issue: https://github.com/milvus-io/milvus/issues/45890
ComputePhraseMatchSlop accepts three pararms:
1. A string: query text
2. Some trings: data texts
3. Analyzer params,
Slop will be calculated for the query text with each data text in the
context of phrase match where they are tokenized with tokenizer with
analyzer params.
So two array will be returned:
1. is_match: is phrase match can sucess
2. slop: the related slop if phrase match can sucess, or -1 is cannot.
---------
Signed-off-by: SpadeA <tangchenjie1210@gmail.com>
issue: #43897
also for issue: #46166
add ack_sync_up flag into broadcast message header, which indicates that
whether the broadcast operation is need to be synced up between the
streaming node and the coordinator.
If the ack_sync_up is false, the broadcast operation will be acked once
the recovery storage see the message at current vchannel, the fast ack
operation can be applied to speed up the broadcast operation.
If the ack_sync_up is true, the broadcast operation will be acked after
the checkpoint of current vchannel reach current message.
The fast ack operation can not be applied to speed up the broadcast
operation, because the ack operation need to be synced up with streaming
node.
e.g. if truncate collection operation want to call ack once callback
after the all segment are flushed at current vchannel, it should set the
ack_sync_up to be true.
TODO: current implementation doesn't promise the ack sync up semantic,
it only promise FastAck operation will not be applied, wait for 3.0 to
implement the ack sync up semantic. only for truncate api now.
---------
Signed-off-by: chyezh <chyezh@outlook.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>
This PR:
1. Define and implement the new FlushAllMessage.
2. Refactor FlushAll to flush the entire cluster.
issue: https://github.com/milvus-io/milvus/issues/45919
---------
Signed-off-by: bigsheeper <yihao.dai@zilliz.com>
issue: #39157
Overview:
Support search by PK by resolving IDs to vectors on Proxy side. Upgrade
go-api to adapt to new proto definitions.
Design:
- Upgrade milvus-proto/go-api to latest master.
- Implement handleIfSearchByPK in Proxy: resolve IDs to vectors via
internal Query, then rewrite SearchRequest.
- Adapt to 'SearchInput' oneof field in SearchRequest across client and
handlers.
- Fix binary vector stride calculation bug in placeholder utils.
Compatibility:
- Old Pymilvus can still work w/o this feature
What is included:
- Dense and Sparse
- Multi vector fields
- Rejection on BM25
What is **not** include:
- Hybrid Search
- EmbeddingList
- Restful API
Signed-off-by: Li Liu <li.liu@zilliz.com>
issue: #46176
- Add checkAligned validation before processing partial update field
data to prevent index out of range panic when field data arrays have
mismatched lengths
- Fix GetNumRowOfFieldDataWithSchema to handle Timestamptz string format
and Geometry WKT format properly
- Add unit tests for empty data array scenarios in partial update
---------
Signed-off-by: Wei Liu <wei.liu@zilliz.com>
Add collection-level granularity to the garbage collector pause/resume
mechanism. Previously, GC pause affected all collections globally. Now
operators can pause GC for specific collections while allowing other
collections to continue normal GC operations.
Changes:
- Add `pausedCollection` concurrent map to track per-collection pause
state
- Extend `Pause()` and `Resume()` methods with `collectionID` parameter
- Add `collectionGCPaused()` helper to check collection pause status
- Skip dropped segment recycling when collection GC is paused
- Update management API to accept optional `collection_id` query
parameter
- Add `GetInt64Value()` utility function for parsing int64 from KV pairs
- Maintain backward compatibility: collectionID <= 0 triggers global
pause
This provides DevOps with finer control over Milvus data lifecycle.
issue: #45941
---------
Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
issue: #44320
Replace the DeduplicateFieldData function with CheckDuplicatePkExist
that returns an error when duplicate primary keys are detected in the
same batch, instead of silently deduplicating.
Changes:
- Replace DeduplicateFieldData with CheckDuplicatePkExist in util.go
- Update upsertTask.PreExecute to return error on duplicate PKs
- Simplify helper function from findLastOccurrenceIndices to
hasDuplicates
- Update unit tests to verify the new error behavior
- Add Python integration tests for duplicate PK error cases
Signed-off-by: Wei Liu <wei.liu@zilliz.com>
Previously, search with highlight only supported using BM25 search text
as the highlight target.
This PR adds support for highlighting with user-defined queries.
relate: https://github.com/milvus-io/milvus/issues/42589
---------
Signed-off-by: aoiasd <zhicheng.yue@zilliz.com>
issue: https://github.com/milvus-io/milvus/issues/45691
Add persistent task management for external collections with automatic
detection of external_source and external_spec changes. When source
changes, the system aborts running tasks and creates new ones, ensuring
only one active task per collection. Tasks validate their source on
completion to prevent superseded tasks from committing results.
---------
Signed-off-by: sunby <sunbingyi1992@gmail.com>
https://github.com/milvus-io/milvus/issues/45544
- Add batch_factor configuration parameter (default: 5) to control
embedding provider batch sizes
- Add disable_func_runtime_check property to bypass function validation
during collection creation
- Add database interceptor support for AddCollectionFunction,
AlterCollectionFunction, and DropCollectionFunction requests
Signed-off-by: junjie.jiang <junjie.jiang@zilliz.com>
issue: #44320
This change adds deduplication logic to handle duplicate primary keys
within a single upsert batch, keeping the last occurrence of each
primary key.
Key changes:
- Add DeduplicateFieldData function to remove duplicate PKs from field
data, supporting both Int64 and VarChar primary keys
- Refactor fillFieldPropertiesBySchema into two separate functions:
validateFieldDataColumns for validation and fillFieldPropertiesOnly for
property filling, improving code clarity and reusability
- Integrate deduplication logic in upsertTask.PreExecute to
automatically deduplicate data before processing
- Add comprehensive unit tests for deduplication with various PK types
(Int64, VarChar) and field types (scalar, vector)
- Add Python integration tests to verify end-to-end behavior
---------
Signed-off-by: Wei Liu <wei.liu@zilliz.com>
issue: #43897
- Part of collection/index related DDL is implemented by WAL-based DDL
framework now.
- Support following message type in wal, CreateCollection,
DropCollection, CreatePartition, DropPartition, CreateIndex, AlterIndex,
DropIndex.
- Part of collection/index related DDL can be synced by new CDC now.
- Refactor some UT for collection/index DDL.
- Add Tombstone scheduler to manage the tombstone GC for collection or
partition meta.
- Move the vchannel allocation into streaming pchannel manager.
---------
Signed-off-by: chyezh <chyezh@outlook.com>
