[GitHub] [spark] kiszk commented on a change in pull request #23171: [SPARK-26205][SQL] Optimize InSet Expression for bytes, shorts, ints, dates

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kiszk commented on a change in pull request #23171: [SPARK-26205][SQL] Optimize InSet Expression for bytes, shorts, ints, dates
URL: https://github.com/apache/spark/pull/23171#discussion_r261882937
 
 

 ##########
 File path: sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/PredicateSuite.scala
 ##########
 @@ -241,6 +242,52 @@ class PredicateSuite extends SparkFunSuite with ExpressionEvalHelper {
     }
   }
 
+  test("SPARK-26205: Optimize InSet for bytes, shorts, ints, dates using switch statements") {
+    val byteValues = Set[Any](1.toByte, 2.toByte, Byte.MinValue, Byte.MaxValue)
+    val shortValues = Set[Any](-10.toShort, 20.toShort, Short.MinValue, Short.MaxValue)
+    val intValues = Set[Any](20, -100, 30, Int.MinValue, Int.MaxValue)
+    val dateValues = Set[Any](
+      CatalystTypeConverters.convertToCatalyst(Date.valueOf("2017-01-01")),
+      CatalystTypeConverters.convertToCatalyst(Date.valueOf("1950-01-02")))
+
+    def check(presentValue: Expression, absentValue: Expression, values: Set[Any]): Unit = {
+      require(presentValue.dataType == absentValue.dataType)
+
+      val nullLiteral = Literal(null, presentValue.dataType)
+
+      checkEvaluation(InSet(nullLiteral, values), expected = null)
+      checkEvaluation(InSet(nullLiteral, values + null), expected = null)
+      checkEvaluation(InSet(presentValue, values), expected = true)
+      checkEvaluation(InSet(presentValue, values + null), expected = true)
+      checkEvaluation(InSet(absentValue, values), expected = false)
+      checkEvaluation(InSet(absentValue, values + null), expected = null)
+    }
+
+    def checkAllTypes(): Unit = {
+      check(presentValue = Literal(2.toByte), absentValue = Literal(3.toByte), byteValues)
+      check(presentValue = Literal(Byte.MinValue), absentValue = Literal(5.toByte), byteValues)
+      check(presentValue = Literal(20.toShort), absentValue = Literal(-14.toShort), shortValues)
+      check(presentValue = Literal(Short.MaxValue), absentValue = Literal(30.toShort), shortValues)
+      check(presentValue = Literal(20), absentValue = Literal(-14), intValues)
+      check(presentValue = Literal(Int.MinValue), absentValue = Literal(2), intValues)
+      check(
+        presentValue = Literal(Date.valueOf("2017-01-01")),
+        absentValue = Literal(Date.valueOf("2017-01-02")),
+        dateValues)
+      check(
+        presentValue = Literal(Date.valueOf("1950-01-02")),
+        absentValue = Literal(Date.valueOf("2017-10-02")),
+        dateValues)
+    }
+
+    withSQLConf(SQLConf.OPTIMIZER_INSET_SWITCH_THRESHOLD.key -> "0") {
+      checkAllTypes()
+    }
+    withSQLConf(SQLConf.OPTIMIZER_INSET_SWITCH_THRESHOLD.key -> "20") {
+      checkAllTypes()
+    }
+  }
 
 Review comment:
   My question addressed what you are talking [here](https://github.com/apache/spark/pull/23171/files#r261253221). The current implementation can accept large int value (e.g. Integer.MAX) for `spark.sql.optimizer.inSetSwitchThreshold`. Thus, I am afraid switch code requires more than 64KB java byte code.
   If the option would have the appropriate upper limit, it is fine.

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