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