actually with var it's the same:
scala> class Person4 {
|
| @scala.beans.BeanProperty var X:Int = 1
| }
defined class Person4
scala> val personEncoder = Encoders.bean[Person4](classOf[Person4])
personEncoder: org.apache.spark.sql.Encoder[Person4] = class[x[0]: int]
scala> val person_rdd =sc.parallelize(Array( (new Person4(), 1), (new
Person4(), 2) ))
person_rdd: org.apache.spark.rdd.RDD[(Person4, Int)] =
ParallelCollectionRDD[3] at parallelize at <console>:39
scala> sqlContext.createDataFrame(person_rdd)
java.lang.UnsupportedOperationException: Schema for type Person4 is not
supported
at
org.apache.spark.sql.catalyst.ScalaReflection$.schemaFor(ScalaReflection.scala:716)
at
org.apache.spark.sql.catalyst.ScalaReflection$$anonfun$schemaFor$2.apply(ScalaReflection.scala:712)
at
org.apache.spark.sql.catalyst.ScalaReflection$$anonfun$schemaFor$2.apply(ScalaReflection.scala:711)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
at scala.collection.immutable.List.map(List.scala:285)
at
org.apache.spark.sql.catalyst.ScalaReflection$.schemaFor(ScalaReflection.scala:711)
at
org.apache.spark.sql.catalyst.ScalaReflection$.schemaFor(ScalaReflection.scala:654)
at
org.apache.spark.sql.SparkSession.createDataFrame(SparkSession.scala:251)
at org.apache.spark.sql.SQLContext.createDataFrame(SQLContext.scala:278)
... 54 elided
On Tue, May 9, 2017 at 11:19 AM, Michael Armbrust <mich...@databricks.com>
wrote:
> I think you are supposed to set BeanProperty on a var as they do here
> <https://github.com/apache/spark/blob/f830bb9170f6b853565d9dd30ca7418b93a54fe3/mllib/src/main/scala/org/apache/spark/mllib/tree/configuration/Strategy.scala#L71-L83>.
> If you are using scala though I'd consider using the case class encoders.
>
> On Tue, May 9, 2017 at 12:21 AM, Yang <teddyyyy...@gmail.com> wrote:
>
>> I'm trying to use Encoders.bean() to create an encoder for my custom
>> class, but it fails complaining about can't find the schema:
>>
>>
>> class Person4 { @scala.beans.BeanProperty def setX(x:Int): Unit = {}
>> @scala.beans.BeanProperty def getX():Int = {1} } val personEncoder =
>> Encoders.bean[Person4](classOf[Person4]) scala> val person_rdd =sc.
>> parallelize(Array( (new Person4(), 1), (new Person4(), 2) )) person_rdd:
>> org.apache.spark.rdd.RDD[(Person4, Int)] = ParallelCollectionRDD[1] at
>> parallelize at <con sole>:31 scala> sqlcontext.createDataFrame(person_rdd
>> ) java.lang.UnsupportedOperationException: Schema for type Person4 is not
>> supported at org.apache.spark.sql.catalyst.ScalaReflection$.schemaFor(Sca
>> laReflection.scala:716) at org.apache.spark.sql.catalyst.
>> ScalaReflection$$anonfun$schemaFor$2.apply(ScalaReflection.scala:71 2)
>> at org.apache.spark.sql.catalyst.ScalaReflection$$anonfun$schemaFor$2.
>> apply(ScalaReflection.scala:71 1) at scala.collection.TraversableLi
>> ke$$anonfun$map$1.apply(TraversableLike.scala:234) at
>>
>>
>> but if u look at the encoder's schema, it does know it:
>> but the system does seem to understand the schema for "Person4":
>>
>>
>> scala> personEncoder.schema
>> res38: org.apache.spark.sql.types.StructType =
>> StructType(StructField(x,IntegerType,false))
>>
>>
>
