[SPARK-24276][SQL] Order of literals in IN should not affect semantic equality

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Canonicalize.scala

@@ -30,6 +30,7 @@ package org.apache.spark.sql.catalyst.expressions
  *    by `hashCode`.
  *  - [[EqualTo]] and [[EqualNullSafe]] are reordered by `hashCode`.
  *  - Other comparisons ([[GreaterThan]], [[LessThan]]) are reversed by `hashCode`.
+ *  - Elements in [[In]] are reordered by `hashCode`.
  */
 object Canonicalize {
   def execute(e: Expression): Expression = {
@@ -85,6 +86,11 @@ object Canonicalize {
     case Not(GreaterThanOrEqual(l, r)) => LessThan(l, r)
     case Not(LessThanOrEqual(l, r)) => GreaterThan(l, r)
 
+    // order the list in the In operator
+    // In subqueries contain only one element of type ListQuery. So checking that the length > 1
+    // we are not reordering In subqueries.
+    case In(value, list) if list.length > 1 => In(value, list.sortBy(_.hashCode()))
+
     case _ => e
   }
 }

sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/CanonicalizeSuite.scala

@@ -0,0 +1,53 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.catalyst.expressions
+
+import org.apache.spark.SparkFunSuite
+import org.apache.spark.sql.catalyst.dsl.plans._
+import org.apache.spark.sql.catalyst.plans.logical.Range
+
+class CanonicalizeSuite extends SparkFunSuite {
+
+  test("SPARK-24276: IN expression with different order are semantically equal") {
+    val range = Range(1, 1, 1, 1)
+    val idAttr = range.output.head
+
+    val in1 = In(idAttr, Seq(Literal(1), Literal(2)))
+    val in2 = In(idAttr, Seq(Literal(2), Literal(1)))
+    val in3 = In(idAttr, Seq(Literal(1), Literal(2), Literal(3)))
+
+    assert(in1.canonicalized.semanticHash() == in2.canonicalized.semanticHash())
+    assert(in1.canonicalized.semanticHash() != in3.canonicalized.semanticHash())
+
+    assert(range.where(in1).sameResult(range.where(in2)))
+    assert(!range.where(in1).sameResult(range.where(in3)))
+
+    val arrays1 = In(idAttr, Seq(CreateArray(Seq(Literal(1), Literal(2))),
+      CreateArray(Seq(Literal(2), Literal(1)))))
+    val arrays2 = In(idAttr, Seq(CreateArray(Seq(Literal(2), Literal(1))),
+      CreateArray(Seq(Literal(1), Literal(2)))))
+    val arrays3 = In(idAttr, Seq(CreateArray(Seq(Literal(1), Literal(2))),
+      CreateArray(Seq(Literal(3), Literal(1)))))
+
+    assert(arrays1.canonicalized.semanticHash() == arrays2.canonicalized.semanticHash())
+    assert(arrays1.canonicalized.semanticHash() != arrays3.canonicalized.semanticHash())
+
+    assert(range.where(arrays1).sameResult(range.where(arrays2)))
+    assert(!range.where(arrays1).sameResult(range.where(arrays3)))
+  }
+}