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Posted to issues@spark.apache.org by "Apache Spark (Jira)" <ji...@apache.org> on 2020/09/04 10:40:00 UTC
[jira] [Assigned] (SPARK-32779) Spark/Hive3 interaction potentially
causes deadlock
[ https://issues.apache.org/jira/browse/SPARK-32779?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-32779:
------------------------------------
Assignee: Apache Spark
> Spark/Hive3 interaction potentially causes deadlock
> ---------------------------------------------------
>
> Key: SPARK-32779
> URL: https://issues.apache.org/jira/browse/SPARK-32779
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.1.0
> Reporter: Bruce Robbins
> Assignee: Apache Spark
> Priority: Major
>
> This is an issue for applications that share a Spark Session across multiple threads.
> sessionCatalog.loadPartition (after checking that the table exists) grabs locks in this order:
> - HiveExternalCatalog
> - HiveSessionCatalog (in Shim_v3_0)
> Other operations (e.g., sessionCatalog.tableExists), grab locks in this order:
> - HiveSessionCatalog
> - HiveExternalCatalog
> [This|https://github.com/apache/spark/blob/ad6b887541bf90cc3ea830a1a3322b71ccdd80ee/sql/hive/src/main/scala/org/apache/spark/sql/hive/client/HiveShim.scala#L1332] appears to be the culprit. Maybe db name should be defaulted _before_ the call to HiveClient so that Shim_v3_0 doesn't have to call back into SessionCatalog. Or possibly this is not needed at all, since loadPartition in Shim_v2_1 doesn't worry about the default db name, but that might be because of differences between Hive client libraries.
> Reproduction case:
> - You need to have a running Hive 3.x HMS instance and the appropriate hive-site.xml for your Spark instance
> - Adjust your spark.sql.hive.metastore.version accordingly
> - It might take more than one try to hit the deadlock
> Launch Spark:
> {noformat}
> bin/spark-shell --conf "spark.sql.hive.metastore.jars=${HIVE_HOME}/lib/*" --conf spark.sql.hive.metastore.version=3.1
> {noformat}
> Then use the following code:
> {noformat}
> import scala.collection.mutable.ArrayBuffer
> import scala.util.Random
> val tableCount = 4
> for (i <- 0 until tableCount) {
> val tableName = s"partitioned${i+1}"
> sql(s"drop table if exists $tableName")
> sql(s"create table $tableName (a bigint) partitioned by (b bigint) stored as orc")
> }
> val threads = new ArrayBuffer[Thread]
> for (i <- 0 until tableCount) {
> threads.append(new Thread( new Runnable {
> override def run: Unit = {
> val tableName = s"partitioned${i + 1}"
> val rand = Random
> val df = spark.range(0, 20000).toDF("a")
> val location = s"/tmp/${rand.nextLong.abs}"
> df.write.mode("overwrite").orc(location)
> sql(
> s"""
> LOAD DATA LOCAL INPATH '$location' INTO TABLE $tableName partition (b=$i)""")
> }
> }, s"worker$i"))
> threads(i).start()
> }
> for (i <- 0 until tableCount) {
> println(s"Joining with thread $i")
> threads(i).join()
> }
> println("All done")
> {noformat}
> The job often gets stuck after one or two "Joining..." lines.
> {{kill -3}} shows something like this:
> {noformat}
> Found one Java-level deadlock:
> =============================
> "worker3":
> waiting to lock monitor 0x00007fdc3cde6798 (object 0x0000000784d98ac8, a org.apache.spark.sql.hive.HiveSessionCatalog),
> which is held by "worker0"
> "worker0":
> waiting to lock monitor 0x00007fdc441d1b88 (object 0x00000007861d1208, a org.apache.spark.sql.hive.HiveExternalCatalog),
> which is held by "worker3"
> {noformat}
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