho Big Data Plugin and Shim Directories

Shims and other parts of the Pentaho Adaptive Big Data Layer are in the Pentaho Big Data Plugin directory. The path to this directory differs by component. You need to know the locations of this directory, in each component, to complete shim configuration and testing tasks.

In the following table, <pentaho home> in the shim locations for each component is the directory where Pentaho is installed:

Components Location of Pentaho Big Data Plugin Directory
PDI client <pentaho home>/design-tools/data-integration/plugins/pentaho-big-data-plugin
Pentaho Server <pentaho home>/server/pentaho-server/pentaho-solutions/system/kettle/plugins/pentaho-big-data-plugin

Shims are located in the pentaho-big-data-plugin/hadoop-configurations directory. Shim directory names consist of a three or four-letter Hadoop Distribution abbreviation followed by the Hadoop Distribution's version number. The version number does not contain a decimal point. For example, the shim directory named cdh59 is the shim for the CDH (Cloudera Distribution for Hadoop), version 5.9. The following table lists the shim directory abbreviations for Hadoop distributions:

Abbreviation Shim
cdh Cloudera's Distribution of Apache Hadoop
emr Amazon Elastic Map Reduce
hdi Microsoft Azure HDInsight
hdp Hortonworks Data Platform
mapr MapR

You will not see the hdi directory until you have unpacked the download as outlined in Step 2.

Step 2: Select the Correct Shim 

Although Pentaho often supports one or more versions of a Hadoop distribution, the download of the Pentaho Suite only contains the latest, supported, Pentaho-certified version of the shim.  The other supported versions of shims can be downloaded from the Pentaho Customer Support Portal

Before you begin, verify that the shim you want is supported by your version of Pentaho shown in the Components Reference.

  1. If you have not downloaded the Azure HDInsight shim, go to the Customer Portal. Sign in using the Pentaho support user name and password provided to you in your Pentaho Welcome Packet. 
  2. In the search box, enter the name of the shim you want. Select the shim from the search results. Optionally, you can browse the shims by version on the Downloads page. 
  3. Read all prerequisites, warnings, and instructions. On the bottom of the page in the Box widget, click the shim zip file to download it.
  4. Navigate to the pentaho-big-data-plugin/hadoop-configurations directory to view the shim directories. 
  5. Unzip the downloaded shim package into the pentaho-big-data-plugin/hadoop-configurations directory.

Step 3: Copy the Configuration Files from Cluster to Shim 

Copying configuration files from the cluster to the shim helps keep key configuration settings in sync with the cluster and reduces configuration errors.

Perform the following steps to copy these configuration file from the cluster to the shim:

  1. Back up the existing HDI shim files in the pentaho-big-data-plugin/hadoop-configurations/hdixx directory. 
  2. Copy the following configuration files from the HDI cluster to pentaho-big-data-plugin/hadoop-configurations/hdixx (overwriting the existing files):
  • core-site.xml
  • hbase-site.xml
  • hdfs-site.xml
  • hive-site.xml
  • mapred-site.xml
  • yarn-site.xml

Step 4: Edit the Shim Configuration Files 

You need to verify or change authentication, Oozie, Hive, MapReduce, and YARN settings in the following files:

  • core-site.xml
  • hbase-site.xml
  • hive-site.xml
  • mapred-site.xml
  • yarn-site.xml

Verify or Edit

To connect to a cluster, perform the following steps to verify that the proxy user values are properly set.

  1. Navigate to the pentaho-big-data-plugin/hadoop-configurations/hdixx directory and open the file.
  2. Add the following values:
Parameter Values
authentication.superuser.provider ​NO_AUTH
pentaho.oozie.proxy.user Add a proxy user's name to access the Oozie service through a proxy, otherwise, leave it set to oozie.
java.system.hdp.version HDI Version. For HDP 2.2, this is
  1. Save and close the file.

Edit core-site.xml

To use WASB storage, perform the following steps for updating the core-site.xml file:

  1. Obtain an unencrypted key from the Azure HDInsight cluster.
  2. Set the following properties in the core-site.xml file:
Parameter Values
  1. Save and close the file.

