diff --git a/python/pyspark/sql/functions.py b/python/pyspark/sql/functions.py
index 925ac34196f4c..8490081facc5a 100644
--- a/python/pyspark/sql/functions.py
+++ b/python/pyspark/sql/functions.py
@@ -1855,6 +1855,21 @@ def array_contains(col, value):
     return Column(sc._jvm.functions.array_contains(_to_java_column(col), value))
 
 
+@since(2.4)
+def arrays_overlap(a1, a2):
+    """
+    Collection function: returns true if the arrays contain any common non-null element; if not,
+    returns null if both the arrays are non-empty and any of them contains a null element; returns
+    false otherwise.
+
+    >>> df = spark.createDataFrame([(["a", "b"], ["b", "c"]), (["a"], ["b", "c"])], ['x', 'y'])
+    >>> df.select(arrays_overlap(df.x, df.y).alias("overlap")).collect()
+    [Row(overlap=True), Row(overlap=False)]
+    """
+    sc = SparkContext._active_spark_context
+    return Column(sc._jvm.functions.arrays_overlap(_to_java_column(a1), _to_java_column(a2)))
+
+
 @since(2.4)
 def slice(x, start, length):
     """
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/FunctionRegistry.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/FunctionRegistry.scala
index 9c370599bc0df..867c2d5eab53d 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/FunctionRegistry.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/FunctionRegistry.scala
@@ -410,6 +410,7 @@ object FunctionRegistry {
     // collection functions
     expression[CreateArray]("array"),
     expression[ArrayContains]("array_contains"),
+    expression[ArraysOverlap]("arrays_overlap"),
     expression[ArrayJoin]("array_join"),
     expression[ArrayPosition]("array_position"),
     expression[ArraySort]("array_sort"),
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/collectionOperations.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/collectionOperations.scala
index 2a4e42d4ba316..c82db839438ed 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/collectionOperations.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/collectionOperations.scala
@@ -18,15 +18,51 @@ package org.apache.spark.sql.catalyst.expressions
 
 import java.util.Comparator
 
+import scala.collection.mutable
+
 import org.apache.spark.sql.catalyst.InternalRow
-import org.apache.spark.sql.catalyst.analysis.TypeCheckResult
+import org.apache.spark.sql.catalyst.analysis.{TypeCheckResult, TypeCoercion}
 import org.apache.spark.sql.catalyst.expressions.ArraySortLike.NullOrder
 import org.apache.spark.sql.catalyst.expressions.codegen._
 import org.apache.spark.sql.catalyst.util.{ArrayData, GenericArrayData, MapData, TypeUtils}
+import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.sql.types._
 import org.apache.spark.unsafe.array.ByteArrayMethods
 import org.apache.spark.unsafe.types.{ByteArray, UTF8String}
 
+/**
+ * Base trait for [[BinaryExpression]]s with two arrays of the same element type and implicit
+ * casting.
+ */
+trait BinaryArrayExpressionWithImplicitCast extends BinaryExpression
+  with ImplicitCastInputTypes {
+
+  @transient protected lazy val elementType: DataType =
+    inputTypes.head.asInstanceOf[ArrayType].elementType
+
+  override def inputTypes: Seq[AbstractDataType] = {
+    (left.dataType, right.dataType) match {
+      case (ArrayType(e1, hasNull1), ArrayType(e2, hasNull2)) =>
+        TypeCoercion.findTightestCommonType(e1, e2) match {
+          case Some(dt) => Seq(ArrayType(dt, hasNull1), ArrayType(dt, hasNull2))
+          case _ => Seq.empty
+        }
+      case _ => Seq.empty
+    }
+  }
+
+  override def checkInputDataTypes(): TypeCheckResult = {
+    (left.dataType, right.dataType) match {
+      case (ArrayType(e1, _), ArrayType(e2, _)) if e1.sameType(e2) =>
+        TypeCheckResult.TypeCheckSuccess
+      case _ => TypeCheckResult.TypeCheckFailure(s"input to function $prettyName should have " +
+        s"been two ${ArrayType.simpleString}s with same element type, but it's " +
+        s"[${left.dataType.simpleString}, ${right.dataType.simpleString}]")
+    }
+  }
+}
+
+
 /**
  * Given an array or map, returns its size. Returns -1 if null.
