cloud-fan commented on code in PR #43585:
URL: https://github.com/apache/spark/pull/43585#discussion_r1377522350
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/InjectRuntimeFilter.scala:
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@@ -26,47 +26,27 @@ import org.apache.spark.sql.catalyst.plans.logical._
import org.apache.spark.sql.catalyst.rules.Rule
import org.apache.spark.sql.catalyst.trees.TreePattern.{INVOKE,
JSON_TO_STRUCT, LIKE_FAMLIY, PYTHON_UDF, REGEXP_EXTRACT_FAMILY, REGEXP_REPLACE,
SCALA_UDF}
import org.apache.spark.sql.internal.SQLConf
-import org.apache.spark.sql.types._
/**
* Insert a runtime filter on one side of the join (we call this side the
application side) if
* we can extract a runtime filter from the other side (creation side). A
simple case is that
* the creation side is a table scan with a selective filter.
- * The runtime filter is logically an IN subquery with the join keys
(converted to a semi join),
- * but can be something different physically, such as a bloom filter.
+ * The runtime filter is logically an IN subquery with the join keys.
Currently it's always
Review Comment:
This is correct, bloom filter is logically an IN subquery but has false
positive.
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