[jira] [Reopened] (HUDI-2487) An empty message in Kafka causes a task exception

["sivabalan narayanan (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/HUDI-2487?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

sivabalan narayanan reopened HUDI-2487:
---------------------------------------

> An empty message in Kafka causes a task exception
> -------------------------------------------------
>
>                 Key: HUDI-2487
>                 URL: https://issues.apache.org/jira/browse/HUDI-2487
>             Project: Apache Hudi
>          Issue Type: Improvement
>          Components: DeltaStreamer
>            Reporter: qianchutao
>            Assignee: qianchutao
>            Priority: Major
>              Labels: easyfix, newbie, pull-request-available
>             Fix For: 0.10.0
>
>   Original Estimate: 24h
>  Remaining Estimate: 24h
>
> h1. Question:
>       When I use deltaStreamer to update hive tables in upsert mode from json data in Kafka to HUDi, if the value of the message body in Kafka is null, the task throws an exception.
> h2. Exception description:
> Lost task 0.1 in stage 2.0 (TID 24, node-group-1UtpO.1f562475-6982-4b16-a50d-d19b0ebff950.com, executor 6): org.apache.hudi.exception.HoodieException: The value of tmSmp can not be null
>  at org.apache.hudi.avro.HoodieAvroUtils.getNestedFieldVal(HoodieAvroUtils.java:463)
>  at org.apache.hudi.utilities.deltastreamer.DeltaSync.lambda$readFromSource$d62e16$1(DeltaSync.java:389)
>  at org.apache.spark.api.java.JavaPairRDD$$anonfun$toScalaFunction$1.apply(JavaPairRDD.scala:1040)
>  at scala.collection.Iterator$$anon$11.next(Iterator.scala:410)
>  at scala.collection.Iterator$$anon$11.next(Iterator.scala:410)
>  at org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:196)
>  at org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:62)
>  at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:58)
>  at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:102)
>  at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55)
>  at org.apache.spark.scheduler.Task.run(Task.scala:123)
>  at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:413)
>  at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1551)
>  at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:419)
>  at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
>  at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
>  at java.lang.Thread.run(Thread.java:748)
> h1. The task Settings:
>  
> {code:java}
> hoodie.datasource.write.precombine.field=tmSmp
> hoodie.datasource.write.recordkey.field=subOrderId,activityId,ticketId
> hoodie.datasource.hive_sync.partition_fields=db,dt
> hoodie.datasource.write.partitionpath.field=db:SIMPLE,dt:SIMPLE
> hoodie.datasource.write.keygenerator.class=org.apache.hudi.keygen.CustomKeyGenerator
> hoodie.datasource.hive_sync.enable=true
> hoodie.datasource.meta.sync.enable=true
> hoodie.datasource.hive_sync.partition_extractor_class=org.apache.hudi.hive.MultiPartKeysValueExtractor
> hoodie.datasource.hive_sync.support_timestamp=true
> hoodie.datasource.hive_sync.auto_create_database=true
> hoodie.meta.sync.client.tool.class=org.apache.hudi.hive.HiveSyncTool
> hoodie.datasource.hive_sync.base_file_format=PARQUET
> {code}
>  
>  
> h1. Spark-submit Script parameter Settings:
>  
> {code:java}
> --class org.apache.hudi.utilities.deltastreamer.HoodieDeltaStreamer
> --source-ordering-field tmSmp \
> --table-type MERGE_ON_READ  \
> --target-table ${TABLE_NAME} \
> --source-class org.apache.hudi.utilities.sources.JsonKafkaSource \
> --schemaprovider-class org.apache.hudi.utilities.schema.FilebasedSchemaProvider \
> --enable-sync \
> --op UPSERT \
> --continuous \
> {code}
>  
>  
>        So I think some optimizations can be made to prevent task throwing, such as filtering messages with a null value in Kafka.
>  



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