Ted,
Thanks for the reply.
My fat jar has dependency with spark related library to only spark-core as
"provided".
Seems like Spark only adds 0.98.7-hadoop2 of hbase-common in spark-example
module.
And if there're two hbase-default.xml in the classpath, should one of them
be loaded, instead of showing (null)?
Best,
Jungtaek Lim (HeartSaVioR)
2015-11-18 13:50 GMT+09:00 Ted Yu <yuzhih...@gmail.com>:
> Looks like there're two hbase-default.xml in the classpath: one for 0.98.6
> and another for 0.98.7-hadoop2 (used by Spark)
>
> You can specify hbase.defaults.for.version.skip as true in your
> hbase-site.xml
>
> Cheers
>
> On Tue, Nov 17, 2015 at 1:01 AM, 임정택 <kabh...@gmail.com> wrote:
>
>> Hi all,
>>
>> I'm evaluating zeppelin to run driver which interacts with HBase.
>> I use fat jar to include HBase dependencies, and see failures on executor
>> level.
>> I thought it is zeppelin's issue, but it fails on spark-shell, too.
>>
>> I loaded fat jar via --jars option,
>>
>> > ./bin/spark-shell --jars hbase-included-assembled.jar
>>
>> and run driver code using provided SparkContext instance, and see
>> failures from spark-shell console and executor logs.
>>
>> below is stack traces,
>>
>> org.apache.spark.SparkException: Job aborted due to stage failure: Task 55
>> in stage 0.0 failed 4 times, most recent failure: Lost task 55.3 in stage
>> 0.0 (TID 281, <svr hostname>): java.lang.NoClassDefFoundError: Could not
>> initialize class org.apache.hadoop.hbase.client.HConnectionManager
>> at org.apache.hadoop.hbase.client.HTable.<init>(HTable.java:197)
>> at org.apache.hadoop.hbase.client.HTable.<init>(HTable.java:159)
>> at
>> org.apache.hadoop.hbase.mapreduce.TableInputFormat.setConf(TableInputFormat.java:101)
>> at
>> org.apache.spark.rdd.NewHadoopRDD$$anon$1.<init>(NewHadoopRDD.scala:128)
>> at org.apache.spark.rdd.NewHadoopRDD.compute(NewHadoopRDD.scala:104)
>> at org.apache.spark.rdd.NewHadoopRDD.compute(NewHadoopRDD.scala:66)
>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
>> at
>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
>> at
>> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:70)
>> at
>> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
>> at org.apache.spark.scheduler.Task.run(Task.scala:70)
>> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
>> at
>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>> at
>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>> at java.lang.Thread.run(Thread.java:745)
>>
>> Driver stacktrace:
>> at
>> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1273)
>> at
>> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1264)
>> at
>> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1263)
>> at
>> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
>> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
>> at
>> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1263)
>> at
>> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:730)
>> at
>> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:730)
>> at scala.Option.foreach(Option.scala:236)
>> at
>> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:730)
>> at
>> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1457)
>> at
>> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1418)
>> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
>>
>>
>> 15/11/16 18:59:57 ERROR Executor: Exception in task 14.0 in stage 0.0 (TID
>> 14)
>> java.lang.ExceptionInInitializerError
>> at org.apache.hadoop.hbase.client.HTable.<init>(HTable.java:197)
>> at org.apache.hadoop.hbase.client.HTable.<init>(HTable.java:159)
>> at
>> org.apache.hadoop.hbase.mapreduce.TableInputFormat.setConf(TableInputFormat.java:101)
>> at
>> org.apache.spark.rdd.NewHadoopRDD$$anon$1.<init>(NewHadoopRDD.scala:128)
>> at org.apache.spark.rdd.NewHadoopRDD.compute(NewHadoopRDD.scala:104)
>> at org.apache.spark.rdd.NewHadoopRDD.compute(NewHadoopRDD.scala:66)
>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
>> at
>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
>> at
>> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:70)
>> at
>> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
>> at org.apache.spark.scheduler.Task.run(Task.scala:70)
>> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
>> 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)
>> Caused by: java.lang.RuntimeException: hbase-default.xml file seems to be
>> for and old version of HBase (null), this version is 0.98.6-cdh5.2.0
>> at
>> org.apache.hadoop.hbase.HBaseConfiguration.checkDefaultsVersion(HBaseConfiguration.java:73)
>> at
>> org.apache.hadoop.hbase.HBaseConfiguration.addHbaseResources(HBaseConfiguration.java:105)
>> at
>> org.apache.hadoop.hbase.HBaseConfiguration.create(HBaseConfiguration.java:116)
>> at
>> org.apache.hadoop.hbase.client.HConnectionManager.<clinit>(HConnectionManager.java:222)
>> ... 18 more
>>
>>
>> Please note that it runs smoothly on spark-submit.
>>
>> Btw, if issue is that hbase-default.xml is not properly loaded (maybe
>> because of classloader), it seems to run properly on driver level.
>>
>> import org.apache.hadoop.hbase.HBaseConfiguration
>> val conf = HBaseConfiguration.create()
>> println(conf.get("hbase.defaults.for.version"))
>>
>> It prints "0.98.6-cdh5.2.0".
>>
>> I'm using Spark-1.4.1-hadoop-2.4-bin, and zeppelin 0.5.5, and HBase
>> 0.98.6-CDH5.2.0.
>>
>> Thanks in advance!
>>
>> Best,
>> Jungtaek Lim (HeartSaVioR)
>>
>
>
--
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