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In Hadoop, Combiner can run 0 1 or many times.
Whether or not the Combiner is invoked depends on the spill (a process in which intermediate data is flushed to disk from memory buffer), and is not guaranteed to run every time.
When map want to merge spill files together to get final map output files, map will check the number of spill (default is 3). If it is > 3, then combiner is called,else not . The property “min.num.spill.for.combine” (default 3) can be configured manually in mapred-site.xml to change this setting.
Follow the link for more detail: Combiner in Hadoop
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If Combiner is specified in MapReduce job, any or zero number of combiners can run.
Whether the combiner is invoked or not depends on the number of spill files generated by the map task.
(Each map task writes it output to a memory buffer, which is 100MB by default. When the contents of buffer reaches threshold(which is 0.8 or 80% by default), a background thread will start to ‘spill’ this contents to the disk.)
If the no. of spill files are atleast 3, then a combiner is run by default. This can be configured by
"min.num.spill.for.combine" property,
which is 3 by default.Follow the link for more detail: Combiner in Hadoop
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The Combiner does not have its own interface and it must implement Reducer interface and reduce() method of combiner will be called on each map output key. The combiner class’s reduce() method must have the same input and output key-value types as the reducer class.
Combiner functions are suitable for producing summary information from a large data set because combiner will replace that set of original map outputs, ideally with fewer records or smaller records.
Hadoop doesn’t guarantee on how many times a combiner function will be called for each map output key. At times, it may not be executed at all, while at times it may be used once, twice, or more times depending on the size and number of output files generated by the mapper for each reducer.
The Reducer class is also used as a Combiner class. Hence the number if combiners will be equal to the number of reducers.
The Combiner class is specified using the below call:
job.setCombinerClass(WcReducer.class);
job.setReducerClass(WcReducer.class);We can see that the Reducer class will be used as a Combiner class.
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Combiner is like mini reducer which tries to reduce the amount the data being transferred from local disk to reducer node for network bandwidth optimization.So it is not always guaranteed that combiner will run.It will run accordiing to requirment.After map phase intermediate output are written to circular buffer(default size is 100 MB) but when it is 80% filled then data is splilled to local disk.When map wants to merge the files then if number of spilled files to be merged is greater than 3 then then the combiner would be executed on top of the “merge” result before writing it to the disk.After merge a single file is written to disk and that file is transferred to reducer .
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