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courses:mapreduce-tutorial [2012/01/25 22:03]
straka 		courses:mapreduce-tutorial [2012/01/27 00:45]
straka
Line 34: Line 34:
   * [[.:mapreduce-tutorial:Step 13]]: Sorting   * [[.:mapreduce-tutorial:Step 13]]: Sorting
   * [[.:mapreduce-tutorial:Step 14]]: N-gram language model   * [[.:mapreduce-tutorial:Step 14]]: N-gram language model
-  * [[.:mapreduce-tutorial:Step 15]]: K-means algorithm+  * [[.:mapreduce-tutorial:Step 15]]: K-means clustering 
 + 
 +===== Day 2 ===== 
 + 
 +Today we will be using the [[http://hadoop.apache.org/common/docs/r1.0.0/api/index.html|Java API]]. 
 + 
 +=== Environment === 
 +  * [[.:mapreduce-tutorial:Step 21]]: Preparing the environment. 
 +  * [[.:mapreduce-tutorial:Step 22]]: Optional -- Setting Eclipse. 
 + 
 +=== Java Hadoop basics ==== 
 +  * [[.:mapreduce-tutorial:Step 23]]: Predefined formats and types. 
 +  * [[.:mapreduce-tutorial:Step 24]]: Mappers, running Java Hadoop jobs. 
 +  * [[.:mapreduce-tutorial:Step 25]]: Reducers, combiners and partitioners. 
 +  * [[.:mapreduce-tutorial:Step 26]]: Counters, compression. 
 +  * [[.:mapreduce-tutorial:Step 27]]: Reusing Mapper and Reducer code. 
 + 
 +=== Exercises === 
 +  * Is [[.:mapreduce-tutorial:Step 13]], [[.:mapreduce-tutorial:Step 14]] and [[.:mapreduce-tutorial:Step 15]] enough? 
 + 
 +=== Advanced topics === 
 +  * Custom input format -- WholeFile and WholeFileAsPath 
 +  * Custom data type -- Pair<A, B>
  
 ===== Other ===== ===== Other =====
   * [[user:majlis:hadoop|Further information]]   * [[user:majlis:hadoop|Further information]]
  

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