Navya Krishnappa created SPARK-22020:
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Summary: 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);
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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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