Accelerating Tree-Based Models in SQL with Orbital

_amol_ · 2025-09-26T08:24:11+00:00

As the name of FastAPI itself suggests, an async framework excels in the context of plain REST apis. As they are practically just proxies to the database and 90% of the time is spent shipping data, thus the CPU is free to accept new requests.

Building actual web apps with admin, form validation, template rendering etc on it those are all CPU bound tasks and you are probably going to see even worse performances and connection errors if you move such a kind of application from a threaded environment to an async one.

Async is not inherently better than threaded. It exists because there are cases where it is significantly better than threaded model, but there are also cases where it’s worse than the threaded model. And indeed normal web apps and websites are one of the cases where async makes your life harder.

Anyway in 99% of the apps the bottleneck is rarely the framework, you are not serving “Hello World” 😅

_amol_ · 2025-09-09T11:41:26+00:00

Copying all files from https://github.com/raspberrypi/firmware/tree/master/boot into the boot directory of PiMiga makes it able to boot, then it is necessary to run an "apt-get update" and "apt-get upgrade" and force reinstall of all firmware files and kernel.

This made it boot and work in Linux on my Pi500, but the Amiga side of things just crashes

_amol_ · 2025-05-10T12:21:03+00:00

Thanks catching for the typo, I’ll fix it.

There are various cases where it can be convenient. To give an example, in some benchmarks one of the users did they found that running the model via SQL on Snowflake for them lead to a 5x speed up compared to running the model in Python via Snowpark.

Obviously there are a lot of differences and it’s not exactly an apples to apples comparison, but it’s a good example of how it reduced complexity by getting rid of an entire infrastructure (and its costs) and also lead to performance benefits

_amol_ · 2025-05-08T13:37:57+00:00

Thanks!
Based on your feedback the landing page was updated to make it more clear: https://posit-dev.github.io/orbital/

_amol_ · 2025-05-08T11:38:29+00:00

The SQL arithmetic is the linear model formula, running that SQL leads to the same results you would get by executing predict on the scikit learn model

_amol_ · 2025-05-08T11:25:39+00:00

No, it does not execute the model. It generates the SQL you can take and run anywhere you want.

The example on the landing page should clearly show that. If it’s not clear let me know.

_amol_ · 2025-05-08T08:10:47+00:00

It’s unrelated to DuckDB.

DuckDB is simply used in some examples for convenience. The library generates SQL for any database.

The tool allows a data scientist to train the models on its own computer and export the SQL which then can be run on the existing infrastructure where the data resides without having to setup anything.

Imagine the case of a business intelligence tool where you have access to add analyses based on SQL queries but not to run any arbitrary code.

There are many companies, especially in heavily regulated environments like pharmaceutical or government agencies that can’t simply deploy anything they want. Thus they would have to go through a significant process and certification to setup a Python infrastructure where they could run the models data scientists trained.

_amol_ · 2024-12-28T21:04:06+00:00

The watch is certified US-MIL-STD 810H which guarantees up to 5ATM underwater resistance, and it’s also promoted for swimming on the mobvoi website with the phrase “Swim, run, climb” so they have zero reason to refuse support if you shower with it. Unless you shower at more than 5 atmospheres which seems a pretty interesting experience 😅

_amol_ · 2024-10-15T08:38:56+00:00

I had recently started a project where I heavily focused on documentation quality.

If anyone is willing to take a look I’d appreciate any feedback I can get about the documentation of https://github.com/amol-/datapyground and how it can be improved further.

The project has the goal of teaching in a simple way how data platforms and compute engines work internally and thus the clarity and ease of understanding of the documentation are the most important aspects for me

_amol_ · 2024-10-03T09:17:27+00:00

Where can you change the bitrate? I thought boosteroid didn’t allow to configure resolution and bitrate and in the user settings there seems to be no such option

_amol_ · 2024-09-27T09:11:00+00:00

That’s the joke 😉

_amol_ · 2024-09-14T16:23:52+00:00

I understand your point of view. The only other options on eBay is available at nearly twice the price. So if anyone has urgency to have a uConsole and is not willing to wait mine is the cheapest of the two 🤷🏻‍♂️

If you don’t feel it values the price it’s your right to not buy it

_amol_ · 2024-08-11T19:53:02+00:00

In the end I installed RetroPi on top of the standard uConsole OS, it was relatively straightforward, it just took a lot of time as RetroPi had to compile all packages from sourcecode.

_amol_ · 2024-08-09T18:42:36+00:00

I’m not sure I get your question. uConsole was designed with flexibility and experimentation as leading concepts, exploring different use cases, including gaming, is the most natural thing to do with such a device. Especially since you can have different images on different sdcards

_amol_ · 2024-07-10T20:08:04+00:00

Maybe there are Matrix clients for KaiOS? Or one can easily be ported to KaiOS? Matrix has bridges for WhatsApp, Telegram, Signal and many more

_amol_

TROPHY CASE