Case sensitive columns identifiers

[giacomochiarella]

Hi everyone! I'm approaching to Redshift and I'm using pyspark to load tables. spark-redshift jar works very well except one thing. I'm loading tables that unfortunately have some columns with the same name but different case sensitivity, like username and userName. Unfortunately I do not have any control on this as they are external sources.
I've tried to use Redshift itself and it seems it can manage the case-sensitiveness. I've been able to create following table:
CREATE TABLE blabla.a ( unapplied numeric(38, 18) NULL, "unApplied" numeric(38, 18) NULL );
as Redshift has this feature executing SET enable_case_sensitive_identifier TO true;.
The RedshiftWriter seems do not have any check here.
Would be very useful if using an option we could enable/disable this feature.

Do you know any workaround?

[jsleight]

From the link you provided it seems like spark-redshift would need a PR to optionally skip the check you linked. If you're up for submitting a PR, I'm happy to help review and ship it 😄 . Probably the best approach is via adding a new writer option to enable case sensitive identifiers.

As a workaround I think you could load the table into redshift with different names and then use aws commands (e.g., boto3, aws cli, etc.) to alter the redshift table afterwards (aws examples).

[giacobbino]

Good to hear. What I did so far is remove the toLowerCase here. To make things working.
I can do the change. I have only one question. Is it enough to add the parameter to Parameter.scala and pass it to RedshiftWriter.unloadData function? Do I need to do anything to make the parameter passed from spark session into MergedParameters input map?

[jsleight]

Is it enough to add the parameter to Parameter.scala and pass it to RedshiftWriter.unloadData function?

I think that is enough. iirc the params get passed in to writer options in DefaultSource via subclassing one of the org.apache.spark.sql.sources

[giacobbino]

PR open #108