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The following deployment patterns are supported for WSO2 ML.

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By default, WSO2 ML runs with an inbuilt Apache Spark instance. However, when working with big data, you can handle those large data sets in a distributed environment through WSO2 ML. You can carry out data pre-processing and model building processes on an Apache Spark cluster to share the workload between the nodes of the cluster. Using a Spark cluster optimizes the performance and reduces the time consumed to build and train a machine learning model for a large data set.

Follow the steps below to run the ML jobs by connecting WSO2 ML to an external Apache Spark cluster.

Info
  • When following the instructions below you need to use Apache Spark version 1.4.1 with Apache Hadoop version 2.6 and later in the Apache Spark cluster.
  • The Spark deployment pattern can be Standalone, Yarn or Mesos.
  • WSO2 ML is unaware of the underlying configuration of the Spark cluster. It only interacts with the Spark master to which the jobs are submitted.

  1. Press Ctrl+C keys to shutdown the WSO2 ML server. For more information on shutting down WSO2 ML server, see Running the Product

    .

    In the <ML_HOME>/repository/conf/etc/spark-config.xml file, enter the Spark master URL as the value of the < spark.master> property as shown in the example below.

    TipYou can find the Spark Master URL in the Apache Spark Web UI as shown below

    .

    Image Removed

    Code Block
    languagexml
    <property name="spark.master">{SPARK_MASTER_URL}</property>
  2. Create a directory named <SPARK_HOME>/ml/ and copy the following jar files into it. These jar files can be found in the <ML_HOME>/repository/components/plugins directory.
    • org.wso2.carbon.ml.core_1.0.2.jar
    • org.wso2.carbon.ml.commons_1.0.2.jar
    • org.wso2.carbon.ml.database_1.0.2.jar
    • kryo_2.24.0.wso2v1.jar

  3. Create a file named spark-env.sh in the <SPARK_HOME>/conf/ directory and add the following entries.

    Code Block
    languagetext
    SPARK_MASTER_IP=127.0.0.1
SPARK_CLASSPATH={SPARK_HOME}/ml/org.wso2.carbon.ml.core_1.0.2.jar:{SPARK_HOME}/ml/org.wso2.carbon.ml.commons_1.0.2.jar:{SPARK_HOME}/ml/org.wso2.carbon.ml.database_1.0.2.jar:{SPARK_HOME}/ml/kryo_2.24.0.wso2v1.jar

  4. Restart the external Spark cluster using the following commands:

    Code Block
    {SPARK_HOME}$ ./sbin/stop-all.sh
{SPARK_HOME}$ ./sbin/start-all.sh

  5. In the <ML_HOME>/repository/conf/etc/spark-config.xml file, enter the Spark master URL as the value of the < spark.master> property as shown in the example below.

    Tip

    You can find the Spark Master URL in the Apache Spark Web UI as shown below.

    Image Added

    Code Block
    languagexml
    <property name="spark.master">{SPARK_MASTER_URL}</property>

  6. Restart the WSO2 ML server. For more information on restarting WSO2 ML server, see Running the Product.

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