[SPARK-19666][SQL] Skip a property without getter in Java schema inference and allow empty bean in encoder creation

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/JavaTypeInference.scala

@@ -117,11 +117,10 @@ object JavaTypeInference {
         val (valueDataType, nullable) = inferDataType(valueType)
         (MapType(keyDataType, valueDataType, nullable), true)
 
-      case _ =>
+      case other =>
         // TODO: we should only collect properties that have getter and setter. However, some tests
         // pass in scala case class as java bean class which doesn't have getter and setter.
-        val beanInfo = Introspector.getBeanInfo(typeToken.getRawType)
-        val properties = beanInfo.getPropertyDescriptors.filterNot(_.getName == "class")
+        val properties = getJavaBeanPropertiesWithGetters(other)
         val fields = properties.map { property =>
           val returnType = typeToken.method(property.getReadMethod).getReturnType
           val (dataType, nullable) = inferDataType(returnType)
@@ -131,9 +130,16 @@ object JavaTypeInference {
     }
   }
 
+  def getJavaBeanPropertiesWithGetters(beanClass: Class[_]): Array[PropertyDescriptor] = {
+    val beanInfo = Introspector.getBeanInfo(beanClass)
+    beanInfo.getPropertyDescriptors
+      .filterNot(_.getName == "class").filter(p => p.getReadMethod != null)
+  }
+
   private def getJavaBeanProperties(beanClass: Class[_]): Array[PropertyDescriptor] = {
     val beanInfo = Introspector.getBeanInfo(beanClass)
     beanInfo.getPropertyDescriptors
+      .filterNot(_.getName == "class")
       .filter(p => p.getReadMethod != null && p.getWriteMethod != null)
   }
 
@@ -299,8 +305,6 @@ object JavaTypeInference {
 
       case other =>
         val properties = getJavaBeanProperties(other)
-        assert(properties.length > 0)
-
         val setters = properties.map { p =>
           val fieldName = p.getName
           val fieldType = typeToken.method(p.getReadMethod).getReturnType
@@ -418,20 +422,15 @@ object JavaTypeInference {
 
         case other =>
           val properties = getJavaBeanProperties(other)
-          if (properties.length > 0) {
-            CreateNamedStruct(properties.flatMap { p =>
-              val fieldName = p.getName
-              val fieldType = typeToken.method(p.getReadMethod).getReturnType
-              val fieldValue = Invoke(
-                inputObject,
-                p.getReadMethod.getName,
-                inferExternalType(fieldType.getRawType))
-              expressions.Literal(fieldName) :: serializerFor(fieldValue, fieldType) :: Nil
-            })
-          } else {
-            throw new UnsupportedOperationException(
-              s"Cannot infer type for class ${other.getName} because it is not bean-compliant")
-          }
+          CreateNamedStruct(properties.flatMap { p =>
+            val fieldName = p.getName
+            val fieldType = typeToken.method(p.getReadMethod).getReturnType
+            val fieldValue = Invoke(
+              inputObject,
+              p.getReadMethod.getName,
+              inferExternalType(fieldType.getRawType))
+            expressions.Literal(fieldName) :: serializerFor(fieldValue, fieldType) :: Nil
+          })
       }
     }
   }

sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala

@@ -1090,14 +1090,14 @@ object SQLContext {
    */
   private[sql] def beansToRows(
         data: Iterator[_],
-        beanInfo: BeanInfo,
+        beanClass: Class[_],
         attrs: Seq[AttributeReference]): Iterator[InternalRow] = {
     val extractors =
-      beanInfo.getPropertyDescriptors.filterNot(_.getName == "class").map(_.getReadMethod)
+      JavaTypeInference.getJavaBeanPropertiesWithGetters(beanClass).map(_.getReadMethod)
     val methodsToConverts = extractors.zip(attrs).map { case (e, attr) =>
       (e, CatalystTypeConverters.createToCatalystConverter(attr.dataType))
     }
-    data.map{ element =>
+    data.map { element =>
       new GenericInternalRow(
         methodsToConverts.map { case (e, convert) => convert(e.invoke(element)) }
       ): InternalRow

sql/core/src/main/scala/org/apache/spark/sql/SparkSession.scala

@@ -17,7 +17,6 @@
 
 package org.apache.spark.sql
 
-import java.beans.Introspector
 import java.io.Closeable
 import java.util.concurrent.atomic.AtomicReference
 
@@ -347,8 +346,7 @@ class SparkSession private(
     val className = beanClass.getName
     val rowRdd = rdd.mapPartitions { iter =>
     // BeanInfo is not serializable so we must rediscover it remotely for each partition.
-      val localBeanInfo = Introspector.getBeanInfo(Utils.classForName(className))
-      SQLContext.beansToRows(iter, localBeanInfo, attributeSeq)
+      SQLContext.beansToRows(iter, Utils.classForName(className), attributeSeq)
     }
     Dataset.ofRows(self, LogicalRDD(attributeSeq, rowRdd)(self))
   }
@@ -374,8 +372,7 @@ class SparkSession private(
    */
   def createDataFrame(data: java.util.List[_], beanClass: Class[_]): DataFrame = {
     val attrSeq = getSchema(beanClass)
-    val beanInfo = Introspector.getBeanInfo(beanClass)
-    val rows = SQLContext.beansToRows(data.asScala.iterator, beanInfo, attrSeq)
+    val rows = SQLContext.beansToRows(data.asScala.iterator, beanClass, attrSeq)
     Dataset.ofRows(self, LocalRelation(attrSeq, rows.toSeq))
   }
 

sql/core/src/test/java/test/org/apache/spark/sql/JavaDataFrameSuite.java

@@ -397,4 +397,21 @@ public void testBloomFilter() {
       Assert.assertTrue(filter4.mightContain(i * 3));
     }
   }
+
+  public static class BeanWithoutGetter implements Serializable {
+    private String a;
+
+    public void setA(String a) {
+      this.a = a;
+    }
+  }
+
+  @Test
+  public void testBeanWithoutGetter() {
+    BeanWithoutGetter bean = new BeanWithoutGetter();
+    List<BeanWithoutGetter> data = Arrays.asList(bean);
+    Dataset<Row> df = spark.createDataFrame(data, BeanWithoutGetter.class);
+    Assert.assertEquals(df.schema().length(), 0);
+    Assert.assertEquals(df.collectAsList().size(), 1);
+  }
 }

sql/core/src/test/java/test/org/apache/spark/sql/JavaDatasetSuite.java

@@ -1276,4 +1276,15 @@ public void test() {
       spark.createDataset(data, Encoders.bean(NestedComplicatedJavaBean.class));
     ds.collectAsList();
   }
+
+  public static class EmptyBean implements Serializable {}
+
+  @Test
+  public void testEmptyBean() {
+    EmptyBean bean = new EmptyBean();
+    List<EmptyBean> data = Arrays.asList(bean);
+    Dataset<EmptyBean> df = spark.createDataset(data, Encoders.bean(EmptyBean.class));
+    Assert.assertEquals(df.schema().length(), 0);
+    Assert.assertEquals(df.collectAsList().size(), 1);
+  }
 }