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courses:mapreduce-tutorial [2012/01/25 12:19]
straka
courses:mapreduce-tutorial [2012/01/25 15:46]
straka
Line 22: Line 22:
   * [[.:mapreduce-tutorial:Step 7]]: Dynamic Hadoop cluster for several computations.   * [[.:mapreduce-tutorial:Step 7]]: Dynamic Hadoop cluster for several computations.
  
-**From now on, run all examples using a one-machine cluster. Running the scripts locally without any cluster has several disadvantages, most notably having only one reducer per job.**+From now on, it is best to run MR jobs using a one-machine cluster. Running the scripts locally without any cluster has several disadvantages, most notably having only one reducer per job.
  
 === MapReduce extended === === MapReduce extended ===
-  * [[.:mapreduce-tutorial:Step 8]]: Multiple reducers and partitioning. +  * [[.:mapreduce-tutorial:Step 8]]: Multiple mappers, reducers and partitioning. 
-Mappers, splits +  * [[.:mapreduce-tutorial:Step 9]]: Hadoop properties. 
-Hadoop properties +  * [[.:mapreduce-tutorial:Step 10]]: Properties of reducerscombiners. 
-Combiners +  * [[.:mapreduce-tutorial:Step 11]]: Initialization and cleanup of MR tasks. 
-setup, cleanup, perl inplace +  * [[.:mapreduce-tutorial:Step 12]]: Additional output from mappers and reducers.
-Work dir+
  
-N-grams +=== Advanced MapReduce exercises === 
-K-means and Iterations+  * [[.:mapreduce-tutorial:Step 13]]: Sorting 
 +  * [[.:mapreduce-tutorial:Step 14]]: N-gram language model 
 +  * [[.:mapreduce-tutorial:Step 15]]: K-means algorithm
  
 ===== Other ===== ===== Other =====
   * [[user:majlis:hadoop|Further information]]   * [[user:majlis:hadoop|Further information]]
  

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