Where database blog posts get flame-broiled to perfection
Alex "Downtime" Rodriguez here. I just finished reading this... aspirational blog post while fondly caressing a sticker for a sharding middleware company that went out of business in 2017. Ah, another "simple" migration guide that reads like it was written by someone who has never been woken up by a PagerDuty alert that just says "502 BAD GATEWAY" in all caps.
Let's file this under "Things That Will Wake Me Up During the Next Long Weekend." Here’s my operations-side review of this beautiful little fantasy you've written.
First, the charming assumption that SQL Server's full-text search and PostgreSQL's tsvector are a one-to-one mapping. This is my favorite part. It’s like saying a unicycle and a motorcycle are the same because they both have wheels. I can already hear the developers a week after launch: "Wait, why are our search results for 'running' no longer matching 'run'? The old system did that!" You've skipped right over the fun parts, like customizing dictionaries, stop words, and stemming rules that are subtly, maddeningly different. But don't worry, I'll figure it out during the emergency hotfix call.
You mention pg_trgm and its friends as if they're magical pixie dust for search. You know what else they are? Glorious, unstoppable index bloat machines. I can't wait to see the performance graphs for this one. The blog post shows the CREATE INDEX command, but conveniently omits the part where that index is 5x the size of the actual table data and consumes all our provisioned IOPS every time a junior dev runs a bulk update script. This is how a "performant new search feature" becomes the reason the entire application grinds to a halt at 2:47 AM on a Saturday.
My absolute favorite trope: the implicit promise of a "seamless" migration. You lay out the steps as if we're just going to pause the entire world, run a few scripts, and flip a DNS record. You didn't mention the part where we have to build a dual-write system, run shadow comparisons for two weeks, and write a 20-page rollback plan that's more complex than the migration itself. It’s like suggesting someone change a car's transmission while it's going 70mph down the highway. What could possibly go wrong?
Ah, and the monitoring strategy. Oh, wait, there isn't one. The guide on how to implement this brave new world is strangely silent on how to actually observe it. What are the key metrics for tsvector query performance? How do I set up alerts for GIN index bloat? Where's the chapter on the custom CloudWatch dashboards I'll have to build from scratch to prove to management that this new system is, in fact, the source of our spiraling AWS bill?
Your guide basically ends with "And they searched happily ever after." Spoiler: they don't.
pg_bigm has a subtle breaking change that wasn't documented anywhere except a random mailing list thread from 2019. The application is down, the blog post author is probably sipping a latte somewhere, and I'm frantically trying to explain to my boss what a "trigram" is.Anyway, great post. I've printed it out and placed it in the folder labeled "Future Root Cause Analysis." I will absolutely not be subscribing. Now if you'll excuse me, I need to go pre-emptively increase our logging budget.