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https://issues.apache.org/jira/browse/SPARK-8409?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Shivaram Venkataraman resolved SPARK-8409.
------------------------------------------
Resolution: Not A Problem
> In windows cant able to read .csv or .json files using read.df()
> -----------------------------------------------------------------
>
> Key: SPARK-8409
> URL: https://issues.apache.org/jira/browse/SPARK-8409
> Project: Spark
> Issue Type: Bug
> Components: Build
> Affects Versions: 1.4.0
> Environment: sparkR API
> Reporter: Arun
> Priority: Critical
> Labels: build
>
> Hi,
> In SparkR shell, I invoke:
> > mydf<-read.df(sqlContext, "/home/esten/ami/usaf.json", source="json",
> > header="false")
> I have tried various filetypes (csv, txt), all fail.
> in sparkR of spark 1.4 for eg.) df_1<- read.df(sqlContext,
> "E:/setup/spark-1.4.0-bin-hadoop2.6/spark-1.4.0-bin-hadoop2.6/examples/src/main/resources/nycflights13.csv",
> source = "csv")
> RESPONSE: "ERROR RBackendHandler: load on 1 failed"
> BELOW THE WHOLE RESPONSE:
> 15/06/16 08:09:13 INFO MemoryStore: ensureFreeSpace(177600) called with
> curMem=0, maxMem=278302556
> 15/06/16 08:09:13 INFO MemoryStore: Block broadcast_0 stored as values in
> memory (estimated size 173.4 KB, free 265.2 MB)
> 15/06/16 08:09:13 INFO MemoryStore: ensureFreeSpace(16545) called with
> curMem=177600, maxMem=278302556
> 15/06/16 08:09:13 INFO MemoryStore: Block broadcast_0_piece0 stored as bytes
> in memory (estimated size 16.2 KB, free 265.2 MB)
> 15/06/16 08:09:13 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory
> on localhost:37142 (size: 16.2 KB, free: 265.4 MB)
> 15/06/16 08:09:13 INFO SparkContext: Created broadcast 0 from load at
> NativeMethodAccessorImpl.java:-2
> 15/06/16 08:09:16 WARN DomainSocketFactory: The short-circuit local reads
> feature cannot be used because libhadoop cannot be loaded.
> 15/06/16 08:09:17 ERROR RBackendHandler: load on 1 failed
> java.lang.reflect.InvocationTargetException
> 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.api.r.RBackendHandler.handleMethodCall(RBackendHandler.scala:127)
>
> at
> org.apache.spark.api.r.RBackendHandler.channelRead0(RBackendHandler.scala:74)
> at
> org.apache.spark.api.r.RBackendHandler.channelRead0(RBackendHandler.scala:36)
> at
> io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105)
>
> at
> io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:333)
>
> at
> io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:319)
>
> at
> io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:103)
>
> at
> io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:333)
>
> at
> io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:319)
>
> at
> io.netty.handler.codec.ByteToMessageDecoder.channelRead(ByteToMessageDecoder.java:163)
>
> at
> io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:333)
>
> at
> io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:319)
>
> at
> io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:787)
>
> at
> io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:130)
>
> at
> io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:511)
> at
> io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:468)
>
> at
> io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:382)
> at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:354)
> at
> io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:116)
>
> at
> io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:137)
>
> at java.lang.Thread.run(Thread.java:745)
> Caused by: org.apache.hadoop.mapred.InvalidInputException: Input path does
> not exist: hdfs://smalldata13.hdp:8020/home/esten/ami/usaf.json
> at
> org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:285)
>
> at
> org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:228)
> at
> org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:313)
> at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:207)
> at
> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
> at
> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
> at scala.Option.getOrElse(Option.scala:120)
> at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
> at
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:32)
>
> at
> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
> at
> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
> at scala.Option.getOrElse(Option.scala:120)
> at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
> at
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:32)
>
> at
> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
> at
> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
> at scala.Option.getOrElse(Option.scala:120)
> at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
> at
> org.apache.spark.rdd.RDD$$anonfun$treeAggregate$1.apply(RDD.scala:1069)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:148)
>
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:109)
>
> at org.apache.spark.rdd.RDD.withScope(RDD.scala:286)
> at org.apache.spark.rdd.RDD.treeAggregate(RDD.scala:1067)
> at org.apache.spark.sql.json.InferSchema$.apply(InferSchema.scala:58)
> at
> org.apache.spark.sql.json.JSONRelation$$anonfun$schema$1.apply(JSONRelation.scala:139)
>
> at
> org.apache.spark.sql.json.JSONRelation$$anonfun$schema$1.apply(JSONRelation.scala:138)
>
> at scala.Option.getOrElse(Option.scala:120)
> at
> org.apache.spark.sql.json.JSONRelation.schema$lzycompute(JSONRelation.scala:137)
>
> at
> org.apache.spark.sql.json.JSONRelation.schema(JSONRelation.scala:137)
> at
> org.apache.spark.sql.sources.LogicalRelation.<init>(LogicalRelation.scala:30)
> at
> org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:120)
> at org.apache.spark.sql.SQLContext.load(SQLContext.scala:1230)
> ... 25 more
> Error: returnStatus == 0 is not TRUE
>
>
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