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From Apache Wiki <wikidi...@apache.org>
Subject [Hadoop Wiki] Trivial Update of "HadoopMapReduce" by AndreyKurdyumov
Date Tue, 10 Jun 2008 23:57:47 GMT
Dear Wiki user,

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The following page has been changed by AndreyKurdyumov:
http://wiki.apache.org/hadoop/HadoopMapReduce

The comment on the change is:
Fixed links broken due to src structure refactoring 3 days ago

------------------------------------------------------------------------------
  writer per configured reduce task. It will then proceed to read
  its !FileSplit using the [http://hadoop.apache.org/core/docs/current/api/org/apache/hadoop/mapred/RecordReader.html
RecordReader] it gets from the specified
  [http://hadoop.apache.org/core/docs/current/api/org/apache/hadoop/mapred/InputFormat.html
InputFormat]. !InputFormat parses the input and generates
- key-value pairs. !InputFormat must also handle records that may be split on the !FileSplit
boundary. For example [http://svn.apache.org/viewcvs.cgi/hadoop/core/trunk/src/java/org/apache/hadoop/mapred/TextInputFormat.java?view=markup
TextInputFormat] will read the last line of the !FileSplit past the split boundary and, when
reading other than the first !FileSplit, !TextInputFormat ignores the content up to the first
newline.
+ key-value pairs. !InputFormat must also handle records that may be split on the !FileSplit
boundary. For example [http://svn.apache.org/viewcvs.cgi/hadoop/core/trunk/src/mapred/org/apache/hadoop/mapred/TextInputFormat.java?view=markup
TextInputFormat] will read the last line of the !FileSplit past the split boundary and, when
reading other than the first !FileSplit, !TextInputFormat ignores the content up to the first
newline.
  
  It is not necessary for the !InputFormat to
  generate both meaningful keys ''and'' values. For example the
@@ -42, +42 @@

  When Mapper output is collected it is partitioned, which means
  that it will be written to the output specified by the
  [http://hadoop.apache.org/core/docs/current/api/org/apache/hadoop/mapred/Partitioner.html
Partitioner]. The default [http://hadoop.apache.org/core/docs/current/api/org/apache/hadoop/mapred/lib/HashPartitioner.html
HashPartitioner] uses the
- hashcode function on the key's class (which means that this hashcode function must be good
in order to achieve an even workload across the reduce tasks).  See [http://svn.apache.org/viewcvs.cgi/hadoop/core/trunk/src/java/org/apache/hadoop/mapred/MapTask.java?view=markup
 MapTask] for details.
+ hashcode function on the key's class (which means that this hashcode function must be good
in order to achieve an even workload across the reduce tasks).  See [http://svn.apache.org/viewcvs.cgi/hadoop/core/trunk/src/mapred/org/apache/hadoop/mapred/MapTask.java?view=markup
 MapTask] for details.
  
  N input files will generate M map tasks to be run and each map
  task will generate as many output files as there are reduce
@@ -80, +80 @@

  == Reduce ==
  When a reduce task starts, its input is scattered in many files across all the nodes where
map tasks ran. If run in
  distributed mode these need to be first copied to the local
- filesystem in a ''copy phase'' (see [http://svn.apache.org/viewcvs.cgi/hadoop/core/trunk/src/java/org/apache/hadoop/mapred/ReduceTaskRunner.java?view=markup
ReduceTaskRunner]).
+ filesystem in a ''copy phase'' (see [https://svn.apache.org/viewcvs.cgi/hadoop/core/trunk/src/mapred/org/apache/hadoop/mapred/ReduceTaskRunner.java?view=markup
ReduceTaskRunner]).
  
  Once all the data is available locally it is appended to one
  file in an ''append phase''. The file is then merge sorted so that the key-value pairs for
  a given key are contiguous (''sort phase''). This makes the actual reduce operation simple:
the file is
  read sequentially and the values are passed to the reduce method
  with an iterator reading the input file until the next key
- value is encountered. See [http://svn.apache.org/viewcvs.cgi/hadoop/core/trunk/src/java/org/apache/hadoop/mapred/ReduceTask.java?view=markup
 ReduceTask] for details.
+ value is encountered. See [http://svn.apache.org/viewcvs.cgi/hadoop/core/trunk/src/mapred/org/apache/hadoop/mapred/ReduceTask.java?view=markup
 ReduceTask] for details.
  
  At the end, the output will consist of one output file per executed reduce
  task. The format of the files can be specified with

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