class HFileWriterImpl (in standalone file) is only present in master branch.
It is not in branch-1.
compressionByName() resides in class with @InterfaceAudience.Private which
got moved in master branch.
So looks like there is some work to be done for backporting to branch-1 :-)
On Sun, Mar 13, 2016 at 1:35 PM, Benjamin Kim <bbuil...@gmail.com> wrote:
> Ted,
>
> I did as you said, but it looks like that HBaseContext relies on some
> differences in HBase itself.
>
> [ERROR]
> /home/bkim/hbase-rel-1.0.2/hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/HBaseContext.scala:30:
> error: object HFileWriterImpl is not a member of package
> org.apache.hadoop.hbase.io.hfile
> [ERROR] import org.apache.hadoop.hbase.io.hfile.{CacheConfig,
> HFileContextBuilder, HFileWriterImpl}
> [ERROR] ^
> [ERROR]
> /home/bkim/hbase-rel-1.0.2/hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/HBaseContext.scala:627:
> error: not found: value HFileWriterImpl
> [ERROR] val hfileCompression = HFileWriterImpl
> [ERROR] ^
> [ERROR]
> /home/bkim/hbase-rel-1.0.2/hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/HBaseContext.scala:750:
> error: not found: value HFileWriterImpl
> [ERROR] val defaultCompression = HFileWriterImpl
> [ERROR] ^
> [ERROR]
> /home/bkim/hbase-rel-1.0.2/hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/HBaseContext.scala:898:
> error: value COMPARATOR is not a member of object
> org.apache.hadoop.hbase.CellComparator
> [ERROR]
> .withComparator(CellComparator.COMPARATOR).withFileContext(hFileContext)
>
> So… back to my original question… do you know when these incompatibilities
> were introduced? If so, I can pulled that version at time and try again.
>
> Thanks,
> Ben
>
> On Mar 13, 2016, at 12:42 PM, Ted Yu <yuzhih...@gmail.com> wrote:
>
> Benjamin:
> Since hbase-spark is in its own module, you can pull the whole hbase-spark
> subtree into hbase 1.0 root dir and add the following to root pom.xml:
> <module>hbase-spark</module>
>
> Then you would be able to build the module yourself.
>
> hbase-spark module uses APIs which are compatible with hbase 1.0
>
> Cheers
>
> On Sun, Mar 13, 2016 at 11:39 AM, Benjamin Kim <bbuil...@gmail.com> wrote:
>
>> Hi Ted,
>>
>> I see that you’re working on the hbase-spark module for hbase. I recently
>> packaged the SparkOnHBase project and gave it a test run. It works like a
>> charm on CDH 5.4 and 5.5. All I had to do was
>> add /opt/cloudera/parcels/CDH/jars/htrace-core-3.1.0-incubating.jar to the
>> classpath.txt file in /etc/spark/conf. Then, I ran spark-shell with “—jars
>> /path/to/spark-hbase-0.0.2-clabs.jar” as an argument and used the
>> easy-to-use HBaseContext for HBase operations. Now, I want to use the
>> latest in Dataframes. Since the new functionality is only in the
>> hbase-spark module, I want to know how to get it and package it for CDH
>> 5.5, which still uses HBase 1.0.0. Can you tell me what version of hbase
>> master is still backwards compatible?
>>
>> By the way, we are using Spark 1.6 if it matters.
>>
>> Thanks,
>> Ben
>>
>> On Feb 10, 2016, at 2:34 AM, Ted Yu <yuzhih...@gmail.com> wrote:
>>
>> Have you tried adding hbase client jars to spark.executor.extraClassPath
>> ?
>>
>> Cheers
>>
>> On Wed, Feb 10, 2016 at 12:17 AM, Prabhu Joseph <
>> prabhujose.ga...@gmail.com> wrote:
>>
>>> + Spark-Dev
>>>
>>> For a Spark job on YARN accessing hbase table, added all hbase client
>>> jars into spark.yarn.dist.files, NodeManager when launching container i.e
>>> executor, does localization and brings all hbase-client jars into executor
>>> CWD, but still the executor tasks fail with ClassNotFoundException of hbase
>>> client jars, when i checked launch container.sh , Classpath does not have
>>> $PWD/* and hence all the hbase client jars are ignored.
>>>
>>> Is spark.yarn.dist.files not for adding jars into the executor classpath.
>>>
>>> Thanks,
>>> Prabhu Joseph
>>>
>>> On Tue, Feb 9, 2016 at 1:42 PM, Prabhu Joseph <
>>> prabhujose.ga...@gmail.com> wrote:
>>>
>>>> Hi All,
>>>>
>>>> When i do count on a Hbase table from Spark Shell which runs as
>>>> yarn-client mode, the job fails at count().
>>>>
>>>> MASTER=yarn-client ./spark-shell
>>>>
>>>> import org.apache.hadoop.hbase.{HBaseConfiguration, HTableDescriptor,
>>>> TableName}
>>>> import org.apache.hadoop.hbase.client.HBaseAdmin
>>>> import org.apache.hadoop.hbase.mapreduce.TableInputFormat
>>>>
>>>> val conf = HBaseConfiguration.create()
>>>> conf.set(TableInputFormat.INPUT_TABLE,"spark")
>>>>
>>>> val hBaseRDD = sc.newAPIHadoopRDD(conf,
>>>> classOf[TableInputFormat],classOf[org.apache.hadoop.hbase.io.ImmutableBytesWritable],classOf[org.apache.hadoop.hbase.client.Result])
>>>> hBaseRDD.count()
>>>>
>>>>
>>>> Tasks throw below exception, the actual exception is swallowed, a bug
>>>> JDK-7172206. After installing hbase client on all NodeManager machines, the
>>>> Spark job ran fine. So I confirmed that the issue is with executor
>>>> classpath.
>>>>
>>>> But i am searching for some other way of including hbase jars in spark
>>>> executor classpath instead of installing hbase client on all NM machines.
>>>> Tried adding all hbase jars in spark.yarn.dist.files , NM logs shows that
>>>> it localized all hbase jars, still the job fails. Tried
>>>> spark.executor.extraClasspath, still the job fails.
>>>>
>>>> Is there any way we can access hbase from Executor without installing
>>>> hbase-client on all machines.
>>>>
>>>>
>>>> 16/02/09 02:34:57 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID
>>>> 0, prabhuFS1): *java.lang.IllegalStateException: unread block data*
>>>> at
>>>> java.io.ObjectInputStream$BlockDataInputStream.setBlockDataMode(ObjectInputStream.java:2428)
>>>> at
>>>> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1382)
>>>> at
>>>> java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1997)
>>>> at
>>>> java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1921)
>>>> at
>>>> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798)
>>>> at
>>>> java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350)
>>>> at
>>>> java.io.ObjectInputStream.readObject(ObjectInputStream.java:370)
>>>> at
>>>> org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:68)
>>>> at
>>>> org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:94)
>>>> at
>>>> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:185)
>>>> at
>>>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>>>> at
>>>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>>>> at java.lang.Thread.run(Thread.java:745)
>>>>
>>>>
>>>>
>>>> Thanks,
>>>> Prabhu Joseph
>>>>
>>>
>>>
>>
>>
>
>
