[
https://issues.apache.org/jira/browse/SPARK-17043?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Sean Owen resolved SPARK-17043.
-------------------------------
Resolution: Duplicate
> Cannot call zipWithIndex on RDD with more than 200 columns (get wrong result)
> -----------------------------------------------------------------------------
>
> Key: SPARK-17043
> URL: https://issues.apache.org/jira/browse/SPARK-17043
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.6.2, 2.0.0
> Reporter: Barry Becker
>
> I have a method that adds a row index column to a dataframe. It only works
> correctly if the dataframe has less than 200 columns. When more than 200
> columns nearly all the data becomes empty (""'s for values).
> {code}
> def zipWithIndex(df: DataFrame, rowIdxColName: String): DataFrame = {
> val nullable = false
> df.sparkSession.createDataFrame(
> df.rdd.zipWithIndex.map{case (row, i) => Row.fromSeq(row.toSeq :+ i)},
> StructType(df.schema.fields :+ StructField(rowIdxColName, LongType,
> nullable))
> )
> }
> {code}
> This might be related to https://issues.apache.org/jira/browse/SPARK-16664
> but I'm not sure. I saw the 200 column threshold and it made me think it
> might be related. I saw this problem in spark 1.6.2 and 2.0.0. Maybe it is
> fixed in 2.0.1 (have not tried yet). I have no idea why the 200 column
> threshold is significant.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
