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Getting Started with Hama on YARN

Preparations

Current Hama and Hadoop requires JRE 1.7 or higher and ssh to be set up between nodes in the cluster:

  • Hadoop-2.x
  • Sun Java JDK 1.7 or higher version

For additional information consult our CompatibilityTable.

This tutorial requires Hadoop 2.x already correctly installed. If you haven't done this yet, please follow the official documentation https://hadoop.apache.org/docs/stable/

Configuration

Only two resource manager address and default filesystem uri properties is essentially needed for Hama on YARN. See also configuration page for advanced configurations of Hama.

Advanced Properties

Property Name

Default

Meaning

hama.appmaster.memory.mb

100mb

The amount of memory used by the BSPApplicationMaster. The total amount of memory used by the ApplicationMaster is calculated as follows. memoryInMb = 3 * BSP_TASK_NUM + hama.appmaster.memory.mb. This is because the application master spawns 1-3 thread per launched task that each should take 1mb, plus a minimum of base memory usage of 100. If you face memory issues, you can set this to a higher value.

Launching Hama on YARN

Ensure that copy yarn-site.xml in in HADOOP_CONF_DIR or YARN_CONF_DIR to HAMA_CONF_DIR. Because this configuration file is used to connect to the YARN. And $HAMA_HOME environment variable must be set.

Launch Hama application which is serialize printing example:

$HAMA_HOME/bin/hama jar hama-yarn-0.7.0-SNAPSHOT.jar org.apache.hama.bsp.YarnSerializePrinting

You should see "Hello BSP Message" which each container spawned in HDFS where you defined output path.

How to write a Hama-YARN job

The BSPModel hasn't changed, but the way to submit a job has.

Basically you just need the following code to submit a Hama-YARN job

    HamaConfiguration conf = new HamaConfiguration();
    YARNBSPJob job = new YARNBSPJob(conf);

    job.setBspClass(HelloBSP.class);
    job.setJarByClass(HelloBSP.class);
    job.setJobName("Serialize Printing");
    job.setMemoryUsedPerTaskInMb(50);
    job.setNumBspTask(2);
    job.waitForCompletion(false);

As you can see, instead of a BSPJob you are starting a YARNBSPJob.

The YARNBSPJob offers an extended API for running on YARN. For example you can set the amount of memory used by a task with

job.setMemoryUsedPerTaskInMb(50);

How to submit a job

General

You have to ways to submit a job, you can either submit it via shell and a packed jar, or you can submit from a java application. In both cases you need the hama-yarn jar in the classpath or inside the jar to run correctly.

Via Shell

bin/yarn jar /path_to_jar org.apache.hama.bsp.YarnSerializePrinting

In this case the jar in /path_to_jar contains the hama-yarn jar or it is already in the classpath of your Hadoop application. You have to replace org.apache.hama.bsp.YarnSerializePrinting with the class which contains the main method which runs the Hama Job.

Via Java Application

Just like in the section above, you have to configure the address of the ResourceManager. Then you can run this from a Java Application, just put it into a main-method.

    HamaConfiguration conf = new HamaConfiguration();
    conf.set("yarn.resourcemanager.address", "0.0.0.0:8040");

    YARNBSPJob job = new YARNBSPJob(conf);
    job.setBspClass(HelloBSP.class);
    job.setJarByClass(HelloBSP.class);
    job.setJobName("Serialize Printing");
    job.setMemoryUsedPerTaskInMb(50);
    job.setNumBspTask(2);
    job.waitForCompletion(false);

How to change existing Hama Jobs to run on YARN

In case you have the following code

    // BSP job configuration
    HamaConfiguration conf = new HamaConfiguration();
    BSPJob bsp = new BSPJob(conf);
    bsp.waitForCompletion(true);

to submit a Hama job. You can just change the BSPJob to YARNBSPJob.

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