May 2017
Beginner to intermediate
596 pages
15h 2m
English
In previous part of the book, we did touch this aspect of compression in brief. Since this is an important aspect for Data Lake, this is revisited in a bit more detail here.
While storing data, to optimize storage (reduce space) and to utilize network bandwidth, often compression methodologies are employed. Data lake deals with massive amount of data and data compression is quite significant. This aspect definitely makes the Data Lake more scalable and brings in lot of flexibility.
In many scenarios existing in an enterprise, the data commonly ingested into Data Lake are in different text formats (CSV, TSV, XML, JSON and so on). These are human readable but occupies huge amount of storage space. In Data Lake, however ...