buska88 opened a new pull request, #47949:
URL: https://github.com/apache/spark/pull/47949
… lay on same host
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### What changes were proposed in this pull request?
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Modify ExecutorAllocationManager calculates maxNeeded logic.If remaining
executors on a same host and pending speculativeTasks exists and will not
execute addExecutor later, exclude current host, makes maxNeeded equal
numExecutorsTarget + 1 to ensure addExecutor will execute later.Then the
speculative task will launch and start.
Just run the follow job on a yarn cluster with one host and the bug will
report.
`object SpecHangJob {
def main(args: Array[String]): Unit = {
val spark =
SparkSession.builder.appName("rss_test").enableHiveSupport().getOrCreate
val sc = spark.sparkContext
val conf = sc.getConf
val taskNum = conf.getInt("spark.test.parallelism", 3)
val seq = (0 until taskNum).toList
sc.parallelize(seq, taskNum).map(
i => {
if (i == 0) {
try {
Thread.sleep(1000 * 60 * 30)
} catch {
case exception: Exception => println(exception.getMessage)
}
} else {
try {
Thread.sleep(1000 * 30)
} catch {
case e: Exception => println(e.getMessage)
}
}
"haha"
}
).collect()}}
`
### Why are the changes needed?
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Because if the host has problem and tasks on it keep not finished, in this
case speculative task will not start any more, make job run time longer than
expect.
### Does this PR introduce _any_ user-facing change?
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No
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By adding a unit test mocking remaining executors lay on same host.And
feature makes speculative task start
### Was this patch authored or co-authored using generative AI tooling?
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No
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