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--- courses:mapreduce-tutorial:step-10 [2012/01/25 15:46]
straka vytvořeno
+++ courses:mapreduce-tutorial:step-10 [2012/01/25 22:12]
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@@ Line 1: / Line 1: @@
-====== MapReduce Tutorial :  ======
+====== MapReduce Tutorial : Combiners ======
+Sometimes the reduce is a binary operation, which is associative and commutative, e.g. ''+''. In that case it is inefficient to produce all the (key, value) pairs in the mappers and send them through the network.
+Instead, reducer can be executed right after the map, on //some portion// of values belonging to the same key. Only the aggregated results are then sent through the network.
+A Hadoop job can have such locally executed reducer, called a //combiner//. If a combiner is specified, the output of a mapper is processed by a combiner before sending the pairs to reducer. The combiner may be invoked 0, 1 or multiple times, usually when the data are written to disk.
+Typically, the combiner is the same as the reducer of a MR job.
+<file perl>
+package Mapper;
+...
+package Reducer;
+...
+package Main;
+use Hadoop::Runner;
+my $runner = Hadoop::Runner->new(
+  mapper => Mapper->new(),
+  combiner => Reducer->new(), # Specify the combiner.
+  reducer => Reducer->new(),
+  input_format => 'KeyValueTextInputFormat');
+...
+</file>
+===== Exercise =====
+Compare the effect of adding the combiner to a MR job which counts occurrences of words in ''/home/straka/wiki/cs-text-medium'': {{:courses:mapreduce-tutorial:step-5-solution1.txt|wc-without-combiner.pl}} and {{:courses:mapreduce-tutorial:step-10.txt|wc-with-combiner.pl}}.
+How would you explain the results?

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