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courses:mapreduce-tutorial:step-3 [2012/01/24 19:14]
straka
courses:mapreduce-tutorial:step-3 [2012/01/25 21:33]
straka
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 ====== MapReduce Tutorial : Basic mapper ====== ====== MapReduce Tutorial : Basic mapper ======
  
-The simplest MR job consists of a mapper only.  The input data is divided in several parts, every processed by an independent mapper, and the results are collected in one directory, one file per mapper.+The simplest Hadoop job consists of a mapper only.  The input data is divided in several parts, every processed by an independent mapper, and the results are collected in one directory, one file per mapper.
  
-===== Example perl mapper =====+The Hadoop framework handles
  
-<code perl>+===== Example Perl mapper ===== 
 + 
 +<file perl mapper.pl>
 #!/usr/bin/perl #!/usr/bin/perl
  
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 $runner->run(); $runner->run();
-</code>+</file>
  
 The values ''input_format'', ''output_format'' and ''output_compression'' could be left out, because they are all set to their default value. The values ''input_format'', ''output_format'' and ''output_compression'' could be left out, because they are all set to their default value.
  
-Resulting script can be executed using +Resulting script can be executed locally (not distributed) using
   perl script.pl run input_directory output_directory   perl script.pl run input_directory output_directory
- 
 All files in input_directory are processes. The output_directory must not exist. All files in input_directory are processes. The output_directory must not exist.
 +
 +===== Exercise =====
 +
 +To check that your Hadoop environment works, try running a MR job on ''/home/straka/wiki/cs-text'', which outputs only articles with names beginning with a (ignoring the case).
 +
 +{{.:step-3-solution.txt|Solution.pl}}

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