“Spark is a general distributed data processing engine built for
speed, ease use, and has become the critical of flexibility”, “It one of
components the big data stack due its ease use, speed, and in to of
flexibility.”, Companies, different industries, have widely adopted in
this scalable data processing system. (Luu. 2021). above In the
references from the book, the first line quote referred speed, of to
ease use, and flexibility. Also, the second line the quote of of
mentioned speed, ease use, and flexibility. And the third line of of
quote told that companies adopt spark because its scalable us of
data processing system. Spark has several advantages when
compared other big data and MapReduce technologies like to
Hadoop and Storm. performan spark runs 100 times faster In ce, in
memory, and times faster disk, than Hadoop. data 10 on In
processing, Sparks performs both batch, real-time, and graph
processing, but Hadoop processes data batches in only. Hadoop’s
MapReduce complex, while Sparks supports user-friendly APIs. is
Apache Spark has its own scheduler, while Hadoop depends on an
external scheduler. Therefore, based the above-stated on
advantages, such Spark are required for big data computing tools as
by companies.
A cluster computing is a set of connected computers (nodes) that
