issue: https://github.com/milvus-io/milvus/issues/27467
>My plan is as follows.
>- [x] M1 Create collection with timestamptz field
>- [x] M2 Insert timestamptz field data
>- [x] M3 Retrieve timestamptz field data
>- [x] M4 Implement handoff
>- [x] M5 Implement compare operator
>- [x] M6 Implement extract operator
>- [x] M8 Support database/collection level default timezone
>- [x] M7 Support STL-SORT index for datatype timestamptz
---
The third PR of issue: https://github.com/milvus-io/milvus/issues/27467,
which completes M5, M6, M7, M8 described above.
## M8 Default Timezone
We will be able to use alter_collection() and alter_database() in a
future Python SDK release to modify the default timezone at the
collection or database level.
For insert requests, the timezone will be resolved using the following
order of precedence: String Literal-> Collection Default -> Database
Default.
For retrieval requests, the timezone will be resolved in this order:
Query Parameters -> Collection Default -> Database Default.
In both cases, the final fallback timezone is UTC.
## M5: Comparison Operators
We can now use the following expression format to filter on the
timestamptz field:
- `timestamptz_field [+/- INTERVAL 'interval_string'] {comparison_op}
ISO 'iso_string' `
- The interval_string follows the ISO 8601 duration format, for example:
P1Y2M3DT1H2M3S.
- The iso_string follows the ISO 8601 timestamp format, for example:
2025-01-03T00:00:00+08:00.
- Example expressions: "tsz + INTERVAL 'P0D' != ISO
'2025-01-03T00:00:00+08:00'" or "tsz != ISO
'2025-01-03T00:00:00+08:00'".
## M6: Extract
We will be able to extract sepecific time filed by kwargs in a future
Python SDK release.
The key is `time_fields`, and value should be one or more of "year,
month, day, hour, minute, second, microsecond", seperated by comma or
space. Then the result of each record would be an array of int64.
## M7: Indexing Support
Expressions without interval arithmetic can be accelerated using an
STL-SORT index. However, expressions that include interval arithmetic
cannot be indexed. This is because the result of an interval calculation
depends on the specific timestamp value. For example, adding one month
to a date in February results in a different number of added days than
adding one month to a date in March.
---
After this PR, the input / output type of timestamptz would be iso
string. Timestampz would be stored as timestamptz data, which is int64_t
finally.
> for more information, see https://en.wikipedia.org/wiki/ISO_8601
---------
Signed-off-by: xtx <xtianx@smail.nju.edu.cn>
issue: #43980
This commit optimizes the partial update merge logic by standardizing
nullable field representation before merge operations to avoid corner
cases during the merge process.
Key changes:
- Unify nullable field data format to FULL FORMAT before merge execution
- Add extensive unit tests for bounds checking and edge cases
The optimization ensures:
- Consistent nullable field representation across SDK and internal
- Proper handling of null values during merge operations
- Prevention of index out-of-bounds errors in vector field updates
- Better error handling and validation for partial update scenarios
This resolves issues where different nullable field formats could cause
merge failures or data corruption during partial update operations.
Signed-off-by: Wei Liu <wei.liu@zilliz.com>
issue: #43980
Fix panic issue caused by incorrect nullable field merging logic when
upsert converts to insert operation on empty tables.
- Add AppendFieldDataWithNullData to handle nullable field merging
- Fix existing data merge with skipAppendNullData=false
- Fix insert data merge with skipAppendNullData=true
- Add unit tests for nullable field data appending scenarios
Signed-off-by: Wei Liu <wei.liu@zilliz.com>
issue: #43980
Fixes a panic that occurred when a partial update was converted to an
insert due to a non-existent primary key. The panic was caused by
missing nullable fields that were not provided in the original partial
update request.
The upsert pre-execution logic is refactored to handle this correctly:
- Explicitly splits upsert data into 'insert' and 'update' batches.
- Automatically generates data for missing nullable or default-value
fields during inserts, preventing the panic.
- Enhances `typeutil.UpdateFieldData` to support different source and
destination indexes for flexible data merging.
- Adds comprehensive unit tests for mixed upsert, pure insert, and pure
update scenarios.
