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Getting AI to write good SQL

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Re: Getting AI to write good SQL

#41

Post by CuriouslyC »

RadiozRadioz wrote: post #22
nashashmi wrote: post #12

AI text to regex solutions would be incredibly handy.

This comment appears frequently and always surprises me. Do people just... not know regex? It seems so foreign to me. It's not like it's some obscure thing, it's absolutely ubiquitous. Relatively speaking it's not very complicated, it's widely documented, has vast learning resources, and has some of the best ROI of any DSL. It's funny to joke that it looks like line noise, but really, there is not a lot to learn to u…

I was using perl in the late 90s for sysadmin stuff, have written web scrapers in python and have a solid history with regex. That being said, AI can still write really complex lookback/lookahead/nested extraction code MUCH faster and with fewer bugs than me, because regex is easy to make small mistakes with even when proficient.

Re: Getting AI to write good SQL

#42

Post by wewewedxfgdf »

CuriouslyC wrote: post #39
wewewedxfgdf wrote: post #26

Can I just say that Google AI Studio with latest Gemini is stunningly, amazingly, game changingly impressive. It leaves Claude and ChatGPT's coding looking like they are from a different century. It's hard to believe these changes are coming in factors of weeks and months. Last month i could not believe how good Claude is. Today I'm not sure how I could continue programming without Google Gemini in my toolkit. Gemini…

I'm really surprised more people haven't caught on. Claude can one shot small stuff of similar complexity, but as soon as you start to really push the model into longer, more involved use cases Gemini pulls way ahead. The context handling is so impressive, in addition to using it for coding agents, I use Gemini as a beta reader for a fairly long manuscript (~85k words) and it absolutely nails it, providing a high lev…

It is absolutely the greatest golden age in programming ever - all these infinitely wealthy companies spending bajillions competing on who can make the best programming companion.

Apart from the apologising. It's silly when the AI apologises with ever more sincere apologies. There should be no apologies from AIs.

Re: Getting AI to write good SQL

#44

Post by tough »

layer8 wrote: post #40
eddd-ddde wrote: post #34

Earlier quoted context omitted.

I know regex. But I use it so sparingly that every time I need it I forgot again the character for word boundary, or the character for whitespace, or the exact incantation for negative lookahead. Is it >!? who knows. A shortcut to type in natural language and get something I can validate in seconds is really useful.

How do you validate it if you don’t know the syntax? Or are you saying that looking up syntax –> semantics is significantly quicker than semantics –> syntax? Which I don’t find to be the case. What takes time is grokking the semantics in context, which you have to do in both cases.

https://regex101.com/

Re: Getting AI to write good SQL

#45

Post by bob1029 »

For the problems where it would matter the most, these tools seem to help the least. The hardest problem domains don't have just one schema to worry about. They have hundreds. If you need to spin up a personal blog or todo list tracker, I have no doubt that Google, et. al. can take you exactly where you want to go.

Re: Getting AI to write good SQL

#46

Post by HideousKojima »

awesome_dude wrote: post #33
AdrianB1 wrote: post #21

In real life I find using AI for SQL dangerous. It allows people that don't know what they do to write queries that can significantly impact servers. In my world databases are relatively big for most developers, but not huge. Sometimes when I want to fine tune a query I am challenging AI to provide a better solution. I give it the already optimized query and I ask for better. I never got a better answer, sometimes be…

Mate, IME programmers who don't know what they are doing just do it anyways then look to blame someone/something else if things turn to custard. AI is just increasing the frequency of things turning to custard :)

AI is most effective as an accountability sink

Re: Getting AI to write good SQL

#47

Post by marcosdumay »

tough wrote: post #44
layer8 wrote: post #40

Earlier quoted context omitted.

How do you validate it if you don’t know the syntax? Or are you saying that looking up syntax –> semantics is significantly quicker than semantics –> syntax? Which I don’t find to be the case. What takes time is grokking the semantics in context, which you have to do in both cases.

https://regex101.com/

Notice that site has a very usable reference list you can consult for all those details the GP forgets.

Re: Getting AI to write good SQL

#48

Post by thingsilearned »

wewewedxfgdf wrote: post #42
CuriouslyC wrote: post #39

Earlier quoted context omitted.

I'm really surprised more people haven't caught on. Claude can one shot small stuff of similar complexity, but as soon as you start to really push the model into longer, more involved use cases Gemini pulls way ahead. The context handling is so impressive, in addition to using it for coding agents, I use Gemini as a beta reader for a fairly long manuscript (~85k words) and it absolutely nails it, providing a high lev…

It is absolutely the greatest golden age in programming ever - all these infinitely wealthy companies spending bajillions competing on who can make the best programming companion. Apart from the apologising. It's silly when the AI apologises with ever more sincere apologies. There should be no apologies from AIs.

companion or replacement?

Re: Getting AI to write good SQL

#49

Post by richardw »

layer8 wrote: post #36
richardw wrote: post #28

Earlier quoted context omitted.

Any algo that a human would follow can be built and tested. If you have 10 analysts you have 10 different skill levels, with differing understanding of the database and business context. So automation gives you a platform to achieve a floor of skill and knowledge. The humans can now be “at least this good or better”. A new analyst instantly gets better, faster. I assume a useful goal would be to guide development of…

But “text to sql” isn’t an algorithm.

The processes the people want the sql for are likely filled with algo’s. An exec wants info in a known domain, set up a text to sql system with lots of context and testing to generate queries. If they think they have something good, get an expert to test and productionise it.

“Thank you for your request. Can you walk me through the steps you’d use to do this manually? What things would you watch out for? What kind of number ranges are reasonable? I can propose an algorithm and you tell me if that’s correct. The admins have set up guidelines on how to reason about customer and purchase data. Is the following consistent with your expectations?”

Re: Getting AI to write good SQL

#50

Post by galenmarchetti »

flysand7 wrote: post #11
mousetree wrote: post #6

Out of all the AI tools and models I’ve tried, the most disappointing is the Gemini built into BigQuery. Despite having well named columns with good descriptions it consistently gets nowhere close to solving the problem.

Having written more SQL than any other programming language by now, every time I've tried to use AI to write the query for me, I'd spend way more time getting the output right than if I'd just written it myself. As a quick aside there's one thing I wish SQL had that would make writing queries so much faster. At work we're using a DSL that has one operator that automatically generates joins from foreign key columns, j…

yeah we’re doing something similar under the hood at AstroBee. it’s way way way easier to handle joins this way.

imo any hope of really leveraging llms in this context needs this + human review on additions to a shared ontology/semantic layer so most of the nuanced stuff is expressed simply and reviewed by engineering before business goes wild with it

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