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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2022/10/24 07:15:36 UTC

[GitHub] [spark] cloud-fan commented on a diff in pull request #38047: [SPARK-40609][SQL] Casts types according to bucket info for Equality expressions

cloud-fan commented on code in PR #38047:
URL: https://github.com/apache/spark/pull/38047#discussion_r1002947943


##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercion.scala:
##########
@@ -751,6 +753,49 @@ abstract class TypeCoercionBase {
     }
   }
 
+  /**
+   * Casts types according to bucket info for Equality expression.
+   */
+  object EqualityTypeCasts extends TypeCoercionRule {
+
+    private def isIntegralTypes(exprs: Seq[Expression]): Boolean = {
+      exprs.map(_.dataType).forall {
+        case _: IntegralType => true
+        case DecimalType.Fixed(_, 0) => true
+        case _ => false
+      }
+    }
+
+    override val transform: PartialFunction[Expression, Expression] = {
+      case b @ Equality(l: Attribute, r: Attribute)
+          if b.childrenResolved && l.dataType != r.dataType && isIntegralTypes(b.children) =>
+        // The result type is:
+        // 1. The attribute data type with larger bucket number.
+        // 2. The attribute data type with larger default size if it is not bucketed attribute.

Review Comment:
   I don't get it. Can you explain more? Are you saying that adding cast to either side is correct, and we need to make a decision with least cost?



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