Reference

Apache Spark: Apache Spark is a unified analytics engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

Spark Application: Spark Applications are applications that use the Spark API to perform distributed data processing tasks. Spark Applications can be written in several languages including Java, Python and more. Spark Applications are files such as JAR files that are run within the Spark framework.

Data Flow Application: Data Flow Applications are templates that bundle together a Spark Application and specify a Spark version, default resource sizing and default application parameters.

Data Flow Run: Data Flow Applications can be run many times. Each of these results in a Data Flow Run object. Resource sizes and parameters can be optionally overridden at run time by the user. A Data Flow Run tracks information relevant to the Application's execution, such as statistics and logs.

Spark UI: The Spark UI is included with Apache Spark and is an important tool for debugging and diagnosing Spark applications. You can access the Spark UI for any Data Flow Run, subject to the Run's authorization policies.

Spark Logs: Spark generates log files which are useful for debugging and diagnostics. Each Data Flow Run automatically stores log files which you can access through the Spark UI or API, subject to the Run's authorization policies.