diff --git a/sql/core/src/main/scala/org/apache/spark/sql/execution/basicPhysicalOperators.scala b/sql/core/src/main/scala/org/apache/spark/sql/execution/basicPhysicalOperators.scala
index 37d750e621c25..2039b8669465e 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/basicPhysicalOperators.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/basicPhysicalOperators.scala
@@ -89,7 +89,13 @@ case class FilterExec(condition: Expression, child: SparkPlan)
 
   // Split out all the IsNotNulls from condition.
   private val (notNullPreds, otherPreds) = splitConjunctivePredicates(condition).partition {
-    case IsNotNull(a: NullIntolerant) if a.references.subsetOf(child.outputSet) => true
+    case IsNotNull(a) => isNullIntolerant(a) && a.references.subsetOf(child.outputSet)
+    case _ => false
+  }
+
+  // If one expression and its children are null intolerant, it is null intolerant.
+  private def isNullIntolerant(expr: Expression): Boolean = expr match {
+    case e: NullIntolerant => e.children.forall(isNullIntolerant)
     case _ => false
   }
 
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
index e87baa454c8b3..66970bcf98060 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
@@ -28,8 +28,8 @@ import org.scalatest.Matchers._
 
 import org.apache.spark.SparkException
 import org.apache.spark.sql.catalyst.TableIdentifier
-import org.apache.spark.sql.catalyst.plans.logical.{OneRowRelation, Project, Union}
-import org.apache.spark.sql.execution.QueryExecution
+import org.apache.spark.sql.catalyst.plans.logical.{Filter, OneRowRelation, Project, Union}
+import org.apache.spark.sql.execution.{FilterExec, QueryExecution}
 import org.apache.spark.sql.execution.aggregate.HashAggregateExec
 import org.apache.spark.sql.execution.exchange.{BroadcastExchangeExec, ReusedExchangeExec, ShuffleExchange}
 import org.apache.spark.sql.functions._
@@ -1617,6 +1617,76 @@ class DataFrameSuite extends QueryTest with SharedSQLContext {
     }
   }
 
+  private def verifyNullabilityInFilterExec(
+      df: DataFrame,
+      expr: String,
+      expectedNonNullableColumns: Seq[String]): Unit = {
+    val dfWithFilter = df.where(s"isnotnull($expr)").selectExpr(expr)
+    // In the logical plan, all the output columns of input dataframe are nullable
+    dfWithFilter.queryExecution.optimizedPlan.collect {
+      case e: Filter => assert(e.output.forall(_.nullable))
+    }
+
+    dfWithFilter.queryExecution.executedPlan.collect {
+      // When the child expression in isnotnull is null-intolerant (i.e. any null input will
+      // result in null output), the involved columns are converted to not nullable;
+      // otherwise, no change should be made.
+      case e: FilterExec =>
+        assert(e.output.forall { o =>
+          if (expectedNonNullableColumns.contains(o.name)) !o.nullable else o.nullable
+        })
+    }
+  }
+
+  test("SPARK-17957: no change on nullability in FilterExec output") {
+    val df = sparkContext.parallelize(Seq(
+      null.asInstanceOf[java.lang.Integer] -> new java.lang.Integer(3),
+      new java.lang.Integer(1) -> null.asInstanceOf[java.lang.Integer],
+      new java.lang.Integer(2) -> new java.lang.Integer(4))).toDF()
+
+    verifyNullabilityInFilterExec(df,
+      expr = "Rand()", expectedNonNullableColumns = Seq.empty[String])
+    verifyNullabilityInFilterExec(df,
+      expr = "coalesce(_1, _2)", expectedNonNullableColumns = Seq.empty[String])
+    verifyNullabilityInFilterExec(df,
+      expr = "coalesce(_1, 0) + Rand()", expectedNonNullableColumns = Seq.empty[String])
+    verifyNullabilityInFilterExec(df,
+      expr = "cast(coalesce(cast(coalesce(_1, _2) as double), 0.0) as int)",
+      expectedNonNullableColumns = Seq.empty[String])
+  }
+
+  test("SPARK-17957: set nullability to false in FilterExec output") {
+    val df = sparkContext.parallelize(Seq(
+      null.asInstanceOf[java.lang.Integer] -> new java.lang.Integer(3),
+      new java.lang.Integer(1) -> null.asInstanceOf[java.lang.Integer],
+      new java.lang.Integer(2) -> new java.lang.Integer(4))).toDF()
+
+    verifyNullabilityInFilterExec(df,
+      expr = "_1 + _2 * 3", expectedNonNullableColumns = Seq("_1", "_2"))
+    verifyNullabilityInFilterExec(df,
+      expr = "_1 + _2", expectedNonNullableColumns = Seq("_1", "_2"))
+    verifyNullabilityInFilterExec(df,
+      expr = "_1", expectedNonNullableColumns = Seq("_1"))
+    // `constructIsNotNullConstraints` infers the IsNotNull(_2) from IsNotNull(_2 + Rand())
+    // Thus, we are able to set nullability of _2 to false.
+    // If IsNotNull(_2) is not given from `constructIsNotNullConstraints`, the impl of
+    // isNullIntolerant in `FilterExec` needs an update for more advanced inference.
+    verifyNullabilityInFilterExec(df,
+      expr = "_2 + Rand()", expectedNonNullableColumns = Seq("_2"))
+    verifyNullabilityInFilterExec(df,
+      expr = "_2 * 3 + coalesce(_1, 0)", expectedNonNullableColumns = Seq("_2"))
+    verifyNullabilityInFilterExec(df,
+      expr = "cast((_1 + _2) as boolean)", expectedNonNullableColumns = Seq("_1", "_2"))
+  }
+
+  test("SPARK-17957: outer join + na.fill") {
+    val df1 = Seq((1, 2), (2, 3)).toDF("a", "b")
+    val df2 = Seq((2, 5), (3, 4)).toDF("a", "c")
+    val joinedDf = df1.join(df2, Seq("a"), "outer").na.fill(0)
+    val df3 = Seq((3, 1)).toDF("a", "d")
+    checkAnswer(joinedDf.join(df3, "a"), Row(3, 0, 4, 1))
+  }
+
   test("SPARK-17123: Performing set operations that combine non-scala native types") {
     val dates = Seq(
       (new Date(0), BigDecimal.valueOf(1), new Timestamp(2)),