Apache Spark, the in-memory processing system that’s fast become a centerpiece of modern big data frameworks, has officially released its long-awaited version 2.0.
Aside from some major usability and performance improvements, Spark 2.0’s mission is to become a total solution for streaming and real-time data. This comes as a number of other projects — including others from the Apache Foundation — provide their own ways to boost real-time and in-memory processing.
Easier on top, faster underneath
Most of Spark 2.0’s big changes have been known well in advance, which has made them even more hotly anticipated.