Github user vanzin commented on a diff in the pull request:
https://github.com/apache/spark/pull/8153#discussion_r37003277
--- Diff:
core/src/main/scala/org/apache/spark/deploy/history/FsHistoryProvider.scala ---
@@ -204,13 +204,20 @@ private[history] class FsHistoryProvider(conf:
SparkConf, clock: Clock)
mod1 >= mod2
}
- logInfos.sliding(20, 20).foreach { batch =>
+ val tasks: Iterator[Future[_]] = logInfos.grouped(20).map { batch =>
--- End diff --
Since we're talking about cleaning this up, you could do this also:
logInfos.grouped(20)
.map { batch =>
replayExecutor.submit(new Runnable {
override def run(): Unit = mergeApplicationListing(batch)
})
}
.foreach { task =>
// Wait for all tasks to finish. This makes sure that checkForLogs
is
// not scheduled again while some tasks are already running in the
// replayExecutor.
try {
task.get()
} catch {
case e: InterruptedException =>
throw e
case e: Exception =>
logWarning("Error replaying logs.", e)
}
}
Note I added some missing exception handling, which would cause you to
revert to the old behavior of piling up executions if an error happened.
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