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https://issues.apache.org/jira/browse/SPARK-34675?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17342311#comment-17342311
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Shubham Chaurasia commented on SPARK-34675:
-------------------------------------------
Thanks for the previous investigations [~maxgekk] [~dongjoon].
I saw something strange on the latest master.
I was doing the same experiment and found that if we have say timezone T1 and
we change either shell timezone using export TZ or if we pass using
{{extraJavaOptions}}, we see different values of timezones.
My system was in UTC.
1) I get following values
{code}
user.timezone - America/Los_Angeles
TimeZone.getDefault - America/Los_Angeles
spark.sql.session.timeZone - America/Los_Angeles
+------------------------+-------------------+------------+
|type |timestamp |millis |
+------------------------+-------------------+------------+
|FROM BEELINE-EXT PARQUET|1989-01-04 16:00:00|599961600000|
|FROM BEELINE-EXT ORC |1989-01-05 00:00:00|599990400000|
|FROM BEELINE-EXT AVRO |1989-01-04 16:00:00|599961600000|
|FROM BEELINE-EXT TEXT |1989-01-05 00:00:00|599990400000|
+------------------------+-------------------+------------+
{code}
when I either change the shell timezone like
{code}
export TZ=America/Los_Angeles
{code}
or if I pass using extraJavaOptions like
{code}
bin/spark-shell --master local --conf
spark.driver.extraJavaOptions='-Duser.timezone=America/Los_Angeles' --conf
spark.executor.extraJavaOptions='-Duser.timezone=America/Los_Angeles'
{code}
Not only with America/Los_Angeles timezone, I tested with Asia/Kolkata as well
and was seeing the same behavior with above steps.
Result with Asia/Kolkata -
{code}
user.timezone - Asia/Kolkata
TimeZone.getDefault - Asia/Kolkata
spark.sql.session.timeZone - Asia/Kolkata
+------------------------+-------------------+------------+
|type |timestamp |millis |
+------------------------+-------------------+------------+
|FROM BEELINE-EXT PARQUET|1989-01-05 05:30:00|599961600000|
|FROM BEELINE-EXT ORC |1989-01-05 00:00:00|599941800000|
|FROM BEELINE-EXT AVRO |1989-01-05 05:30:00|599961600000|
|FROM BEELINE-EXT TEXT |1989-01-05 00:00:00|599941800000|
+------------------------+-------------------+------------+
{code}
> TimeZone inconsistencies when JVM and session timezones are different
> ---------------------------------------------------------------------
>
> Key: SPARK-34675
> URL: https://issues.apache.org/jira/browse/SPARK-34675
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.4.7
> Reporter: Shubham Chaurasia
> Priority: Major
> Fix For: 3.2.0
>
>
> Inserted following data with UTC as both JVM and session timezone.
> Spark-shell launch command
> {code}
> bin/spark-shell --conf spark.hadoop.metastore.catalog.default=hive --conf
> spark.sql.catalogImplementation=hive --conf
> spark.hadoop.hive.metastore.uris=thrift://localhost:9083 --conf
> spark.driver.extraJavaOptions=' -Duser.timezone=UTC' --conf
> spark.executor.extraJavaOptions='-Duser.timezone=UTC'
> {code}
> Table creation
> {code:scala}
> sql("use ts").show
> sql("create table spark_parquet(type string, t timestamp) stored as
> parquet").show
> sql("create table spark_orc(type string, t timestamp) stored as orc").show
> sql("create table spark_avro(type string, t timestamp) stored as avro").show
> sql("create table spark_text(type string, t timestamp) stored as
> textfile").show
> sql("insert into spark_parquet values ('FROM SPARK-EXT PARQUET', '1989-01-05
> 01:02:03')").show
> sql("insert into spark_orc values ('FROM SPARK-EXT ORC', '1989-01-05
> 01:02:03')").show
> sql("insert into spark_avro values ('FROM SPARK-EXT AVRO', '1989-01-05
> 01:02:03')").show
> sql("insert into spark_text values ('FROM SPARK-EXT TEXT', '1989-01-05
> 01:02:03')").show
> {code}
> Used following function to check and verify the returned timestamps
> {code:scala}
> scala> :paste
> // Entering paste mode (ctrl-D to finish)
> def showTs(
> db: String,
> tables: String*
> ): org.apache.spark.sql.Dataset[org.apache.spark.sql.Row] = {
> sql("use " + db).show
> import scala.collection.mutable.ListBuffer
> var results = new ListBuffer[org.apache.spark.sql.DataFrame]()
> for (tbl <- tables) {
> val query = "select * from " + tbl
> println("Executing - " + query);
> results += sql(query)
> }
> println("user.timezone - " + System.getProperty("user.timezone"))
> println("TimeZone.getDefault - " + java.util.TimeZone.getDefault.getID)
> println("spark.sql.session.timeZone - " +
> spark.conf.get("spark.sql.session.timeZone"))
> var unionDf = results(0)
> for (i <- 1 until results.length) {
> unionDf = unionDf.unionAll(results(i))
> }
> val augmented = unionDf.map(r => (r.getString(0), r.getTimestamp(1),
> r.getTimestamp(1).getTime))
> val renamed = augmented.withColumnRenamed("_1",
> "type").withColumnRenamed("_2", "ts").withColumnRenamed("_3", "millis")
> renamed.show(false)
> return renamed
> }
> // Exiting paste mode, now interpreting.
