To be fair they could have done an experiment on a transaction that typically requires a person in the loop. Rather than choosing a vending machine which, already, does not require a person in the loop for the transaction.
Interesting choice of Pandas in this day and age. Maybe he’s after imparting general concepts that you could apply to any tabular data manipulator rather than selecting for the latest shiny tool.
Agreed, but maybe the step change there is refactoring the data model, not continuing to author “hairy” sql via LLM that’s all fine until it breaks… and you end having to mend the nastiness back into compliance the ol’ fashion way
What is the human need to bash SQL at all costs? At its core, such a simple syntax, yet its so powerful at aggregating/manipulating tabular data and the like. Instead we’d rather declaratively say what we want in a more verbose/disjointed way… fascinating
“We filtered first instead of reading an entire table from disk and performing a lookup”
Where both OLAP and OLTP dbms would benefit.
To your point, it’s clear certain workloads lend themselves to OLAP and columnar storage much better, but “an endless sequence of misbehavior” seems a bit harsh .
I love a semantic layer as much as the next guy...
Pivoting a decent sized BI shop toward using one instead of splashing the same SQL all over the place is *tough*. It's one of those: "the analyst could have been building important report for director and you want them to create re-usable logic??? we'll do that later, get report done now. Just copy/paste that SQL over here"
This is how you end up with the the 1000 model, "the numbers don't match up", hot mess situations that gain momentum and are hard to slow down.
Another great way to increase your surface area for luck is being born in a first world country with access to a computer. I hear that has a good success rate!
Too many factors to possibly diagnose if “it’s you”, or even if there is something “to fix”.
Anecdotally, I desire to hang out with people who share my interests and want to do similar activities that we both enjoy.
I’m a few years removed from college now, and it’s highlighted to me just how special living closely with people of similar age and interest does for one’s social life. Once you spread out, gain dependents, work, etc… it’s much more of an effort to stay in touch.
Just because someone doesn’t reciprocate your effort to connect doesn’t necessarily mean they don’t want to hang out with you.
Eh it's not that bad, lived in Phoenix for 25 years so I'm used to it... vacation weather for 7 months of the year. Great access to nature. There's always trade-offs no matter where you live.
All excellent points. The best is when most workloads on the cluster use a temp table with an identical name. Then someone comes along and accidentally drops the TEMP from the their temp table ctas and it gets smashed into the public schema.
“Table already exists…”scheduled job run failure galore, fun times.
Steering has gone out twice on a family member’s Model Y. N=1 example but plenty of other companies now make EVs and they do a decent job of it… shedding 29% still leaves the company at an astronomical valuation, ~100bn larger market cap than Toyota.