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Getting AI to write good SQL

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Re: Getting AI to write good SQL

#21

Post by AdrianB1 »

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 because AI is hallucinating or because the changes that it proposes are not working in a way that is beneficial, it is like an idiot parrot is telling what it overheard in the brothel - good info if it is a war brothel frequented by enemy officers in 1916, but not these days.

Re: Getting AI to write good SQL

#22

Post by RadiozRadioz »

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 understand 90% of the expressions people actually write.

It takes far longer to tell an AI what you want than to write a regex yourself.

Re: Getting AI to write good SQL

#23

Post by emptysea »

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…

That's one of the features of EdgeQL:

    select Movie {
      id,
      title,
      actors: {
        name
      }
    };
https://docs.geldata.com/learn/edgeql#select-objects

Although I think good enough language server / IDE could automatically insert the join when you typed `credit.CLIENT->NAME`

Re: Getting AI to write good SQL

#24

Post by phillipcarter »

tango12 wrote: post #17

What’s the eventual goal of text to sql? Is it to build a copilot for a data analyst or to get business insight without going through an analyst? If it’s the latter - then imho no amount of text to sql sophistication will solve the problem because it’s impossible for a non analyst to understand if the sql is correct or sufficient. These don’t seem like text2sql problems: > Why did we hit only 80% of our daily ecommme…

> These don’t seem like text2sql problems:

Correct, but I would propose two things to add to your analysis:

1. Natural language text is a universal input to LLM systems

2. text2sql makes the foundation of retrieving the information that can help answer these higher-level questions

And so in my mind, the goals for text2sql might be a copilot (near-term), but the long-term is to have a good foundation for automating text2sql calls, comparing results, and pulling them into a larger workflow precisely to help answer the kinds of questions you're proposing.

There's clearly much work needed to achieve that goal.

Re: Getting AI to write good SQL

#25

Post by efromvt »

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…

(Shameless plug) writing the same joins over and over (and refactoring when you update stuff) was one of my biggest boilerplate annoyances with SQL - I’ve tried to fix that while still keeping the rest of SQL in https://trilogydata.dev/

Re: Getting AI to write good SQL

#26

Post by wewewedxfgdf »

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 AI Studio is such a giant leap ahead in programming I have to pinch myself when I'm using it.

Re: Getting AI to write good SQL

#27

Post by tough »

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…

Its something you use so sparingly far away usually that never sticks around

Re: Getting AI to write good SQL

#28

Post by richardw »

tango12 wrote: post #17

What’s the eventual goal of text to sql? Is it to build a copilot for a data analyst or to get business insight without going through an analyst? If it’s the latter - then imho no amount of text to sql sophistication will solve the problem because it’s impossible for a non analyst to understand if the sql is correct or sufficient. These don’t seem like text2sql problems: > Why did we hit only 80% of our daily ecommme…

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 the system in coordination with experts, test it, have the AI explain all trade offs, potential bugs, sense check it against expected results etc.

Taste is hard to automate. Real insight is hard to automate. But a domain expert who isn’t an “analyst” can go extremely far with well designed automation and a sense of what rational results should look like. Obviously the state of the art isn’t perfect but you asked about goals, so those would be my goals.

Re: Getting AI to write good SQL

#29

Post by jacob019 »

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…

The first languge I used to solve real problems was perl, where regex is a first class citizen. In python less so, most of my python scripts don't use it. I love regex but know several developers who avoid it like plague. You don't know what you don't know, and there's nothing wrong with that. LLM's are super helpful for getting up to speed on stuff.

Re: Getting AI to write good SQL

#30

Post by carderne »

quantadev wrote: post #10
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 proper constraints and foreign keys that are clear is generally all that's needed in my experience. Are you sure your tables have well defined constraints, so that the AI can be absolutely 100% sure how everything links up? SQL is very precise, but only if you're utilizing constraints and foreign key definitions well.

It’s BigQuery, so it likely won’t have any of these.
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