It is said that there are only two hard things in computer science: cache invalidation and naming things. The story goes: you have something that is expensive to compute, so you compute it once and then you cache it and use the cached value in the future. But the inputs to that computation change, and so the cached value grows stale. You have to decide when and how to recompute that value.

In Ktistec, presenting accurate tag counts is expensive because not every tagged post counts. Posts are deleted, actors are blocked. My own drafts don't count, but when they're published they do. A post tagged with the same hashtag more than once, must count as one. And tag cardinality is not uniform: #3dprinting has hundreds of thousands of posts, others have one or two. Even with indexes, there is no single query that counts all cases in an acceptable amount of time.

So I reached for a cache, counted once and then cached the count. Because I didn't want to maintain adjustments from every place in the code that changed something that touched the count, I settled for eventual consistency and recomputed counts after every server restart.

As it turns out, that's not good enough. On a server with reasonable traffic, an event that affects some tag's count happens every few hours. Days or weeks later there is significant drift. Worse, the implementation didn't recompute on first read, it recomputed on first write (a new tagged object arrives).

This release fixes all that. Counts are still eventually consistent, but all counts are recomputed in a regular background task, so they really are eventually consistent, and care was taken in constructing the query to minimize database (read) locking to ~100-200msec.

Is it better? Yes! Is it perfect? Probably not. Cache invalidation is hard.

Here's the full changelog for this release:

Added

• Background task to reconcile tag statistics.

Fixed

• Prevent model hook callbacks from interleaving.
• Add spacing between content and the sticky footer.

Changed

• Replace Semantic UI with Fomantic UI.
• Cache the PURL and GoToSocial JSON-LD contexts.
• Reduce database lock time when reconciling tags.
• Block npm dependency install scripts.

Removed

• The unused idx_relationships_type database index.

In the next release, I'm going to fix a few bugs in the Mastodon-compatible API. These require an internal redesign, so I've held off until a few other things were out of the way. And I'm turning my attention to reading and better tools for surfacing and finding interesting content.

#ktistec #crystallang #activitypub #fediverse

I need to use a prefix to namespace status IDs vs. boost IDs in the #ktistec Mastodon-compatible API. In Mastodon, a boost is just a status and they share the same ID namespace. Ktistec predates its Mastodon-compatible API, so statuses and boosts are maintained in different tables. I wanted to use an emoji (✍️ vs. 📣) to distinguish them, but that breaks too many clients.

Shame...

hung up three sets of curtains… hit studs on every hole. it’s surprising what makes me happy.

I really enjoy optimization. Release v3.5.0 of Ktistec doesn't drop significant new features, but it does deliver a ~15% smaller executable and significantly faster queries on anonymous endpoints. The two are intertwined.

The size reduction comes from replacing a poorly designed, custom rules engine with a materialized view layer that uses SQL to define membership in a collection. The rules engine worked well enough but required a lot of supporting code to present rules as a DSL (Domain Specific Language) over the domain objects in ktistec. The driving realization was that SQL is a DSL and membership in a collection is just a query and domain objects are just rows. Voilà!

Query performance improvements came from using this new view layer to materialize two very popular but expensive-to-query views: the instance's public timeline and public hashtag pages. Because both are public pages they receive more traffic than internal pages.

The problem with the original queries was that performance was not uniform. Querying for posts with popular tags was okay. Querying for posts with sparse tags was very slow. I could have added more indexes, but that's its own cost. After the change, endpoints all respond in a consistent ~10msec timeframe and the CPU barely registers when a crawler hits. (I don't want to make things easier for bots, but I don't want to pay a tax for their activity either—ask me about my new nginx configuration.)

Here is the full changelog:

Added

• Lightweight probe endpoint for authenticated sessions.
• max-id and min-id pagination links on web pages.

Fixed

• Correct the notifications collection's JSON representation.
• Accept both single-value and array forms of JSON-LD properties.
• Handle variation in schema.org property mapping.

Changed

• Faster timeline, public, hashtag, and notification collections.
• Adjust the layout of actor profile properties.

Removed

• The school dependency; replaced by activity processors and materialized views.
• The openssl_ext dependency; vendored in.

There are still a few slow queries. In the next release I'm going to see if I can get everything under 10msec, and maybe release a new feature, too. 🚀

#ktistec #crystallang #activitypub #fediverse

i predict there will be a day in 2026, in the npm ecosystem, in which it will be impossible to simultaneously update a package to fix a critical zero day without also downloading a required transitive dependency that introduces another...

i think the defining characteristic of a "grey beard" (other than having an actual grey beard) is stories like: "decades ago, a guy i worked with wrote a script called bup that saved changes to a named file, regardless of the version control system in use. git? no problem! rcs? no problem! cvs? no problem!"

i still have the script. 👈

I just finished working on improvements to #ktistec that cut about 15% off the built executable size, and speed up some of the more common public queries by 2x to 5x (they were already fast, so this is headroom).

It does this by replacing a poorly designed, feature poor, custom rules engine with a materialized view layer that uses SQL as its DSL (domain specific language).

I am about to smoke test it on my own site. If it’s not available—well, you know why! 😀

bitten

https://github.com/mastodon/mastodon/issues/18361

#ktistec #jsonld