Spark Performance Tuning refers to the process of adjusting settings to record for memory, cores, and instances used by the system. This process guarantees that the Spark has a flawless performance and also prevents bottlenecking of resources in Spark.

Sometimes, Spark runs slowly because there are too many concurrent tasks running. The capacity for high concurrency is a beneficial feature, as it provides Spark-native fine-grained sharing. This leads to maximum resource utilization while cutting down query latencies.

Choose the target Spark app based on the job run ID to open the Jobs tab. Incomplete job runs, such as streaming job runs, are listed in Show incomplete applications. The Jobs tab shows a summary of all jobs in the Spark application. To determine any stage or task failures, check the total number of tasks.