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TaskSet is a collection of independent tasks of a stage (and a stage execution attempt) that are missing (uncomputed), i.e. for which computation results are unavailable (as RDD blocks on BlockManagers on executors).

In other words, a TaskSet represents the missing partitions of a stage that (as tasks) can be run right away based on the data that is already on the cluster, e.g. map output files from previous stages, though they may fail if this data becomes unavailable.

Since the tasks are only the missing tasks, their number does not necessarily have to be the number of all the tasks of a stage. For a brand new stage (that has never been attempted to compute) their numbers are exactly the same.

Once DAGScheduler submits the missing tasks for execution (to the TaskScheduler), the execution of the TaskSet is managed by a TaskSetManager that allows for spark.task.maxFailures.

Creating Instance

TaskSet takes the following to be created:

TaskSet is created when:


id: String

TaskSet is uniquely identified by an id that uses the stageId followed by the stageAttemptId with the comma (.) in-between:


Textual Representation

toString: String

toString follows the pattern:

TaskSet [stageId].[stageAttemptId]

Task Scheduling Prioritization (FIFO Scheduling)

TaskSet is given a priority when created.

The priority is the ID of the earliest-created active job that needs the stage (that is given when DAGScheduler is requested to submit the missing tasks of a stage).

Once submitted for execution, the priority is the priority of the TaskSetManager (which is a Schedulable) that is used for task prioritization (prioritizing scheduling of tasks) in the FIFO scheduling mode.