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Posted to issues@spark.apache.org by "matt hoffman (JIRA)" <ji...@apache.org> on 2015/08/31 21:46:47 UTC
[jira] [Commented] (SPARK-6961) Cannot save data to parquet files
when executing from Windows from a Maven Project
[ https://issues.apache.org/jira/browse/SPARK-6961?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14723933#comment-14723933 ]
matt hoffman commented on SPARK-6961:
-------------------------------------
How is that an installation-side issue? There is no requirement that users install any Hadoop utilities along with Spark, correct? WINUTILS.EXE is something that is bundled by Hadoop (although it isn't packaged in Hadoop by default, according to http://www.barik.net/archive/2015/01/19/172716/).
> Cannot save data to parquet files when executing from Windows from a Maven Project
> ----------------------------------------------------------------------------------
>
> Key: SPARK-6961
> URL: https://issues.apache.org/jira/browse/SPARK-6961
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.3.0
> Reporter: Bogdan Niculescu
> Priority: Critical
>
> I have setup a project where I am trying to save a DataFrame into a parquet file. My project is a Maven one with Spark 1.3.0 and Scala 2.11.5 :
> {code:xml}
> <spark.version>1.3.0</spark.version>
> <dependency>
> <groupId>org.apache.spark</groupId>
> <artifactId>spark-core_2.11</artifactId>
> <version>${spark.version}</version>
> </dependency>
> <dependency>
> <groupId>org.apache.spark</groupId>
> <artifactId>spark-sql_2.11</artifactId>
> <version>${spark.version}</version>
> </dependency>
> {code}
> A simple version of my code that reproduces consistently the problem that I am seeing is :
> {code}
> import org.apache.spark.sql.SQLContext
> import org.apache.spark.{SparkConf, SparkContext}
> case class Person(name: String, age: Int)
> object DataFrameTest extends App {
> val conf = new SparkConf().setMaster("local[4]").setAppName("DataFrameTest")
> val sc = new SparkContext(conf)
> val sqlContext = new SQLContext(sc)
> val persons = List(Person("a", 1), Person("b", 2))
> val rdd = sc.parallelize(persons)
> val dataFrame = sqlContext.createDataFrame(rdd)
> dataFrame.saveAsParquetFile("test.parquet")
> }
> {code}
> All the time the exception that I am getting is :
> {code}
> Exception in thread "main" java.lang.NullPointerException
> at java.lang.ProcessBuilder.start(ProcessBuilder.java:1010)
> at org.apache.hadoop.util.Shell.runCommand(Shell.java:404)
> at org.apache.hadoop.util.Shell.run(Shell.java:379)
> at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:589)
> at org.apache.hadoop.util.Shell.execCommand(Shell.java:678)
> at org.apache.hadoop.util.Shell.execCommand(Shell.java:661)
> at org.apache.hadoop.fs.RawLocalFileSystem.setPermission(RawLocalFileSystem.java:639)
> at org.apache.hadoop.fs.FilterFileSystem.setPermission(FilterFileSystem.java:468)
> at org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:456)
> at org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:424)
> at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:905)
> at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:886)
> at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:783)
> at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:772)
> at parquet.hadoop.ParquetFileWriter.writeMetadataFile(ParquetFileWriter.java:409)
> at parquet.hadoop.ParquetFileWriter.writeMetadataFile(ParquetFileWriter.java:401)
> at org.apache.spark.sql.parquet.ParquetTypesConverter$.writeMetaData(ParquetTypes.scala:443)
> at org.apache.spark.sql.parquet.ParquetRelation2$MetadataCache.prepareMetadata(newParquet.scala:240)
> at org.apache.spark.sql.parquet.ParquetRelation2$MetadataCache$$anonfun$6.apply(newParquet.scala:256)
> at org.apache.spark.sql.parquet.ParquetRelation2$MetadataCache$$anonfun$6.apply(newParquet.scala:251)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:245)
> at scala.collection.immutable.List.map(List.scala:285)
> at org.apache.spark.sql.parquet.ParquetRelation2$MetadataCache.refresh(newParquet.scala:251)
> at org.apache.spark.sql.parquet.ParquetRelation2.<init>(newParquet.scala:370)
> at org.apache.spark.sql.parquet.DefaultSource.createRelation(newParquet.scala:96)
> at org.apache.spark.sql.parquet.DefaultSource.createRelation(newParquet.scala:125)
> at org.apache.spark.sql.sources.ResolvedDataSource$.apply(ddl.scala:308)
> at org.apache.spark.sql.DataFrame.save(DataFrame.scala:1123)
> at org.apache.spark.sql.DataFrame.saveAsParquetFile(DataFrame.scala:922)
> at sparkTest.DataFrameTest$.delayedEndpoint$sparkTest$DataFrameTest$1(DataFrameTest.scala:17)
> at sparkTest.DataFrameTest$delayedInit$body.apply(DataFrameTest.scala:8)
> at scala.Function0$class.apply$mcV$sp(Function0.scala:40)
> at scala.runtime.AbstractFunction0.apply$mcV$sp(AbstractFunction0.scala:12)
> at scala.App$$anonfun$main$1.apply(App.scala:76)
> at scala.App$$anonfun$main$1.apply(App.scala:76)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at scala.collection.generic.TraversableForwarder$class.foreach(TraversableForwarder.scala:35)
> at scala.App$class.main(App.scala:76)
> at sparkTest.DataFrameTest$.main(DataFrameTest.scala:8)
> at sparkTest.DataFrameTest.main(DataFrameTest.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 com.intellij.rt.execution.application.AppMain.main(AppMain.java:134)
> {code}
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