Getting Started with Hama on YARN (Hadoop 0.23.x)
If you are a total newb to Hama, please go directly to the Full Walkthrough section.
Requirements
Current Hama and Hadoop requires JRE 1.6 or higher and ssh to be set up between nodes in the cluster:
- Hadoop-0.23.x
- Sun Java JDK 1.6.x or higher version
For additional information consult our CompatibilityTable.
This tutorial requires Hadoop 0.23.0 already correctly installed. If you haven't done this yet, please follow the official documentation http://hadoop.apache.org/common/docs/r0.23.0/
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(); 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);
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 configure a job
There are some configuration values that the job needs to have in order to submit sucessfully to YARN infrastructure.
The importantest configuration is the yarn.resourcemanager.address
. This should point to the address (hostname+port) where your ResourceManager runs, for example localhost:8040
.
Another important configuration value is the amount of memory used by the BSPApplicationMaster. You can configure a base amount of memory for the application master with this configuration key
hama.appmaster.memory.mb
By default, this is set to 100mb.
The total amount of memory used by the ApplicationMaster is calculated as follows
int memoryInMb = 3 * this.getNumBspTask() + conf.getInt("hama.appmaster.memory.mb", 100)
This is because the application master spawns 1-3 threads 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.
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
.
Full Walkthrough
This walkthrough guides you step by step to a working Hama BSP application on YARN. However, you must have correctly installed Hadoop 0.23.x on your machine.
<TODO>
Make some fancy pictures from eclipse and how to get a jar out of it and submit.