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--- courses:mapreduce-tutorial:step-8 [2012/01/29 21:04]
straka
+++ courses:mapreduce-tutorial:step-8 [2012/01/31 15:55] (current)
straka
@@ Line 12: / Line 12: @@
 To use multiple reducers, the MR job must be executed by a cluster (even with one computer), not locally. The number of reducers is specified by ''-r'' flag:
-  perl script.pl run [-jt cluster_master | -c cluster_size [-w sec_to_wait]] [-r number_of_reducers]
+  perl script.pl [-jt cluster_master | -c cluster_size [-w sec_to_wait]] [-r number_of_reducers]
 Optimal number of reducers is the same as the number of machines in the cluster, so that all the reducers can run in parallel at the same time.
@@ Line 21: / Line 21: @@
 By default, (key, value) pair is sent to a reducer number //hash(key) modulo number_of_reducers//. This guarantees that for one key, all its values are processed by a unique reducer.
-To override the default behaviour, MR job can specify a //partitioner//. A partitioner is given every (key, value) pair produced by a mapper, it is also given the number of reducers, and outputs the zero-based number of reducer, where this (key, value) pair belongs:
+To override the default behaviour, MR job can specify a //partitioner//. A partitioner is given every (key, value) pair produced by a mapper, it is also given the number of reducers, and outputs the zero-based number of reducer, where this (key, value) pair belongs.
+A partitioner should be provided if
+  * the default partitioner fails to distribute the data between reducers equally, i.e., some of the reducers operate on much more data than others.
+  * you need an explicit control of (key, value) placement. This can happen for example when [[.:step-13|sorting data]].
 <code perl>
-package Partitioner;
+package My::Partitioner;
 use Moose;
 with 'Hadoop::Partitioner';
@@ Line 35: / Line 39: @@
 ...
-package Main;
+package main;
 use Hadoop::Runner;
 my $runner = Hadoop::Runner->new(
   ...
-  partitioner => Partitioner->new(),
+  partitioner => My::Partitioner->new(),
   ...);
 ...
@@ Line 48: / Line 52: @@
 ===== The order of keys during reduce =====
-It is guaranteed that every reducer processes the keys in //ascending order//.
+It is guaranteed that every reducer processes the keys in //ascending lexicographic order//.
 On the other hand, the order of values belonging to one key is undefined.
@@ Line 56: / Line 60: @@
 Run one MR job on '/home/straka/wiki/cs-text-medium', which creates two output files -- one with ascending list of unique article names and the other with an ascending list of unique words. You can download the template {{:courses:mapreduce-tutorial:step-8-exercise.txt|step-8-exercise.pl}}  and execute it.
   wget --no-check-certificate 'https://wiki.ufal.ms.mff.cuni.cz/_media/courses:mapreduce-tutorial:step-8-exercise.txt' -O 'step-8-exercise.pl'
-  rm -rf step-8-out-ex; perl step-8-exercise.pl run /home/straka/wiki/cs-text-medium/ step-8-out-ex
+  # NOW EDIT THE FILE
+  # $EDITOR step-8-exercise.pl
+  rm -rf step-8-out-ex; perl step-8-exercise.pl -c 2 -r 2 /home/straka/wiki/cs-text-medium/ step-8-out-ex
   less step-8-out-ex/part-*
@@ Line 62: / Line 68: @@
 You can also download the solution {{:courses:mapreduce-tutorial:step-8-solution.txt|step-8-solution.pl}} and check the correct output.
   wget --no-check-certificate 'https://wiki.ufal.ms.mff.cuni.cz/_media/courses:mapreduce-tutorial:step-8-solution.txt' -O 'step-8-solution.pl'
-  rm -rf step-8-out-sol; perl step-8-solution.pl run /home/straka/wiki/cs-text-medium/ step-8-out-sol
+  # NOW VIEW THE FILE
+  # $EDITOR step-8-solution.pl
+  rm -rf step-8-out-sol; perl step-8-solution.pl -c 2 -r 2 /home/straka/wiki/cs-text-medium/ step-8-out-sol
   less step-8-out-sol/part-*

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