Here is related code:
private static void checkDefaultsVersion(Configuration conf) {
if (conf.getBoolean("hbase.defaults.for.version.skip", Boolean.FALSE))
return;
String defaultsVersion = conf.get("hbase.defaults.for.version");
String thisVersion = VersionInfo.getVersion();
if (!thisVersion.equals(defaultsVersion)) {
throw new RuntimeException(
"hbase-default.xml file seems to be for an older version of HBase ("
+
defaultsVersion + "), this version is " + thisVersion);
null means that "hbase.defaults.for.version" was not set in the other
hbase-default.xml
Can you retrieve the classpath of Spark task so that we can have more clue ?
Cheers
On Tue, Nov 17, 2015 at 10:06 PM, 임정택 <kabh...@gmail.com> wrote:
> 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)
>>>
>>
>>
>
>
> --
> Name : 임 정택
> Blog : http://www.heartsavior.net / http://dev.heartsavior.net
> Twitter : http://twitter.com/heartsavior
> LinkedIn : http://www.linkedin.com/in/heartsavior
>
