[jira] [Assigned] (SPARK-11180) DataFrame.na.fill does not support Boolean Type:

2015-10-19 Thread Apache Spark (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-11180?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Apache Spark reassigned SPARK-11180:


Assignee: Apache Spark

>  DataFrame.na.fill does not support Boolean Type:
> -
>
> Key: SPARK-11180
> URL: https://issues.apache.org/jira/browse/SPARK-11180
> Project: Spark
>  Issue Type: Improvement
>  Components: SQL
>Affects Versions: 1.5.0, 1.5.1
>Reporter: Satya Narayan
>Assignee: Apache Spark
>Priority: Minor
>
> Currently  DataFrame.na.fill does not support  Boolean primitive type. We 
> have use cases where while data massaging/preparation we want to fill boolean 
> columns with false/true value. 
> Ex: 
> val empDf = sqlContext.createDataFrame(Seq[(Integer,String,java.lang.Boolean)]
> ((1,null,null),(2,"SVP",true),(3,"Dir",false)))
> .toDF("EmpId","Designation","isOfficer")
> empDf: org.apache.spark.sql.DataFrame = [EmpId: int, Designation: string, 
> isOfficer: boolean]
> scala> empDf.show
> |EmpId|Designation|isOfficer|
> |1|   null| null|
> |2|SVP| true|
> |3|Dir|false|
> We want to set "isOfficer" false whenever there is null. 
> scala> empDf.na.fill(Map("isOfficer"->false))
> throws exception 
> java.lang.IllegalArgumentException: Unsupported value type java.lang.Boolean 
> (false).
>   at 
> org.apache.spark.sql.DataFrameNaFunctions$$anonfun$fill0$1.apply(DataFrameNaFunctions.scala:370)
> ...
> Can you add support for Boolean into na.fill function.



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[jira] [Assigned] (SPARK-11180) DataFrame.na.fill does not support Boolean Type:

2015-10-19 Thread Apache Spark (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-11180?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Apache Spark reassigned SPARK-11180:


Assignee: (was: Apache Spark)

>  DataFrame.na.fill does not support Boolean Type:
> -
>
> Key: SPARK-11180
> URL: https://issues.apache.org/jira/browse/SPARK-11180
> Project: Spark
>  Issue Type: Improvement
>  Components: SQL
>Affects Versions: 1.5.0, 1.5.1
>Reporter: Satya Narayan
>Priority: Minor
>
> Currently  DataFrame.na.fill does not support  Boolean primitive type. We 
> have use cases where while data massaging/preparation we want to fill boolean 
> columns with false/true value. 
> Ex: 
> val empDf = sqlContext.createDataFrame(Seq[(Integer,String,java.lang.Boolean)]
> ((1,null,null),(2,"SVP",true),(3,"Dir",false)))
> .toDF("EmpId","Designation","isOfficer")
> empDf: org.apache.spark.sql.DataFrame = [EmpId: int, Designation: string, 
> isOfficer: boolean]
> scala> empDf.show
> |EmpId|Designation|isOfficer|
> |1|   null| null|
> |2|SVP| true|
> |3|Dir|false|
> We want to set "isOfficer" false whenever there is null. 
> scala> empDf.na.fill(Map("isOfficer"->false))
> throws exception 
> java.lang.IllegalArgumentException: Unsupported value type java.lang.Boolean 
> (false).
>   at 
> org.apache.spark.sql.DataFrameNaFunctions$$anonfun$fill0$1.apply(DataFrameNaFunctions.scala:370)
> ...
> Can you add support for Boolean into na.fill function.



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