> The bytes pass through a small Cloudflare Worker on the way, because the free r2.dev URL is rate-limited.
For a 40MB file I suggest hosting it directly on GitHub Pages - that's effectively a free CORS-enabled CDN and supports HTTP range requests, so you should be able to get that demo working without needing to involve Cloudflare Workers at all.
> A dashboard like this one is designed to answer a bounded set of analytical questions ~ requests per day, requests per day for one agency, all-time totals by borough. Each question can be answered by GROUP BY queries, so we can precompute them all ahead of time and save each result as its own small table, called a grouping set. Stack all of the grouping sets in one Parquet file, one section per set, and you have a data cube. A grouping set is only useful if it either enables a question to be answered, or reduces the latency of pulling the data.
A clever repurposing of technologies but realistically only worthwhile for static datasets with range payloads small enough to fit into a web response.
> your pipeline has to rebuild each customer’s file fast enough to meet the update cadence. ... data that updates on a coarse schedule rather than in realtime
It doesn't have to all live in the same Parquet file. you can have a Parquet file for all your historical data, plus one for the current week which is updated often cheaply, and then when the week is over you merge that into your big parquet file.
You're making it seem like there's hard limits to what can be done but while there definitely is, you can do incredible stuff.
For a 40MB file I suggest hosting it directly on GitHub Pages - that's effectively a free CORS-enabled CDN and supports HTTP range requests, so you should be able to get that demo working without needing to involve Cloudflare Workers at all.
What's the benefit of "data cubes" over caching?
> your pipeline has to rebuild each customer’s file fast enough to meet the update cadence. ... data that updates on a coarse schedule rather than in realtime
I expect that if your overall data is less than a GB this trick will work really well for you.
You're making it seem like there's hard limits to what can be done but while there definitely is, you can do incredible stuff.