fix(driver-memory): accept the engine QueryAST in aggregate() (analytics fallback)#1703
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…ics fallback)
ObjectQL's engine calls driver.aggregate(object, AST) with the same
{ where, groupBy, aggregations } shape find() consumes — but the in-memory
driver's aggregate() only understood MongoDB pipeline arrays, so the
analytics RAW_SQL_UNSUPPORTED fallback (framework#1701) crashed with
"this[#pipeline].map is not a function" on in-memory environments — the
last broken link in dataset queries on staging tenants.
aggregate() now detects the AST shape and serves it through the SAME
where-filter + performAggregation path find() uses (count/sum/avg/min/max,
multi-field groupBy, aliases); a real pipeline array keeps the Mingo
behavior unchanged.
driver-memory: 68 tests green (3 new: grouped sums via AST, where+no-groupBy
single-row totals, pipeline-array passthrough).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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Completes the staging "No rows" fix chain (framework#1701 was layer 1).
After #1701, dataset queries on in-memory environments correctly fall back from NativeSQL to the aggregate strategy — which then crashed with
this[#pipeline].map is not a function:ObjectQL.aggregatehands drivers the QueryAST ({where, groupBy, aggregations}), butInMemoryDriver.aggregate()only understood MongoDB pipeline arrays (Mingo).aggregate()now detects the AST shape and serves it through the same where-filter +performAggregationpathfind()already uses (the shapes match exactly —{function, field, alias}); real pipeline arrays keep the Mingo passthrough unchanged.Test: driver-memory 68 green — new: grouped sums via AST;
where+ no-groupBy single-row totals; pipeline-array passthrough.Staging validation: bump cloud
.framework-shaafter merge → the expense Spending Dashboard should finally render real numbers.🤖 Generated with Claude Code