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https://issues.apache.org/jira/browse/SPARK-8409?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14589906#comment-14589906
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Shivaram Venkataraman commented on SPARK-8409:
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The error here is that the file it is looking for is
'hdfs://smalldata13.hdp:8020/home/esten/ami/usaf.json' and is not found. Please
copy the file out to HDFS for it to work correctly.
To use CSV you will need to add the Spark CSV package to SparkR and
https://gist.github.com/shivaram/d0cd4aa5c4381edd6f85#file-dataframe_example-r-L6
has some instructions for this
> 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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