Apache Spark™ is the largest lightening & fast processing engine for analytics approach (hundred times faster than Hadoop), Apache spark contributed from 250 high rank organizations like Netflix, yahoo, eBay, it supports programming language likes Java, Python, Scala, R, SQL, and managed with sophisticated core API. Spark’s engine, process multiple petabytes of data on clusters (group of machines, pools the resources of many machines together) over 8000 nodes, utilizing advanced libraries (SQL queries- streaming data, machine learning and graph processing, the libraries might be combined for more productivities). Apache Spark™ has seen immense growth over the past several years, including its compatibility with Delta Lake. Delta Lake is an open-source storage layer that sits on top of the existing data lake file storage, such as AWS S3, Azure Data Lake Storage, or HDFS. Delta Lake brings reliability, performance, and lifecycle management to data lakes. Spark is a tool for just that, managing and coordinating the execution of tasks on data across a cluster of computers. The cluster of machines that Spark will leverage to execute tasks will be managed by a cluster manager like Spark’s Standalone cluster manager (The cluster manager controls physical machines and allocates resources to Spark Applications), YARN, or Mesos. We then submit Spark Applications to these cluster managers which will grant resources to the application so that we can complete our work, Spark Applications consist of a driver process and a set of executor processes. “Data Bricks company”