Sean is right, casting timestamps to strings (which is what show() does)
uses the local timezone, either the Java default zone `user.timezone`,
the Spark default zone `spark.sql.session.timeZone` or the default
DataFrameWriter zone `timeZone`(when writing to file).
You say you are in PST, which is UTC - 8 hours. But I think this
currently observes daylight saving, so PDT, which is UTC - 7 hours.
Then, your UTC timestamp is correctly displayed in local PDT time. Try
the change above settings to display in different timezones. Inspecting
the underlying long value as suggested by Sean is best practice to get
hold of the true timestamp.
Cheers,
Enrico
Am 09.06.23 um 00:53 schrieb Sean Owen:
You sure it is not just that it's displaying in your local TZ? Check
the actual value as a long for example. That is likely the same time.
On Thu, Jun 8, 2023, 5:50 PM karan alang <karan.al...@gmail.com> wrote:
ref :
https://stackoverflow.com/questions/76436159/apache-spark-not-reading-utc-timestamp-from-mongodb-correctly
Hello All,
I've data stored in MongoDB collection and the timestamp column is
not being read by Apache Spark correctly. I'm running Apache Spark
on GCP Dataproc.
Here is sample data :
-----
|In Mongo : timeslot_date : timeslot |timeslot_date |
+--------------------------+------
1683527400|{2023-05-08T06:30:00Z}| When I use pyspark to read this
: +----------+-------------------+ timeslot |timeslot_date |
+----------+-------------------+ 1683527400|2023-05-07 23:30:00|
+----------------+-------+-----|
|-----|
|
My understanding is, data in Mongo is in UTC format i.e.
2023-05-08T06:30:00Z is in UTC format. I'm in PST timezone. I'm
not clear why spark is reading it a different timezone format
(neither PST nor UTC) Note - it is not reading it as PST timezone,
if it was doing that it would advance the time by 7 hours, instead
it is doing the opposite.
Where is the default timezone format taken from, when Spark is
reading data from MongoDB ?
Any ideas on this ?
tia!
|
