[SPARK-15268][SQL] Make JavaTypeInference work with UDTRegistration

## What changes were proposed in this pull request?

We have a private `UDTRegistration` API to register user defined type. Currently `JavaTypeInference` can't work with it. So `SparkSession.createDataFrame` from a bean class will not correctly infer the schema of the bean class.

## How was this patch tested?
`VectorUDTSuite`.

Author: Liang-Chi Hsieh <simonh@tw.ibm.com>

Closes #13046 from viirya/fix-udt-registry-javatypeinference.

1 files changed, 16 insertions, 0 deletions

diff --git a/mllib/src/test/scala/org/apache/spark/ml/linalg/VectorUDTSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/linalg/VectorUDTSuite.scala
index 6d01d8f282..7b50876d33 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/linalg/VectorUDTSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/linalg/VectorUDTSuite.scala
@@ -17,9 +17,19 @@
 
 package org.apache.spark.ml.linalg
 
+import scala.beans.BeanInfo
+
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.sql.catalyst.JavaTypeInference
 import org.apache.spark.sql.types._
 
+@BeanInfo
+case class LabeledPoint(label: Double, features: Vector) {
+  override def toString: String = {
+    s"($label,$features)"
+  }
+}
+
 class VectorUDTSuite extends SparkFunSuite {
 
   test("preloaded VectorUDT") {
@@ -36,4 +46,10 @@ class VectorUDTSuite extends SparkFunSuite {
       assert(udt.simpleString == "vector")
     }
   }
+
+  test("JavaTypeInference with VectorUDT") {
+    val (dataType, _) = JavaTypeInference.inferDataType(classOf[LabeledPoint])
+    assert(dataType.asInstanceOf[StructType].fields.map(_.dataType)
+      === Seq(new VectorUDT, DoubleType))
+  }
 }