This methods fires at the end of each Task and collects metrics flattened into the taskMetricsData ListBuffer Note all times are in ms, cpu time and shufflewrite are originally in nanosec, thus in the code are divided by 1e6
This methods fires at the end of each Task and collects metrics flattened into the taskMetricsData ListBuffer Note all times are in ms, cpu time and shufflewrite are originally in nanosec, thus in the code are divided by 1e6
TaskInfoRecorderListener: this listener gathers metrics with Task execution granularity It is based on the Spark Listener interface Task metrics are stored in memory and use to produce a report that aggregates resource consumption they can also be consumed "raw" (transformed into a DataFrame and/or saved to a file)