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https://issues.apache.org/jira/browse/SPARK-8409?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14595568#comment-14595568
]
Arun commented on SPARK-8409:
-----------------------------
Hi Shivram,
I tried putting those files in that destination as discussed in earlier
conversation, but that dint work well.
Then i tried installing the csv package in my home, private internet which is
not under restrictions or proxies,but i got the following errors.Can you check
in windows environment by putting this code ".\sparkR --packages
com.databricks:spark-csv_2.10:1.0.3" , whether the issue is in network or in
windows environment.
E:\spark-1.4.0-bin-hadoop2.6\bin>.\sparkR --packages com.databricks:spark-csv_2.
10:1.0.3
R version 3.2.1 (2015-06-18) -- "World-Famous Astronaut"
Copyright (C) 2015 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
Natural language support but running in an English locale
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
Launching java with spark-submit command E:\spark-1.4.0-bin-hadoop2.6\bin\../bin
/spark-submit.cmd "--packages" "com.databricks:spark-csv_2.10:1.0.3" "sparkr-sh
ell" C:\Users\acer1\AppData\Local\Temp\Rtmp0gENwW\backend_port198831cf7692
Ivy Default Cache set to: C:\Users\acer1\.ivy2\cache
The jars for the packages stored in: C:\Users\acer1\.ivy2\jars
:: loading settings :: url = jar:file:/E:/spark-1.4.0-bin-hadoop2.6/lib/spark-as
sembly-1.4.0-hadoop2.6.0.jar!/org/apache/ivy/core/settings/ivysettings.xml
com.databricks#spark-csv_2.10 added as a dependency
:: resolving dependencies :: org.apache.spark#spark-submit-parent;1.0
confs: [default]
You probably access the destination server through a proxy server that is not we
ll configured.
You probably access the destination server through a proxy server that is not we
ll configured.
You probably access the destination server through a proxy server that is not we
ll configured.
You probably access the destination server through a proxy server that is not we
ll configured.
:: resolution report :: resolve 23610ms :: artifacts dl 0ms
:: modules in use:
---------------------------------------------------------------------
| | modules || artifacts |
| conf | number| search|dwnlded|evicted|| number|dwnlded|
---------------------------------------------------------------------
| default | 1 | 0 | 0 | 0 || 0 | 0 |
---------------------------------------------------------------------
:: problems summary ::
:::: WARNINGS
Host repo1.maven.org not found. url=https://repo1.maven.org/maven2/com/d
atabricks/spark-csv_2.10/1.0.3/spark-csv_2.10-1.0.3.pom
Host repo1.maven.org not found. url=https://repo1.maven.org/maven2/com/d
atabricks/spark-csv_2.10/1.0.3/spark-csv_2.10-1.0.3.jar
Host dl.bintray.com not found. url=http://dl.bintray.com/spark-packages/
maven/com/databricks/spark-csv_2.10/1.0.3/spark-csv_2.10-1.0.3.pom
Host dl.bintray.com not found. url=http://dl.bintray.com/spark-packages/
maven/com/databricks/spark-csv_2.10/1.0.3/spark-csv_2.10-1.0.3.jar
module not found: com.databricks#spark-csv_2.10;1.0.3
==== local-m2-cache: tried
file:/C:/Users/acer1/.m2/repository/com/databricks/spark-csv_2.10/1.0.
3/spark-csv_2.10-1.0.3.pom
-- artifact com.databricks#spark-csv_2.10;1.0.3!spark-csv_2.10.jar:
file:/C:/Users/acer1/.m2/repository/com/databricks/spark-csv_2.10/1.0.
3/spark-csv_2.10-1.0.3.jar
==== local-ivy-cache: tried
-- artifact com.databricks#spark-csv_2.10;1.0.3!spark-csv_2.10.jar:
file:/C:/Users/acer1/.ivy2/local/com.databricks\spark-csv_2.10\1.0.3\j
ars\spark-csv_2.10.jar
==== central: tried
https://repo1.maven.org/maven2/com/databricks/spark-csv_2.10/1.0.3/spa
rk-csv_2.10-1.0.3.pom
-- artifact com.databricks#spark-csv_2.10;1.0.3!spark-csv_2.10.jar:
https://repo1.maven.org/maven2/com/databricks/spark-csv_2.10/1.0.3/spa
rk-csv_2.10-1.0.3.jar
==== spark-packages: tried
http://dl.bintray.com/spark-packages/maven/com/databricks/spark-csv_2.
10/1.0.3/spark-csv_2.10-1.0.3.pom
-- artifact com.databricks#spark-csv_2.10;1.0.3!spark-csv_2.10.jar:
http://dl.bintray.com/spark-packages/maven/com/databricks/spark-csv_2.
10/1.0.3/spark-csv_2.10-1.0.3.jar
::::::::::::::::::::::::::::::::::::::::::::::
:: UNRESOLVED DEPENDENCIES ::
::::::::::::::::::::::::::::::::::::::::::::::
:: com.databricks#spark-csv_2.10;1.0.3: not found
::::::::::::::::::::::::::::::::::::::::::::::
:: USE VERBOSE OR DEBUG MESSAGE LEVEL FOR MORE DETAILS
Exception in thread "main" java.lang.RuntimeException: [unresolved dependency: c
om.databricks#spark-csv_2.10;1.0.3: not found]
at org.apache.spark.deploy.SparkSubmitUtils$.resolveMavenCoordinates(Spa
rkSubmit.scala:978)
at org.apache.spark.deploy.SparkSubmit$.prepareSubmitEnvironment(SparkSu
bmit.scala:262)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:144)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:111)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
15/06/22 14:26:39 INFO Utils: Shutdown hook called
Error in SparkR::sparkR.init(Sys.getenv("MASTER", unset = "")) :
JVM is not ready after 10 seconds
>
> 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: SparkR, Windows
> Affects Versions: 1.4.0
> Environment: sparkR API
> Reporter: Arun
> Priority: Critical
>
> 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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