[jira] [Updated] (SPARK-23074) Dataframe-ified zipwithindex

["Sean Owen (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-23074?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sean Owen updated SPARK-23074:
------------------------------
    Affects Version/s:     (was: 2.4.0)
             Priority: Minor  (was: Major)

You can create a DataFrame from the result of .zipWithIndex on an RDD, as you see here.

There's already a rowNumber function in Spark SQL, however, which sounds like the native equivalent?

> Dataframe-ified zipwithindex
> ----------------------------
>
>                 Key: SPARK-23074
>                 URL: https://issues.apache.org/jira/browse/SPARK-23074
>             Project: Spark
>          Issue Type: New Feature
>          Components: Spark Core
>    Affects Versions: 2.3.0
>            Reporter: Ruslan Dautkhanov
>            Priority: Minor
>              Labels: dataframe, rdd
>
> Would be great to have a daraframe-friendly equivalent of rdd.zipWithIndex():
> {code:java}
> import org.apache.spark.sql.DataFrame
> import org.apache.spark.sql.types.{LongType, StructField, StructType}
> import org.apache.spark.sql.Row
> def dfZipWithIndex(
>   df: DataFrame,
>   offset: Int = 1,
>   colName: String = "id",
>   inFront: Boolean = true
> ) : DataFrame = {
>   df.sqlContext.createDataFrame(
>     df.rdd.zipWithIndex.map(ln =>
>       Row.fromSeq(
>         (if (inFront) Seq(ln._2 + offset) else Seq())
>           ++ ln._1.toSeq ++
>         (if (inFront) Seq() else Seq(ln._2 + offset))
>       )
>     ),
>     StructType(
>       (if (inFront) Array(StructField(colName,LongType,false)) else Array[StructField]()) 
>         ++ df.schema.fields ++ 
>       (if (inFront) Array[StructField]() else Array(StructField(colName,LongType,false)))
>     )
>   ) 
> }
> {code}
> credits: [https://stackoverflow.com/questions/30304810/dataframe-ified-zipwithindex]



--
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