Any one who has used spark this way or has faced similar issue, please help.
Thanks,
-Vibhor
On Wed, May 28, 2014 at 6:03 PM, Vibhor Banga <vibhorba...@gmail.com> wrote:
> Hi all,
>
> I am facing issues while using spark with HBase. I am getting
> NullPointerException at org.apache.hadoop.hbase.TableName.valueOf
> (TableName.java:288)
>
> Can someone please help to resolve this issue. What am I missing ?
>
>
> I am using following snippet of code -
>
> Configuration config = HBaseConfiguration.create();
>
> config.set("hbase.zookeeper.znode.parent", "hostname1");
> config.set("hbase.zookeeper.quorum","hostname1");
> config.set("hbase.zookeeper.property.clientPort","2181");
> config.set("hbase.master", "hostname1:
> config.set("fs.defaultFS","hdfs://hostname1/");
> config.set("dfs.namenode.rpc-address","hostname1:8020");
>
> config.set(TableInputFormat.INPUT_TABLE, "tableName");
>
> JavaSparkContext ctx = new JavaSparkContext(args[0], "Simple",
> System.getenv(sparkHome),
> JavaSparkContext.jarOfClass(Simple.class));
>
> JavaPairRDD<ImmutableBytesWritable, Result> hBaseRDD
> = ctx.newAPIHadoopRDD( config, TableInputFormat.class,
> ImmutableBytesWritable.class, Result.class);
>
> Map<ImmutableBytesWritable, Result> rddMap = hBaseRDD.collectAsMap();
>
>
> But when I go to the spark cluster and check the logs, I see following
> error -
>
> INFO NewHadoopRDD: Input split: w3-target1.nm.flipkart.com:,
> 14/05/28 16:48:51 ERROR TableInputFormat: java.lang.NullPointerException
> at org.apache.hadoop.hbase.TableName.valueOf(TableName.java:288)
> at org.apache.hadoop.hbase.client.HTable.<init>(HTable.java:154)
> at
> org.apache.hadoop.hbase.mapreduce.TableInputFormat.setConf(TableInputFormat.java:99)
> at
> org.apache.spark.rdd.NewHadoopRDD$$anon$1.<init>(NewHadoopRDD.scala:92)
> at org.apache.spark.rdd.NewHadoopRDD.compute(NewHadoopRDD.scala:84)
> at org.apache.spark.rdd.NewHadoopRDD.compute(NewHadoopRDD.scala:48)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:241)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:232)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:109)
> at org.apache.spark.scheduler.Task.run(Task.scala:53)
> at
> org.apache.spark.executor.Executor$TaskRunner$$anonfun$run$1.apply$mcV$sp(Executor.scala:211)
> at
> org.apache.spark.deploy.SparkHadoopUtil$$anon$1.run(SparkHadoopUtil.scala:42)
> at
> org.apache.spark.deploy.SparkHadoopUtil$$anon$1.run(SparkHadoopUtil.scala:41)
> at java.security.AccessController.doPrivileged(Native Method)
> at javax.security.auth.Subject.doAs(Subject.java:415)
> at
> org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1121)
> at
> org.apache.spark.deploy.SparkHadoopUtil.runAsUser(SparkHadoopUtil.scala:41)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:176)
> 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,
>
> -Vibhor
>
>
