Barry Becker created SPARK-17043:
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Summary: 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: 2.0.0, 1.6.2
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.
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