0.25.4 - Paradedb — ContextQMD

New Features 🎉

Added support for aggregate score joins, enabling queries to ORDER BY a sum of scores across joined tables.
Added paradedb.vector_clusters to inspect per-cluster posting list sizes and ball-bound radii for vector indexes.

Cross-table disjunctive search predicates (e.g. a.text @@@ 'foo' OR b.text @@@ 'bar') now evaluate via predicate tagging rather than UDFs, improving low-selectivity disjunctive join query performance by up to 22x.
MPP self-loops across stages on the same worker now communicate over an in-memory channel, eliminating in-process serialization overhead.
Dynamic shared memory (DSM) allocation for parallel index scans on PostgreSQL 15–17 now sizes EXPLAIN info slots only when used, reducing shared memory overhead from ~66MB to ~2MB.
Eliminated redundant eager planning passes in AggregateScan and JoinScan, sizing DSM allocations directly from physical stages.
Gate MPP execution behind a minimum row count, configurable via paradedb.mpp_min_rows.

Parallel MPP worker scans and leader consumers now replay the leaders's segment view and mutable segment bounds.
AggregateScan now validates collation semantics during GROUP BY pushdown, falling back to PostgreSQL for non-deterministic collations and GROUPING SETS.
Plain EXPLAIN now matches runtime behavior by rendering the serial execution plan when task discovery finds fewer than 2 parallel tasks.
Dynamic filter pushdown is now tracked and reported via metrics across MPP execution stages.
EXPLAIN plans for the aggregate and join scan now display the table name or alias.

The full changelog is available on the GitHub Release.