[jira] [Commented] (SPARK-17922) ClassCastException java.lang.ClassCastException: org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator cannot be cast to org.apache.spark.sql.catalyst.expressions.UnsafeProjection

["Apache Spark (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-17922?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15596527#comment-15596527 ] 

Apache Spark commented on SPARK-17922:
--------------------------------------

User 'AbhiMadav' has created a pull request for this issue:
https://github.com/apache/spark/pull/15591

> ClassCastException java.lang.ClassCastException: org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator cannot be cast to org.apache.spark.sql.catalyst.expressions.UnsafeProjection 
> ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-17922
>                 URL: https://issues.apache.org/jira/browse/SPARK-17922
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.0.0
>            Reporter: kanika dhuria
>
> I am using spark 2.0
> Seeing class loading issue because the whole stage code gen is generating multiple classes with same name as "org.apache.spark.sql.catalyst.expressions.GeneratedClass"
> I am using dataframe transform. and within transform i use Osgi.
> Osgi replaces the thread context class loader to ContextFinder which looks at all the class loaders in the stack to find out the new generated class and finds the GeneratedClass with inner class GeneratedIterator byteclass loader(instead of falling back to the byte class loader created by janino compiler), since the class name is same that byte class loader loads the class and returns GeneratedClass$GeneratedIterator instead of expected GeneratedClass$UnsafeProjection.
> Can we generate different classes with different names or is it expected to generate one class only? 
> This is the somewhat I am trying to do 
> {noformat} 
> import org.apache.spark.sql._
> import org.apache.spark.sql.types._
> import com.databricks.spark.avro._
>   def exePart(out:StructType): ((Iterator[Row]) => Iterator[Row]) = {
> //Initialize osgi
>      (rows:Iterator[Row]) => {
>          var outi = Iterator[Row]() 
>          while(rows.hasNext) {    
>              val r = rows.next         
>              outi = outi.++(Iterator(Row(r.get(0))))          
>          } 
>          //val ors = Row("abc")               
>          //outi =outi.++( Iterator(ors))  
>          outi
>      }
>   }
> def transform1( outType:StructType) :((DataFrame) => DataFrame) = {
>      (d:DataFrame) => {
>       val inType = d.schema
>       val rdd = d.rdd.mapPartitions(exePart(outType))
>       d.sqlContext.createDataFrame(rdd, outType)
>     }
>    
>   }
> val df = spark.read.avro("file:///data/builds/a1.avro")
> val df1 = df.select($"id2").filter(false)
> val df2 = df1.transform(transform1(StructType(StructField("p1", IntegerType, true)::Nil))).createOrReplaceTempView("tbl0")
> spark.sql("insert overwrite table testtable select p1 from tbl0")
> {noformat} 



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