---------
Signed-off-by: Wei Liu <wei.liu@zilliz.com>
Ref https://github.com/milvus-io/milvus/issues/42148
This PR supports create index for vector array (now, only for
`DataType.FLOAT_VECTOR`) and search on it.
The index type supported in this PR is `EMB_LIST_HNSW` and the metric
type is `MAX_SIM` only.
The way to use it:
```python
milvus_client = MilvusClient("xxx:19530")
schema = milvus_client.create_schema(enable_dynamic_field=True, auto_id=True)
...
struct_schema = milvus_client.create_struct_array_field_schema("struct_array_field")
...
struct_schema.add_field("struct_float_vec", DataType.ARRAY_OF_VECTOR, element_type=DataType.FLOAT_VECTOR, dim=128, max_capacity=1000)
...
schema.add_struct_array_field(struct_schema)
index_params = milvus_client.prepare_index_params()
index_params.add_index(field_name="struct_float_vec", index_type="EMB_LIST_HNSW", metric_type="MAX_SIM", index_params={"nlist": 128})
...
milvus_client.create_index(COLLECTION_NAME, schema=schema, index_params=index_params)
```
Note: This PR uses `Lims` to convey offsets of the vector array to
knowhere where vectors of multiple vector arrays are concatenated and we
need offsets to specify which vectors belong to which vector array.
---------
Signed-off-by: SpadeA <tangchenjie1210@gmail.com>
Signed-off-by: SpadeA-Tang <tangchenjie1210@gmail.com>
issue: #29735
Implement partial field update functionality for upsert operations,
supporting scalar, vector, and dynamic JSON fields without requiring all
collection fields.
Changes:
- Add queryPreExecute to retrieve existing records before upsert
- Implement UpdateFieldData function for merging data
- Add IDsChecker utility for efficient primary key lookups
- Fix JSON data creation in tests using proper map marshaling
- Add test cases for partial updates of different field types
Signed-off-by: Wei Liu <wei.liu@zilliz.com>
Ref https://github.com/milvus-io/milvus/issues/42148https://github.com/milvus-io/milvus/pull/42406 impls the segcore part of
storage for handling with VectorArray.
This PR:
1. impls the go part of storage for VectorArray
2. impls the collection creation with StructArrayField and VectorArray
3. insert and retrieve data from the collection.
---------
Signed-off-by: SpadeA <tangchenjie1210@gmail.com>
Signed-off-by: SpadeA-Tang <tangchenjie1210@gmail.com>
Signed-off-by: SpadeA-Tang <u6748471@anu.edu.au>
Previous code uses diskSegmentMaxSize if and only if all of the
collection's vector fields are indexed with DiskANN index.
When introducing sparse vectors, since sparse vector cannot be indexed
with DiskANN index, collections with both dense and sparse vectors will
use maxSize instead.
This PR changes the requirments of using diskSegmentMaxSize to all dense
vectors are indexed with DiskANN indexs, ignoring sparse vector fields.
See also: #43193
Signed-off-by: yangxuan <xuan.yang@zilliz.com>
Related to #42489
Since load list works as hint after cachelayer implemented, the related
check logic could be removed to keep code logic clean.
---------
Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
See #36264
In this PR:
- Enhanced error handling in parse of grouping field.
- Fixed null handling in reduce tasks in proxy nodes.
- Updated tests to reflect changes in error handling and data processing
logic.
---------
Signed-off-by: Ted Xu <ted.xu@zilliz.com>
Merge RootCoord, DataCoord And QueryCoord into MixCoord
Make Session into one
issue : https://github.com/milvus-io/milvus/issues/37764
---------
Signed-off-by: Xianhui.Lin <xianhui.lin@zilliz.com>
issue: https://github.com/milvus-io/milvus/issues/39818
This PR mimics Varchar data type, allows insert, search, query, delete,
full-text search and others.
Functionalities related to filter expressions are disabled temporarily.
Storage changes for Text data type will be in the following PRs.
