Abstract
Apache Spark programming framework provides an effective and vigorous open-source solution for Big data testing and management. It offers a rich set of big data applications through a programming interface. Testing procedures deliver optimum solutions to complex business problems like analyzing large data volumes. A typical test engineer demands manual to automatic testing which assists the testing strategy with minimal effort. Big data testing means, verification, and validation of data while storing and processing it. This research paper demonstrates the challenges with new high-performance analytics for simpler and faster testing processing of relevant data. It enables, timely and accurate insights using Big data testing predict analytics and can manage large quantities of Structured, Semi-structured, and Unstructured data forms with spark analysis. These methods are evaluated using Extract, Transformation, Loading, and Apache spark procedures. The proposed Big data testing method has statistically outperformed conventional procedures.