The tutorial expects you to be logged to a computer in the UFAL cluster and be able to submit jobs using SGE. In this environment, Hadoop is installed in /SGE/HADOOP/active
.
To use the Perl MapReduce API, you need
Moose
.Hadoop
.The standard Moose package is available in the UFAL environment, just add
. /net/work/projects/perl_repo/admin/bin/setup_platform
to .profile
or .bashrc
or type it in the shell
echo -e "\n#MR Tutorial - Moose" >> ~/.bashrc echo ". /net/work/projects/perl_repo/admin/bin/setup_platform" >> ~/.bashrc
The custom Hadoop package is available in /net/projects/hadoop/perl
, just add
export PERLLIB="$PERLLIB:/net/projects/hadoop/perl/" export PERL5LIB="$PERL5LIB:/net/projects/hadoop/perl"
to .profile
, .bash_profile
, .bashrc
or type it in the shell.
echo -e "\n#MR Tutorial - Hadoop" >> ~/.bashrc echo 'export PERLLIB="$PERLLIB:/net/projects/hadoop/perl/"' >> ~/.bashrc echo 'export PERL5LIB="$PERL5LIB:/net/projects/hadoop/perl"' >> ~/.bashrc
If you are not logged in the UFAL cluster, you will need:
conf/hadoop-env.sh
file and make sure there is valid line export JAVA_HOME=/path/to/your/jdk
hadoop
containing the Perl API and Java extensions.hadoop_prefix
to point to your Hadoop installationMakefile
s contain absolute path to the hadoop
repository – please correct it
When using local Hadoop installation, you must run all jobs either locally in a single thread or start a local cluster and use -jt
for the jobs to use it (see using-a-running-cluster).
Overview | Step 2: Input and output format, testing data. |