legate.pandas
An Aspiring Drop-In Replacement for Pandas at Scale (by nv-legate)
distributed
A distributed task scheduler for Dask (by dask)
legate.pandas | distributed | |
---|---|---|
1 | 3 | |
72 | 1,544 | |
- | 0.6% | |
0.0 | 9.6 | |
over 2 years ago | 3 days ago | |
C++ | Python | |
Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
legate.pandas
Posts with mentions or reviews of legate.pandas.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-11-17.
-
Dask – a flexible library for parallel computing in Python
I see they also have have pandas replacement: https://github.com/nv-legate/legate.pandas. How is it different from cuDF?
distributed
Posts with mentions or reviews of distributed.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-11-17.
-
Shuffling large data at constant memory in Dask
Thanks, if you give it a try, you can share your experience in this GitHub issue, where developers are collecting info for further improvements. https://github.com/dask/distributed/discussions/7509
- Great forward progress on squashing cluster deadlocks
-
Dask – a flexible library for parallel computing in Python
I would not recommend Dask. We use it just for simple job scheduling (that is, none of its fancy data structures) and run into issues just getting the work done efficiently. This issue, for instance, keeps the cluster from actually being utilized fully: https://github.com/dask/distributed/issues/4501. I feel like I'm on crazy pills, because it seems pretty serious yet it's gotten no attention.
What are some alternatives?
When comparing legate.pandas and distributed you can also consider the following projects:
cunumeric - An Aspiring Drop-In Replacement for NumPy at Scale
mpire - A Python package for easy multiprocessing, but faster than multiprocessing
cudf - cuDF - GPU DataFrame Library
tdigest - t-Digest data structure in Python. Useful for percentiles and quantiles, including distributed enviroments like PySpark