[GitHub] spark issue #13912: [SPARK-16216][SQL] CSV data source supports custom date ...

[deanchen <gi...@git.apache.org>]

Github user deanchen commented on the issue:

    https://github.com/apache/spark/pull/13912
  
    @srowen @rxin Would love to see this get merged as this has been a pain point for us. Not a fan of timezoneless dates as an engineer but the need to passthrough or write timezoneless dates to csv's has been a necessary task due to a variety of reasons in the past.
    
    We use Spark to parse large amounts of daily financial asset data with pre-agreed upon date conventions. Most of the dates we deal doesn't belong to a timezone and are treated more like indices with the maximum granularity of a day. The CSV reports we produce for our customers do not ever contain timezone as a result and almost all dates as passthrough from the original timezoneless dates. 
    
    This is not just a common pattern with financial data, but also common practice in large companies I've worked at in the past. A large tech company I've worked at in the past used the convention of MST date and datetime for all internal systems(database included).
    



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