lambdo
sliding-window-aggregators
| lambdo | sliding-window-aggregators | |
|---|---|---|
| 3 | 2 | |
| 22 | 41 | |
| - | - | |
| 0.0 | 4.2 | |
| over 3 years ago | 8 months ago | |
| Python | C++ | |
| MIT License | Apache License 2.0 |
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lambdo
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Why isn't differential dataflow more popular?
It will return the sum of all values in column A. For large tables it will take some time to compute the result. Now assume we append a new record and want to get the new result. The traditional approach is execute this query again. A better approach is to process this new record only by adding its value in A to the result of the previous query. It is important in (stateful) stream processing.
Something similar is implemented in these libraries which however rely on a different data processing conception (alternative to map-reduce):
https://github.com/asavinov/prosto - Functions matter! No join-groupby, No map-reduce.
https://github.com/asavinov/lambdo - Feature engineering and machine learning: together at last!
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Feature Processing in Go
I find this project quite interesting because sklearn has a good general design including data transformations and it does make sense to provide compatible functionality for Go.
Feature engineering in general is a hot topic and especially if features are not simple hard-coded transformations but rather can be learned from data. For example, I developed a toolkit intended for combining feature engineering and ML:
https://github.com/asavinov/lambdo - Feature engineering and machine learning: together at last!
sliding-window-aggregators
- Query Engines: Push vs. Pull
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Why isn't differential dataflow more popular?
Myself and a few others have done a lot of research on performing sliding window aggregations updates without recomputing everything. Our code is on github, and the README has links to the papers: https://github.com/IBM/sliding-window-aggregators
What are some alternatives?
differential-dataflow - An implementation of differential dataflow using timely dataflow on Rust.
timely-dataflow - A modular implementation of timely dataflow in Rust
ballista - Distributed compute platform implemented in Rust, and powered by Apache Arrow.
rslint - A (WIP) Extremely fast JavaScript and TypeScript linter and Rust crate
diagnostics - Diagnostic tools for timely dataflow computations
tablespoon - 🥄✨Time-series Benchmark methods that are Simple and Probabilistic
blog - Some notes on things I find interesting and important.
openHistorian - The Open Source Time-Series Data Historian
Hydra - Functional hybrid modelling (FHM) language for modelling and simulation of physical systems using implicitly formulated (undirected) Differential Algebraic Equations (DAEs)