[
https://issues.apache.org/jira/browse/SPARK-6961?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14743537#comment-14743537
]
Steve Loughran commented on SPARK-6961:
---------------------------------------
Well, its an installation-side issue in that "if it isn't there you can fix it
with a re-installation".
The fact that things are failing with an utterly useless error message, that is
very much a code-side issue. HADOOP-10775 is going to add extra checks and a
link to a wiki entry (https://wiki.apache.org/hadoop/WindowsProblems) with some
advice. One troublespot there is that code is often just referencing a field
(which is set to null on a load failure); the patch will have to make sure we
switch to exception-raising getters as needed, and that the callers handle the
raised exceptions properly.
> 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}
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
