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Posted to issues@spark.apache.org by "Waldemar (Jira)" <ji...@apache.org> on 2020/02/03 07:32:00 UTC

[jira] [Created] (SPARK-30706) TimeZone in writing pure date type in CSV output

Waldemar created SPARK-30706:
--------------------------------

             Summary: TimeZone in writing pure date type in CSV output
                 Key: SPARK-30706
                 URL: https://issues.apache.org/jira/browse/SPARK-30706
             Project: Spark
          Issue Type: Bug
          Components: Spark Shell
    Affects Versions: 2.4.3
            Reporter: Waldemar


If I read string date from CSV file, then cast to date type and write into CSV file again on the west of Greenwich to csv file again it writes date of one day ago. This way making this operation in loop we can get unwillingly past date.

If the spark-shell work on the east of Greenwich all is OK.


Example of code:
{code:java}
//
val test_5_load = "hdfs://192.168.44.161:8020/db/wbiernacki/test_5_load.csv"
val test_5_save = "hdfs://192.168.44.161:8020/db/wbiernacki/test_5_save.csv"
val test_5 = spark.read.format("csv")
  .option("header","true")
  .load( test_5_load )
  .withColumn("begin",to_date(col("begin" ),"yyyy-MM-dd"))
  .withColumn("end" ,to_date(col("end" ),"yyyy-MM-dd"))
test_5.show()
test_5
  .write.mode("overwrite")
  .format("csv")
  .option("header","true")
  .save( test_5_save )

{code}
 Please perform this few times.. The test_5_load.csv file looks like:
{code:java}
// 
+--------+----------+----------+----+
| patient|     begin|       end| new|
+--------+----------+----------+----+
|waldemar|2015-09-22|2015-09-23|old1|
+--------+----------+----------+----+{code}
 



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