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https://issues.apache.org/jira/browse/SPARK-9206?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Sean Owen updated SPARK-9206:
-----------------------------
Assignee: Dennis Huo
> ClassCastException using HiveContext with GoogleHadoopFileSystem as
> fs.defaultFS
> --------------------------------------------------------------------------------
>
> Key: SPARK-9206
> URL: https://issues.apache.org/jira/browse/SPARK-9206
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.4.1
> Reporter: Dennis Huo
> Assignee: Dennis Huo
> Fix For: 1.5.0
>
>
> Originally reported on StackOverflow:
> http://stackoverflow.com/questions/31478955/googlehadoopfilesystem-cannot-be-cast-to-hadoop-filesystem
> Google's "bdutil" command-line tool
> (https://github.com/GoogleCloudPlatform/bdutil) is one of the main supported
> ways of deploying Hadoop and Spark cluster on Google Cloud Platform, and has
> default settings which configure fs.defaultFS to use the Google Cloud Storage
> connector for Hadoop (and performs installation of the connector jarfile on
> top of tarball-based Hadoop and Spark distributions).
> Starting in Spark 1.4.1, taking a default bdutil-based Spark deployment,
> running "spark-shell", and then trying to read a file with sqlContext like:
> {code}
> sqlContext.parquetFile("gs://my-bucket/my-file.parquet")
> {code}
> results in the following:
> {noformat}
> 15/07/20 20:59:14 DEBUG IsolatedClientLoader: shared class:
> com.google.cloud.hadoop.fs.gcs.GoogleHadoopFileSystem
> java.lang.RuntimeException: java.lang.ClassCastException:
> com.google.cloud.hadoop.fs.gcs.GoogleHadoopFileSystem cannot be cast to
> org.apache.hadoop.fs.FileSystem
> at
> org.apache.hadoop.hive.ql.session.SessionState.start(SessionState.java:346)
> at
> org.apache.spark.sql.hive.client.ClientWrapper.<init>(ClientWrapper.scala:116)
> at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
> at
> sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:57)
> at
> sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
> at java.lang.reflect.Constructor.newInstance(Constructor.java:526)
> at
> org.apache.spark.sql.hive.client.IsolatedClientLoader.liftedTree1$1(IsolatedClientLoader.scala:172)
> at
> org.apache.spark.sql.hive.client.IsolatedClientLoader.<init>(IsolatedClientLoader.scala:168)
> at
> org.apache.spark.sql.hive.HiveContext.metadataHive$lzycompute(HiveContext.scala:213)
> at
> org.apache.spark.sql.hive.HiveContext.metadataHive(HiveContext.scala:176)
> at
> org.apache.spark.sql.hive.HiveContext$$anon$2.<init>(HiveContext.scala:371)
> at
> org.apache.spark.sql.hive.HiveContext.catalog$lzycompute(HiveContext.scala:371)
> at org.apache.spark.sql.hive.HiveContext.catalog(HiveContext.scala:370)
> at
> org.apache.spark.sql.hive.HiveContext$$anon$1.<init>(HiveContext.scala:383)
> at
> org.apache.spark.sql.hive.HiveContext.analyzer$lzycompute(HiveContext.scala:383)
> at org.apache.spark.sql.hive.HiveContext.analyzer(HiveContext.scala:382)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.assertAnalyzed(SQLContext.scala:931)
> at org.apache.spark.sql.DataFrame.<init>(DataFrame.scala:131)
> at org.apache.spark.sql.DataFrame$.apply(DataFrame.scala:51)
> at
> org.apache.spark.sql.SQLContext.baseRelationToDataFrame(SQLContext.scala:438)
> at
> org.apache.spark.sql.DataFrameReader.parquet(DataFrameReader.scala:264)
> at org.apache.spark.sql.SQLContext.parquetFile(SQLContext.scala:1099)
> at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:19)
> at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:24)
> at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:26)
> at $iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:28)
> at $iwC$$iwC$$iwC$$iwC.<init>(<console>:30)
> at $iwC$$iwC$$iwC.<init>(<console>:32)
> at $iwC$$iwC.<init>(<console>:34)
> at $iwC.<init>(<console>:36)
> at <init>(<console>:38)
> at .<init>(<console>:42)
> at .<clinit>(<console>)
> at .<init>(<console>:7)
> at .<clinit>(<console>)
> at $print(<console>)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:606)
> at
> org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
> at
> org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1338)
> at
> org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
> at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
> at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
> at
> org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:857)
> at
> org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:902)
> at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:814)
> at org.apache.spark.repl.SparkILoop.processLine$1(SparkILoop.scala:657)
> at org.apache.spark.repl.SparkILoop.innerLoop$1(SparkILoop.scala:665)
> at
> org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$loop(SparkILoop.scala:670)
> at
> org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:997)
> at
> org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
> at
> org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
> at
> scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
> at
> org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:945)
> at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1059)
> at org.apache.spark.repl.Main$.main(Main.scala:31)
> at org.apache.spark.repl.Main.main(Main.scala)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:606)
> at
> org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:665)
> at
> org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:170)
> at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:193)
> at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:112)
> at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
> Caused by: java.lang.ClassCastException:
> com.google.cloud.hadoop.fs.gcs.GoogleHadoopFileSystem cannot be cast to
> org.apache.hadoop.fs.FileSystem
> at
> org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2595)
> at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:91)
> at
> org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2630)
> at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2612)
> at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:370)
> at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:169)
> at
> org.apache.hadoop.hive.ql.session.SessionState.start(SessionState.java:342)
> ... 67 more
> {noformat}
> This appears to be a combination of
> https://github.com/apache/spark/commit/9ac8393663d759860c67799e000ec072ced76493
> and its related "isolated classloader" changes with the
> IsolatedClientLoader.isSharedClass method including "com.google.*" alongside
> java.lang.*, java.net.*, etc., as shared classes, presumably for inclusion of
> Guava and possibly protobuf and gson libraries.
> Unfortunately, this also includes the Hadoop extended libraries like
> com.google.cloud.hadoop.fs.gcs.GoogleHadoopFileSystem
> (https://github.com/GoogleCloudPlatform/bigdata-interop) and
> com.google.cloud.bigtable.*
> (https://github.com/GoogleCloudPlatform/cloud-bigtable-client).
> This can be reproduced by downloading bdutil from
> https://github.com/GoogleCloudPlatform/bdutil, modifying
> bdutil/extensions/spark/spark_env.sh to set SPARK_HADOOP2_TARBALL_URI to some
> Spark 1.4.1 tarball URI (http URIs should work as well) and then deploying a
> cluster with:
> {code}
> ./bdutil -p <your project> -b <your GCS bucket> -z us-central1-f -e hadoop2
> -e spark deploy
> ./bdutil -p <your project> -b <your GCS bucket> -z us-central1-f -e hadoop2
> -e spark shell
> {code}
> The last command opens an SSH session; then type:
> {code}
> spark-shell
> > sqlContext.parquetFile("gs://your-bucket/some/path/to/parquet/file.parquet")
> {code}
> The ClassCastException should then immediately get thrown.
> The simple fix of simply excluding com.google.cloud.* from being "shared
> classes" appears to work just fine in an end-to-end bdutil-based deployment.
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