  */
@@ -529,6 +565,235 @@ case class ArrayContains(left: Expression, right: Expression)
   override def prettyName: String = "array_contains"
 }
 
+/**
+ * Checks if the two arrays contain at least one common element.
+ */
+// scalastyle:off line.size.limit
+@ExpressionDescription(
+  usage = "_FUNC_(a1, a2) - Returns true if a1 contains at least a non-null element present also in a2. If the arrays have no common element and they are both non-empty and either of them contains a null element null is returned, false otherwise.",
+  examples = """
+    Examples:
+      > SELECT _FUNC_(array(1, 2, 3), array(3, 4, 5));
+       true
+  """, since = "2.4.0")
+// scalastyle:off line.size.limit
+case class ArraysOverlap(left: Expression, right: Expression)
+  extends BinaryArrayExpressionWithImplicitCast {
+
+  override def checkInputDataTypes(): TypeCheckResult = super.checkInputDataTypes() match {
+    case TypeCheckResult.TypeCheckSuccess =>
+      if (RowOrdering.isOrderable(elementType)) {
+        TypeCheckResult.TypeCheckSuccess
+      } else {
+        TypeCheckResult.TypeCheckFailure(s"${elementType.simpleString} cannot be used in comparison.")
+      }
+    case failure => failure
+  }
+
+  @transient private lazy val ordering: Ordering[Any] =
+    TypeUtils.getInterpretedOrdering(elementType)
+
+  @transient private lazy val elementTypeSupportEquals = elementType match {
+    case BinaryType => false
+    case _: AtomicType => true
+    case _ => false
+  }
+
+  @transient private lazy val doEvaluation = if (elementTypeSupportEquals) {
+    fastEval _
+  } else {
+    bruteForceEval _
+  }
+
+  override def dataType: DataType = BooleanType
+
+  override def nullable: Boolean = {
+    left.nullable || right.nullable || left.dataType.asInstanceOf[ArrayType].containsNull ||
+      right.dataType.asInstanceOf[ArrayType].containsNull
+  }
+
+  override def nullSafeEval(a1: Any, a2: Any): Any = {
+    doEvaluation(a1.asInstanceOf[ArrayData], a2.asInstanceOf[ArrayData])
+  }
+
+  /**
+   * A fast implementation which puts all the elements from the smaller array in a set
+   * and then performs a lookup on it for each element of the bigger one.
+   * This eval mode works only for data types which implements properly the equals method.
+   */
+  private def fastEval(arr1: ArrayData, arr2: ArrayData): Any = {
+    var hasNull = false
+    val (bigger, smaller) = if (arr1.numElements() > arr2.numElements()) {
+      (arr1, arr2)
+    } else {
+      (arr2, arr1)
+    }
+    if (smaller.numElements() > 0) {
+      val smallestSet = new mutable.HashSet[Any]
+      smaller.foreach(elementType, (_, v) =>
+        if (v == null) {
+          hasNull = true
+        } else {
+          smallestSet += v
+        })
+      bigger.foreach(elementType, (_, v1) =>
+        if (v1 == null) {
+          hasNull = true
+        } else if (smallestSet.contains(v1)) {
+          return true
+        }
+      )
+    }
+    if (hasNull) {
+      null
+    } else {
+      false
+    }
+  }
+
+  /**
+   * A slower evaluation which performs a nested loop and supports all the data types.
