vladimirg-db commented on code in PR #48222:
URL: https://github.com/apache/spark/pull/48222#discussion_r1773690351
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sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala:
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@@ -759,6 +759,14 @@ object SQLConf {
.checkValue(_ > 0, "The initial number of partitions must be positive.")
.createOptional
+ lazy val TRIM_COLLATION_ENABLED =
+ buildConf("spark.sql.collation.trim.enabled")
+ .doc("Trim collation feature is under development and its use should be
done under this" +
Review Comment:
Would be nice to have a description for this feature here.
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sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/rules.scala:
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@@ -640,6 +639,26 @@ case class QualifyLocationWithWarehouse(catalog:
SessionCatalog) extends Rule[Lo
}
}
+object TrimCollationCheck extends (LogicalPlan => Unit) {
Review Comment:
Sure.
- The rules run in fixed point (many iterations) over the whole logical
plan, which can be super slow for big logical plans. Every new rule slows down
those corner cases.
- Analyzer logic depends on the ordering of rules, which is very hard to get
right, and there are frequent regressions related to unobvious outcome of some
new rule.
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