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From "Brad Willard (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-8128) Schema Merging Broken: Dataframe Fails to Recognize Column in Schema
Date Thu, 11 Jun 2015 21:34:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-8128?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Brad Willard updated SPARK-8128:
--------------------------------
    Summary: Schema Merging Broken: Dataframe Fails to Recognize Column in Schema  (was: Dataframe
Fails to Recognize Column in Schema)

> Schema Merging Broken: Dataframe Fails to Recognize Column in Schema
> --------------------------------------------------------------------
>
>                 Key: SPARK-8128
>                 URL: https://issues.apache.org/jira/browse/SPARK-8128
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark, Spark Core
>    Affects Versions: 1.3.0, 1.3.1, 1.4.0
>            Reporter: Brad Willard
>
> I'm loading a folder of parquet files with about 600 parquet files and loading it into
one dataframe so schema merging is involved. There is some bug with the schema merging that
you print the schema and it shows and attributes. However when you run a query and filter
on that attribute is errors saying it's not in the schema.
> I think this bug could be related to an attribute name being reused in a nested object.
 "mediaProcessingState" appears twice in the schema and is the problem.
> sdf = sql_context.parquet('/parquet/big_data_folder')
> sdf.printSchema()
> root
>  |-- _id: string (nullable = true)
>  |-- addedOn: string (nullable = true)
>  |-- attachment: string (nullable = true)
>  .......
> |-- items: array (nullable = true)
>  |    |-- element: struct (containsNull = true)
>  |    |    |-- _id: string (nullable = true)
>  |    |    |-- addedOn: string (nullable = true)
>  |    |    |-- authorId: string (nullable = true)
>  |    |    |-- mediaProcessingState: long (nullable = true)
>  |-- mediaProcessingState: long (nullable = true)
>  |-- title: string (nullable = true)
>  |-- key: string (nullable = true)
> sdf.filter(sdf.mediaProcessingState == 3).count()
> causes this exception
> Py4JJavaError: An error occurred while calling o67.count.
> : org.apache.spark.SparkException: Job aborted due to stage failure: Task 1106 in stage
4.0 failed 30 times, most recent failure: Lost task 1106.29 in stage 4.0 (TID 70565, XXXXXXXXXXXXXXX):
java.lang.IllegalArgumentException: Column [mediaProcessingState] was not found in schema!
>     at parquet.Preconditions.checkArgument(Preconditions.java:47)
>     at parquet.filter2.predicate.SchemaCompatibilityValidator.getColumnDescriptor(SchemaCompatibilityValidator.java:172)
>     at parquet.filter2.predicate.SchemaCompatibilityValidator.validateColumn(SchemaCompatibilityValidator.java:160)
>     at parquet.filter2.predicate.SchemaCompatibilityValidator.validateColumnFilterPredicate(SchemaCompatibilityValidator.java:142)
>     at parquet.filter2.predicate.SchemaCompatibilityValidator.visit(SchemaCompatibilityValidator.java:76)
>     at parquet.filter2.predicate.SchemaCompatibilityValidator.visit(SchemaCompatibilityValidator.java:41)
>     at parquet.filter2.predicate.Operators$Eq.accept(Operators.java:162)
>     at parquet.filter2.predicate.SchemaCompatibilityValidator.validate(SchemaCompatibilityValidator.java:46)
>     at parquet.filter2.compat.RowGroupFilter.visit(RowGroupFilter.java:41)
>     at parquet.filter2.compat.RowGroupFilter.visit(RowGroupFilter.java:22)
>     at parquet.filter2.compat.FilterCompat$FilterPredicateCompat.accept(FilterCompat.java:108)
>     at parquet.filter2.compat.RowGroupFilter.filterRowGroups(RowGroupFilter.java:28)
>     at parquet.hadoop.ParquetRecordReader.initializeInternalReader(ParquetRecordReader.java:158)
>     at parquet.hadoop.ParquetRecordReader.initialize(ParquetRecordReader.java:138)
>     at org.apache.spark.rdd.NewHadoopRDD$$anon$1.<init>(NewHadoopRDD.scala:133)
>     at org.apache.spark.rdd.NewHadoopRDD.compute(NewHadoopRDD.scala:104)
>     at org.apache.spark.rdd.NewHadoopRDD.compute(NewHadoopRDD.scala:66)
>     at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
>     at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
>     at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
>     at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
>     at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
>     at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
>     at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
>     at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
>     at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
>     at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
>     at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
>     at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
>     at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
>     at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
>     at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
>     at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
>     at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
>     at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
>     at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
>     at org.apache.spark.scheduler.Task.run(Task.scala:64)
>     at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
>     at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>     at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>     at java.lang.Thread.run(Thread.java:745)
> You also get the same error if you register it as a temp table and try to execute the
same sql query.



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