apache / apache/parquet-java

Occasional corruption of parquet files , parquet writer might not be calling ParquetFileWriter->end()

Aperta
#2,109 1 commento 0 reazioni 0 assegnatari Vedi su GitHub
Component: Parquet Priority: Major Type: bug
Lingua principale
Java
Stelle
3.1k
Fork
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Merge medio
3g 12h
PR unite (30g)
33

Descrizione

We have a high volume streaming service which works most of the time . But off late we have been observing that some of the parquet files written out by write flow are getting corrupted. This is manifested in our reading flow with the following exception

Writer version - 1.6.0 , Reader version - 1.7.0
Caused by: java.lang.RuntimeException: hdfs://Ingest/ingest/jobs/2017-11-30/00-05/part4139 is not a Parquet file. expected magic number at tail [80, 65, 82, 49] but found [-28, -126, 1, 1]
at org.apache.parquet.hadoop.ParquetFileReader.readFooter(ParquetFileReader.java:422)
at org.apache.parquet.hadoop.ParquetFileReader.readFooter(ParquetFileReader.java:385)
at org.apache.parquet.hadoop.ParquetRecordReader.initializeInternalReader(ParquetRecordReader.java:157)
at org.apache.parquet.hadoop.ParquetRecordReader.initialize(ParquetRecordReader.java:140)
at org.apache.spark.rdd.SqlNewHadoopRDD$$anon$1.(SqlNewHadoopRDD.scala:180)
at org.apache.spark.rdd.SqlNewHadoopRDD.compute(SqlNewHadoopRDD.scala:126)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)```

After looking at the code , i can see that one of the possible causes is/are
1] footer not being serialized in the writer due to end not being called
but we are not seeing any exceptions on the writer.
2] data size - does data size has impact ? There will be cases when row group sizes will be huge as it is activity data of a user

We are using default parquet block size and hdfs block size . Other than upgrading to the latest version and re-test , what are the options we have to debug a issue like this

**Reporter**: [venkata yerubandi](https://issues.apache.org/jira/secure/ViewProfile.jspa?name=raoyvn)

**Note**: *This issue was originally created as [PARQUET-1176](https://issues.apache.org/jira/browse/PARQUET-1176). Please see the [migration documentation](https://issues.apache.org/jira/browse/PARQUET-2502) for further details.*

Guida per i contributori

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Direzione di ricerca

Inizia esaminando le posizioni dello stack trace di ParquetFileReader.readFooter, in particolare ParquetFileReader.java:422, e ispeziona il percorso di scrittura per verificare se viene chiamato ParquetFileWriter->end(). Riproduci la corruzione nel servizio di streaming ad alto volume variando le dimensioni dei row-group e dei blocchi HDFS. Il lavoro è completato quando è stata identificata la causa dell’assenza del magic number finale ed è stato documentato un percorso di debugging o correzione verificato.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Valutazione

Stack tecnologico
java, spark
Ambito
data-engineering
Tipo di issue
Bug
Difficoltà
4/5
Tempo stimato
3-5 giorni
Stato di attività
Ferma
Chiarezza
Da chiarire
Idoneità per principianti
25/100

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