Claude 351610d18c Implement aggregate execution with wide-batch model ... Add runtime support for aggregate functions (count, sum, avg, min, max) with GROUP BY semantics, built on a single wide RecordBatch that eliminates correlation tracking by construction. Execution engine (exec/query.rs): - Replace HashMap<String, RecordBatch> with Option<RecordBatch> where columns are prefixed as <variable>.<property> - NodeScan prefixes columns and cross-joins with existing batch - Expand collects (src_row, dst_id) pairs, takes wide batch rows, appends prefixed destination columns via hconcat - Filter applies single mask to entire wide batch - AntiJoin: fast-path returns BooleanArray mask; slow-path slices one row for inner pipeline execution Projection engine (exec/projection.rs): - aggregate_return groups rows by non-aggregate key columns using length-prefixed string encoding, computes per-group aggregates - SUM accumulates into f64 to avoid integer overflow - MIN/MAX support both numeric and string types - Empty input returns count=0, others=null Compiler (typecheck.rs): - T8: split MIN/MAX from SUM/AVG — allow string arguments - T9: non-aggregate expressions in aggregate queries must be property accesses or variables - SUM type inference returns Float64 (matching runtime) Tests: 8 new integration tests covering grouped count, global count, sum/avg/min/max per company, aggregate+order+limit, string min/max, multi-hop aggregates, and edge cases. https://claude.ai/code/session_019o5NRyYomgETFyd7hpiLey		2026-04-12 20:59:13 +00:00
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omnigraph	Implement aggregate execution with wide-batch model	2026-04-12 20:59:13 +00:00
omnigraph-cli	Prepare v0.2.0 release	2026-04-12 20:35:34 +03:00
omnigraph-compiler	Implement aggregate execution with wide-batch model	2026-04-12 20:59:13 +00:00
omnigraph-server	Prepare v0.2.0 release	2026-04-12 20:35:34 +03:00