You can do it.
If you understand how Hadoop works, then you should realized that it's
a Python question and a Linux question.
Pass the native files via -files and setup environment variables
via mapred.child.env.
I've done a similar thing with Ruby. For Ruby, the environment
variables are PATH, GEM_HOME, GEM_PATH, LD_LIBRARY_PATH and RUBYLIB.
-D
mapred.child.env=PATH=ruby-1.9.2-p180/bin:'$PATH',GEM_HOME=ruby-1.9.2-p180,LD_LIBRARY_PATH=ruby-1.9.2-p180/lib,GEM_PATH=ruby-1.9.2-p180,RUBYLIB=ruby-1.9.2-p180/lib/ruby/site_ruby/1.9.1:ruby-1.9.2-p180/lib/ruby/site_ruby/1.9.1/x86_64-linux:ruby-1.9.2-p180/lib/ruby/site_ruby:ruby-1.9.2-p180/lib/ruby/vendor_ruby/1.9.1:ruby-1.9.2-p180/lib/ruby/vendor_ruby/1.9.1/x86_64-linux:ruby-1.9.2-p180/lib/ruby/vendor_ruby:ruby-1.9.2-p180/lib/ruby/1.9.1:ruby-1.9.2-p180/lib/ruby/1.9.1/x86_64-linux
\
-files ruby-1.9.2-p180 \
On Thu, Sep 1, 2011 at 8:01 PM, Xiong Deng dbigb...@gmail.com wrote:
Hi,
I have successfully installed scipy on my Python 2.7 on my local Linux, and
I want to pack my Python2.7 (with scipy) onto Hadoop and run my Python
MapReduce scripts, like this:
20 ${HADOOP_HOME}/bin/hadoop streaming \$
21 -input ${input} \$
22 -output ${output} \$
23 -mapper python27/bin/python27.sh rp_extractMap.py \$
24 -reducer python27/bin/python27.sh rp_extractReduce.py \$
25 -partitioner org.apache.hadoop.mapred.lib.KeyFieldBasedPartitioner
\$
26 -file rp_extractMap.py \$
27 -file rp_extractReduce.py \$
28 -file shitu_conf.py \$
29 -cacheArchive /share/python27.tar.gz#python27 \$
30 -outputformat org.apache.hadoop.mapred.TextOutputFormat \$
31 -inputformat org.apache.hadoop.mapred.CombineTextInputFormat \$
32 -jobconf mapred.max.split.size=51200 \$
33 -jobconf mapred.job.name=[reserve_price][rp_extract] \$
34 -jobconf mapred.job.priority=HIGH \$
35 -jobconf mapred.job.map.capacity=1000 \$
36 -jobconf mapred.job.reduce.capacity=200 \$
37 -jobconf mapred.reduce.tasks=200$
38 -jobconf num.key.fields.for.partition=2$
I have to do this, because the Hadoop server installed its own python of
very low version which may not support some of my python scripts, and I do
not have privilege to install scipy lib on that server. So,I have to use the
-cacheArchieve command to include my own python2.7 with scipy
But, I find out that some of the .so in scipy are linked to other dynamic
libs outside Python2.7.. For example
$ ldd
~/local/python-2.7.2/lib/python2.7/site-packages/scipy/linalg/flapack.so
liblapack.so = /usr/local/atlas/lib/liblapack.so
(0x002a956fd000)
libatlas.so = /usr/local/atlas/lib/libatlas.so (0x002a95df3000)
libgfortran.so.3 =
/home/work/local/gcc-4.6.1/lib64/libgfortran.so.3 (0x002a9668d000)
libm.so.6 = /lib64/tls/libm.so.6 (0x002a968b6000)
libgcc_s.so.1 = /home/work/local/gcc-4.6.1/lib64/libgcc_s.so.1
(0x002a96a3c000)
libquadmath.so.0 =
/home/work/local/gcc-4.6.1/lib64/libquadmath.so.0 (0x002a96b51000)
libc.so.6 = /lib64/tls/libc.so.6 (0x002a96c87000)
libpthread.so.0 = /lib64/tls/libpthread.so.0 (0x002a96ebb000)
/lib64/ld-linux-x86-64.so.2 (0x00552000)
So, my question is: how can I include this libs? Should I search for all the
linked .so and .a under my local linux and pack them together with
Python2.7??? If yes, How can I get a full list of the libs needed and How
can make the packed Python2.7 know where to find the new libs??
Thanks
Xiong
