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Posted to user@spark.apache.org by felicia <sh...@tsmc.com> on 2015/05/08 04:39:24 UTC
SparkSQL issue: Spark 1.3.1 + hadoop 2.6 on CDH5.3 with parquet
Hi all,
I'm able to run SparkSQL through python/java and retrieve data from ordinary
table,
but when trying to fetch data from parquet table, following error shows up:\
which is pretty straight-forward indicating that parquet-related class was
not found;
we tried to add /usr/lib/parquet/lib & /usr/lib/parquet to SPARK_CLASSPATH
and it doesn't seems to work,
what is the proper way to solve this issue? Do we have to re-compile Spark
with Parquet-related jars?
Thanks!
ERROR hive.log: error in initSerDe: java.lang.ClassNotFoundException Class
parquet.hive.serde.ParquetHiveSerDe not found
java.lang.ClassNotFoundException: Class parquet.hive.serde.ParquetHiveSerDe
not found
at
org.apache.hadoop.conf.Configuration.getClassByName(Configuration.java:1980)
at
org.apache.hadoop.hive.metastore.MetaStoreUtils.getDeserializer(MetaStoreUtils.java:337)
at
org.apache.hadoop.hive.ql.metadata.Table.getDeserializerFromMetaStore(Table.java:288)
at org.apache.hadoop.hive.ql.metadata.Table.getDeserializer(Table.java:281)
at org.apache.hadoop.hive.ql.metadata.Table.getCols(Table.java:631)
at org.apache.hadoop.hive.ql.metadata.Table.checkValidity(Table.java:189)
at org.apache.hadoop.hive.ql.metadata.Hive.getTable(Hive.java:1017)
at org.apache.hadoop.hive.ql.metadata.Hive.getTable(Hive.java:950)
at
org.apache.spark.sql.hive.HiveMetastoreCatalog.lookupRelation(HiveMetastoreCatalog.scala:78)
at
org.apache.spark.sql.hive.HiveContext$$anon$2.org$apache$spark$sql$catalyst$analysis$OverrideCatalog$$super$lookupRelation(HiveContext.scala:253)
at
org.apache.spark.sql.catalyst.analysis.OverrideCatalog$$anonfun$lookupRelation$3.apply(Catalog.scala:137)
at
org.apache.spark.sql.catalyst.analysis.OverrideCatalog$$anonfun$lookupRelation$3.apply(Catalog.scala:137)
at scala.Option.getOrElse(Option.scala:120)
at
org.apache.spark.sql.catalyst.analysis.OverrideCatalog$class.lookupRelation(Catalog.scala:137)
at
org.apache.spark.sql.hive.HiveContext$$anon$2.lookupRelation(HiveContext.scala:253)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$$anonfun$apply$5.applyOrElse(Analyzer.scala:143)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$$anonfun$apply$5.applyOrElse(Analyzer.scala:138)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:144)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:162)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
at
scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
at scala.collection.AbstractIterator.to(Iterator.scala:1157)
at
scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
at
scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformChildrenDown(TreeNode.scala:191)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:147)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:162)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
at
scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
at scala.collection.AbstractIterator.to(Iterator.scala:1157)
at
scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
at
scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformChildrenDown(TreeNode.scala:191)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:147)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:135)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.apply(Analyzer.scala:138)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.apply(Analyzer.scala:137)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1$$anonfun$apply$2.apply(RuleExecutor.scala:61)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1$$anonfun$apply$2.apply(RuleExecutor.scala:59)
at
scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:111)
at scala.collection.immutable.List.foldLeft(List.scala:84)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1.apply(RuleExecutor.scala:59)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1.apply(RuleExecutor.scala:51)
at scala.collection.immutable.List.foreach(List.scala:318)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor.apply(RuleExecutor.scala:51)
at
org.apache.spark.sql.SQLContext$QueryExecution.analyzed$lzycompute(SQLContext.scala:411)
at
org.apache.spark.sql.SQLContext$QueryExecution.analyzed(SQLContext.scala:411)
at
org.apache.spark.sql.SQLContext$QueryExecution.withCachedData$lzycompute(SQLContext.scala:412)
at
org.apache.spark.sql.SQLContext$QueryExecution.withCachedData(SQLContext.scala:412)
at
org.apache.spark.sql.SQLContext$QueryExecution.optimizedPlan$lzycompute(SQLContext.scala:413)
at
org.apache.spark.sql.SQLContext$QueryExecution.optimizedPlan(SQLContext.scala:413)
at
org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan$lzycompute(SQLContext.scala:418)
at
org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan(SQLContext.scala:416)
at
org.apache.spark.sql.SQLContext$QueryExecution.executedPlan$lzycompute(SQLContext.scala:422)
at
org.apache.spark.sql.SQLContext$QueryExecution.executedPlan(SQLContext.scala:422)
at org.apache.spark.sql.SchemaRDD.collect(SchemaRDD.scala:432)
at
org.apache.spark.sql.api.java.JavaSchemaRDD.collect(JavaSchemaRDD.scala:114)
at com.tsmc.recommand.MainOfRecommandCalc.main(MainOfRecommandCalc.java:61)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:483)
at
org.apache.spark.deploy.yarn.ApplicationMaster$$anon$2.run(ApplicationMaster.scala:441)
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Re: SparkSQL issue: Spark 1.3.1 + hadoop 2.6 on CDH5.3 with parquet
Posted by Satya <sa...@seagate.com>.
Hello,
We are also experiencing the same error. Can you please provide the steps
that resolved the issue.
Thanks
Satya
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Re: SparkSQL issue: Spark 1.3.1 + hadoop 2.6 on CDH5.3 with parquet
Posted by felicia <sh...@tsmc.com>.
Hi all,
Thanks for the help on this case!
we finally settle this by adding a jar named: parquet-hive-bundle-1.5.0.jar
when submitting jobs through spark-submit,
where this jar file does not exist in our CDH5.3 anyway (we've downloaded it
from http://mvnrepository.com/artifact/com.twitter/parquet-hive/1.5.0)
hope this helps!
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Re: SparkSQL issue: Spark 1.3.1 + hadoop 2.6 on CDH5.3 with parquet
Posted by Marcelo Vanzin <va...@cloudera.com>.
On Thu, May 7, 2015 at 7:39 PM, felicia <sh...@tsmc.com> wrote:
> we tried to add /usr/lib/parquet/lib & /usr/lib/parquet to SPARK_CLASSPATH
> and it doesn't seems to work,
>
To add the jars to the classpath you need to use "/usr/lib/parquet/lib/*",
otherwise you're just adding the directory (and not the files within it).
--
Marcelo