[
https://issues.apache.org/jira/browse/SPARK-24673?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16526307#comment-16526307
]
Antonio Murgia commented on SPARK-24673:
----------------------------------------
Looks doable. Should I go with a method overload, resulting in:
{code:java}
functions.from_utc_timestamp(ts: Column, tz: String)
functions.from_utc_timestamp(ts: Column, tz: Column)
{code}
Or is there some limitation I am not aware of?
Also do you think
{code:java}
to_utc_timestamp{code}
should receive the same treatment?
> scala sql function from_utc_timestamp second argument could be Column instead
> of String
> ---------------------------------------------------------------------------------------
>
> Key: SPARK-24673
> URL: https://issues.apache.org/jira/browse/SPARK-24673
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 2.3.1
> Reporter: Antonio Murgia
> Priority: Minor
>
> As of 2.3.1 the scala API for the built-in function from_utc_timestamp
> (org.apache.spark.sql.functions#from_utc_timestamp) is less powerful than its
> SQL counter part. In particular, given a dataset/dataframe with the following
> schema:
> {code:java}
> CREATE TABLE MY_TABLE (
> ts TIMESTAMP,
> tz STRING
> ){code}
> from the SQL api I can do something like:
> {code:java}
> SELECT FROM_UTC_TIMESTAMP(TS, TZ){code}
> while from the programmatic api I simply cannot because
> {code:java}
> functions.from_utc_timestamp(ts: Column, tz: String){code}
> second argument is a String.
--
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
