MaxHalford/tuna

:fish: A streaming ETL for fish

27
/ 100
Experimental

This project helps process very large datasets by calculating running statistics on data that won't fit into your computer's memory. You input raw data, often from CSV files, and it outputs aggregated results like averages, sums, or variances for different categories. This is ideal for data analysts, business intelligence professionals, or researchers who need to analyze massive streaming or batch datasets efficiently.

No commits in the last 6 months.

Use this if you need to calculate aggregate statistics like means, sums, or variances on datasets that are too large to load entirely into memory.

Not ideal if your datasets are small enough to process with standard in-memory tools or if you need complex, multi-stage data transformations beyond aggregation.

data-analysis business-intelligence large-data-processing streaming-analytics dataset-aggregation
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 6 / 25

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Stars

13

Forks

1

Language

Go

License

MIT

Category

go-ml-bindings

Last pushed

Jan 24, 2019

Commits (30d)

0

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