diff --git a/docs/sql-migration-guide.md b/docs/sql-migration-guide.md
index 76df66b9de50c..c6cb52d29344b 100644
--- a/docs/sql-migration-guide.md
+++ b/docs/sql-migration-guide.md
@@ -224,6 +224,8 @@ license: |
 
   - Since Spark 3.0, when casting string value to integral types(tinyint, smallint, int and bigint), datetime types(date, timestamp and interval) and boolean type, the leading and trailing whitespaces (<= ASCII 32) will be trimmed before converted to these type values, e.g. `cast(' 1\t' as int)` results `1`, `cast(' 1\t' as boolean)` results `true`, `cast('2019-10-10\t as date)` results the date value `2019-10-10`. In Spark version 2.4 and earlier, while casting string to integrals and booleans, it will not trim the whitespaces from both ends, the foregoing results will be `null`, while to datetimes, only the trailing spaces (= ASCII 32) will be removed.
 
+  - Since Spark 3.0, An analysis exception will be thrown when hash expressions are applied on elements of MapType. To restore the behavior before Spark 3.0, set `spark.sql.legacy.useHashOnMapType` to true.
+    
   - Since Spark 3.0, numbers written in scientific notation(e.g. `1E2`) would be parsed as Double. In Spark version 2.4 and earlier, they're parsed as Decimal. To restore the behavior before Spark 3.0, you can set `spark.sql.legacy.exponentLiteralAsDecimal.enabled` to `true`.
 
   - Since Spark 3.0, we pad decimal numbers with trailing zeros to the scale of the column for `spark-sql` interface, for example:
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/hash.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/hash.scala
index 52429a63b306d..14d5f25d42d0d 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/hash.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/hash.scala
@@ -32,6 +32,7 @@ import org.apache.spark.sql.catalyst.expressions.codegen._
 import org.apache.spark.sql.catalyst.expressions.codegen.Block._
 import org.apache.spark.sql.catalyst.util.{ArrayData, MapData}
 import org.apache.spark.sql.catalyst.util.DateTimeConstants._
+import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.types._
 import org.apache.spark.unsafe.Platform
 import org.apache.spark.unsafe.hash.Murmur3_x86_32
@@ -232,9 +233,6 @@ case class Crc32(child: Expression) extends UnaryExpression with ImplicitCastInp
  *  - array:              The `result` starts with seed, then use `result` as seed, recursively
  *                        calculate hash value for each element, and assign the element hash value
  *                        to `result`.
- *  - map:                The `result` starts with seed, then use `result` as seed, recursively
- *                        calculate hash value for each key-value, and assign the key-value hash
- *                        value to `result`.
  *  - struct:             The `result` starts with seed, then use `result` as seed, recursively
  *                        calculate hash value for each field, and assign the field hash value to
  *                        `result`.
@@ -249,10 +247,21 @@ abstract class HashExpression[E] extends Expression {
 
   override def nullable: Boolean = false
 
+  private def hasMapType(dt: DataType): Boolean = {
+    dt.existsRecursively(_.isInstanceOf[MapType])
+  }
+
   override def checkInputDataTypes(): TypeCheckResult = {
     if (children.length < 1) {
       TypeCheckResult.TypeCheckFailure(
         s"input to function $prettyName requires at least one argument")
+    } else if (children.exists(child => hasMapType(child.dataType)) &&
+      !SQLConf.get.getConf(SQLConf.LEGACY_USE_HASH_ON_MAPTYPE)) {
+      TypeCheckResult.TypeCheckFailure(
+        s"input to function $prettyName cannot contain elements of MapType. In Spark, same maps " +
+          "may have different hashcode, thus hash expressions are prohibited on MapType " +
+          s"elements. To restore previous behavior set ${SQLConf.LEGACY_USE_HASH_ON_MAPTYPE.key} " +
+          "to true.")
     } else {
       TypeCheckResult.TypeCheckSuccess
     }
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
index 8c5debd28ce56..424ab20d254a6 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
@@ -2205,6 +2205,12 @@ object SQLConf {
       .booleanConf
       .createWithDefault(false)
 
+  val LEGACY_USE_HASH_ON_MAPTYPE = buildConf("spark.sql.legacy.useHashOnMapType")
+    .doc("When set to true, hash expressions can be applied on elements of MapType. Otherwise, " +
+      "an analysis exception will be thrown.")
+    .booleanConf
+    .createWithDefault(false)
+
   /**
    * Holds information about keys that have been deprecated.
    *
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/HashExpressionsSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/HashExpressionsSuite.scala
index e6cf979649c83..68da1faaa8f45 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/HashExpressionsSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/HashExpressionsSuite.scala
@@ -554,28 +554,14 @@ class HashExpressionsSuite extends SparkFunSuite with ExpressionEvalHelper {
       .add("arrayOfString", arrayOfString)
       .add("arrayOfArrayOfString", ArrayType(arrayOfString))
       .add("arrayOfArrayOfInt", ArrayType(ArrayType(IntegerType)))
-      .add("arrayOfMap", ArrayType(mapOfString))
       .add("arrayOfStruct", ArrayType(structOfString))
       .add("arrayOfUDT", arrayOfUDT))
 
-  testHash(
-    new StructType()
-      .add("mapOfIntAndString", MapType(IntegerType, StringType))
-      .add("mapOfStringAndArray", MapType(StringType, arrayOfString))
-      .add("mapOfArrayAndInt", MapType(arrayOfString, IntegerType))
-      .add("mapOfArray", MapType(arrayOfString, arrayOfString))
-      .add("mapOfStringAndStruct", MapType(StringType, structOfString))
-      .add("mapOfStructAndString", MapType(structOfString, StringType))
-      .add("mapOfStruct", MapType(structOfString, structOfString)))
-
   testHash(
     new StructType()
       .add("structOfString", structOfString)
       .add("structOfStructOfString", new StructType().add("struct", structOfString))
       .add("structOfArray", new StructType().add("array", arrayOfString))
-      .add("structOfMap", new StructType().add("map", mapOfString))
-      .add("structOfArrayAndMap",
-        new StructType().add("array", arrayOfString).add("map", mapOfString))
       .add("structOfUDT", structOfUDT))
 
   test("hive-hash for decimal") {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
index d6efb2f91ca0b..6e6dce0bce218 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
@@ -2120,6 +2120,25 @@ class SQLQuerySuite extends QueryTest with SharedSparkSession with AdaptiveSpark
     }
   }
 
+  test("SPARK-27619: Throw analysis exception when hash and xxhash64 is used on MapType") {
+    Seq("hash", "xxhash64").foreach {
+      case hashExpression =>
+        intercept[AnalysisException] {
+          spark.createDataset(Map(1 -> 10, 2 -> 20) :: Nil).selectExpr(s"$hashExpression(*)")
+        }
+    }
+  }
+
+  test("SPARK-27619: when spark.sql.legacy.useHashOnMapType is true, hash can be used on Maptype") {
+    Seq("hash", "xxhash64").foreach {
+      case hashExpression =>
+        withSQLConf(SQLConf.LEGACY_USE_HASH_ON_MAPTYPE.key -> "true") {
+          val df = spark.createDataset(Map() :: Nil)
+          checkAnswer(df.selectExpr(s"$hashExpression(*)"), sql(s"SELECT $hashExpression(map())"))
+        }
+    }
+  }
+
   test("xxhash64 function") {
     val df = Seq(1 -> "a", 2 -> "b").toDF("i", "j")
     withTempView("tbl") {