Combiner Implementation and internal working

Question

I want to use a combiner in my MR code say WordCount.

How should I implement it?

What sort of data is being passed to the reducer from the combiner?

It will be great if anyone of you can provide me codes of both Combiner as well as the Reducer.

It will be better if you can explain the way the combiner works

I am new to mapreduce and I am at a learning stage.

Thanks in advance :)

score 2 · Answer 1 · answered Jun 10 '16 at 20:48

the combiner is doing the same work as reducer ,it can implement the reducer interface and over ride it's reduce method.if you use combiner,smaller amount of the network bandwidth is enough to transfer intermediate (o/p of mapper) to reducer.

you can use the same reduce method (belongs to your own reducer) code in combiner reduce method if your application used in reducer is obey both Commutative and Associative.

there is no rule to execute the Combiner even though you write the combiner for your MR(map reduce) application.to execute the combiner for sure the num of spills should be 3 at least.

for ex my mapper output is ,,,,,<34>. with out combiner ,my input to reducer is . with combiner ,i can pass input to reducer is like ,.

you seem to have left out a part of the answer. is it? – Aniruddha Sinha Jun 13 '16 at 04:57 — Aniruddha Sinha, Jun 13 '16 at 04:57

score 1 · Answer 2 · answered Oct 29 '15 at 07:37

Combiner is used in between mapper and reducer to reduce the amount of data transfer between map and reduce phase.

Combiner implementation is similar to reducer implementation. It should implement reduce interface's reduce method. The input and output key value pairs should be similar to that of reducer.

In our driver we can just mention our reducer class as combiner

job.setCombinerClass(MyReducer.class)

Combiners can be used only on functions which are commutative and associative.

For example maximum of numbers

Map 1 output - (23,27, 31) -> Combiner -> 31
Map 2 output - (22,36,33,45) -> Combiner -> 45
Map 3 output - (41,33,15,16) -> Combiner -> 41

Combiner acts on each of the mapper's output.

Combiner output - (31,45,41) ->Reducer -> 45

Amount of data transfer is now reduced which is evident from the example.

score 0 · Accepted Answer · answered Oct 29 '15 at 08:01

A Combiner, also known as a semi-reducer.

The main function of a Combiner is to summarize the map output records with the same key.

The Combiner class is used in between the Map class and the Reduce class to reduce the volume of data transfer between Map and Reduce

Explanation with sample code.

MAP Input:

What do you mean by Object
What do you know about Java
What is Java Virtual Machine
How Java enabled High Performance

MAP output

<What,1> <do,1> <you,1> <mean,1> <by,1> <Object,1>
<What,1> <do,1> <you,1> <know,1> <about,1> <Java,1>
<What,1> <is,1> <Java,1> <Virtual,1> <Machine,1>
<How,1> <Java,1> <enabled,1> <High,1> <Performance,1>

This MAP output will be passed as input to Combiner.

Combiner output

   <What,1,1,1> <do,1,1> <you,1,1> <mean,1> <by,1> <Object,1>
   <know,1> <about,1> <Java,1,1,1>
   <is,1> <Virtual,1> <Machine,1>
   <How,1> <enabled,1> <High,1> <Performance,1>

This combiner output is passed as input to Reducer.

Reducer Output

   <What,3> <do,2> <you,2> <mean,1> <by,1> <Object,1>
   <know,1> <about,1> <Java,3>
   <is,1> <Virtual,1> <Machine,1>
   How,1> <enabled,1> <High,1> <Performance,1>

If you are using java, below code will set Combiner & Reducer to same class, which is ideal.

  job.setJarByClass(WordCount.class);
  job.setMapperClass(TokenizerMapper.class);
  job.setCombinerClass(IntSumReducer.class);
  job.setReducerClass(IntSumReducer.class);

Have a look at working example in java @tutorialspoint

Combiner Implementation and internal working

3 Answers3

Linked

Related