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