[
https://issues.apache.org/jira/browse/SPARK-17174?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Xin Ren updated SPARK-17174:
----------------------------
Component/s: SQL
> Provide support for Timestamp type Column in add_months function to return
> HH:mm:ss
> -----------------------------------------------------------------------------------
>
> Key: SPARK-17174
> URL: https://issues.apache.org/jira/browse/SPARK-17174
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core, SQL
> Affects Versions: 2.0.0
> Reporter: Amit Baghel
> Priority: Minor
>
> add_months function currently supports Date types. If Column is Timestamp
> type then it adds month to date but it doesn't return timestamp part
> (HH:mm:ss). See the code below.
> {code}
> import java.util.Calendar
> val now = Calendar.getInstance().getTime()
> val df = sc.parallelize((0 to 3).map(i => {now.setMonth(i); (i, new
> java.sql.Timestamp(now.getTime))}).toSeq).toDF("ID", "DateWithTS")
> df.withColumn("NewDateWithTS", add_months(df("DateWithTS"),1)).show
> {code}
> Above code gives following response. See the HH:mm:ss is missing from
> NewDateWithTS column.
> {code}
> +---+--------------------+-------------+
> | ID| DateWithTS|NewDateWithTS|
> +---+--------------------+-------------+
> | 0|2016-01-21 09:38:...| 2016-02-21|
> | 1|2016-02-21 09:38:...| 2016-03-21|
> | 2|2016-03-21 09:38:...| 2016-04-21|
> | 3|2016-04-21 09:38:...| 2016-05-21|
> +---+--------------------+-------------+
> {code}
--
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
