Timothy C. Arland created SPARK-39513:
-----------------------------------------
Summary: HiveMetastore serializable exception with Spark 3.3.0
Key: SPARK-39513
URL: https://issues.apache.org/jira/browse/SPARK-39513
Project: Spark
Issue Type: Bug
Components: Kubernetes
Affects Versions: 3.3.0
Reporter: Timothy C. Arland
Running this command-line with provided configuration works fine in Spark
3.2.1:
${SPARK_HOME}/bin/spark-shell \
> --master k8s://https://10.96.0.1:443 \
> --deploy-mode client \
> --name spark-shell --conf spark.scheduler.minRegisteredResourcesRatio=1
> --conf spark.executor.instances=8 --conf spark.executor.cores=1 --conf
> spark.executor.limit.cores=2 --conf spark.executor.memory=4g --conf
> spark.driver.cores=1 --conf spark.driver.limit.cores=1 --conf
> spark.driver.memory=1g --conf
> spark.kubernetes.container.image=<myimagerepo>/spark:v3.2.1-thebe-2206.10
> --conf spark.kubernetes.driver.pod.name=spark-shell-driver-jglxk --conf
> spark.kubernetes.namespace=spark --conf
> spark.kubernetes.authenticate.driver.serviceAccountName=spark --conf
> spark.hadoop.fs.s3a.endpoint=http://10.96.45.95:80 --conf
> spark.hadoop.fs.s3a.access.key=<myaccesskey> --conf
> spark.hadoop.fs.s3a.secret.key=<mysecretkey> --conf
> spark.hadoop.fs.s3a.path.style.access=true --conf
> spark.hadoop.fs.s3a.block.size=512M --conf
> spark.hadoop.fs.s3a.committer.magic.enabled=false --conf
> spark.hadoop.fs.s3a.committer.name=directory --conf
> spark.hadoop.fs.s3a.committer.staging.abort.pending.uploads=true --conf
> spark.hadoop.fs.s3a.committer.staging.conflict-mode=append --conf
> spark.hadoop.fs.s3a.committer.staging.tmp.path=/tmp/staging --conf
> spark.hadoop.fs.s3a.committer.staging.unique-filenames=true --conf
> spark.hadoop.fs.s3a.committer.threads=2048 --conf
> spark.hadoop.fs.s3a.connection.establish.timeout=5000 --conf
> spark.hadoop.fs.s3a.connection.maximum=8192 --conf
> spark.hadoop.fs.s3a.connection.ssl.enabled=false --conf
> spark.hadoop.fs.s3a.connection.timeout=200000 --conf
> spark.hadoop.fs.s3a.fast.upload.active.blocks=2048 --conf
> spark.hadoop.fs.s3a.fast.upload.buffer=disk --conf
> spark.hadoop.fs.s3a.fast.upload=true --conf
> spark.hadoop.fs.s3a.impl=org.apache.hadoop.fs.s3a.S3AFileSystem --conf
> spark.hadoop.fs.s3a.max.total.tasks=2048 --conf
> spark.hadoop.fs.s3a.multipart.size=512M --conf
> spark.hadoop.fs.s3a.multipart.threshold=512M --conf
> spark.hadoop.fs.s3a.socket.recv.buffer=65536 --conf
> spark.hadoop.fs.s3a.socket.send.buffer=65536 --conf
> spark.hadoop.fs.s3a.threads.max=2048 --conf
> spark.eventLog.dir=s3a://spark/spark-logs --conf spark.eventLog.enabled=true
> --conf spark.hadoop.metastore.catalog.default=hive --conf
> spark.sql.warehouse.dir=s3a//hive/warehouse --conf
> spark.sql.hive.metastore.dir=s3a://hive/warehouse --conf
> spark.sql.hive.metastore.version=3.1.2 --conf
> spark.sql.hive.metastore.jars=path --conf
> spark.sql.hive.metastore.jars.path=file:///opt/hive/lib/*.jar --conf
> spark.hadoop.hive.metastore.uris=thrift://hive-metastore.trino.svc.cluster.local:9083
With Spark 3.3.0 image, this same command yields the following exception when
running spark.catalog functions:
{{2022-06-19T00:57:13,687 INFO [main]
org.apache.hadoop.hive.metastore.HiveMetaStoreClient - Opened a connection to
metastore, current connections: 1 2022-06-19T00:57:13,701 INFO [main]
org.apache.hadoop.hive.metastore.HiveMetaStoreClient - Connected to metastore.
