maropu commented on a change in pull request #23854: [SPARK-22000][SQL] Address
missing Upcast in JavaTypeInference.deserializerFor
URL: https://github.com/apache/spark/pull/23854#discussion_r259685461
##########
File path:
sql/core/src/test/java/test/org/apache/spark/sql/JavaBeanDeserializationSuite.java
##########
@@ -115,6 +119,74 @@ public void testBeanWithMapFieldsDeserialization() {
Assert.assertEquals(records, MAP_RECORDS);
}
+ @Test
+ public void testSpark22000() {
+ List<Row> inputRows = new ArrayList<>();
Review comment:
How about this case?
```
scala> :paste
class BeanClass extends Serializable {
private var id: Int = _
def getId(): Int = id
def setId(i: Int): Unit = { id = i }
}
implicit val encoder = org.apache.spark.sql.Encoders.bean(classOf[BeanClass])
Seq("1", "2", "a").toDF("id").as[BeanClass].collect
org.apache.spark.sql.AnalysisException: Cannot up cast `id` from string to
int as it may truncate
The type path of the target object is:
- field (class: "int",
name: "id")
- root class: "BeanClass"
You can either add an explicit cast to the input data or choose a higher
precision type of the field in the target object;
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveUpCast$.org$apache$spark$sql$catalyst$analysis$Analyzer$ResolveUpCast$$fail(Analyzer.scala:2536)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveUpCast$$anonfun$apply$29$$anonfun$applyOrElse$129.applyOrElse(Analyzer.scala:2552)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveUpCast$$anonfun$apply$29$$anonfun$applyOrElse$129.applyOrElse(Analyzer.scala:2547)
at
org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDown$1(TreeNode.scala:258)
at
org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:72)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:258)
at
org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDown$3(TreeNode.scala:263)
at
org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$mapChildren$1(TreeNode.scala:328)
at
org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:189)
at
org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:326)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:263)
at
org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDown$3(TreeNode.scala:263)
at
org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$mapChildren$2(TreeNode.scala:345)
```
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