Apache Spark is a framework used in cluster computing environments for analyzing big data. This platform became widely popular due to its ease of use and the improved data processing speeds.

Apache Spark is able to distribute a workload across a group of computers in a cluster to more effectively process large sets of data. This open-source engine supports a wide array of programming languages. This includes Java, Scala, Python, and R. Apache Spark being an open-source framework for Bigdata has a various advantage over other big data solutions like Apache Spark is Dynamic in Nature, it supports in-memory Computation of RDDs. It provides a provision of reusability, Fault Tolerance, real-time stream processing and many more.

Key features available in Apache Spark:

• Fault Tolerance
• Dynamic in Nature
• In-Memory Computation in Spark
• Reusability
• Support for multiple Languages
• Advanced Analytics
• Real Time Stream Processing

Note: Refer the Apache Spark text document on Desktop.

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