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Hadoop Interview Questions


1)   Define Hadoop?


A> Hadoop is a distributed computing platform which was developed using Java

2)  What Kind of Hardware does hadoop support?

A>Hadoop can run on a dual processor/ dual core machines with 4-8 GB RAM

3) What are the common input formats defined in Hadoop?

A> The common input formats are

                                                    1.     TextInputFormat
                                               2.     KeyValueInputFormat
                                               3.     SequenceFileInputFormat
4)  What is InputSplit ?

A> When hadoop runs job, it splits input files into chunks and assign each split to a mapper for processing which is called InputSplit.

5)  How many InputSplits does Hadoop Framework make?

A> Hadoop will make 5 splits as following:

                                                 1. One split for 64K files
                                                 2. Two splits for 65MB files, and
                                                 3. Two splits for 127MB files

6)  Define the use of RecordReader ?

A> InputSplit is assigned with a work but doesn't know how to access it the record   holder class is totally responsible for loading the data from its source and convert it   into keys pair suitable for reading by the Mapper the RecordReaders instance can be defined by the Input Format

7)  What is JobTracker ?

A>JobTracker is a service within Hadoop which runs MapReduce jobs on the cluster.

8)  Define TaskTracker ?

A>TaskTracker is a node in the cluster that accepts tasks like MapReduce and Shuffle operations from a JobTracker.

9) What is Hadoop Streaming?

A>Hadoop streaming is a utility which allows you to create and run map/reduce job ita generic API that allows programs written in any languages to be used as Hadoop   mapper.

10)What is a combiner?


A> Combiner is a mini-reduce process which operates only on data generated by a   mapper when mapper emits the data, combiner receives it as input and sends the   output to reducer.


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