olaky commented on code in PR #39408:
URL: https://github.com/apache/spark/pull/39408#discussion_r1063498040
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sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileSourceStrategy.scala:
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@@ -258,6 +258,24 @@ object FileSourceStrategy extends Strategy with
PredicateHelper with Logging {
val outputAttributes = readDataColumns ++ generatedMetadataColumns ++
partitionColumns ++ constantMetadataColumns
+
+ // The metadata attribute references in the filters also have to be
categorized as either
+ // constant or generated metadata attributes. Only data filters can
contain metadata filters.
+ def categorizeFileSourceMetadataAttributesInFilters(
+ filters: Seq[Expression]): Seq[Expression] =
+ filters.map { filter =>
+ filter.transform {
+ case attr: AttributeReference if
FileSourceMetadataAttribute.unapply(attr).isDefined =>
+ if (attr.dataType.asInstanceOf[StructType].fieldNames
+ .forall(fieldName => constantMetadataColumns.exists(fieldName
== _.name))) {
Review Comment:
That is a really good idea, I did settle for something along those lines: I
am rebinding the references to the flattened columns. This way the filters do
again reference columns that are actually part of the schema
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