Spark gives a SQL interface for a NoSQL Cassandra database that is running ad hoc tasks, such as generating business reports on the fly, data analysis, debugging, and finding data patterns. This chapter provided a brief overview of the Spark architecture, which stands on top among other sets of available tools; it offers ease of installation and a huge community, as well as backing up on Hadoop for data warehousing. It also discusses different ways of installation, along with a custom all-in-one Docker image, which has Apache Cassandra, a monitoring stack, and Spark including PySpark, SparkR, and Jupyter with their dependencies. The Docker image has several flags that can be enabled based on the use case or toolset to test locally along with their configurations.
Having a web UI is very helpful for debugging long-running tasks along with resources being available and allocated...