Answer / Puneet Deval

In MapReduce, a Partitioner is responsible for distributing data from Input Splits evenly across multiple mappers in a way that balances the workload. This is crucial for ensuring efficient processing and reducing job completion time.nnThe Partitioner takes the intermediate key-value pairs output by the mapper and partitions them based on a partitioning scheme. Common partitioning schemes include RoundRobin (equally distributes data across all mappers) and KeyBasedPartitioning (partitions data based on input keys). The choice of partitioner can significantly impact the performance and scalability of MapReduce jobs.

Can you tell us how many daemon processes run on a hadoop system?

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What is shuffling and sorting in mapreduce?

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Explain the sequence of execution of all the components of MapReduce like a map, reduce, recordReader, split, combiner, partitioner, sort, shuffle.

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what are the basic parameters of a Mapper?

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when do reducers play their role in a mapreduce task?

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Can there be no Reducer?

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Why Hadoop MapReduce?

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What is Reduce only jobs?

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