Answer / Nitin Kumar Sinha

Shuffling is the process of moving intermediate data from mappers to reducers. Sorting happens during this phase where data is sorted by key. This allows reducers to process data efficiently.

Mention what are the main configuration parameters that user need to specify to run mapreduce job?

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What is mapper in map reduce?

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When is the reducers are started in a MapReduce job?

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What is the need of MapReduce?

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What is the sequence of execution of Mapper, Combiner, and Partitioner in MapReduce?

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How does Hadoop Classpath plays a vital role in stopping or starting in Hadoop daemons?

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What are the advantages of using map side join in mapreduce?

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In Map Reduce why map write output to Local Disk instead of HDFS?

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What is Output Format in MapReduce?

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What combiners are and when you should utilize a combiner in a map reduce job?

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What is the problem with the small file in Hadoop?

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What is the need of key-value pair to process the data in MapReduce?

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