gvolpe/hll-algorithm-sample
HLL Algorithm and Web Scraping sample
This project helps you quickly estimate the number of unique items in very large datasets without having to store all of them. It takes in streams of data, like web traffic logs or scraped website links, and provides a surprisingly accurate count of distinct elements. It's useful for data analysts, operations engineers, or anyone needing to understand the scale of unique entities in massive data streams without consuming vast amounts of memory.
No commits in the last 6 months.
Use this if you need to estimate the number of unique visitors to a website, unique items in a log file, or unique links found during web scraping, especially when the dataset is too large to fit into memory.
Not ideal if you require an exact count of unique items or need to retrieve the individual unique items themselves.
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/perception/gvolpe/hll-algorithm-sample"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
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