Josh Rosen created SPARK-19529:
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Summary: TransportClientFactory.createClient() shouldn't call
awaitUninterruptibly()
Key: SPARK-19529
URL: https://issues.apache.org/jira/browse/SPARK-19529
Project: Spark
Issue Type: Bug
Components: Shuffle, Spark Core
Affects Versions: 2.1.0, 2.0.0, 1.6.0
Reporter: Josh Rosen
Assignee: Josh Rosen
In Spark's Netty RPC layer, TransportClientFactory.createClient() calls
awaitUninterruptibly() on a Netty future while waiting for a connection to be
established. This creates problem when a Spark task is interrupted while
blocking in this call (which can happen in the event of a slow connection which
will eventually time out). This has bad impacts on task cancellation when
interruptOnCancel = true.
As an example of the impact of this problem, I experienced significant numbers
of uncancellable "zombie tasks" on a production cluster where several tasks
were blocked trying to connect to a dead shuffle server and then continued
running as zombies after I cancelled the associated Spark stage. The zombie
tasks ran for several minutes with the following stack:
{code}
java.lang.Object.wait(Native Method)
java.lang.Object.wait(Object.java:460)
io.netty.util.concurrent.DefaultPromise.await0(DefaultPromise.java:607)
io.netty.util.concurrent.DefaultPromise.awaitUninterruptibly(DefaultPromise.java:301)
org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:224)
org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:179)
=> holding Monitor(java.lang.Object@1849476028})
org.apache.spark.network.shuffle.ExternalShuffleClient$1.createAndStart(ExternalShuffleClient.java:105)
org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:140)
org.apache.spark.network.shuffle.RetryingBlockFetcher.start(RetryingBlockFetcher.java:120)
org.apache.spark.network.shuffle.ExternalShuffleClient.fetchBlocks(ExternalShuffleClient.java:114)
org.apache.spark.storage.ShuffleBlockFetcherIterator.sendRequest(ShuffleBlockFetcherIterator.scala:169)
org.apache.spark.storage.ShuffleBlockFetcherIterator.fetchUpToMaxBytes(ShuffleBlockFetcherIterator.scala:
350)
org.apache.spark.storage.ShuffleBlockFetcherIterator.initialize(ShuffleBlockFetcherIterator.scala:286)
org.apache.spark.storage.ShuffleBlockFetcherIterator.<init>(ShuffleBlockFetcherIterator.scala:120)
org.apache.spark.shuffle.BlockStoreShuffleReader.read(BlockStoreShuffleReader.scala:45)
org.apache.spark.sql.execution.ShuffledRowRDD.compute(ShuffledRowRDD.scala:169)
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
[...]
{code}
I believe that we can easily fix this by using the
InterruptedException-throwing await() instead.
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