[jira] [Updated] (SPARK-17174) Provide support for Timestamp type Column in add_months function to return HH:mm:ss

2019-05-20 Thread Hyukjin Kwon (JIRA) 


 [ 
https://issues.apache.org/jira/browse/SPARK-17174?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Hyukjin Kwon updated SPARK-17174:
-
Labels: bulk-closed  (was: )

> 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
>  Labels: bulk-closed
>
> 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}



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[jira] [Updated] (SPARK-17174) Provide support for Timestamp type Column in add_months function to return HH:mm:ss

2016-08-22 Thread Xin Ren (JIRA) 

 [ 
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}



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[jira] [Updated] (SPARK-17174) Provide support for Timestamp type Column in add_months function to return HH:mm:ss

2016-08-20 Thread Amit Baghel (JIRA) 

 [ 
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.

{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}

  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.

{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|
+---++-+


> 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.
> {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}



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[jira] [Updated] (SPARK-17174) Provide support for Timestamp type Column in add_months function to return HH:mm:ss

2016-08-20 Thread Amit Baghel (JIRA) 

 [ 
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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