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scalaapache-sparkhbasebulk-delete

Spark program to bulkdelete hbase rows throws AbstractMethodError

Following is my code block in spark application to delete set of rowkeys (rePartitionedRowKeys) from hbase table,

hbaseContext.bulkDelete[Array[Byte]](rePartitionedRowKeys,
        TableName.valueOf(hbaseTableName),
        putRecord => new Delete(putRecord), batchSize)

Related dependencies in pom.xml are,

<dependency>
    <groupId>org.apache.hbase</groupId>
    <artifactId>hbase-spark</artifactId>
    <version>1.2.0-cdh5.7.0</version>
    <scope>compile</scope>
</dependency>        
<dependency>
    <groupId>org.apache.spark</groupId>
    <artifactId>spark-streaming_2.10</artifactId>
    <version>1.6.0-cdh5.7.0</version>
    <scope>provided</scope>
</dependency>

When I run the application, I am getting AbstractMethodError for one of the log method,

org.apache.spark.SparkException: Job aborted due to stage failure: Task 3 in stage 4.0 failed 4 times, most recent failure: Lost task 3.3 in stage 4.0 (TID 17, c175vjt.int.westgroup.com, executor 2): java.lang.AbstractMethodError: org.apache.hadoop.hbase.spark.HBaseContext.initializeLogIfNecessary(Z)V
    at org.apache.spark.Logging$class.log(Logging.scala:50)
    at org.apache.hadoop.hbase.spark.HBaseContext.log(HBaseContext.scala:60)
    at org.apache.spark.Logging$class.logDebug(Logging.scala:62)
    at org.apache.hadoop.hbase.spark.HBaseContext.logDebug(HBaseContext.scala:60)
    at org.apache.hadoop.hbase.spark.HBaseContext.applyCreds(HBaseContext.scala:235)
    at org.apache.hadoop.hbase.spark.HBaseContext.org$apache$hadoop$hbase$spark$HBaseContext$$hbaseForeachPartition(HBaseContext.scala:482)
    at org.apache.hadoop.hbase.spark.HBaseContext$$anonfun$org$apache$hadoop$hbase$spark$HBaseContext$$bulkMutation$1.apply(HBaseContext.scala:322)
    at org.apache.hadoop.hbase.spark.HBaseContext$$anonfun$org$apache$hadoop$hbase$spark$HBaseContext$$bulkMutation$1.apply(HBaseContext.scala:322)
    at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$33.apply(RDD.scala:920)
    at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$33.apply(RDD.scala:920)
    at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1866)
    at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1866)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
    at org.apache.spark.scheduler.Task.run(Task.scala:89)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:242)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)

Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1457) ~[spark-assembly-1.6.0-cdh5.10.2-hadoop2.6.0-cdh5.10.2.jar:na]
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1445) ~[spark-assembly-1.6.0-cdh5.10.2-hadoop2.6.0-cdh5.10.2.jar:na]
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1444) ~[spark-assembly-1.6.0-cdh5.10.2-hadoop2.6.0-cdh5.10.2.jar:na]

Am I missing any dependency jars or is it due to jar conflict ? Thanks in advance

Solution

  • I was using CDH5.5.7 jars with Spark 1.5.1 but spark-hbase related jars were pointing to cdh5.7.0.

    Then I upgraded the CDH version to 5.10.2 and made all other jars compatible to cdh5.10.2 which resolved AbstractMethodError.