Why is HDFS used for the applications with large data sets, and not for the multiple small files?

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Dec 18, 2018 in Big Data Hadoop by Frankie
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HDFS is more efficient for a large number of data sets, maintained in a single file as compared to the small chunks of data stored in multiple files. As the NameNode performs storage of metadata for the file system in RAM, the amount of memory limits the number of files in HDFS file system. In simple words, more files will generate more metadata, that will, in turn, require more memory (RAM). It is recommended that metadata of a block, file, or directory should take 150 bytes.

answered Dec 18, 2018 by Neha
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