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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2015/10/19 08:45:05 UTC
[jira] [Assigned] (SPARK-11180) DataFrame.na.fill does not support
Boolean Type:
[ 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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