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https://issues.apache.org/jira/browse/SPARK-18424?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Bill Chambers updated SPARK-18424:
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Summary: Single Funct (was: Improve Date Parsing Semantics & Functionality)
> Single Funct
> ------------
>
> Key: SPARK-18424
> URL: https://issues.apache.org/jira/browse/SPARK-18424
> Project: Spark
> Issue Type: Improvement
> Reporter: Bill Chambers
> Assignee: Bill Chambers
> Priority: Minor
>
> I've found it quite cumbersome to work with dates thus far in Spark, it can
> be hard to reason about the timeformat and what type you're working with, for
> instance:
> say that I have a date in the format
> {code}
> 2017-20-12
> // Y-D-M
> {code}
> In order to parse that into a Date, I have to perform several conversions.
> {code}
> to_date(
> unix_timestamp(col("date"), dateFormat)
> .cast("timestamp"))
> .alias("date")
> {code}
> I propose simplifying this by adding a to_date function (exists) but adding
> one that accepts a format for that date. I also propose a to_timestamp
> function that also supports a format.
> so that you can avoid entirely the above conversion.
> It's also worth mentioning that many other databases support this. For
> instance, mysql has the STR_TO_DATE function, netezza supports the
> to_timestamp semantic.
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