I don't want to query with a distinct on the partitioned columns, the df
contains over 1 Billion of records.
I just want to know the partitions that were created..
On Thu, Jun 25, 2020 at 4:04 PM Jörn Franke <jornfra...@gmail.com> wrote:
> By doing a select on the df ?
>
> Am 25.06.2020 um 14:52 schrieb Tzahi File <tzahi.f...@ironsrc.com>:
>
>
> Hi,
>
> I'm using pyspark to write df to s3, using the following command:
> "df.write.partitionBy("day","hour","country").mode("overwrite").parquet(s3_output)".
>
> Is there any way to get the partitions created?
> e.g.
> day=2020-06-20/hour=1/country=US
> day=2020-06-20/hour=2/country=US
> ......
>
> --
> Tzahi File
> Data Engineer
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--
Tzahi File
Data Engineer
[image: ironSource] <http://www.ironsrc.com/>
email tzahi.f...@ironsrc.com
mobile +972-546864835
fax +972-77-5448273
ironSource HQ - 121 Derech Menachem Begin st. Tel Aviv
ironsrc.com <http://www.ironsrc.com/>
[image: linkedin] <https://www.linkedin.com/company/ironsource>[image:
twitter] <https://twitter.com/ironsource>[image: facebook]
<https://www.facebook.com/ironSource>[image: googleplus]
<https://plus.google.com/+ironsrc>
This email (including any attachments) is for the sole use of the intended
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