+   */
+  private def bruteForceEval(arr1: ArrayData, arr2: ArrayData): Any = {
+    var hasNull = false
+    if (arr1.numElements() > 0 && arr2.numElements() > 0) {
+      arr1.foreach(elementType, (_, v1) =>
+        if (v1 == null) {
+          hasNull = true
+        } else {
+          arr2.foreach(elementType, (_, v2) =>
+            if (v2 == null) {
+              hasNull = true
+            } else if (ordering.equiv(v1, v2)) {
+              return true
+            }
+          )
+        })
+    }
+    if (hasNull) {
+      null
+    } else {
+      false
+    }
+  }
+
+  override def doGenCode(ctx: CodegenContext, ev: ExprCode): ExprCode = {
+    nullSafeCodeGen(ctx, ev, (a1, a2) => {
+      val smaller = ctx.freshName("smallerArray")
+      val bigger = ctx.freshName("biggerArray")
+      val comparisonCode = if (elementTypeSupportEquals) {
+        fastCodegen(ctx, ev, smaller, bigger)
+      } else {
+        bruteForceCodegen(ctx, ev, smaller, bigger)
+      }
+      s"""
+         |ArrayData $smaller;
+         |ArrayData $bigger;
+         |if ($a1.numElements() > $a2.numElements()) {
+         |  $bigger = $a1;
+         |  $smaller = $a2;
+         |} else {
+         |  $smaller = $a1;
+         |  $bigger = $a2;
+         |}
+         |if ($smaller.numElements() > 0) {
+         |  $comparisonCode
+         |}
+       """.stripMargin
+    })
+  }
+
+  /**
+   * Code generation for a fast implementation which puts all the elements from the smaller array
+   * in a set and then performs a lookup on it for each element of the bigger one.
+   * It works only for data types which implements properly the equals method.
+   */
+  private def fastCodegen(ctx: CodegenContext, ev: ExprCode, smaller: String, bigger: String): String = {
+    val i = ctx.freshName("i")
+    val getFromSmaller = CodeGenerator.getValue(smaller, elementType, i)
+    val getFromBigger = CodeGenerator.getValue(bigger, elementType, i)
+    val javaElementClass = CodeGenerator.boxedType(elementType)
+    val javaSet = classOf[java.util.HashSet[_]].getName
+    val set = ctx.freshName("set")
+    val addToSetFromSmallerCode = nullSafeElementCodegen(
+      smaller, i, s"$set.add($getFromSmaller);", s"${ev.isNull} = true;")
+    val elementIsInSetCode = nullSafeElementCodegen(
+      bigger,
+      i,
+      s"""
+         |if ($set.contains($getFromBigger)) {
+         |  ${ev.isNull} = false;
+         |  ${ev.value} = true;
+         |  break;
+         |}
+       """.stripMargin,
+      s"${ev.isNull} = true;")
+    s"""
+       |$javaSet<$javaElementClass> $set = new $javaSet<$javaElementClass>();
+       |for (int $i = 0; $i < $smaller.numElements(); $i ++) {
+       |  $addToSetFromSmallerCode
+       |}
+       |for (int $i = 0; $i < $bigger.numElements(); $i ++) {
+       |  $elementIsInSetCode
+       |}
+     """.stripMargin
+  }
+
+  /**
+   * Code generation for a slower evaluation which performs a nested loop and supports all the data types.
+   */
+  private def bruteForceCodegen(ctx: CodegenContext, ev: ExprCode, smaller: String, bigger: String): String = {
+    val i = ctx.freshName("i")
+    val j = ctx.freshName("j")
+    val getFromSmaller = CodeGenerator.getValue(smaller, elementType, j)
+    val getFromBigger = CodeGenerator.getValue(bigger, elementType, i)
+    val compareValues = nullSafeElementCodegen(
+      smaller,
+      j,
+      s"""
+         |if (${ctx.genEqual(elementType, getFromSmaller, getFromBigger)}) {
+         |  ${ev.isNull} = false;
+         |  ${ev.value} = true;
+         |}
+       """.stripMargin,
+      s"${ev.isNull} = true;")
+    val isInSmaller = nullSafeElementCodegen(
