[SPARK-19980][SQL] Add NULL checks in Bean serializer

## What changes were proposed in this pull request?
A Bean serializer in `ExpressionEncoder`  could change values when Beans having NULL. A concrete example is as follows;
```
scala> :paste
class Outer extends Serializable {
  private var cls: Inner = _
  def setCls(c: Inner): Unit = cls = c
  def getCls(): Inner = cls
}

class Inner extends Serializable {
  private var str: String = _
  def setStr(s: String): Unit = str = str
  def getStr(): String = str
}

scala> Seq("""{"cls":null}""", """{"cls": {"str":null}}""").toDF().write.text("data")
scala> val encoder = Encoders.bean(classOf[Outer])
scala> val schema = encoder.schema
scala> val df = spark.read.schema(schema).json("data").as[Outer](encoder)
scala> df.show
+------+
|   cls|
+------+
|[null]|
|  null|
+------+

scala> df.map(x => x)(encoder).show()
+------+
|   cls|
+------+
|[null]|
|[null]|     // <-- Value changed
+------+
```

This is because the Bean serializer does not have the NULL-check expressions that the serializer of Scala's product types has. Actually, this value change does not happen in Scala's product types;

```
scala> :paste
case class Outer(cls: Inner)
case class Inner(str: String)

scala> val encoder = Encoders.product[Outer]
scala> val schema = encoder.schema
scala> val df = spark.read.schema(schema).json("data").as[Outer](encoder)
scala> df.show
+------+
|   cls|
+------+
|[null]|
|  null|
+------+

scala> df.map(x => x)(encoder).show()
+------+
|   cls|
+------+
|[null]|
|  null|
+------+
```

This pr added the NULL-check expressions in Bean serializer along with the serializer of Scala's product types.

## How was this patch tested?
Added tests in `JavaDatasetSuite`.

Author: Takeshi Yamamuro <yamamuro@apache.org>

Closes #17347 from maropu/SPARK-19980.

1 files changed, 9 insertions, 2 deletions

diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/JavaTypeInference.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/JavaTypeInference.scala
index 4ff87edde1..9d4617dda5 100644
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/JavaTypeInference.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/JavaTypeInference.scala
@@ -343,7 +343,11 @@ object JavaTypeInference {
    */
   def serializerFor(beanClass: Class[_]): CreateNamedStruct = {
     val inputObject = BoundReference(0, ObjectType(beanClass), nullable = true)
-    serializerFor(inputObject, TypeToken.of(beanClass)).asInstanceOf[CreateNamedStruct]
+    val nullSafeInput = AssertNotNull(inputObject, Seq("top level input bean"))
+    serializerFor(nullSafeInput, TypeToken.of(beanClass)) match {
+      case expressions.If(_, _, s: CreateNamedStruct) => s
+      case other => CreateNamedStruct(expressions.Literal("value") :: other :: Nil)
+    }
   }
 
   private def serializerFor(inputObject: Expression, typeToken: TypeToken[_]): Expression = {
@@ -427,7 +431,7 @@ object JavaTypeInference {
 
         case other =>
           val properties = getJavaBeanReadableAndWritableProperties(other)
-          CreateNamedStruct(properties.flatMap { p =>
+          val nonNullOutput = CreateNamedStruct(properties.flatMap { p =>
             val fieldName = p.getName
             val fieldType = typeToken.method(p.getReadMethod).getReturnType
             val fieldValue = Invoke(
@@ -436,6 +440,9 @@ object JavaTypeInference {
               inferExternalType(fieldType.getRawType))
             expressions.Literal(fieldName) :: serializerFor(fieldValue, fieldType) :: Nil
           })
+
+          val nullOutput = expressions.Literal.create(null, nonNullOutput.dataType)
+          expressions.If(IsNull(inputObject), nullOutput, nonNullOutput)
       }
     }
   }