[
https://issues.apache.org/jira/browse/SPARK-28189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Luke updated SPARK-28189:
-------------------------
Summary: Pyspark - df.drop() is Case Sensitive when Referring to Upstream
Tables (was: Pyspark - df.drop is Case Sensitive when Referring to Upstream
Tables)
> Pyspark - df.drop() is Case Sensitive when Referring to Upstream Tables
> ------------------------------------------------------------------------
>
> Key: SPARK-28189
> URL: https://issues.apache.org/jira/browse/SPARK-28189
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 2.4.0
> Reporter: Luke
> Priority: Minor
>
> Column names in general are case insensitive in Pyspark, and df.drop("col")
> in general is also case insensitive.
> However, when referring to an upstream table, such as from a join, e.g.
> {code:java}
> vals1 = [('Pirate',1),('Monkey',2),('Ninja',3),('Spaghetti',4)]
> df1 = spark.createDataFrame(valuesA, ['KEY','field'])
> vals2 = [('Rutabaga',1),('Pirate',2),('Ninja',3),('Darth Vader',4)]
> df2 = spark.createDataFrame(valuesB, ['KEY','CAPS'])
> df_joined = df1.join(df2, df1['key'] = df2['key'], "left")
> {code}
>
> drop will become case sensitive. e.g.
> {code:java}
> # from above, df1 consists of columns ['KEY', 'field']
> # from above, df2 consists of columns ['KEY', 'CAPS']
> df_joined.select(df2['key']) # will give a result
> df_joined.drop(caps) # will also give a result
> {code}
> however, note the following
> {code:java}
> df_joined.drop(df2['key']) # no-op
> df_joined.drop(df2['caps']) # no-op
> df_joined.drop(df2['KEY']) # will drop column as expected
> df_joined.drop(df2['CAPS']) # will drop column as expected
> {code}
>
>
> so in summary, using df.drop(df2['col']) doesn't align with expected case
> insensitivity for column names, even though functions like select, join, and
> dropping a column generally are case insensitive.
>
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
