I have 3 nodes at home (hdp1, hdp2 and hdp3) which are running Hortonworks Data Platform (HDP). I have HDFS, Zookeeper and Spark installed on the cluster.
To test running Spark on Mesos, I decided to reuse the cluster for simplicity's sake.
All I did was:
(1) install Mesos master on node hdp1.
(2) install Mesos slave on node hdp2 and hdp3.
(3) configure the master and slaves accordingly.
NOTE:
(i) For more information about the installation and configuration of Mesos, you can refer to this blog entry.
(ii) I reuse Zookeeper that was installed with HDP.
Once Mesos is up and running, I decided to carry out a very simple test that is described as follow:
(1) Use "spark-shell" as the Spark client to connect to the Mesos cluster.
(2) Load a sample text file into HDFS.
(3) Use spark-shell to perform a line count on the loaded text file.
First, let's see what is the command that you can use to connect spark-shell to a running Mesos cluster.
TIPS: All you need to do is to use the "--master" option to point to the Mesos cluster at "mesos://<IP-or-hostname of Mesos master>:5050".
Then, let's load a sample text file into HDSF using the "hadoop fs -put" command.
Once the sample text file is loaded, let's create a spark RDD using it.
TIPS: You can use the "sc.textFile" function and points it to "hdfs://<namenode>:8020/<path to file>".
After the RDD is created, let's run a count on it using the "count()" function.
You can see from the screenshot above and below that, Spark (through Mesos) has submitted 2 tasks that are executed on node hdp2 and hdp3 respectively.
You can also see from the screenshot above that the end result is returned as "4" (which means 4 lines in the file - which is correct!).
So, that is how easy it is to run Spark on Mesos.
Hope that you are going to try it out!
