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Hyukjin Kwon edited comment on SPARK-16896 at 8/9/16 9:47 AM: -------------------------------------------------------------- [~srowen] Oh, I am sorry, I coundn't see the comment above. Please ignore the comment I just left. I thought you left the comment for mine. was (Author: hyukjin.kwon): Sean, If my understanding is correct, we have tried to resembles {{read.csv}} in R. For example, we renamed `deimilter` to `sep` and `charset` to `encoding` to match up with R in SPARK-12668 Also, assuming from the PR I tried (https://github.com/apache/spark/pull/11457), I assume it'd be better if both `read.csv` in R and `read.csv` in Spark are similar. I didn't want to say we must match but it'd be nicer if we resembles the behaviour in R. This is because also we have a good reference here in R. > Loading csv with duplicate column names > --------------------------------------- > > Key: SPARK-16896 > URL: https://issues.apache.org/jira/browse/SPARK-16896 > Project: Spark > Issue Type: Bug > Components: SQL > Affects Versions: 2.0.0 > Reporter: Aseem Bansal > > It would be great if the library allows us to load csv with duplicate column > names. I understand that having duplicate columns in the data is odd but > sometimes we get data that has duplicate columns. Getting upstream data like > that can happen. We may choose to ignore them but currently there is no way > to drop those as we are not able to load them at all. Currently as a > pre-processing I loaded the data into R, changed the column names and then > make a fixed version with which Spark Java API can work. > But if talk about other options, e.g. R has read.csv which automatically > takes care of such situation by appending a number to the column name. > Also case sensitivity in column names can also cause problems. I mean if we > have columns like > ColumnName, columnName > I may want to have them as separate. But the option to do this is not > documented. -- 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