Ricardo Gaspar created KUDU-2633:
------------------------------------
Summary: Missing documentation about Spark's KuduContext API
Key: KUDU-2633
URL: https://issues.apache.org/jira/browse/KUDU-2633
Project: Kudu
Issue Type: Improvement
Components: api, integration, spark
Affects Versions: 1.7.1, 1.8.0, 1.7.0, 1.6.0
Reporter: Ricardo Gaspar
Right now there's no place to check the documentation about methods belonging
to KuduContext.
The only resources available only show some examples:
[https://kudu.apache.org/docs/developing.html#_spark_integration_best_practices]
Even when including the dependency in the IDE there are no documentation for
each method.
For example, I was getting a SparkException (which does not describe the actual
error) when, accidentally, inserting rows in a table that already had the same
rows. And the method *insertRows* from KuduContext does not mention that an
exception can be thrown.
Exception example:
{code:java}
18/12/05 11:26:35 ERROR core.JobRunShell: Job DEFAULT.EventKpisConsumer threw
an unhandled Exception:
org.apache.spark.SparkException: Job aborted due to stage failure: Aborting
TaskSet 109.0 because task 3 (partition 3) cannot run anywhere due to node and
executor blacklist. Blacklisting behavior can be configured via
spark.blacklist.*.
at
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1524)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1512)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1511)
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at
org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1511)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
at scala.Option.foreach(Option.scala:257)
at
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:814)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1739)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1694)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1683)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at
org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:630)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2031)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2052)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2071)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2096)
at
org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:926)
at
org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:924)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:924)
at
org.apache.spark.sql.Dataset$$anonfun$foreachPartition$1.apply$mcV$sp(Dataset.scala:2340)
at
org.apache.spark.sql.Dataset$$anonfun$foreachPartition$1.apply(Dataset.scala:2340)
at
org.apache.spark.sql.Dataset$$anonfun$foreachPartition$1.apply(Dataset.scala:2340)
at
org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2827)
at org.apache.spark.sql.Dataset.foreachPartition(Dataset.scala:2339)
at
org.apache.kudu.spark.kudu.KuduContext.writeRows(KuduContext.scala:246)
at
org.apache.kudu.spark.kudu.KuduContext.insertRows(KuduContext.scala:197)
at
com.xpandit.bdu.altice.EventKpisKafkaConsumer.run(EventKpisKafkaConsumer.scala:193)
at
com.xpandit.bdu.altice.scheduling.RunnableInterruptableJob.execute(CronScheduler.scala:73)
at org.quartz.core.JobRunShell.run(JobRunShell.java:207)
at
org.quartz.simpl.SimpleThreadPool$WorkerThread.run(SimpleThreadPool.java:560)
{code}
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