Map Reduce: An Effective and Flexible Data Processing Tool

MapReduce is a data processing and generating tool which is used for large data sets. This programming model is very effectively used to create a system to simplify the construction of inverted index which is used for handling the search results in Google. Apart from this, Map Reduce technology has been used for several other programs that include the algorithm for large-scale graph processing, data processing, statistical data interpretation and machine learning. Many organizations outside Google has also used this Map reduce technology to their benefit. It is a technology which can be easily used by the programmers with no experience of parallel and distributed systems. Usually, a normal MapReduce computation has the capacity to process many terabytes of data on several machines, close to thousands.

MapReduce is a data processing tool which is efficient enough to parallelize and executes automatically all the programs which are running on the large cluster of machines. In the process, the runtime system is the one which takes care of all the details involved in the execution that includes partitioning of the input data, scheduling the execution of programs running across the network, tackling machine failures, and managing the inter-machine communication. In parallel database systems this data processing tool is extensively used. Here, the query language created is used to express the computations which are supported by MapReduce.

Several misconceptions are associated with this technology which has put this into scanner. It has been believed that Map Reduce is incapable of using indices that suggests a full scan of all input data in the system; it involves the use of inefficient textual data formats; and its input results and output results are always simple files in a file system. But due to its many advantages like this tool is independent of storage systems; it facilitates the processing of data without loading it into the database; and it processes the complex transformations easily as compared to the SQL systems; which has made it more popular than the other data processing tools.

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