May 2017
Intermediate to advanced
294 pages
7h 33m
English
Content preview from Apache Spark 2.x Cookbook
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Using compression to improve performance
Data compression involves encoding information using fewer bits than the original representation. Compression has an important role to play in big data technologies. It makes both storage and transport of data more efficient.
When data is compressed, it becomes smaller, so both disk I/O and network I/O become faster. It also saves storage space. Every optimization has a cost, and the cost of compression comes in the form of added CPU cycles to compress and decompress data.
Hadoop needs to split data to put them into blocks, irrespective of whether the data is compressed or not. Only a few compression formats are splittable.
The two most popular compression formats for big data loads are Lempel-Ziv-Oberhumer ...
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