Narrowed down to some version incompatibility with Phoenix 4.7 ,

Including $SPARK_HOME/lib/phoenix-4.7.0-HBase-1.1-client-spark.jar to
extraClassPath and that trigger the issue above.

I ll have a go at adding the individual dependencies as opposed to this fat
jar and see how it goes.

Thanks


On Thu, Apr 28, 2016 at 10:52 AM, pierre lacave <pie...@lacave.me> wrote:

> Thanks Ted,
>
> I am actually using the hadoop free version of spark
> (spark-1.5.0-bin-without-hadoop) over hadoop 2.6.1, so could very well be
> related indeed.
>
> I have configured spark-env.sh with export
> SPARK_DIST_CLASSPATH=$($HADOOP_PREFIX/bin/hadoop classpath), which is the
> only version of hadoop on the system (2.6.1) and able to interface with
> hdfs (on no secured zones)
>
> Interestingly running this in the repl works fine
>
> // Create a simple DataFrame, stored into a partition directory
> val df1 = sc.makeRDD(1 to 5).map(i => (i, i * 2)).toDF("single", "double")
> df1.write.parquet("/securedzone/test")
>
>
> but if packaged as an app and ran in local or yarn client/cluster mode, it
> fails with the error described.
>
> I am not including any hadoop specific, so not sure where the difference
> in DFSClient could come from.
>
> [info] Loading project definition from
> /Users/zoidberg/Documents/demo/x/trunk/src/jobs/project
> [info] Set current project to root (in build
> file:/Users/zoidberg/Documents/demo/x/trunk/src/jobs/)
> [info] Updating
> {file:/Users/zoidberg/Documents/demo/x/trunk/src/jobs/}common...
> [info] com.demo.project:root_2.10:0.2.3 [S]
> [info] com.demo.project:common_2.10:0.2.3 [S]
> [info]   +-joda-time:joda-time:2.8.2
> [info]
> [info] Resolving org.fusesource.jansi#jansi;1.4 ...
> [info] Done updating.
> [info] Updating
> {file:/Users/zoidberg/Documents/demo/x/trunk/src/jobs/}extract...
> [info] Resolving org.fusesource.jansi#jansi;1.4 ...
> [info] Done updating.
> [info] com.demo.project:extract_2.10:0.2.3 [S]
> [info]   +-com.demo.project:common_2.10:0.2.3 [S]
> [info]   | +-joda-time:joda-time:2.8.2
> [info]   |
> [info]   +-com.databricks:spark-csv_2.10:1.3.0 [S]
> [info]     +-com.univocity:univocity-parsers:1.5.1
> [info]     +-org.apache.commons:commons-csv:1.1
> [info]
> [success] Total time: 9 s, completed 28-Apr-2016 10:40:25
>
>
> I am assuming I do not need to rebuild spark to use it with hadoop 2.6.1
> and that the spark with user provided hadoop would let me do that,
>
>
> $HADOOP_PREFIX/bin/hadoop classpath expends to:
>
>
> /usr/local/project/hadoop/conf:/usr/local/project/hadoop/share/hadoop/common/lib/*:/usr/local/project/hadoop/share/hadoop/common/*:/usr/local/project/hadoop/share/hadoop/hdfs:/usr/local/project/hadoop/share/hadoop/hdfs/lib/*:/usr/local/project/hadoop/share/hadoop/hdfs/*:/usr/local/project/hadoop/share/hadoop/yarn/lib/*:/usr/local/project/hadoop/share/hadoop/yarn/*:/usr/local/project/hadoop/share/hadoop/mapreduce/lib/*:/usr/local/project/hadoop/share/hadoop/mapreduce/*:/contrib/capacity-scheduler/*.jar
>
> Thanks
>
>
> On Sun, Apr 24, 2016 at 2:20 AM, Ted Yu <yuzhih...@gmail.com> wrote:
>
>> Can you check that the DFSClient Spark uses is the same version as on
>> the server side ?
>>
>> The client and server (NameNode) negotiate a "crypto protocol version" -
>> this is a forward-looking feature.
>> Please note:
>>
>> bq. Client provided: []
>>
>> Meaning client didn't provide any supported crypto protocol version.
>>
>> Cheers
>>
>> On Wed, Apr 20, 2016 at 3:27 AM, pierre lacave <pie...@lacave.me> wrote:
>>
>>> Hi
>>>
>>>
>>> I am trying to use spark to write to a protected zone in hdfs, I am able to 
>>> create and list file using the hdfs client but when writing via Spark I get 
>>> this exception.
>>>
>>> I could not find any mention of CryptoProtocolVersion in the spark doc.
>>>
>>>
>>> Any idea what could have gone wrong?
>>>
>>>
>>> spark (1.5.0), hadoop (2.6.1)
>>>
>>>
>>> Thanks
>>>
>>>
