[HUDI-2487] An empty message in Kafka causes a task exception

• Type: Improvement
• Status: Resolved
• Priority: Major
• Resolution: Fixed
• Fix Version/s: 0.10.0
• Component/s: deltastreamer
• Labels: easyfix newbie pull-request-available
• Assignee: qianchutao
• Reporter: qianchutao
• Due: 30/Sep/21
• Created: 25/Sep/21 06:12
• Updated: 03/Nov/21 11:27
• Resolved: 03/Nov/21 11:27

Description

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.

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)

The task Settings:

 

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

 

 

Spark-submit Script parameter Settings:

 

--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 \

 

 

       So I think some optimizations can be made to prevent task throwing, such as filtering messages with a null value in Kafka.

 

Issue Links

• links to: GitHub Pull Request #3715