4 ms·
Every fast write moves work somewhere else
- cpard 2mo agoWhen I saw the title the first thing I thought of was schema on read versus schema on right when in data platforms. You can make writes faster and part of that is by not dealing with schema resolution but you do push the work somewhere else there too. I guess the same principles apply on many different levels, from when you write to the file system up to how you deal with conflicted data types during data ingestion.
- xixixao 2mo ago2 angles I think DB designers don’t often think about: 1. Durability extends to the client. Replicated db might ack a write to client, but what if that ack gets lost on the way back over network? If client talks to the DB over simple HTTP, the write might first look like a failure. Can the client retry? 2. Human perception times are biological and don’t change much. But everything in the tech stack has gotten so so much faster since the 80s. Throughput matters, sure, but latency (relatively speaking), is much less of a constraint now than it was.
- cyberpunk 2mo ago1) you ack the ack, then ack the ack ack ;) 2) depends, i have a database that farks up a pretty complex distributed system when clients write from another az, latency really can be an issue for some workloads
- aleksiy123 2mo agoToday I learned there’s a name for the general version of this idea. https://en.wikipedia.org/wiki/Waterbed_theory https://en.wikipedia.org/wiki/Waterbed_theory At a certain point in a solution everything you do to optimize (“push”) in one area will cause a negative effect in a different area (“bulge”). But this is a nice concrete example.
- shayonj 2mo agov interesting. Thanks for sharing. I kept seeing this phenomenon of "no free lunches". TIL about the waterbed theory.
- ttoinou 2mo agoIt’s called constraints and tradeoffs yeah
- aleksiy123 2mo agoSure, but I like how this feels more tactile and how things may bulge in unexpected way. Like pushing clay around into the right shape of the problem while it’s fighting you. Constraints and tradeoff feels like the simplified textbook model.
- ambicapter 2mo agoYou're getting downvoted but I had the same thought. This sounds like engineering. I do believe there are some cases where pushing the problem to a different place is the right thing to do, sometimes that different place is contextually better suited to that task, so you do actually gain performance or capability from moving the problem around.
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- baq 2mo agoI like minimal irreducible inherent complexity of a problem or a system (waterbed or zero-point would work I guess) and then you can derive some form of a law of conservation of complexity… if you can measure it. You can definitely feel it, though. edit: see also ‘No Silver Bullet’ and its essential vs accidental complexity; but don’t disregard Kolmogorov, either, even if it isn’t strictly engineering.
- mkeeter 2mo agoAnother fun failure mode in the same vein: if you are emulating an NVMe device and declare that a write operation is successful once bytes are in memory, you will quickly find yourself buffering arbitrarily large amounts of data as "persist to disk" (SSD speed) falls behind "acknowledge writes" (RAM speed). If you do not add backpressure to your system intentionally, it will be added for you – and you may not like where it's placed! (This also happens at the SSD level: burst writes can be very fast as data is buffered in the SSD's own RAM, then performance steady-states at the true write speed once that's saturated)
- throwaway_95283 2mo agoif you use the linux kernel that amount of ram is tunable, and write will cause backpressure on its own when this is exceeded.
- martheen 2mo agoUFS WriteBooster not only have a buffer that eventually need to be flushed, since it uses flash cells with pseudo-SLC behavior, the write amplification is even higher, to the point that they give it a special flag because using it all the time will just kill the media faster.