[SPARK-37829][SQL] Dataframe.joinWith outer-join should return a null value for unmatched row

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/encoders/ExpressionEncoder.scala

@@ -97,22 +97,29 @@ object ExpressionEncoder {
     }
     val newSerializer = CreateStruct(serializers)
 
+    def nullSafe(input: Expression, result: Expression): Expression = {
+      If(IsNull(input), Literal.create(null, result.dataType), result)
+    }
+
     val newDeserializerInput = GetColumnByOrdinal(0, newSerializer.dataType)
-    val deserializers = encoders.zipWithIndex.map { case (enc, index) =>
+    val childrenDeserializers = encoders.zipWithIndex.map { case (enc, index) =>
       val getColExprs = enc.objDeserializer.collect { case c: GetColumnByOrdinal => c }.distinct
       assert(getColExprs.size == 1, "object deserializer should have only one " +
         s"`GetColumnByOrdinal`, but there are ${getColExprs.size}")
 
       val input = GetStructField(newDeserializerInput, index)
-      enc.objDeserializer.transformUp {
+      val childDeserializer = enc.objDeserializer.transformUp {
         case GetColumnByOrdinal(0, _) => input
       }
-    }
-    val newDeserializer = NewInstance(cls, deserializers, ObjectType(cls), propagateNull = false)
 
-    def nullSafe(input: Expression, result: Expression): Expression = {
-      If(IsNull(input), Literal.create(null, result.dataType), result)
+      if (enc.objSerializer.nullable) {
+        nullSafe(input, childDeserializer)
+      } else {
+        childDeserializer
+      }
     }
+    val newDeserializer =
+      NewInstance(cls, childrenDeserializers, ObjectType(cls), propagateNull = false)
 
     new ExpressionEncoder[Any](
       nullSafe(newSerializerInput, newSerializer),

sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala

@@ -33,6 +33,7 @@ import org.apache.spark.internal.config.MAX_RESULT_SIZE
 import org.apache.spark.scheduler.{SparkListener, SparkListenerJobStart}
 import org.apache.spark.sql.catalyst.{FooClassWithEnum, FooEnum, ScroogeLikeExample}
 import org.apache.spark.sql.catalyst.encoders.{OuterScopes, RowEncoder}
+import org.apache.spark.sql.catalyst.expressions.GenericRowWithSchema
 import org.apache.spark.sql.catalyst.plans.{LeftAnti, LeftSemi}
 import org.apache.spark.sql.catalyst.util.sideBySide
 import org.apache.spark.sql.execution.{LogicalRDD, RDDScanExec, SQLExecution}
@@ -2429,6 +2430,50 @@ class DatasetSuite extends QueryTest
       assert(parquetFiles.size === 10)
     }
   }
+
+  test("SPARK-37829: DataFrame outer join") {
+    // Same as "SPARK-15441: Dataset outer join" but using DataFrames instead of Datasets
+    val left = Seq(ClassData("a", 1), ClassData("b", 2)).toDF().as("left")
+    val right = Seq(ClassData("x", 2), ClassData("y", 3)).toDF().as("right")
+    val joined = left.joinWith(right, $"left.b" === $"right.b", "left")
+
+    val leftFieldSchema = StructType(
+      Seq(
+        StructField("a", StringType),
+        StructField("b", IntegerType, nullable = false)
+      )
+    )
+    val rightFieldSchema = StructType(
+      Seq(
+        StructField("a", StringType),
+        StructField("b", IntegerType, nullable = false)
+      )
+    )
+    val expectedSchema = StructType(
+      Seq(
+        StructField(
+          "_1",
+          leftFieldSchema,
+          nullable = false
+        ),
+        // This is a left join, so the right output is nullable:
+        StructField(
+          "_2",
+          rightFieldSchema
+        )
+      )
+    )
+    assert(joined.schema === expectedSchema)
+
+    val result = joined.collect().toSet
+    val expected = Set(
+      new GenericRowWithSchema(Array("a", 1), leftFieldSchema) ->
+        null,
+      new GenericRowWithSchema(Array("b", 2), leftFieldSchema) ->
+        new GenericRowWithSchema(Array("x", 2), rightFieldSchema)
+    )
+    assert(result == expected)
+  }
 }
 
 class DatasetLargeResultCollectingSuite extends QueryTest