Besides, you probably don't want "done" jobs in the same table as pending or retriable jobs - as you scale up, you likely want to archive them as it provides various operational advantages, at no cost.
Nothing a well-trained model won't be able to instantly solve. It's literally just grunt work, not rocket science.
F DRMs though. Good news is those AAA games are rarely worth anyone's time anyways. Better spin up indies or classic games - a good SNES game is worth a hundred of those garbo AAA license rehashes.
Can we just flag this kind of misleading and propagandist content? It’s literally content+karma farming, and brainwashing hot garbage.
Total rage bait that doesn’t have its place on platforms catering for higher educated and science oriented people.
Nuclear plants evaporates water, water rains down a few kilometers away, gets collected in sewer, recycled/filtered and re-injected in the system.
You know what doesn’t get recycled? Coal & gas burning pollution & CO2. And you know what doesn't get re-injected? Lost lives to pollution and global warming.
> All this stuff is just done automatically in Rust. If you have to write out the code by yourself, that's more work, and a huge chance for bugs. The compiler is doing some very complex tracking to figure out what to drop when and where. You'd have to do that all in your head correctly without its help.
What prevents anyone from dedicating a Zig memory allocator to the job (and all of its subtasks), and simply freeing the entire allocator at the end of the job? No baby-sitting needed.
Or if the mindset is really to be assisted, because “very complex” and too “much work”, may as well use a garbage collected language.
> It's knowing the compiler is on your side and taking care of all this that makes it magical.
Until you got used to it, and trusted it so much, and it suddenly misses something - either after a compiler update, or after some unsupported code introduced, and that shit takes down prod on a Friday. I’m not going to take the chance, thank you, I can call free() and valgrind.
I am sorry, are you non-sarcastically arguing that being able to pass through airport security, potentially accessing cockpits and planting bombs onboard airplanes, with a high-school level SQL injection on a federal website used by dozens of airlines & airlines employees, is actually, "fine"?
Besides, I am not sure what sort of "security through obscurity" you are talking about? Ian and Sam found it, and frankly - with a public page, page title + first h1 tag clearly stating that this relates to a Cockpit Access system, this has got to show up in a shit ton of security research search engines instantly.
We’ve maintained a financial exchange w/ margining for 8 years with it, and I guarantee you that everyone was more than relieved - customers and employees alike, once we were able to lift and shift the whole thing to Java.
The readability and scalability is abysmal as soon as you move on from a quant desk scenario (which everyone agrees, it is more than amazing at.. panda and dask frames all feel like kindergarten toys compared), the disaster recovery options are basically bound to having distributed storage - which are by the way “too slow” for any real KDB application given the whole KDB concept marries storage and compute in a single thread.. and use-cases of data historical data, such as mentioned in the article, become very quickly awful: one kdb process handles one request at once, so you end up having to deploy & maintain hundreds of RDB keeping the last hour in memory, HDBs with the actual historical data, pausing for hourly write downs of the data, mirroring trees replicating the data using IPC over TCP from the matching engine down to the RDBs/HDBs, recon jobs to verify that the data across all the hosts.. Not to mention that such a TCP-IPC distribution tree with single threaded applications means that any single replica stuck down the line (e.g. big query, or too slow to restart) will typically lead to a complete lockup - all the way to the matching engine - so then you need to start writing logic for circuit breakers to trip both the distribution & the querying (nothing out of the box). And then at some point you need to start implementing custom sharding mechanisms for both distribution & querying (nothing out of the box once again..!) across the hundreds of processes and dozens of servers (which has implications with the circuit breakers) because replicating the whole KDB dataset across dozens of servers (to scale the requests/sec you can factually serve in a reasonable timeframe) get absolutely batshit crazy expensive.
And this is the architecture as designed and recommended by the KX consultants that you end up having to hire to “scale” to service nothing but a few billions dollars in daily leveraged trades.
Everything we have is now in Java - all financial/mathematical logic ported over 1:1 with no changes in data schema (neither in house neither for customers), uses disruptors, convenient chronicle/aeron queues that we can replay anytime (recovery, certifying, troubleshooting, rollback, benchmarks, etc), and infinitely scalable and sharded s3/trino/scylladb for historical.. Performance is orders of magnitude up (despite the thousands of hours micro-optimizing the KDB stack + the millions in KX consultants - and without any Java optimizations really), incidents became essentially non-existent overnight, and the payroll + infra bills got also divided by a very meaningful factor :]