[GitHub] [spark] gengliangwang commented on a change in pull request #29075: [SPARK-32284][SQL] Avoid expanding too many CNF predicates in partition pruning

[GitBox <gi...@apache.org>]

gengliangwang commented on a change in pull request #29075:
URL: https://github.com/apache/spark/pull/29075#discussion_r453408669



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File path: sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/PruneHiveTablePartitions.scala
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@@ -54,9 +55,15 @@ private[sql] class PruneHiveTablePartitions(session: SparkSession)
     val normalizedFilters = DataSourceStrategy.normalizeExprs(
       filters.filter(f => f.deterministic && !SubqueryExpression.hasSubquery(f)), relation.output)
     val partitionColumnSet = AttributeSet(relation.partitionCols)
-    ExpressionSet(normalizedFilters.filter { f =>
+    val (partitionFilters, remainingFilters) = normalizedFilters.partition { f =>
       !f.references.isEmpty && f.references.subsetOf(partitionColumnSet)
-    })
+    }
+    // Try extracting more convertible partition filters from the remaining filters by converting
+    // them into CNF.
+    val remainingFilterInCnf = remainingFilters.flatMap(CNFConversion)
+    val extraPartitionFilters = remainingFilterInCnf.filter(f =>
+      !f.references.isEmpty && f.references.subsetOf(partitionColumnSet))
+    ExpressionSet(partitionFilters ++ extraPartitionFilters)

Review comment:
       The `filters` here is already processed with `splitConjunctivePredicates` in `PhysicalOperation.unapply`. That's why the original code before #28805 doesn't call `splitConjunctivePredicates` either.




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