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Posted to issues@spark.apache.org by "François Garillot (JIRA)" <ji...@apache.org> on 2015/07/29 22:20:05 UTC
[jira] [Commented] (SPARK-9442) java.lang.ArithmeticException: / by
zero when reading Parquet
[ https://issues.apache.org/jira/browse/SPARK-9442?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14646692#comment-14646692 ]
François Garillot commented on SPARK-9442:
------------------------------------------
This may not be a Spark issue, but rather a Parquet Hadoop Reader issue. It looks like the total time spent reading may be reported wrong here:
https://github.com/Parquet/parquet-mr/blob/master/parquet-hadoop/src/main/java/parquet/hadoop/InternalParquetRecordReader.java#L110
Note this function outputs log messages that look like:
"Assembled and processed x records from y columns in t ms: n rec/ms, p cell/ms"
Do you see any of those, turning logging on at the info level ?
> java.lang.ArithmeticException: / by zero when reading Parquet
> -------------------------------------------------------------
>
> Key: SPARK-9442
> URL: https://issues.apache.org/jira/browse/SPARK-9442
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.4.1
> Reporter: DB Tsai
>
> I am counting how many records in my nested parquet file with this schema,
> {code}
> scala> u1aTesting.printSchema
> root
> |-- profileId: long (nullable = true)
> |-- country: string (nullable = true)
> |-- data: array (nullable = true)
> | |-- element: struct (containsNull = true)
> | | |-- videoId: long (nullable = true)
> | | |-- date: long (nullable = true)
> | | |-- label: double (nullable = true)
> | | |-- weight: double (nullable = true)
> | | |-- features: vector (nullable = true)
> {code}
> and the number of the records in the nested data array is around 10k, and each of the parquet file is around 600MB. The total size is around 120GB.
> I am doing a simple count
> {code}
> scala> u1aTesting.count
> parquet.io.ParquetDecodingException: Can not read value at 100 in block 0 in file hdfs://compute-1.amazonaws.com:9000/users/dbtsai/testing/u1old/20150721/part-r-00115-d70c946b-b0f0-45fe-9965-b9f062b9ec6d.gz.parquet
> at parquet.hadoop.InternalParquetRecordReader.nextKeyValue(InternalParquetRecordReader.java:213)
> at parquet.hadoop.ParquetRecordReader.nextKeyValue(ParquetRecordReader.java:204)
> at org.apache.spark.sql.sources.SqlNewHadoopRDD$$anon$1.hasNext(SqlNewHadoopRDD.scala:163)
> at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at org.apache.spark.sql.execution.Aggregate$$anonfun$doExecute$1$$anonfun$6.apply(Aggregate.scala:129)
> at org.apache.spark.sql.execution.Aggregate$$anonfun$doExecute$1$$anonfun$6.apply(Aggregate.scala:126)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$17.apply(RDD.scala:686)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$17.apply(RDD.scala:686)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:70)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
> at org.apache.spark.scheduler.Task.run(Task.scala:70)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
> 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)
> Caused by: java.lang.ArithmeticException: / by zero
> at parquet.hadoop.InternalParquetRecordReader.checkRead(InternalParquetRecordReader.java:109)
> at parquet.hadoop.InternalParquetRecordReader.nextKeyValue(InternalParquetRecordReader.java:193)
> ... 21 more
> {code}
> BTW, no all the tasks fail, and some of them are successful.
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