Data Science Training with Apache Spark, an open source cluster computing system, is growing fast. Apache Spark has a growing ecosystem of libraries and framework to enable advanced data analytics. Apache Spark’s rapid success is due to its power and ease-of-use. It is more productive and has faster runtime than the typical MapReduce BigData based analytics. Apache Spark provides in-memory, distributed computing. It has APIs in Java, Scala, Python, and R. The Spark Ecosystem is shown below.
The entire ecosystem is built on top of the core engine. The core enables in-memory computation for speed and its API has support for Java, Scala, Python, and R. Streaming enables processing streams of data in real time.
The reason people are so interested in Apache Spark is it puts the power of Hadoop in the hands of developers. It is easier to set up an Apache Spark cluster than a Hadoop Cluster. It runs faster. And it is a lot easier to program. It puts the promise and power of Big Data and real-time analysis in the hands of the masses.