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
WordMean
WordMean.WordMeanMapper	Maps words from line of text into 2 key-value pairs; one key-value pair for counting the word, another for counting its length.
WordMean.WordMeanReducer	Performs integer summation of all the values for each key.
WordMedian
WordMedian.WordMedianMapper	Maps words from line of text into a key-value pair; the length of the word as the key, and 1 as the value.
WordMedian.WordMedianReducer	Performs integer summation of all the values for each key.
WordStandardDeviation
WordStandardDeviation.WordStandardDeviationMapper	Maps words from line of text into 3 key-value pairs; one key-value pair for counting the word, one for counting its length, and one for counting the square of its length.
WordStandardDeviation.WordStandardDeviationReducer	Performs integer summation of all the values for each key.

Package org.apache.hadoop.examples Description

Hadoop example code.