+      bigger,
+      i,
+      s"""
+         |for (int $j = 0; $j < $smaller.numElements() && !${ev.value}; $j ++) {
+         |  $compareValues
+         |}
+       """.stripMargin,
+      s"${ev.isNull} = true;")
+    s"""
+       |for (int $i = 0; $i < $bigger.numElements() && !${ev.value}; $i ++) {
+       |  $isInSmaller
+       |}
+     """.stripMargin
+  }
+
+  def nullSafeElementCodegen(
+      arrayVar: String,
+      index: String,
+      code: String,
+      isNullCode: String): String = {
+    if (inputTypes.exists(_.asInstanceOf[ArrayType].containsNull)) {
+      s"""
+         |if ($arrayVar.isNullAt($index)) {
+         |  $isNullCode
+         |} else {
+         |  $code
+         |}
+       """.stripMargin
+    } else {
+      code
+    }
+  }
+
+  override def prettyName: String = "arrays_overlap"
+}
+
 /**
  * Slices an array according to the requested start index and length
  */
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/CollectionExpressionsSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/CollectionExpressionsSuite.scala
index 57fc5f75dbca7..6ae1ac18c4dc4 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/CollectionExpressionsSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/CollectionExpressionsSuite.scala
@@ -136,6 +136,72 @@ class CollectionExpressionsSuite extends SparkFunSuite with ExpressionEvalHelper
     checkEvaluation(ArrayContains(a3, Literal.create(null, StringType)), null)
   }
 
+  test("ArraysOverlap") {
+    val a0 = Literal.create(Seq(1, 2, 3), ArrayType(IntegerType))
+    val a1 = Literal.create(Seq(4, 5, 3), ArrayType(IntegerType))
+    val a2 = Literal.create(Seq(null, 5, 6), ArrayType(IntegerType))
+    val a3 = Literal.create(Seq(7, 8), ArrayType(IntegerType))
+    val a4 = Literal.create(Seq[String](null, ""), ArrayType(StringType))
+    val a5 = Literal.create(Seq[String]("", "abc"), ArrayType(StringType))
+    val a6 = Literal.create(Seq[String]("def", "ghi"), ArrayType(StringType))
+
+    val emptyIntArray = Literal.create(Seq.empty[Int], ArrayType(IntegerType))
+
+    checkEvaluation(ArraysOverlap(a0, a1), true)
+    checkEvaluation(ArraysOverlap(a0, a2), null)
+    checkEvaluation(ArraysOverlap(a1, a2), true)
+    checkEvaluation(ArraysOverlap(a1, a3), false)
+    checkEvaluation(ArraysOverlap(a0, emptyIntArray), false)
+    checkEvaluation(ArraysOverlap(a2, emptyIntArray), false)
+    checkEvaluation(ArraysOverlap(emptyIntArray, a2), false)
+
+    checkEvaluation(ArraysOverlap(a4, a5), true)
+    checkEvaluation(ArraysOverlap(a4, a6), null)
+    checkEvaluation(ArraysOverlap(a5, a6), false)
+
+    // null handling
+    checkEvaluation(ArraysOverlap(emptyIntArray, a2), false)
+    checkEvaluation(ArraysOverlap(
+      emptyIntArray, Literal.create(Seq(null), ArrayType(IntegerType))), false)
+    checkEvaluation(ArraysOverlap(Literal.create(null, ArrayType(IntegerType)), a0), null)
+    checkEvaluation(ArraysOverlap(a0, Literal.create(null, ArrayType(IntegerType))), null)
+    checkEvaluation(ArraysOverlap(
+      Literal.create(Seq(null), ArrayType(IntegerType)),
+      Literal.create(Seq(null), ArrayType(IntegerType))), null)
+
+    // arrays of binaries
+    val b0 = Literal.create(Seq[Array[Byte]](Array[Byte](1, 2), Array[Byte](3, 4)),
+      ArrayType(BinaryType))
+    val b1 = Literal.create(Seq[Array[Byte]](Array[Byte](5, 6), Array[Byte](1, 2)),
+      ArrayType(BinaryType))
+    val b2 = Literal.create(Seq[Array[Byte]](Array[Byte](2, 1), Array[Byte](4, 3)),
+      ArrayType(BinaryType))
+
+    checkEvaluation(ArraysOverlap(b0, b1), true)
+    checkEvaluation(ArraysOverlap(b0, b2), false)
+