}}
{{2022-06-19T00:57:13,701 INFO [main]
org.apache.hadoop.hive.metastore.RetryingMetaStoreClient -
RetryingMetaStoreClient proxy=class org.apache.hadoop.hive.ql.}}
{{metadata.SessionHiveMetaStoreClient ugi=root (auth:SIMPLE) retries=1 delay=1
lifetime=0
}}
{{java.lang.NoClassDefFoundError: scala/Serializable
}}
{{ at java.base/java.lang.ClassLoader.defineClass1(Native Method)
}}
{{ at java.base/java.lang.ClassLoader.defineClass(Unknown Source)
}}
{{ at java.base/java.security.SecureClassLoader.defineClass(Unknown Source)
}}
{{ at java.base/jdk.internal.loader.BuiltinClassLoader.defineClass(Unknown
Source)
}}
{{ at
java.base/jdk.internal.loader.BuiltinClassLoader.findClassOnClassPathOrNull(Unknown
Source) }}
{{ at java.base/jdk.internal.loader.BuiltinClassLoader.loadClassOrNull(Unknown
Source) }}
{{ at java.base/jdk.internal.loader.BuiltinClassLoader.loadClass(Unknown
Source) }}
{{ at
java.base/jdk.internal.loader.ClassLoaders$AppClassLoader.loadClass(Unknown
Source) }}
{{ at java.base/java.lang.ClassLoader.loadClass(Unknown Source)
}}
{{ at
org.apache.spark.sql.catalyst.analysis.RewriteDeleteFromTable$.apply(RewriteDeleteFromTable.scala:39)
}}
{{ at
org.apache.spark.sql.catalyst.analysis.RewriteDeleteFromTable$.apply(RewriteDeleteFromTable.scala:37)
}}
{{ at
org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$2(RuleExecutor.scala:211)
}}
{{ at scala.collection.LinearSeqOps.foldLeft(LinearSeq.scala:169)
}}
{{ at scala.collection.LinearSeqOps.foldLeft$(LinearSeq.scala:165)
}}
{{ at scala.collection.immutable.List.foldLeft(List.scala:79)
}}
{{ at
org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1(RuleExecutor.scala:208)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1$adapted(RuleExecutor.scala:200)
}}
{{ at scala.collection.immutable.List.foreach(List.scala:333)
}}
{{ at
org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:200)
}}
{{ at
org.apache.spark.sql.catalyst.analysis.Analyzer.org$apache$spark$sql$catalyst$analysis$Analyzer$$executeSameContext(Analyzer.scala:227)
}}
{{ at
org.apache.spark.sql.catalyst.analysis.Analyzer.$anonfun$execute$1(Analyzer.scala:223)
}}
{{ at
org.apache.spark.sql.catalyst.analysis.AnalysisContext$.withNewAnalysisContext(Analyzer.scala:172)
}}
{{ at
org.apache.spark.sql.catalyst.analysis.Analyzer.execute(Analyzer.scala:223)
}}
{{ at
org.apache.spark.sql.catalyst.analysis.Analyzer.execute(Analyzer.scala:187)
}}
{{ at
org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$executeAndTrack$1(RuleExecutor.scala:179)
}}
{{ at
org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:88)
}}
{{ at
org.apache.spark.sql.catalyst.rules.RuleExecutor.executeAndTrack(RuleExecutor.scala:179)
}}
{{ at
org.apache.spark.sql.catalyst.analysis.Analyzer.$anonfun$executeAndCheck$1(Analyzer.scala:208)
}}
{{ at
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper$.markInAnalyzer(AnalysisHelper.scala:330)
}}
{{ at
org.apache.spark.sql.catalyst.analysis.Analyzer.executeAndCheck(Analyzer.scala:207)
}}
{{ at
org.apache.spark.sql.execution.QueryExecution.$anonfun$analyzed$1(QueryExecution.scala:76)
}}
{{ at
org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:111)
}}
{{ at
org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$2(QueryExecution.scala:185)
}}
{{ at
org.apache.spark.sql.execution.QueryExecution$.withInternalError(QueryExecution.scala:510)
}}
{{ at
org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$1(QueryExecution.scala:185)
}}
{{ at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:779)
}}
{{ at
org.apache.spark.sql.execution.QueryExecution.executePhase(QueryExecution.scala:184)
}}
{{ at
org.apache.spark.sql.execution.QueryExecution.analyzed$lzycompute(QueryExecution.scala:76)
}}
{{ at
org.apache.spark.sql.execution.QueryExecution.analyzed(QueryExecution.scala:74)
}}
{{ at
org.apache.spark.sql.execution.QueryExecution.assertAnalyzed(QueryExecution.scala:66}}
{{Not sure what I am missing between the two versions. Using spark 3.3.0 with
hadoop 3.3.2 and hive 3.1.3}}
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