Comments (8)
Thanks for the issue report. What is the issue? Polars is faster right?
from polars.
Yes, but you seemed to think both should take the same amount of time:
https://discord.com/channels/908022250106667068/911186243465904178/1197589716929871974
And while we are at it, this one:
pl.scan_parquet(path, hive_partitioning=True).filter(part='part0').collect()
is definitely slower than that one:
pl.scan_pyarrow_dataset(ds.dataset(path, partitioning='hive')).filter(part='part0').collect()
(note the **kwargs syntax here)
from polars.
Is this cloud or local?
Please provide the traces as that will tell us if it's skipping files since it seems in the .filter(part='part0')
case that it isn't properly skipping files.
from polars.
Local.
Traces: what should I run for that?
from polars.
No, I think Polars should be faster. :)
from polars.
I will close this as as there isn't anything unexpected. Thanks for your report.
from polars.
Even this is expected?
pl.scan_parquet(path, hive_partitioning=True).filter(part='part0').collect()
is definitely slower than that one:
pl.scan_pyarrow_dataset(ds.dataset(path, partitioning='hive')).filter(part='part0').collect()
(part
being the partitioning column)
Just in case you did not notice.
from polars.
Looks like this is your issue.
from polars.
Related Issues (20)
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from polars.