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Posted to issues@spark.apache.org by "Matthew Sinton-Hewitt (JIRA)" <ji...@apache.org> on 2017/10/26 14:08:00 UTC

[jira] [Updated] (SPARK-22364) unix_timestamp function sets valid dates to null

     [ https://issues.apache.org/jira/browse/SPARK-22364?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Matthew Sinton-Hewitt updated SPARK-22364:
------------------------------------------
    Description: 
org.apache.spark.sql.functions.unix_timestamp sets some valid dates to null.

The dates happen to be the at the start of Daylight Savings time (UK and possibly elsewhere).

{code:java}
import spark.implicits._

SparkSession.builder.getOrCreate()
.sparkContext.parallelize(
   Seq("25/03/2012 00:59", "25/03/2012 01:00", "25/03/2012 01:59", "25/03/2012 02:01"))
      .toDF("date")
      .select(unix_timestamp($"date", "dd/MM/yyyy HH:mm"))
      .show(false)

// results:
// 1332637140, null, null, 1332637260
{code}

  was:
org.apache.spark.sql.functions.unix_timestamp sets some valid dates to null.

The dates happen to be the at the start of Daylight Savings time (UK and possibly elsewhere).

{code:scala}
import spark.implicits._

SparkSession.builder.getOrCreate()
.sparkContext.parallelize(
   Seq("25/03/2012 00:59", "25/03/2012 01:00", "25/03/2012 01:59", "25/03/2012 02:01"))
      .toDF("date")
      .select(unix_timestamp($"date", "dd/MM/yyyy HH:mm"))
      .show(false)

// results:
// 1332637140, null, null, 1332637260
{code}


> unix_timestamp function sets valid dates to null
> ------------------------------------------------
>
>                 Key: SPARK-22364
>                 URL: https://issues.apache.org/jira/browse/SPARK-22364
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.2.0
>         Environment: Windows 10, United Kingdom
>            Reporter: Matthew Sinton-Hewitt
>
> org.apache.spark.sql.functions.unix_timestamp sets some valid dates to null.
> The dates happen to be the at the start of Daylight Savings time (UK and possibly elsewhere).
> {code:java}
> import spark.implicits._
> SparkSession.builder.getOrCreate()
> .sparkContext.parallelize(
>    Seq("25/03/2012 00:59", "25/03/2012 01:00", "25/03/2012 01:59", "25/03/2012 02:01"))
>       .toDF("date")
>       .select(unix_timestamp($"date", "dd/MM/yyyy HH:mm"))
>       .show(false)
> // results:
> // 1332637140, null, null, 1332637260
> {code}



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