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https://issues.apache.org/jira/browse/SPARK-22020?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Navya Krishnappa reopened SPARK-22020:
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This is not working as expected. Please refer the above-mentioned description
> Support session local timezone
> ------------------------------
>
> Key: SPARK-22020
> URL: https://issues.apache.org/jira/browse/SPARK-22020
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.2.0
> Reporter: Navya Krishnappa
>
> As of Spark 2.1, Spark SQL assumes the machine timezone for datetime
> manipulation, which is bad if users are not in the same timezones as the
> machines, or if different users have different timezones.
> Input data:
> Date,SparkDate,SparkDate1,SparkDate2
> 04/22/2017T03:30:02,2017-03-21T03:30:02,2017-03-21T03:30:02.02Z,2017-03-21T00:00:00Z
> I have set the below value to set the timeZone to UTC. It is adding the
> current timeZone value even though it is in the UTC format.
> spark.conf.set("spark.sql.session.timeZone", "UTC")
> Expected : Time should remain same as the input since it's already in UTC
> format
> var df1 = spark.read.option("delimiter", ",").option("qualifier",
> "\"").option("inferSchema","true").option("header", "true").option("mode",
> "PERMISSIVE").option("timestampFormat","MM/dd/yyyy'T'HH:mm:ss.SSS").option("dateFormat",
> "MM/dd/yyyy'T'HH:mm:ss").csv("DateSpark.csv");
> df1: org.apache.spark.sql.DataFrame = [Name: string, Age: int ... 5 more
> fields]
> scala> df1.show(false);
> ------------------------------------------------------------------------------
> Name Age Add Date SparkDate SparkDate1 SparkDate2
> ------------------------------------------------------------------------------
> abc 21 bvxc 04/22/2017T03:30:02 2017-03-21 03:30:02
> 2017-03-21 09:00:02.02 2017-03-21 05:30:00
> ------------------------------------------------------------------------------
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