Edit hbase-site.xml

Edit the location of the temporary directory in the hbase-site.xml file to create an HBase local storage directory as follows:

  1. Navigate to the pentaho-big-data-plugin/hadoop-configurations/hdixx directory and open the hbase-site.xml file.
  2. Add the following value:
Parameter Value
hbase.tmp.dir  /tmp/hadoop/hbase
  1. Save and close the file.

Edit hive-site.xml 

Verify that the hive.metastore.uris parameter is set in the hive-site.xml file through the following steps:

  1. Navigate to the pentaho-big-data-plugin/hadoop-configurations/hdixx directory and open the hive-site.xml file.
  2. Add the following value:
Parameter Value
hive.metastore.uris Set this to the location of your hive metastore. 
  1. Save and close the file.

Edit hdfs-site.xml 

Set the dfs.internal.nameservices parameter value in the file through the following steps:

  1. Navigate to the pentaho-big-data-plugin/hadoop-configurations/hdixx directory and open the file.
  2. Add these values:
Parameter Value
dfs.internal.nameservices Set the value to your alias name for the HDFS name nodes.
  1. Save and close the file.

Edit mapred-site.xml 

Edit the mapred-site.xml file to indicate where the job history logs are stored and to allow MapReduce jobs to run across platforms as follows:

  1. Navigate to the pentaho-big-data-plugin/hadoop-configurations/hdixx directory and open the mapred-site.xml file.
  2. Add the following values:
Parameter Value
mapreduce.jobhistory.address Set this to the directory where you want to store the job history logs. 

Add classpath information. Here is an example:


Set the framework path. Here is an example:

</property> Add this property to allow MapReduce jobs to run on either Windows client or Linux server platforms:
  1. Save and close the file.

Edit yarn-site.xml

Verify that the following parameters are set in the yarn-site.xml file:

  1. Navigate to the pentaho-big-data-plugin/hadoop-configurations/hdixx directory and open the yarn-site.xml file.
  2. Add the following values:
Parameter Values

​Add the classpaths needed to run YARN applications. Use commas to separate multiple paths. Here is an example:

<property> <name>yarn.application.classpath</name>
yarn.resourcemanager.hostname Update the hostname in your environment or use the default:
yarn.resourcemanager.address Update the hostname and port for your environment.
yarn.resourcemanager.admin.address Update the hostname and port for your environment.
  1. Save and close the file.

Connect to a Hadoop Cluster with the PDI Client 

Once you have set up your shim, you must make it active, then configure and test the connection to the cluster. For details on setting up the connection, see the article Connect to a Hadoop Cluster with the PDI Client.

Connect Other Pentaho Components to the Azure HDInsight Cluster 

These instructions explain how to create and test a connection to the cluster in the Pentaho Server. Creating and testing a connection to the other components involves two tasks:

  • Setting the active shim on the Pentaho Server
  • Configuring and testing the cluster connections

Set the Active Shim on the Pentaho Server

Modify the file to set the active shim for the Pentaho Server.

  1. Stop the component.
  2. Locate the pentaho-big-data-plugin directory for your component. 
  3. Navigate to the hadoop-configurations directory.
  4. Navigate to the pentaho-big-data-plugin directory and open the file.
  5. Set the active.hadoop.configuration property to the directory name of the shim you want to make active. Here is an example:
  1. Save and close the file.
  2. Restart the component.

Create and Test Connections 

Connection tests appear in the following table:

Component Test
Pentaho Server for DI

Create a transformation in the PDI client and run it remotely.

Pentaho Server for BA Create a connection to the cluster in the Data Source Wizard.

Once you have connected to the cluster and its services properly, provide connection information to users who need access to the cluster and its services. Those users can only obtain access from computers that have been properly configured to connect to the cluster.

These users need the following information to connect:

  • Hadoop distribution and version of the cluster
  • HDFS, JobTracker, ZooKeeper, and Hive2/Impala Hostnames, IP addresses and port numbers
  • Oozie URL (if used)
  • Users also require the appropriate permissions to access the directories they need on HDFS. This typically includes their home directory and any other required directories.

They might also need more information depending on the job entries, transformation steps, and services they use. See Hadoop Connection and Access Information List for a more detailed list of information that your users might need from you.

For troubleshooting cluster and service configuration Issues, refer to Big Data Issues.