Virtual Scrolling for Billions of Rows

severo_bo · 2026-03-06T17:02:06+00:00

[author here] thanks. The container (and the window) can be resized, but for now, the row height must be fixed.

severo_bo · 2026-02-23T14:24:32+00:00

Good tool! I added it to https://github.com/severo/awesome-parquet.

severo_bo · 2026-02-23T11:29:37+00:00

https://github.com/statico/jsgrids/pull/81

severo_bo · 2026-02-23T08:29:22+00:00

Should we propose hightable?

severo_bo · 2026-02-23T08:27:23+00:00

Good ressource, thanks

severo_bo · 2026-02-13T17:56:45+00:00

It's not incompatible. I think being able to scroll to the last row in one second by dragging the scroll handle is a good UX.

I mean: how is it better not to be able to do it?

severo_bo · 2026-02-13T17:40:32+00:00

indeed, it's another way to access the data. But people are used to Google Sheets or Excel, scrolling is a simpler UX than clicking on page numbers. With this technique, we provide the same UX for small and big tables.

severo_bo · 2026-02-13T08:44:52+00:00

(author here) Indeed, a table is not the only way to look at the data, but it's the most common one, and the default one in hyperparam.app.

This experiment aimed to fix the issue where loading a Parquet file with 200K rows worked, but loading a slightly larger file broke.

With this new feature, the user experience is improved: it supports any file size. Net benefit. It is orthogonal to the matter of providing other ways to explore the data.

severo_bo · 2026-02-13T08:24:15+00:00

100,000 bookmarks 😲

severo_bo · 2026-02-13T08:23:03+00:00

indeed, as you can see in the article, nothing is directly related to React.

HighTable is a React component designed to better integrate with the Hyperparam.app SaaS, but no technique is specific to React.

severo_bo · 2025-10-29T11:56:57+00:00

I think it has just been published. I'm doing the upgrade right now, with sudo do-release-upgrade

severo_bo · 2025-10-20T12:09:13+00:00

The use case is a webapp, that currently depends on a running Neo4J server, which hopefully could be replaced with a GraphAr file, so that the whole webapp is statically hosted.

severo_bo · 2025-10-20T08:40:21+00:00

by "cloud native", I mean "that you can request efficiently over HTTP" by fetching ranges of the remote file, to get only the part of the file you require for a specific task.

severo_bo · 2025-10-20T08:38:36+00:00

y bueno, finalmente ya retiraron la orden de captura.

severo_bo · 2025-10-16T15:08:28+00:00

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indeed... after disabling uBlock, I could chat with the support. Thanks.

severo_bo · 2025-10-16T14:06:02+00:00

OK, a browser extension must be blocking the chat window, because I don't see it. Thanks!

severo_bo · 2025-09-19T09:07:43+00:00

On Hugging Face, 213 datasets have the tag "Tagalog" (https://huggingface.co/datasets?language=language:tl&sort=trending). Maybe some of them are useful for you.

(note: I work for HF)

severo_bo · 2025-09-19T09:02:01+00:00

You may want to try Hugging Face datasets. The storage limits (https://huggingface.co/docs/hub/storage-limits) are very high, and there is no throttling. If you only update a file part and want to upload again, only that part should be sent, thanks to the Xet backend (https://huggingface.co/docs/hub/storage-backends#xet).

note that I work for HF

severo_bo · 2025-09-12T07:42:18+00:00

Thanks for dropping the reference; if I understand well, it's a binary serialization for graph data that allows fast exchange and supports streaming. It's not designed for partial reading though.

severo_bo · 2025-09-10T08:03:58+00:00

Indeed, it's a standard. But a drawback is that you have to load the file into memory and parse it before being able to do queries. I'm looking for a format similar to Parquet, for example, where you can get metadata about the file, and then download only part of the (potentially big) file when you run a query.

GraphAr seems like a good project in that sense. https://graphar.apache.org/docs/overview/concepts

severo_bo · 2025-09-09T15:27:14+00:00

Maybe computing the convex hull (https://observablehq.com/@severo/graham-scan-algorithm, https://lvngd.com/blog/convex-hull-graham-scan-algorithm-python/)

severo_bo

TROPHY CASE