+    // arrays of complex data types
+    val aa0 = Literal.create(Seq[Array[String]](Array[String]("a", "b"), Array[String]("c", "d")),
+      ArrayType(ArrayType(StringType)))
+    val aa1 = Literal.create(Seq[Array[String]](Array[String]("e", "f"), Array[String]("a", "b")),
+      ArrayType(ArrayType(StringType)))
+    val aa2 = Literal.create(Seq[Array[String]](Array[String]("b", "a"), Array[String]("f", "g")),
+      ArrayType(ArrayType(StringType)))
+
+    checkEvaluation(ArraysOverlap(aa0, aa1), true)
+    checkEvaluation(ArraysOverlap(aa0, aa2), false)
+
+    // null handling with complex datatypes
+    val emptyBinaryArray = Literal.create(Seq.empty[Array[Byte]], ArrayType(BinaryType))
+    val arrayWithBinaryNull = Literal.create(Seq(null), ArrayType(BinaryType))
+    checkEvaluation(ArraysOverlap(emptyBinaryArray, b0), false)
+    checkEvaluation(ArraysOverlap(b0, emptyBinaryArray), false)
+    checkEvaluation(ArraysOverlap(emptyBinaryArray, arrayWithBinaryNull), false)
+    checkEvaluation(ArraysOverlap(arrayWithBinaryNull, emptyBinaryArray), false)
+    checkEvaluation(ArraysOverlap(arrayWithBinaryNull, b0), null)
+    checkEvaluation(ArraysOverlap(b0, arrayWithBinaryNull), null)
+  }
+
   test("Slice") {
     val a0 = Literal.create(Seq(1, 2, 3, 4, 5, 6), ArrayType(IntegerType))
     val a1 = Literal.create(Seq[String]("a", "b", "c", "d"), ArrayType(StringType))
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/functions.scala b/sql/core/src/main/scala/org/apache/spark/sql/functions.scala
index 550571a61a036..2a8fe583b83bc 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/functions.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/functions.scala
@@ -3085,6 +3085,17 @@ object functions {
     ArrayContains(column.expr, Literal(value))
   }
 
+  /**
+   * Returns `true` if `a1` and `a2` have at least one non-null element in common. If not and both
+   * the arrays are non-empty and any of them contains a `null`, it returns `null`. It returns
+   * `false` otherwise.
+   * @group collection_funcs
+   * @since 2.4.0
+   */
+  def arrays_overlap(a1: Column, a2: Column): Column = withExpr {
+    ArraysOverlap(a1.expr, a2.expr)
+  }
+
   /**
    * Returns an array containing all the elements in `x` from index `start` (or starting from the
    * end if `start` is negative) with the specified `length`.
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala
index e26565cd153b4..d08982a138bc5 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameFunctionsSuite.scala
@@ -442,6 +442,35 @@ class DataFrameFunctionsSuite extends QueryTest with SharedSQLContext {
     )
   }
 
+  test("arrays_overlap function") {
+    val df = Seq(
+      (Seq[Option[Int]](Some(1), Some(2)), Seq[Option[Int]](Some(-1), Some(10))),
+      (Seq[Option[Int]](Some(1), Some(2)), Seq[Option[Int]](Some(-1), None)),
+      (Seq[Option[Int]](Some(3), Some(2)), Seq[Option[Int]](Some(1), Some(2)))
+    ).toDF("a", "b")
+
+    val answer = Seq(Row(false), Row(null), Row(true))
+
+    checkAnswer(df.select(arrays_overlap(df("a"), df("b"))), answer)
+    checkAnswer(df.selectExpr("arrays_overlap(a, b)"), answer)
+
+    checkAnswer(
+      Seq((Seq(1, 2, 3), Seq(2.0, 2.5))).toDF("a", "b").selectExpr("arrays_overlap(a, b)"),
+      Row(true))
+
+    intercept[AnalysisException] {
+      sql("select arrays_overlap(array(1, 2, 3), array('a', 'b', 'c'))")
+    }
+
+    intercept[AnalysisException] {
+      sql("select arrays_overlap(null, null)")
+    }
+
+    intercept[AnalysisException] {
+      sql("select arrays_overlap(map(1, 2), map(3, 4))")
+    }
+  }
+
   test("slice function") {
     val df = Seq(
       Seq(1, 2, 3),