diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala
index 2aeb9575f1dd2..55adc06320a58 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala
@@ -331,7 +331,10 @@ object ColumnPruning extends Rule[LogicalPlan] {
         }.unzip._1
       }
       a.copy(child = Expand(newProjects, newOutput, grandChild))
-    // TODO: support some logical plan for Dataset
+
+    // Prunes the unused columns from child of MapPartitions
+    case mp @ MapPartitions(_, _, _, child) if (child.outputSet -- mp.references).nonEmpty =>
+      mp.copy(child = prunedChild(child, mp.references))
 
     // Prunes the unused columns from child of Aggregate/Window/Expand/Generate
     case a @ Aggregate(_, _, child) if (child.outputSet -- a.references).nonEmpty =>
diff --git a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ColumnPruningSuite.scala b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ColumnPruningSuite.scala
index 715d01a3cd876..5cab1fc95a364 100644
--- a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ColumnPruningSuite.scala
+++ b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/ColumnPruningSuite.scala
@@ -17,9 +17,12 @@
 
 package org.apache.spark.sql.catalyst.optimizer
 
+import scala.reflect.runtime.universe.TypeTag
+
 import org.apache.spark.sql.catalyst.analysis
 import org.apache.spark.sql.catalyst.dsl.expressions._
 import org.apache.spark.sql.catalyst.dsl.plans._
+import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder
 import org.apache.spark.sql.catalyst.expressions.{Ascending, Explode, Literal, SortOrder}
 import org.apache.spark.sql.catalyst.plans.PlanTest
 import org.apache.spark.sql.catalyst.plans.logical._
@@ -249,5 +252,16 @@ class ColumnPruningSuite extends PlanTest {
     comparePlans(Optimize.execute(query), expected)
   }
 
+  implicit private def productEncoder[T <: Product : TypeTag] = ExpressionEncoder[T]()
+  private val func = identity[Iterator[OtherTuple]] _
+
+  test("Column pruning on MapPartitions") {
+    val input = LocalRelation('_1.int, '_2.int, 'c.int)
+    val plan1 = MapPartitions(func, input)
+    val correctAnswer1 =
+      MapPartitions(func, Project(Seq('_1, '_2), input)).analyze
+    comparePlans(Optimize.execute(plan1.analyze), correctAnswer1)
+  }
+
   // todo: add more tests for column pruning
 }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala
index 33df6375e3aad..79e10215f4d3f 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala
@@ -113,7 +113,7 @@ class DatasetSuite extends QueryTest with SharedSQLContext {
       ("a", 2), ("b", 3), ("c", 4))
   }
 
-  test("map with type change") {
+  test("map with type change with the exact matched number of attributes") {
     val ds = Seq(("a", 1), ("b", 2), ("c", 3)).toDS()
 
     checkAnswer(
@@ -123,6 +123,15 @@ class DatasetSuite extends QueryTest with SharedSQLContext {
       OtherTuple("a", 1), OtherTuple("b", 2), OtherTuple("c", 3))
   }
 
+  test("map with type change with less attributes") {
+    val ds = Seq(("a", 1, 3), ("b", 2, 4), ("c", 3, 5)).toDS()
+
+    checkAnswer(
+      ds.as[OtherTuple]
+        .map(identity[OtherTuple]),
+      OtherTuple("a", 1), OtherTuple("b", 2), OtherTuple("c", 3))
+  }
+
   test("map and group by with class data") {
     // We inject a group by here to make sure this test case is future proof
     // when we implement better pipelining and local execution mode.