Github user JoshRosen commented on a diff in the pull request:
https://github.com/apache/spark/pull/15743#discussion_r86407326
--- Diff: core/src/main/scala/org/apache/spark/ui/jobs/UIData.scala ---
@@ -197,8 +196,32 @@ private[spark] object UIData {
shuffleWriteMetrics: ShuffleWriteMetricsUIData)
case class InputMetricsUIData(bytesRead: Long, recordsRead: Long)
+ object InputMetricsUIData {
+ def apply(metrics: InputMetrics): InputMetricsUIData = {
+ if (metrics.bytesRead == 0 && metrics.recordsRead == 0) {
+ EMPTY
+ } else {
+ new InputMetricsUIData(
+ bytesRead = metrics.bytesRead,
+ recordsRead = metrics.recordsRead)
+ }
+ }
+ val EMPTY = InputMetricsUIData(0, 0)
+ }
case class OutputMetricsUIData(bytesWritten: Long, recordsWritten: Long)
+ object OutputMetricsUIData {
+ def apply(metrics: OutputMetrics): OutputMetricsUIData = {
+ if (metrics.bytesWritten == 0 && metrics.recordsWritten == 0) {
--- End diff --
For OutputMetrics, I'd actually assume the opposite: these metrics are
referring to bytes written to an external system, not bytes written to shuffle,
so the majority of tasks won't have non-zero values for this metric (all but
the last stage in a multi-stage job, for example).
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