Apache Hadoop is a distributed open-source storage that is used when dealing with enormous data. This helps us to use the ability to handle big data in parallel processing.
Benefits of Adopting Apache Hadoop
Hadoop clusters operate and maintain multiple copies to ensure data consistency. Using Hadoop, a total of 4500 machines can be connected.
The entire process is broken into pieces and runs in parallel, thus saving time and using Hadoop to process a total of 25 Petabyte (1 PB = 1000 TB) files.
Hadoop constructs datasets at every stage in case of a long request. It also conducts the query on multiple datasets to prevent loss of process in the event of individual failure. These steps make Hadoop processing more effective and precise.
Hadoop queries are as comfortable as coding in any language. To allow parallel processing, we need to change the way we think about creating a request.
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