> scala> showTs("ts", "spark_parquet", "spark_orc", "spark_avro", "spark_text")
> Hive Session ID = daa82b83-b50d-4038-97ee-1ecb2d01b368
> ++
> ||
> ++
> ++
> Executing - select * from spark_parquet
> Executing - select * from spark_orc
> Executing - select * from spark_avro
> Executing - select * from spark_text
> user.timezone - UTC
> TimeZone.getDefault - UTC
> spark.sql.session.timeZone - UTC
> +----------------------+-------------------+------------+
>
> |type |ts |millis |
> +----------------------+-------------------+------------+
> |FROM SPARK-EXT PARQUET|1989-01-05 01:02:03|599965323000|
> |FROM SPARK-EXT ORC |1989-01-05 01:02:03|599965323000|
> |FROM SPARK-EXT AVRO |1989-01-05 01:02:03|599965323000|
> |FROM SPARK-EXT TEXT |1989-01-05 01:02:03|599965323000|
> +----------------------+-------------------+------------+
> {code}
> 1. Set session timezone to America/Los_Angeles
> {code:scala}
> scala> spark.conf.set("spark.sql.session.timeZone", "America/Los_Angeles")
> scala> showTs("ts", "spark_parquet", "spark_orc", "spark_avro", "spark_text")
> ++
> ||
> ++
> ++
> Executing - select * from spark_parquet
> Executing - select * from spark_orc
> Executing - select * from spark_avro
> Executing - select * from spark_text
> user.timezone - UTC
> TimeZone.getDefault - UTC
> spark.sql.session.timeZone - America/Los_Angeles
> +----------------------+-------------------+------------+
> |type |ts |millis |
> +----------------------+-------------------+------------+
> |FROM SPARK-EXT PARQUET|1989-01-04 17:02:03|599965323000|
> |FROM SPARK-EXT ORC |1989-01-04 17:02:03|599965323000|
> |FROM SPARK-EXT AVRO |1989-01-04 17:02:03|599965323000|
> |FROM SPARK-EXT TEXT |1989-01-04 17:02:03|599965323000|
> +----------------------+-------------------+------------+
> {code}
> 2. Started shell (JVM) in America/Los_Angeles timezone (which sets session
> timezone also to America/Los_Angeles)
> {code:scala}
> bin/spark-shell --conf spark.hadoop.metastore.catalog.default=hive --conf
> spark.sql.catalogImplementation=hive --conf
> spark.hadoop.hive.metastore.uris=thrift://localhost:9083 --conf
> spark.driver.extraJavaOptions=' -Duser.timezone=America/Los_Angeles' --conf
> spark.executor.extraJavaOptions='-Duser.timezone=America/Los_Angeles'
> scala> showTs("ts", "spark_parquet", "spark_orc", "spark_avro", "spark_text")
> Hive Session ID = 10ff355c-318d-4cb8-870f-a388652133b1
> ++
> ||
> ++
> ++
> Executing - select * from spark_parquet
> Executing - select * from spark_orc
> Executing - select * from spark_avro
> Executing - select * from spark_text
> user.timezone - America/Los_Angeles
> TimeZone.getDefault - America/Los_Angeles
> spark.sql.session.timeZone - America/Los_Angeles
> +----------------------+-------------------+------------+
>
> |type |ts |millis |
> +----------------------+-------------------+------------+
> |FROM SPARK-EXT PARQUET|1989-01-04 17:02:03|599965323000|
> |FROM SPARK-EXT ORC |1989-01-05 01:02:03|599994123000|
> |FROM SPARK-EXT AVRO |1989-01-05 01:02:03|599994123000|
> |FROM SPARK-EXT TEXT |1989-01-05 01:02:03|599994123000|
> +----------------------+-------------------+------------+
> {code}
> As we can see in 1 and 2, parquet and other formats are behaving differently.
> In 1 - {{1989-01-04 17:02:03|599965323000}} seems correct according to
> {{America/Los_Angeles}} timezone as the original value inserted in UTC was
> {{1989-01-05 01:02:03 which is equal to 599965323000 UTC}}
> In 2 - only parquet seems to be correct while the other formats are producing
> {{1989-01-05 01:02:03|599994123000}} which should not be the case if we are
> using a different timezone ( {{America/Los_Angeles}} ). I think they are
> coming from individual file format readers (avro, orc, text) but then they
> don't produce a converted value in {{America/Los_Angeles}} timezone. I saw
> orc reader adjusting offset according to writer and reader(JVM)
> timezone(probably avro is doing the same) but then we are not seeing the end
> value in spark according to {{spark.sql.session.timeZone}}
> Are there any guidelines/docs around how to use timezones with spark ?
> cc [~cloud_fan] [~hyukjin.kwon] [~dongjoon]
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