related: #36380
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- Core invariant: aggregation is centralized and schema-aware — all
aggregate functions are created via the exec Aggregate registry
(milvus::exec::Aggregate) and validated by ValidateAggFieldType, use a
single in-memory accumulator layout (Accumulator/RowContainer) and
grouping primitives (GroupingSet, HashTable, VectorHasher), ensuring
consistent typing, null semantics and offsets across planner → exec →
reducer conversion paths (toAggregateInfo, Aggregate::create,
GroupingSet, AggResult converters).
- Removed / simplified logic: removed ad‑hoc count/group-by and reducer
code (CountNode/PhyCountNode, GroupByNode/PhyGroupByNode, cntReducer and
its tests) and consolidated into a unified AggregationNode →
PhyAggregationNode + GroupingSet + HashTable execution path and
centralized reducers (MilvusAggReducer, InternalAggReducer,
SegcoreAggReducer). AVG now implemented compositionally (SUM + COUNT)
rather than a bespoke operator, eliminating duplicate implementations.
- Why this does NOT cause data loss or regressions: existing data-access
and serialization paths are preserved and explicitly validated —
bulk_subscript / bulk_script_field_data and FieldData creation are used
for output materialization; converters (InternalResult2AggResult ↔
AggResult2internalResult, SegcoreResults2AggResult ↔
AggResult2segcoreResult) enforce shape/type/row-count validation; proxy
and plan-level checks (MatchAggregationExpression,
translateOutputFields, ValidateAggFieldType, translateGroupByFieldIds)
reject unsupported inputs (ARRAY/JSON, unsupported datatypes) early.
Empty-result generation and explicit error returns guard against silent
corruption.
- New capability and scope: end-to-end GROUP BY and aggregation support
added across the stack — proto (plan.proto, RetrieveRequest fields
group_by_field_ids/aggregates), planner nodes (AggregationNode,
ProjectNode, SearchGroupByNode), exec operators (PhyAggregationNode,
PhyProjectNode) and aggregation core (Aggregate implementations:
Sum/Count/Min/Max, SimpleNumericAggregate, RowContainer, GroupingSet,
HashTable) plus proxy/querynode reducers and tests — enabling grouped
and global aggregation (sum, count, min, max, avg via sum+count) with
schema-aware validation and reduction.
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Signed-off-by: MrPresent-Han <chun.han@gmail.com>
Co-authored-by: MrPresent-Han <chun.han@gmail.com>
1. Add global scheduler for datacoord.
2. Define and implement new CreateTask, QueryTask, DropTask interfaces.
3. Refine Import, Compaction, Stats, Index task.
issue: https://github.com/milvus-io/milvus/issues/41123
Co-authored-by: Cai Zhang <cai.zhang@zilliz.com>
