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Jan 8 in Big Data | Hadoop
Q:

What is the need of MapReduce?

1 Answer

Jan 8
MapReduce is a data processing paradigm in itself. This was one of its kind data processing and has been transformative. While using MapReduce we are moving computation to data which is less costly as compared to when data is moved to the computation.

Before the development of Hadoop MapReduce, the huge volume of data processing was very difficult as hundreds and thousands of processors (CPU) were needed to handle the huge amount of data. Moreover, parallelization and distribution were also not possible with huge data sets. Map reduce makes these things possible and easy on top of that, it also provides I/O scheduling, status, and monitoring of job.
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