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Posted to issues@spark.apache.org by "Cheng Lian (JIRA)" <ji...@apache.org> on 2017/01/26 18:34:25 UTC
[jira] [Commented] (SPARK-18539) Cannot filter by nonexisting
column in parquet file
[ https://issues.apache.org/jira/browse/SPARK-18539?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15840186#comment-15840186 ]
Cheng Lian commented on SPARK-18539:
------------------------------------
[~viirya], sorry for the (super) late reply. What I mentioned was a *nullable* column instead of a *null* column. To be more specific, say we have two Parquet files:
- File {{A}} has columns {{<a, b>}}
- File {{B}} has columns {{<a, b, c>}}, where {{c}} is marked as nullable (or {{optional}} in the term of Parquet)
Then it should be fine to treat these two files as a single dataset with a merged schema {{<a, b, c>}} and you should be able to push down predicates involving {{c}}.
BTW, the Parquet community just made a patch release 1.8.2 that includes a fix for PARQUET-389 and we probably will upgrade to 1.8.2 in 2.2.0. Then we'll have a proper fix for this issue and remove the workaround we did while doing schema merging.
> Cannot filter by nonexisting column in parquet file
> ---------------------------------------------------
>
> Key: SPARK-18539
> URL: https://issues.apache.org/jira/browse/SPARK-18539
> Project: Spark
> Issue Type: Bug
> Affects Versions: 2.0.1, 2.0.2
> Reporter: Vitaly Gerasimov
> Priority: Critical
>
> {code}
> import org.apache.spark.SparkConf
> import org.apache.spark.sql.SparkSession
> import org.apache.spark.sql.types.DataTypes._
> import org.apache.spark.sql.types.{StructField, StructType}
> val sc = SparkSession.builder().config(new SparkConf().setMaster("local")).getOrCreate()
> val jsonRDD = sc.sparkContext.parallelize(Seq("""{"a":1}"""))
> sc.read
> .schema(StructType(Seq(StructField("a", IntegerType))))
> .json(jsonRDD)
> .write
> .parquet("/tmp/test")
> sc.read
> .schema(StructType(Seq(StructField("a", IntegerType), StructField("b", IntegerType, nullable = true))))
> .load("/tmp/test")
> .createOrReplaceTempView("table")
> sc.sql("select b from table where b is not null").show()
> {code}
> returns:
> {code}
> 16/11/22 17:43:47 ERROR Executor: Exception in task 0.0 in stage 1.0 (TID 1)
> java.lang.IllegalArgumentException: Column [b] was not found in schema!
> at org.apache.parquet.Preconditions.checkArgument(Preconditions.java:55)
> at org.apache.parquet.filter2.predicate.SchemaCompatibilityValidator.getColumnDescriptor(SchemaCompatibilityValidator.java:190)
> at org.apache.parquet.filter2.predicate.SchemaCompatibilityValidator.validateColumn(SchemaCompatibilityValidator.java:178)
> at org.apache.parquet.filter2.predicate.SchemaCompatibilityValidator.validateColumnFilterPredicate(SchemaCompatibilityValidator.java:160)
> at org.apache.parquet.filter2.predicate.SchemaCompatibilityValidator.visit(SchemaCompatibilityValidator.java:100)
> at org.apache.parquet.filter2.predicate.SchemaCompatibilityValidator.visit(SchemaCompatibilityValidator.java:59)
> at org.apache.parquet.filter2.predicate.Operators$NotEq.accept(Operators.java:194)
> at org.apache.parquet.filter2.predicate.SchemaCompatibilityValidator.validate(SchemaCompatibilityValidator.java:64)
> at org.apache.parquet.filter2.compat.RowGroupFilter.visit(RowGroupFilter.java:59)
> at org.apache.parquet.filter2.compat.RowGroupFilter.visit(RowGroupFilter.java:40)
> at org.apache.parquet.filter2.compat.FilterCompat$FilterPredicateCompat.accept(FilterCompat.java:126)
> at org.apache.parquet.filter2.compat.RowGroupFilter.filterRowGroups(RowGroupFilter.java:46)
> at org.apache.spark.sql.execution.datasources.parquet.SpecificParquetRecordReaderBase.initialize(SpecificParquetRecordReaderBase.java:110)
> at org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.initialize(VectorizedParquetRecordReader.java:109)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat$$anonfun$buildReader$1.apply(ParquetFileFormat.scala:367)
> at org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat$$anonfun$buildReader$1.apply(ParquetFileFormat.scala:341)
> at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:116)
> at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:91)
> at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.scan_nextBatch$(Unknown Source)
> at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
> at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370)
> at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:246)
> at org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:240)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803)
> at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:803)
> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
> at org.apache.spark.scheduler.Task.run(Task.scala:86)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
> 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)
> {code}
> expected result:
> {code}
> +---+
> | b|
> +---+
> +---+
> {code}
> It works fine in 2.0.0 and 1.6.2. However, if I only select the nonexisting column (without filter) it also works fine.
> Query plan:
> {code}
> == Parsed Logical Plan ==
> 'Project ['b]
> +- 'Filter isnotnull('b)
> +- 'UnresolvedRelation `table`
> == Analyzed Logical Plan ==
> b: int
> Project [b#8]
> +- Filter isnotnull(b#8)
> +- SubqueryAlias table
> +- Relation[a#7,b#8] parquet
> == Optimized Logical Plan ==
> Project [b#8]
> +- Filter isnotnull(b#8)
> +- Relation[a#7,b#8] parquet
> == Physical Plan ==
> *Project [b#8]
> +- *Filter isnotnull(b#8)
> +- *BatchedScan parquet [b#8] Format: ParquetFormat, InputPaths: file:/tmp/test, PartitionFilters: [], PushedFilters: [IsNotNull(b)], ReadSchema: struct<b:int>
> {code}
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