bruh
Roughly 80/20 read to write. On the instance's gp3 EBS volume (which is pretty slow), we've pushed ~700 write transactions per second without much problem.
This is just untrue - the naive implementation (make the API call, write a single row to the db) will work fine, as transactions are quite fast on modern hardware. What do you consider "serious" work? We've served a…
This is basically Breiman's "two cultures" at play. Do you care about optimizing y-hat, or do you care about doing inference on some parameters in your model? Depends on the business case, typically.
You can do fairly well here with ridge regression as a poor man's hierarchical model. We've used this library's Bayesian ridge regression to support a geo-pricing strategy (and it contains the Dirichlet-Multinomial…
All databases are painful in their own way. I've used all three at various times in my career, and I think SQLite behaves quite predictably, which has made it a lot easier for me personally to administrate. If I had to…
Agree on many things here, but SQLite does support WAL mode which supports 1 writer/N writer readers with snapshot isolation on reads. Writes are serialized but still quite fast. SQLite (actually SQL-ite, like a…
We've used this Python package to do this: https://github.com/bayesianbandits/bayesianbandits
Yep, we use Litestream. It's been very reliable.
FWIW, I've been running a system with roughly 100K users, about 25 qps on average, with a single SQLite file for several years. No issues with data.
We've used this library for Bayesian contextual bandits in production (we have a critical business use case supported by a ~200K feature sparse Linear UCB bandit). It's a small community, but it's also a small enough…
We do zero-downtime deployments with a single Docker volume containing the db. Spin up a container running the new code, wait til it's healthy, then kill the old container.
We have some analytics queries powered by Airflow running on a separate box. We set up Litestream to replicate to that box via SFTP, and then dump changes hourly into Snowflake.
You are still correct for network filesystems, but there are no issues opening multiple connections on the same host (even across OCI container boundaries).
You can have as many connections from as many processes as you want.
Yes, we've used the Litestream + SQLite + Go webserver route in production for several years and while we've had to deal with all of these issues, on the whole I don't have a strong argument for going back and doing it…
No, you definitely have to pick your battles. Something that you want to continuously optimize over time makes a lot more sense than something where it's reasonable to test and the commit to a path forever.
Indeed, we are well aware.
I don't know, all of these are pretty surmountable. We've done dynamic pricing with contextual multi-armed bandits, in which each context gets a single decision per time block and gross profit is summed up at the end of…
We've been happy using Thompson sampling in production with this library https://github.com/bayesianbandits/bayesianbandits
Nah, just SQLite. I had to learn a number of things about good SQLite defaults and habits, but that was years back before it really started to take off in this space. Now, there are tons of blogs you can refer to giving…
I use SQLite for this sort of thing (small e-commerce storefront, wife's niche popular blog, etc.). Actually, I use multiple - one for the DB and Diskcache for the cache. Caching is cheap, backup is trivial and cheap,…
Indeed. I've found that as long as you store your database on a modern NVMe drive, you can easily push 5K+ write transactions per second with SQLite. I've worked at very large companies who received an order of…
You can have multiple containers on the same host use the same db via Docker volumes - we have a number of production services set up this way.
I've used HTMX quite frequently recently for internal frontends (admin pages, reporting, etc.). It's quite good. A pattern I've been using a lot is not changing the backend at all - each endpoint still returns the full…
bruh
Roughly 80/20 read to write. On the instance's gp3 EBS volume (which is pretty slow), we've pushed ~700 write transactions per second without much problem.
This is just untrue - the naive implementation (make the API call, write a single row to the db) will work fine, as transactions are quite fast on modern hardware. What do you consider "serious" work? We've served a…
This is basically Breiman's "two cultures" at play. Do you care about optimizing y-hat, or do you care about doing inference on some parameters in your model? Depends on the business case, typically.
You can do fairly well here with ridge regression as a poor man's hierarchical model. We've used this library's Bayesian ridge regression to support a geo-pricing strategy (and it contains the Dirichlet-Multinomial…
All databases are painful in their own way. I've used all three at various times in my career, and I think SQLite behaves quite predictably, which has made it a lot easier for me personally to administrate. If I had to…
Agree on many things here, but SQLite does support WAL mode which supports 1 writer/N writer readers with snapshot isolation on reads. Writes are serialized but still quite fast. SQLite (actually SQL-ite, like a…
We've used this Python package to do this: https://github.com/bayesianbandits/bayesianbandits
Yep, we use Litestream. It's been very reliable.
FWIW, I've been running a system with roughly 100K users, about 25 qps on average, with a single SQLite file for several years. No issues with data.
We've used this library for Bayesian contextual bandits in production (we have a critical business use case supported by a ~200K feature sparse Linear UCB bandit). It's a small community, but it's also a small enough…
We do zero-downtime deployments with a single Docker volume containing the db. Spin up a container running the new code, wait til it's healthy, then kill the old container.
We have some analytics queries powered by Airflow running on a separate box. We set up Litestream to replicate to that box via SFTP, and then dump changes hourly into Snowflake.
You are still correct for network filesystems, but there are no issues opening multiple connections on the same host (even across OCI container boundaries).
You can have as many connections from as many processes as you want.
Yes, we've used the Litestream + SQLite + Go webserver route in production for several years and while we've had to deal with all of these issues, on the whole I don't have a strong argument for going back and doing it…
No, you definitely have to pick your battles. Something that you want to continuously optimize over time makes a lot more sense than something where it's reasonable to test and the commit to a path forever.
Indeed, we are well aware.
I don't know, all of these are pretty surmountable. We've done dynamic pricing with contextual multi-armed bandits, in which each context gets a single decision per time block and gross profit is summed up at the end of…
We've been happy using Thompson sampling in production with this library https://github.com/bayesianbandits/bayesianbandits
Nah, just SQLite. I had to learn a number of things about good SQLite defaults and habits, but that was years back before it really started to take off in this space. Now, there are tons of blogs you can refer to giving…
I use SQLite for this sort of thing (small e-commerce storefront, wife's niche popular blog, etc.). Actually, I use multiple - one for the DB and Diskcache for the cache. Caching is cheap, backup is trivial and cheap,…
Indeed. I've found that as long as you store your database on a modern NVMe drive, you can easily push 5K+ write transactions per second with SQLite. I've worked at very large companies who received an order of…
You can have multiple containers on the same host use the same db via Docker volumes - we have a number of production services set up this way.
I've used HTMX quite frequently recently for internal frontends (admin pages, reporting, etc.). It's quite good. A pattern I've been using a lot is not changing the backend at all - each endpoint still returns the full…