>>> org.apache.hadoop.ipc.RemoteException(org.apache.hadoop.hdfs.UnknownCryptoProtocolVersionException):
>>>  No crypto protocol versions provided by the client are supported. Client 
>>> provided: [] NameNode supports: 
>>> [CryptoProtocolVersion{description='Unknown', version=1, 
>>> unknownValue=null}, CryptoProtocolVersion{description='Encryption zones', 
>>> version=2, unknownValue=null}]
>>>     at 
>>> org.apache.hadoop.hdfs.server.namenode.FSNamesystem.chooseProtocolVersion(FSNamesystem.java:2468)
>>>     at 
>>> org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFileInt(FSNamesystem.java:2600)
>>>     at 
>>> org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFile(FSNamesystem.java:2520)
>>>     at 
>>> org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.create(NameNodeRpcServer.java:579)
>>>     at 
>>> org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.create(ClientNamenodeProtocolServerSideTranslatorPB.java:394)
>>>     at 
>>> org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)
>>>     at 
>>> org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:619)
>>>     at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:962)
>>>     at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2040)
>>>     at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2036)
>>>     at java.security.AccessController.doPrivileged(Native Method)
>>>     at javax.security.auth.Subject.doAs(Subject.java:415)
>>>     at 
>>> org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1656)
>>>     at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2034)
>>>
>>>     at org.apache.hadoop.ipc.Client.call(Client.java:1411)
>>>     at org.apache.hadoop.ipc.Client.call(Client.java:1364)
>>>     at 
>>> org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:206)
>>>     at com.sun.proxy.$Proxy13.create(Unknown Source)
>>>     at 
>>> org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.create(ClientNamenodeProtocolTranslatorPB.java:264)
>>>     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.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:187)
>>>     at 
>>> org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
>>>     at com.sun.proxy.$Proxy14.create(Unknown Source)
>>>     at 
>>> org.apache.hadoop.hdfs.DFSOutputStream.newStreamForCreate(DFSOutputStream.java:1612)
>>>     at org.apache.hadoop.hdfs.DFSClient.create(DFSClient.java:1488)
>>>     at org.apache.hadoop.hdfs.DFSClient.create(DFSClient.java:1413)
>>>     at 
>>> org.apache.hadoop.hdfs.DistributedFileSystem$6.doCall(DistributedFileSystem.java:387)
>>>     at 
>>> org.apache.hadoop.hdfs.DistributedFileSystem$6.doCall(DistributedFileSystem.java:383)
>>>     at 
>>> org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
>>>     at 
>>> org.apache.hadoop.hdfs.DistributedFileSystem.create(DistributedFileSystem.java:383)
>>>     at 
>>> org.apache.hadoop.hdfs.DistributedFileSystem.create(DistributedFileSystem.java:327)
>>>     at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:906)
>>>     at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:799)
>>>     at 
>>> org.apache.hadoop.mapred.TextOutputFormat.getRecordWriter(TextOutputFormat.java:123)
>>>     at org.apache.spark.SparkHadoopWriter.open(SparkHadoopWriter.scala:91)
>>>     at 
>>> org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13.apply(PairRDDFunctions.scala:1104)
>>>     at 
>>> org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$13.apply(PairRDDFunctions.scala:1095)
>>>     at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
>>>     at org.apache.spark.scheduler.Task.run(Task.scala:88)
>>>     at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
>>>     at 
>>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>>>     at 
>>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>>>     at java.lang.Thread.run(Thread.java:745)
>>>
>>>
>>>
>>>
>>
>

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