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Posted to issues@spark.apache.org by "Amit Baghel (JIRA)" <ji...@apache.org> on 2016/08/21 04:31:21 UTC
[jira] [Updated] (SPARK-17174) Provide support for Timestamp type
Column in add_months function to return HH:mm:ss
[ https://issues.apache.org/jira/browse/SPARK-17174?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Amit Baghel updated SPARK-17174:
--------------------------------
Description:
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.
+---+--------------------+-------------+
| 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|
+---+--------------------+-------------+
was:
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.
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
Above code gives following response. See the HH:mm:ss is missing from NewDateWithTS column.
+---+--------------------+-------------+
| 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|
+---+--------------------+-------------+
> 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
> 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.
> +---+--------------------+-------------+
> | 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|
> +---+--------------------+-------------+
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