Apache Spark is an open-source cluster computing framework. It comes with programming interfaces for entire clusters. With SQL, machine learning, real-time data streaming, graph processing, and other features, this leads to incredibly rapid big data processing. The bedrock of Apache Spark is Spark Core, which is built on RDD abstraction. DataFrames are used by Spark SQL to accommodate structured and semi-structured data. Apache Spark is also quite versatile, and it can run on a standalone cluster mode or Hadoop YARN, EC2, Mesos, Kubernetes, etc. You can also access data through non-relational databases such as Apache Cassandra, Apache HBase, Apache Hive, and others like the Hadoop Distributed File System. Apache Spark can also combine historical and live data to create real-time judgments, ideal for applications like predictive analytics, fraud detection, sentiment analysis, etc.
Hop onto the repository here: https://github.com/apache/spark