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  1. Spark
  2. SPARK-8409

In windows cant able to read .csv or .json files using read.df()

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Details

    • Bug
    • Status: Resolved
    • Critical
    • Resolution: Not A Problem
    • 1.4.0
    • None
    • SparkR, Windows
    • None
    • sparkR API

    Description

      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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            Unassigned Unassigned
            b.arungunalan@gmail.com Arun
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              Created:
              Updated:
              Resolved: