Apache Spark is a highly distributed compute engine, which comes with promises of speed and reliability for the computations. As a framework it's based on Hadoop, but it's further enhanced to perform in memory computations to cater to interactive queries and near real-time stream processing. The parallel processing clustering and in-memory processing offer Spark an edge in terms of performance and reliability. Today Apache Spark is known for its proven salient features:
- Speed and efficiency: While it runs off traditional disk-based HDFS, it has 100x higher speed, because of in-memory computations and savings on disk I/O. It saves the intermediate results in memory, thus saving the overall execution time.
- Extensibility and compatibility: It has a variety of interaction APIs for developers to choose from. It comes out of the box with Java, Scala, and Python APIs.
- Analytics and ML: It provides robust support for all machine learning and graph algorithms. In fact, now it's becoming...