[jira] [Updated] (SPARK-22316) Cannot Select ReducedAggregator Column

["Hyukjin Kwon (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-22316?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon updated SPARK-22316:
---------------------------------
    Labels: bulk-closed  (was: )

> Cannot Select ReducedAggregator Column
> --------------------------------------
>
>                 Key: SPARK-22316
>                 URL: https://issues.apache.org/jira/browse/SPARK-22316
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 2.2.0
>            Reporter: Russell Spitzer
>            Priority: Minor
>              Labels: bulk-closed
>
> Given a dataset which has been run through reduceGroups like this
> {code}
> case class Person(name: String, age: Int)
> case class Customer(id: Int, person: Person)
> val ds = spark.createDataset(Seq(Customer(1,Person("russ", 85))))
> val grouped = ds.groupByKey(c => c.id).reduceGroups( (x,y) => x )
> {code}
> We end up with a Dataset with the schema
> {code}
>  org.apache.spark.sql.types.StructType = 
> StructType(
>   StructField(value,IntegerType,false), 
>   StructField(ReduceAggregator(Customer),
>     StructType(StructField(id,IntegerType,false),
>     StructField(person,
>       StructType(StructField(name,StringType,true),
>       StructField(age,IntegerType,false))
>    ,true))
> ,true))
> {code}
> The column names are 
> {code}
> Array(value, ReduceAggregator(Customer))
> {code}
> But you cannot select the "ReduceAggregatorColumn"
> {code}
> grouped.select(grouped.columns(1))
> org.apache.spark.sql.AnalysisException: cannot resolve '`ReduceAggregator(Customer)`' given input columns: [value, ReduceAggregator(Customer)];;
> 'Project ['ReduceAggregator(Customer)]
> +- Aggregate [value#338], [value#338, reduceaggregator(org.apache.spark.sql.expressions.ReduceAggregator@5ada573, Some(newInstance(class Customer)), Some(class Customer), Some(StructType(StructField(id,IntegerType,false), StructField(person,StructType(StructField(name,StringType,true), StructField(age,IntegerType,false)),true))), input[0, scala.Tuple2, true]._1 AS value#340, if ((isnull(input[0, scala.Tuple2, true]._2) || None.equals)) null else named_struct(id, assertnotnull(assertnotnull(input[0, scala.Tuple2, true]._2)).id AS id#195, person, if (isnull(assertnotnull(assertnotnull(input[0, scala.Tuple2, true]._2)).person)) null else named_struct(name, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, assertnotnull(assertnotnull(assertnotnull(input[0, scala.Tuple2, true]._2)).person).name, true), age, assertnotnull(assertnotnull(assertnotnull(input[0, scala.Tuple2, true]._2)).person).age) AS person#196) AS _2#341, newInstance(class scala.Tuple2), assertnotnull(assertnotnull(input[0, Customer, true])).id AS id#195, if (isnull(assertnotnull(assertnotnull(input[0, Customer, true])).person)) null else named_struct(name, staticinvoke(class org.apache.spark.unsafe.types.UTF8String, StringType, fromString, assertnotnull(assertnotnull(assertnotnull(input[0, Customer, true])).person).name, true), age, assertnotnull(assertnotnull(assertnotnull(input[0, Customer, true])).person).age) AS person#196, StructField(id,IntegerType,false), StructField(person,StructType(StructField(name,StringType,true), StructField(age,IntegerType,false)),true), true, 0, 0) AS ReduceAggregator(Customer)#346]
>    +- AppendColumns <function1>, class Customer, [StructField(id,IntegerType,false), StructField(person,StructType(StructField(name,StringType,true), StructField(age,IntegerType,false)),true)], newInstance(class Customer), [input[0, int, false] AS value#338]
>       +- LocalRelation [id#197, person#198]
> {code}
> You can work around this by using "toDF" to rename the column
> {code}
> scala> grouped.toDF("key", "reduced").select("reduced")
> res55: org.apache.spark.sql.DataFrame = [reduced: struct<id: int, person: struct<name: string, age: int>>]
> {code}
> I think that all invocations of 
> {code}
> ds.select(ds.columns(i))
> {code}
> For all valid i < columns size should work.



--
This message was sent by Atlassian JIRA
(v7.6.3#76005)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org