[jira] [Created] (HUDI-468) Not an avro data file - error while archiving post rename() change

["Vinoth Chandar (Jira)" <ji...@apache.org>]

Vinoth Chandar created HUDI-468:
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             Summary: Not an avro data file - error while archiving post rename() change
                 Key: HUDI-468
                 URL: https://issues.apache.org/jira/browse/HUDI-468
             Project: Apache Hudi (incubating)
          Issue Type: Bug
          Components: Write Client
            Reporter: Vinoth Chandar
            Assignee: Balaji Varadarajan
             Fix For: 0.5.1


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|http://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|http://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
19/12/24 13:34:09 ERROR HoodieCommitArchiveLog: Failed to archive commits, .commit file: 20191224132942.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|http://org.apache.hudi.io/].HoodieCommitArchiveLog.convertToAvroRecord(HoodieCommitArchiveLog.java:294)
at [org.apache.hudi.io|http://org.apache.hudi.io/].HoodieCommitArchiveLog.archive(HoodieCommitArchiveLog.java:253)
at [org.apache.hudi.io|http://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)



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