62dabf9a11
The /samples/ top-level tree is replaced with sibling files in each
knowledge-layer folder. An article and its demonstrations now live
side-by-side:
microsoft/knowledge/<domain>/<slug>.md
microsoft/knowledge/<domain>/<slug>.good.al
microsoft/knowledge/<domain>/<slug>.bad.al
Rationale:
- Proximity. An article and its paired samples are one unit; the
filesystem now reflects that.
- Layer ownership. Samples inherit layer precedence for free -- a
/custom/ fork can override an article and its samples atomically,
which the shared /samples/ tree previously made awkward.
- Trivial migration path. Action-skill source globs
(*/knowledge/<domain>/**/*.md) are unchanged; sample discovery is a
sibling-filename lookup.
Changes:
- git mv of all 65 sample files from samples/<domain>/<slug>/{bad,good}.al
to microsoft/knowledge/<domain>/<slug>.{bad,good}.al (history preserved).
- Update See-sample references in all 37 articles that ship samples.
- skills/read.md: replace the no-code-blocks bullet with a pointer to a
new Sample files section that fully specifies the sibling convention,
the kinds (good/bad + forward-compatible), multi-technology rules,
demonstration-only status, and layer-precedence behaviour.
- skills/write.md: update the samples pointer to match.
- README.md: annotate the knowledge tree with the sample sibling shape.
- samples/README.md deleted; content lifted into skills/read.md.
- Both generators (C:\temp\gen_performance_knowledge.py,
C:\temp\gen_security_knowledge.py) updated to emit at the new paths
and to stop writing samples/README.md. Re-running them is idempotent
against the committed layout.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
1.5 KiB
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performance |
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Use CalcSums to aggregate filtered sets
Seed article. Converted from an existing performance-review prompt to bootstrap the BCQuality performance corpus. Domain stewards should expand, restructure, and refine as needed.
Description
When the task is to compute a sum over a filtered set, CalcSums lets the platform push the aggregation down to SQL using SIFT indexes. Iterating rows in AL to accumulate a total transports every row's data to the runtime only to discard it after adding one field. On ledger-entry-scale tables this difference is dramatic. The same SIFT infrastructure backs Sum-style FlowFields; when the value you need is already declared as a FlowField, calling CalcSums on the underlying table with the correct filters produces the same aggregate.
Best Practice
Set the required filters on the record, then call CalcSums on the field you want aggregated. Ensure the table has a key whose SumIndexFields includes the summed field and whose key prefix matches the filters (see add-sift-keys-for-flowfields).
See sample: use-calcsums-for-flowfield-totals.good.al.
Anti Pattern
Looping a filtered set with FindSet and adding a field to an accumulator on every iteration performs work in AL that SQL already knows how to do in one aggregate query.
See sample: use-calcsums-for-flowfield-totals.bad.al.