81–90 of 127 posts
Design Database for SSD would still go a very very long way before what I think the author is suggesting which is designing for cloud or datacenter.
Earlier quoted context omitted.
Till the financial controller shows up at the very least. Also even if not required makes reasoning about how systems work a hell lot easier. So for vast majority that doesn't need massive throughtputs sacrificing some speed for easier to understand consistency model is worthy tradeoff
All financial systems don't care about time. Prety much all financial transactions are settled with a given date, not instantly. Go sell some stocks, it takes 2 days to actually settle. (May be hidden by your provider, but that how it works). For that matter, the ultimate in BASE for financial transactions is the humble check. That is a great example of "money out" that will only be settled at some time in the future…
Earlier quoted context omitted.
Committing to NVMe drive properly is really costly. I'm talking using O_DIRECT | OSYNC or fsync here. Can be in the order of whole milliseconds, easily. And it is much worse if you are using cloud systems.
Isn't that why a WAL exists, so you didn't actually need to do that with eg postgres and other rdbms?
You must have a single flushed write to disk to be durable, but it doesn't need the second write.
This made sense for product catalogs, employee dept and e-commerce type of use cases.
But it's an extremely poor fit for storing a world model that LLMs are building in an opaque and probabilistic way.
Prediction: a new data model will take over in the next 5 years. It might use some principles from many decades of relational DBs, but will also be different in fundamental ways.
Earlier quoted context omitted.
Skipping flushing the local disk seems rather silly to me: - A modern high end SSD commits faster than the one way time to anywhere much farther than a few miles away. (Do the math. A few tens of microseconds specified write latency is pretty common. NVDIMMs (a sadly dying technology) can do even better. The speed of light is only so fast. - Unfortunate local correlated failures happen. IMO it’s quite nice to be able…
Committing to NVMe drive properly is really costly. I'm talking using O_DIRECT | OSYNC or fsync here. Can be in the order of whole milliseconds, easily. And it is much worse if you are using cloud systems.
You know you need to be careful when an Amazon engineer will argue for a database architecture that fully leverages (and makes you dependent of) the strengths of their employer's product. In particular: > Commit-to-disk on a single system is both unnecessary (because we can replicate across storage on multiple systems) and inadequate (because we don’t want to lose writes even if a single system fails). This is surely…
Skipping flushing the local disk seems rather silly to me: - A modern high end SSD commits faster than the one way time to anywhere much farther than a few miles away. (Do the math. A few tens of microseconds specified write latency is pretty common. NVDIMMs (a sadly dying technology) can do even better. The speed of light is only so fast. - Unfortunate local correlated failures happen. IMO it’s quite nice to be able…
It is. Coordinated failures shouldn't be a surprise these days. It's kind of sad to here that from an AWS engineer. Same data pattern fills the buffers and crashes multiple servers, while they were all "hoping" that others fsynced the data, but it turns out they all filled up and crashed. That's just one case there are others.
I should add that the bond between relational databases and spinning rust goes back further. My dad, who started working as a programmer in the 60s with just magtape as storage, talked about the early era of disks as a big step forward but requiring a lot of detailed work to decide where to put the data and how to find it again. For him, databases were a solution to the problems that that disks created for programmer…
I'm not sure I totally understand the timeline you're describing, but my understanding is that relational databases themselves were only invented in the 1970s. Is your reference to the 60s just giving context for when he started but before this link happened (with the idea that the problems predated the solution)?
Earlier quoted context omitted.
Skipping flushing the local disk seems rather silly to me: - A modern high end SSD commits faster than the one way time to anywhere much farther than a few miles away. (Do the math. A few tens of microseconds specified write latency is pretty common. NVDIMMs (a sadly dying technology) can do even better. The speed of light is only so fast. - Unfortunate local correlated failures happen. IMO it’s quite nice to be able…
> Skipping flushing the local disk seems rather silly to me It is. Coordinated failures shouldn't be a surprise these days. It's kind of sad to here that from an AWS engineer. Same data pattern fills the buffers and crashes multiple servers, while they were all "hoping" that others fsynced the data, but it turns out they all filled up and crashed. That's just one case there are others.
Earlier quoted context omitted.
Committing to NVMe drive properly is really costly. I'm talking using O_DIRECT | OSYNC or fsync here. Can be in the order of whole milliseconds, easily. And it is much worse if you are using cloud systems.
I just tested the mediocre enterprise nvme I have sitting on my desk (micron 7400 pro), it does over 30000 fsyncs per second (over a thunderbolt adapter to my laptop, even)
Earlier quoted context omitted.
Skipping flushing the local disk seems rather silly to me: - A modern high end SSD commits faster than the one way time to anywhere much farther than a few miles away. (Do the math. A few tens of microseconds specified write latency is pretty common. NVDIMMs (a sadly dying technology) can do even better. The speed of light is only so fast. - Unfortunate local correlated failures happen. IMO it’s quite nice to be able…
Committing to NVMe drive properly is really costly. I'm talking using O_DIRECT | OSYNC or fsync here. Can be in the order of whole milliseconds, easily. And it is much worse if you are using cloud systems.