issue: https://github.com/milvus-io/milvus/issues/46517
ref: https://github.com/milvus-io/milvus/issues/42148
This PR supports match operator family with struct array and brute force
search only.
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
- Core invariant: match operators only target struct-array element-level
predicates and assume callers provide a correct row_start so element
indices form a contiguous range; IArrayOffsets implementations convert
row-level bitmaps/rows (starting at row_start) into element-level
bitmaps or a contiguous element-offset vector used by brute-force
evaluation.
- New capability added: end-to-end support for MATCH_* semantics
(match_any, match_all, match_least, match_most, match_exact) — parser
(grammar + proto), planner (ParseMatchExprs), expr model
(expr::MatchExpr), compilation (Expr→PhyMatchFilterExpr), execution
(PhyMatchFilterExpr::Eval uses element offsets/bitmaps), and unit tests
(MatchExprTest + parser tests). Implementation currently works for
struct-array inputs and uses brute-force element counting via
RowBitsetToElementOffsets/RowBitsetToElementBitset.
- Logic removed or simplified and why: removed the ad-hoc
DocBitsetToElementOffsets helper and consolidated offset/bitset
derivation into IArrayOffsets::RowBitsetToElementOffsets and a
row_start-aware RowBitsetToElementBitset, and removed EvalCtx overloads
that embedded ExprSet (now EvalCtx(exec_ctx, offset_input)). This
centralizes array-layout logic in ArrayOffsets and removes duplicated
offset conversion and EvalCtx variants that were redundant for
element-level evaluation.
- No data loss / no behavior regression: persistent formats are
unchanged (no proto storage or on-disk layout changed); callers were
updated to supply row_start and now route through the centralized
ArrayOffsets APIs which still use the authoritative
row_to_element_start_ mapping, preserving exact element index mappings.
Eval logic changes are limited to in-memory plumbing (how
offsets/bitmaps are produced and how EvalCtx is constructed); expression
evaluation still invokes exprs_->Eval where needed, so existing behavior
and stored data remain intact.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: SpadeA <tangchenjie1210@gmail.com>
Signed-off-by: SpadeA-Tang <tangchenjie1210@gmail.com>
issue: https://github.com/milvus-io/milvus/issues/42148
For a vector field inside a STRUCT, since a STRUCT can only appear as
the element type of an ARRAY field, the vector field in STRUCT is
effectively an array of vectors, i.e. an embedding list.
Milvus already supports searching embedding lists with metrics whose
names start with the prefix MAX_SIM_.
This PR allows Milvus to search embeddings inside an embedding list
using the same metrics as normal embedding fields. Each embedding in the
list is treated as an independent vector and participates in ANN search.
Further, since STRUCT may contain scalar fields that are highly related
to the embedding field, this PR introduces an element-level filter
expression to refine search results.
The grammar of the element-level filter is:
element_filter(structFieldName, $[subFieldName] == 3)
where $[subFieldName] refers to the value of subFieldName in each
element of the STRUCT array structFieldName.
It can be combined with existing filter expressions, for example:
"varcharField == 'aaa' && element_filter(struct_field, $[struct_int] ==
3)"
A full example:
```
struct_schema = milvus_client.create_struct_field_schema()
struct_schema.add_field("struct_str", DataType.VARCHAR, max_length=65535)
struct_schema.add_field("struct_int", DataType.INT32)
struct_schema.add_field("struct_float_vec", DataType.FLOAT_VECTOR, dim=EMBEDDING_DIM)
schema.add_field(
"struct_field",
datatype=DataType.ARRAY,
element_type=DataType.STRUCT,
struct_schema=struct_schema,
max_capacity=1000,
)
...
filter = "varcharField == 'aaa' && element_filter(struct_field, $[struct_int] == 3 && $[struct_str] == 'abc')"
res = milvus_client.search(
COLLECTION_NAME,
data=query_embeddings,
limit=10,
anns_field="struct_field[struct_float_vec]",
filter=filter,
output_fields=["struct_field[struct_int]", "varcharField"],
)
```
TODO:
1. When an `element_filter` expression is used, a regular filter
expression must also be present. Remove this restriction.
2. Implement `element_filter` expressions in the `query`.
---------
Signed-off-by: SpadeA <tangchenjie1210@gmail.com>
issue: #39541
This PR implements random sample, the syntax is:
```
filter="random_sample(factor)"
or
filter="boolean_expression && random_sample(factor)"
where
factor is a float between (0, 1) and
boolean_expression is like
"1 <= number < 10", "color in ["read, "blue"]" or others
```
---------
Signed-off-by: SpadeA-Tang <tangchenjie1210@gmail.com>
Signed-off-by: SpadeA <tangchenjie1210@gmail.com>
issue: #36672
The expression supports filling elements through templates, which helps
to reduce the overhead of parsing the elements.
---------
Signed-off-by: Cai Zhang <cai.zhang@zilliz.com>
