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risenW avatar risenW commented on August 21, 2024 5

@opeyemibami can you do some benchmarks comparison between danfojs ops and vanilla Js?

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risenW avatar risenW commented on August 21, 2024 2

Some answers to your questions.

  1. There are no performance official benchmarks for now. Most operations (especially mathematical ops) should be faster because we're using tfjs under the hood.
  2. In the browser, we are using @tensorflow/tfjs, it's optimised with webgl and makes math ops faster as well.
  3. Most functions are asynchronous, and should not block the main thread.

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motin avatar motin commented on August 21, 2024 1

On this topic, it would be very interesting to see how/if mentioned Danfo operations benefit from the tfjs wasm backend (https://www.npmjs.com/package/@tensorflow/tfjs-backend-wasm). If you benchmark, please include that in the benchmarks! :)

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nite avatar nite commented on August 21, 2024 1

I'm just doing a spike with danfo, and came across this post.

I might be missing something, but I have this spike:
https://codesandbox.io/s/danfojs-sandbox-ivyzk

A simple groupBy sum with lodash takes 53ms, and with danfo 42s.
What am I missing?

t1 53.80000001192093
t2 42480.09999996424 

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batjko avatar batjko commented on August 21, 2024

A related topic would be memory requirements.
I'm only minimally familiar with pandas and don't know how they do it, but how are large datasets affecting memory usage? If I have a 10MB json and apply a few transforms on it that return new data frames each time, is any stream processing used that Node is very famous for, for example?

I have seen #84 as well, which indicates that some ideas for performance optimisations are in the works, which is awesome.
Are there any docs about it or timelines attached.

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github-actions avatar github-actions commented on August 21, 2024

Stale issue message

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