Advanced Query (Datalog)
When one filter line isn't enough — rules that join, derive and condense
Transcript
What if your report did not have to be clicked together from ten views, but grew from a single rule — a rule that describes what counts and recomputes on its own? Over the next few minutes you will hear where the filter line ends and where Datalog begins.
A Simple Query filters one property and becomes a view. That is enough as long as you check one thing. But the moment you want to connect two — open tasks from a quarter's meetings, grouped by project — the filter line runs out. It checks blocks one by one against fixed criteria; it joins nothing, derives nothing, adds nothing up.
Datalog turns that around. You do not describe the search path, you describe the goal. You say what should be true and leave the how to the engine. That is the heart of any declarative language, and database research has documented the advantage consistently since the foundations of Datalog theory.
A rule has two parts. One part says which value you want to see. The other lists the conditions, line by line. Variables connect the lines — where the same variable appears more than once, that is a join, a bridge across blocks. This is exactly where a filter line turns into a connected report.
Three building blocks carry you far. First, the rule describes the goal, not the path. Second, each condition line is one criterion, and shared variables connect them into a join. Third, aggregates condense the match set — you count, sum, group, and many blocks become one number per group.
This power has a price. An unbounded or recursive rule can sweep the whole store several times over. Set limits, check the speed, and save a rule as a standing view only once it stays fast enough. And without clean properties no rule will bite — data discipline stays the quiet precondition.
The honest question at the end: how many of your reports do you rebuild every week because they connect several criteria no filter line can hold? If the figure is high, the steeper learning curve pays off. Described once as a rule, your second brain builds the report — and keeps it current while you think.
A Simple Query filters one property and becomes a view. But the moment you want to connect two things — open tasks from a quarter's meetings, grouped by project — the filter line runs out. Datalog starts exactly there: you describe the relationship as a rule, and mium derives the rest.
Where the filter line runs out
A filter line checks blocks one by one against fixed criteria. It can't join across blocks, derive nothing and add nothing up. Multi-criteria reports you'd otherwise click together by hand from several views — and maintain them the same way. Datalog turns that around: one rule that describes the relationships, and an engine that evaluates it.
Anatomy of a rule
A Datalog rule has two parts: :find says which value you want to see, :where lists the conditions — one per line. Variables such as ?task connect the lines; where the same variable appears more than once, that is a join.
[:find ?task
:where
[?task "type" "task"]
[?task "status" "offen"]
[?task "von-meeting" ?m]
[?m "tag" "q3"]]
;; offene Aufgaben aus Q3-Meetings — ein Join über ?m5 building blocks for Advanced Query
- The rule describes the goal (:find), not the search path — you say what, not how.
- Each :where line is a condition; shared variables connect them into a join.
- Aggregates condense: count, sum, max, min, avg over the matched set.
- A rule is reusable — name it, and it becomes a view for the whole team.
- Set limits: recursive or unbounded joins need a bound, or the evaluation gets expensive.
Example: counting open tasks per project
[:find ?projekt (count ?task)
:where
[?task "type" "task"]
[?task "status" "offen"]
[?task "projekt" ?projekt]]
;; ein Report: pro Projekt die Zahl offener AufgabenBefore and after — Simple Query vs Datalog
| Capability | Simple Query | Datalog |
|---|---|---|
| Criteria | one property | any number |
| Joining across blocks | no | yes (join over variables) |
| Deriving / aggregating | no | count··sum··group |
| Reusable | as a view | as a named rule |
| Learning curve | minutes | steeper, but more powerful |
An honest question
How many of your reports do you rebuild every week because they connect several criteria no filter line can hold? The answer decides whether Datalog's steeper learning curve pays off for you — or whether a Simple Query already does the job.
Describe what counts — mium works out the rest.
One rule, and your second brain builds the report — and keeps it current while you think. No export, no clicking together; a companion that understands your criteria.
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