Package org.apache.hadoop.examples

Hadoop example code.

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          Description

Class Summary
AggregateWordCount This is an example Aggregated Hadoop Map/Reduce application.
AggregateWordCount.WordCountPlugInClass  
AggregateWordHistogram This is an example Aggregated Hadoop Map/Reduce application.
AggregateWordHistogram.AggregateWordHistogramPlugin  
BaileyBorweinPlouffe A map/reduce program that uses Bailey-Borwein-Plouffe to compute exact digits of Pi.
BaileyBorweinPlouffe.BbpInputFormat Input format for the BaileyBorweinPlouffe.BbpMapper.
BaileyBorweinPlouffe.BbpMapper Mapper class computing digits of Pi.
BaileyBorweinPlouffe.BbpReducer Reducer for concatenating map outputs.
BaileyBorweinPlouffe.BbpSplit Input split for the BaileyBorweinPlouffe.BbpInputFormat.
DBCountPageView This is a demonstrative program, which uses DBInputFormat for reading the input data from a database, and DBOutputFormat for writing the data to the database.
ExampleDriver A description of an example program based on its class and a human-readable description.
Grep  
Join Given a set of sorted datasets keyed with the same class and yielding equal partitions, it is possible to effect a join of those datasets prior to the map.
MultiFileWordCount MultiFileWordCount is an example to demonstrate the usage of MultiFileInputFormat.
MultiFileWordCount.CombineFileLineRecordReader RecordReader is responsible from extracting records from a chunk of the CombineFileSplit.
MultiFileWordCount.MapClass This Mapper is similar to the one in MultiFileWordCount.MapClass.
MultiFileWordCount.MyInputFormat To use CombineFileInputFormat, one should extend it, to return a (custom) RecordReader.
MultiFileWordCount.WordOffset This record keeps <filename,offset> pairs.
QuasiMonteCarlo A map/reduce program that estimates the value of Pi using a quasi-Monte Carlo (qMC) method.
QuasiMonteCarlo.QmcMapper Mapper class for Pi estimation.
QuasiMonteCarlo.QmcReducer Reducer class for Pi estimation.
RandomTextWriter This program uses map/reduce to just run a distributed job where there is no interaction between the tasks and each task writes a large unsorted random sequence of words.
RandomWriter This program uses map/reduce to just run a distributed job where there is no interaction between the tasks and each task write a large unsorted random binary sequence file of BytesWritable.
SecondarySort This is an example Hadoop Map/Reduce application.
SecondarySort.FirstGroupingComparator Compare only the first part of the pair, so that reduce is called once for each value of the first part.
SecondarySort.FirstPartitioner Partition based on the first part of the pair.
SecondarySort.IntPair Define a pair of integers that are writable.
SecondarySort.IntPair.Comparator A Comparator that compares serialized IntPair.
SecondarySort.MapClass Read two integers from each line and generate a key, value pair as ((left, right), right).
SecondarySort.Reduce A reducer class that just emits the sum of the input values.
Sort<K,V> This is the trivial map/reduce program that does absolutely nothing other than use the framework to fragment and sort the input values.
WordCount  
WordCount.IntSumReducer  
WordCount.TokenizerMapper  
 

Package org.apache.hadoop.examples Description

Hadoop example code.



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