[HUDI-453] Throw failed to archive commits error when writing data to MOR/COW table

• Type: Bug
• Status: Closed
• Priority: Major
• Resolution: Fixed
• Fix Version/s: 0.5.1
• Component/s: writer-core
• Labels: pull-request-available
• Assignee: lamber-ken
• Reporter: lamber-ken
• Created: 23/Dec/19 17:32
• Updated: 03/Feb/20 03:16
• Resolved: 30/Dec/19 19:52

Description

Throw failed to archive commits error when writing data to table, here are reproduce steps.

1, Build from latest source

mvn clean package -DskipTests -DskipITs -Dcheckstyle.skip=true -Drat.skip=true

2, Write Data

export SPARK_HOME=/work/BigData/install/spark/spark-2.3.3-bin-hadoop2.6
${SPARK_HOME}/bin/spark-shell --jars `ls packaging/hudi-spark-bundle/target/hudi-spark-bundle-*.*.*-SNAPSHOT.jar` --conf 'spark.serializer=org.apache.spark.serializer.KryoSerializer'

import org.apache.spark.sql.SaveMode._

var datas = List("{ \"name\": \"kenken\", \"ts\": 1574297893836, \"age\": 12, \"location\": \"latitude\"}")
val df = spark.read.json(spark.sparkContext.parallelize(datas, 2))
df.write.format("org.apache.hudi").
    option("hoodie.insert.shuffle.parallelism", "10").
    option("hoodie.upsert.shuffle.parallelism", "10").
    option("hoodie.delete.shuffle.parallelism", "10").
    option("hoodie.bulkinsert.shuffle.parallelism", "10").
    option("hoodie.datasource.write.recordkey.field", "name").
    option("hoodie.datasource.write.partitionpath.field", "location").
    option("hoodie.datasource.write.precombine.field", "ts").
    option("hoodie.table.name", "hudi_mor_table").
    mode(Overwrite).
    save("file:///tmp/hudi_mor_table")

3, Append Data

df.write.format("org.apache.hudi").
    option("hoodie.insert.shuffle.parallelism", "10").
    option("hoodie.upsert.shuffle.parallelism", "10").
    option("hoodie.delete.shuffle.parallelism", "10").
    option("hoodie.bulkinsert.shuffle.parallelism", "10").
    option("hoodie.datasource.write.recordkey.field", "name").
    option("hoodie.datasource.write.partitionpath.field", "location").
    option("hoodie.datasource.write.precombine.field", "ts").
    option("hoodie.keep.max.commits", "5").
    option("hoodie.keep.min.commits", "4").
    option("hoodie.cleaner.commits.retained", "3").
    option("hoodie.table.name", "hudi_mor_table").
    mode(Append).
    save("file:///tmp/hudi_mor_table")

4, Repeat about six times Append Data operation(above), will get the stackstrace

19/12/23 01:30:48 ERROR HoodieCommitArchiveLog: Failed to archive commits, .commit file: 20191224004558.clean.requested
java.io.IOException: Not an Avro data file
at org.apache.avro.file.DataFileReader.openReader(DataFileReader.java:50)
at org.apache.hudi.common.util.AvroUtils.deserializeAvroMetadata(AvroUtils.java:147)
at org.apache.hudi.common.util.CleanerUtils.getCleanerPlan(CleanerUtils.java:88)
at org.apache.hudi.io.HoodieCommitArchiveLog.convertToAvroRecord(HoodieCommitArchiveLog.java:294)
at org.apache.hudi.io.HoodieCommitArchiveLog.archive(HoodieCommitArchiveLog.java:253)
at org.apache.hudi.io.HoodieCommitArchiveLog.archiveIfRequired(HoodieCommitArchiveLog.java:122)
at org.apache.hudi.HoodieWriteClient.commit(HoodieWriteClient.java:562)
at org.apache.hudi.HoodieWriteClient.commit(HoodieWriteClient.java:523)
at org.apache.hudi.HoodieWriteClient.commit(HoodieWriteClient.java:514)
at org.apache.hudi.HoodieSparkSqlWriter$.write(HoodieSparkSqlWriter.scala:159)
at org.apache.hudi.DefaultSource.createRelation(DefaultSource.scala:91)
at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:45)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:86)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:656)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:656)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:656)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:273)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:267)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:225)

Issue Links

• links to: GitHub Pull Request #1128