cloud-fan commented on a change in pull request #26624:
URL: https://github.com/apache/spark/pull/26624#discussion_r420630835
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File path: core/src/main/scala/org/apache/spark/util/ThreadUtils.scala
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@@ -157,23 +259,23 @@ private[spark] object ThreadUtils {
*/
def newDaemonFixedThreadPool(nThreads: Int, prefix: String):
ThreadPoolExecutor = {
val threadFactory = namedThreadFactory(prefix)
- Executors.newFixedThreadPool(nThreads,
threadFactory).asInstanceOf[ThreadPoolExecutor]
+ MDCAwareThreadPoolExecutor.newFixedThreadPool(nThreads, threadFactory)
Review comment:
I only find one executor use case: `ContinuousCoalesceRDD`, which is for
continuous streaming. But the runnable submitted to the thread pool does not
have logging.
I checked some other methods in `ThreadUtils` but couldn't find executor
usages that need logging.
What's your target use case? Usually a Spark task takes one CPU core, so
it's very rare to use a thread pool within a Spark task,
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