Big Data

What is Hadoop

Hadoop is an open-source software package that utilizes large scale data processing by using the Hadoop Distributed File System (HDFS) to provide fast bandwidth of large data across clusters. Using the Hadoop interface, it is possible to split large data across both nodes and processors to increase data processing time. Hadoop’s advantage is processing large data files (gigabytes to terabyte range), in a non-POSIX compliant filesystem to increase throughput performance. Hadoop is currently installed on the Spruce Knob cluster.

Using Hadoop on the cluster

Running Hadoop jobs are very similar to running other jobs on the cluster. You will run all of your commands within a PBS job script. However, before you run Hadoop commands, you need to start the Hadoop datanode. To do this, you need to load a few module files and run a few start-up scripts. In addition a specific PBS directive (PBS -W) needs to be specified so Hadoop runs properly:

#PBS -W x=nmatchpolicy:exactnode

module load compilers/java/jre1.8.0
module load libraries/DFS/myhadoop

source $MH_HOME/etc/spruce_default.conf
myhadoop-configure.sh

start-all.sh

Below these lines, you can place your intended hadoop commands. At the end of your script, you need to stop the hadoop datanode:

stop-all.sh

myhadoop-cleanup.sh

Both of these commands will end the Hadoop backend. Hadoop commands after the cleanup scripts will result in errors. Here is an example Hadoop script that will run on 3 nodes with 1 processor a node. The example is a wordcount program that is distributed with Hadoop that counts the presence of all words in small sample of Shakespeare playwrights taken from Project Gutenberg.

#!/bin/bash

#PBS -q standby
#PBS -N hadoop_job
#PBS -l nodes=3:ppn=1
#PBS -o hadoop_run.out
#PBS -e hadoop_run.err
#PBS -W x=nmatchpolicy:exactnode
#PBS -V

module load compilers/java/jre1.8.0
module load libraries/DFS/myhadoop

# Configure myHadoop environment
source $MH_HOME/etc/spruce_default.conf
myhadoop-configure.sh

# Start Hadoop Cluster
start-all.sh


#### Run your jobs here
echo "Run some test Hadoop jobs"
hadoop dfs -mkdir Data
hadoop dfs -copyFromLocal $HADOOP_HOME/data/gutenberg Data
hadoop dfs -ls Data/gutenberg
hadoop jar /shared/software/myhadoop/hadoop-1.2.1/hadoop-examples-1.2.1.jar wordcount Data/gutenberg Outputs
hadoop dfs -ls Outputs
echo

#### Stop the Hadoop cluster
stop-all.sh

#### Cleanup myHadoop configurations
myhadoop-cleanup.sh

exit 0

R Interface with Hadoop - Rhipe

Running large datasets within R is difficult since R loads all data into memory. However, using Hadoop with R can overcome that limitation. To use the R package Rhipe, after setting up the hadoop datanode, you can load the two modules for the dynamically shared R binary and the Rhipe R package:

module load compilers/R/3.1.0
module load libraries/R/Rhipe

Note: Rhipe must be loaded after the R module - otherwise you will get a pre-requisite error.

Further Information

Useful Webpages

• Apache Hadoop

• Myhadoop Sourceforge

• Rhipe

Useful Books

Hadoop: The Definitive Guide. Tom White. ISBN: 978-1-4493-1152-0

Parallel R. Q.E. McCallum and S. Watson. ISBN: 978-1-4493-0992-3