cloud-fan commented on code in PR #39408:
URL: https://github.com/apache/spark/pull/39408#discussion_r1069078184
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sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PartitioningAwareFileIndex.scala:
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@@ -76,28 +76,34 @@ abstract class PartitioningAwareFileIndex(
// be applied to files.
val fileMetadataFilterOpt = dataFilters.filter { f =>
f.references.nonEmpty && f.references.forall {
- case FileSourceMetadataAttribute(_) => true
+ case FileSourceConstantMetadataAttribute(_) => true
case _ => false
}
}.reduceOption(expressions.And)
- // - create a bound references for filters: put the metadata struct at 0
position for each file
- // - retrieve the final metadata struct (could be pruned) from filters
+ // - Retrieve all required metadata attributes and put them into a sequence
+ // - Bind all file constant metadata attribute references to their
respective index
+ val requiredMetadataColumnNames: mutable.Buffer[String] =
mutable.Buffer.empty
Review Comment:
is this really helpful? All the values are already in memory. We just need
to build a row and evaluate the filter. Doing column pruning doesn't seem to
help for this case.
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