tl;dr: a proposal for a pyspark "DynamicDataFrame" class that would make it
easier to inherit from it while keeping dataframe methods.
Hello everyone. We have been working for a long time with PySpark and more
specifically with DataFrames. In our pipelines we have several tables, with
specific pur
it can be
helpful or not, and what would be the best strategy, in your opinion, to
pursue it.
Thank you very much!
Pablo
On Thu, Nov 4, 2021 at 9:44 PM Pablo Alcain <
pablo.alc...@wildlifestudios.com> wrote:
> tl;dr: a proposal for a pyspark "DynamicDataFrame" class that wo
me" would be the boilerplate code that allows you to decide
more granularly what methods you want to delegate.
> (BusinessModel(spark.createDataFrame([(1, "DEC")], ("id", "month")))
> .select("id")
> .with_price(0.0)
> .select("pric