Signed-off-by: Patrick Weizhi Xu <weizhi.xu@zilliz.com>
issue: #38399
- Add new rpc for transfer broadcast to streaming coord
- Add broadcast service at streaming coord to make broadcast message
sent automicly
Signed-off-by: chyezh <chyezh@outlook.com>
issue: #38399
- move the lifetime implementation of common code out of the server
level lifetime implementation
Signed-off-by: chyezh <chyezh@outlook.com>
sparse vectors may have arbitrary number of non zeros and it is hard to
optimize without knowing the actual distribution of nnz. this PR adds a
metric for analyzing that.
issue: https://github.com/milvus-io/milvus/issues/35853
comparing with https://github.com/milvus-io/milvus/pull/38328, this
includes also metric for FTS in query node delegator
also fixed a bug of sparse when searching by pk
Signed-off-by: Buqian Zheng <zhengbuqian@gmail.com>
enhance :
1. alterindex delete properties
We have introduced a new parameter deleteKeys to the alterindex
functionality, which allows for the deletion of properties within an
index. This enhancement provides users with the flexibility to manage
index properties more effectively by removing specific keys as needed.
2. altercollection delete properties
We have introduced a new parameter deleteKeys to the altercollection
functionality, which allows for the deletion of properties within an
collection. This enhancement provides users with the flexibility to
manage collection properties more effectively by removing specific keys
as needed.
3.support altercollectionfield
We currently support modifying the fieldparams of a field in a
collection using altercollectionfield, which only allows changes to the
max-length attribute.
Key Points:
- New Parameter - deleteKeys: This new parameter enables the deletion of
specified properties from an index. By passing a list of keys to
deleteKeys, users can remove the corresponding properties from the
index.
- Mutual Exclusivity: The deleteKeys parameter cannot be used in
conjunction with the extraParams parameter. Users must choose one
parameter to pass based on their requirement. If deleteKeys is provided,
it indicates an intent to delete properties; if extraParams is provided,
it signifies the addition or update of properties.
issue: https://github.com/milvus-io/milvus/issues/37436
---------
Signed-off-by: Xianhui.Lin <xianhui.lin@zilliz.com>
RESTful API. The influenced API are as follows:
- Handler. insert
- HandlerV1. insert/upsert
- HandlerV2. insert/upsert/search
We do not modify search API in Handler/HandlerV1 because they do not
support fp16/bf16 vectors.
module github.com/milvus-io/milvus/pkg:
Add `Float32ArrayToBFloat16Bytes()`, `Float32ArrayToFloat16Bytes()` and
`Float32ArrayToBytes()`. These method will be used in GoSDK in the
future.
issue: #37448
Signed-off-by: Yinzuo Jiang <yinzuo.jiang@zilliz.com>
Signed-off-by: Yinzuo Jiang <jiangyinzuo@foxmail.com>
issue: ##36621
- For simple types in a struct, add "string" to the JSON tag for
automatic string conversion during JSON encoding.
- For complex types in a struct, replace "int64" with "string."
Signed-off-by: jaime <yun.zhang@zilliz.com>
issue: #34298
because all vector index config checker has been moved into
vector_index_checker, then the useless checkers can be removed.
Signed-off-by: xianliang.li <xianliang.li@zilliz.com>
issue:https://github.com/milvus-io/milvus/issues/27576
# Main Goals
1. Create and describe collections with geospatial fields, enabling both
client and server to recognize and process geo fields.
2. Insert geospatial data as payload values in the insert binlog, and
print the values for verification.
3. Load segments containing geospatial data into memory.
4. Ensure query outputs can display geospatial data.
5. Support filtering on GIS functions for geospatial columns.
# Solution
1. **Add Type**: Modify the Milvus core by adding a Geospatial type in
both the C++ and Go code layers, defining the Geospatial data structure
and the corresponding interfaces.
2. **Dependency Libraries**: Introduce necessary geospatial data
processing libraries. In the C++ source code, use Conan package
management to include the GDAL library. In the Go source code, add the
go-geom library to the go.mod file.
3. **Protocol Interface**: Revise the Milvus protocol to provide
mechanisms for Geospatial message serialization and deserialization.
4. **Data Pipeline**: Facilitate interaction between the client and
proxy using the WKT format for geospatial data. The proxy will convert
all data into WKB format for downstream processing, providing column
data interfaces, segment encapsulation, segment loading, payload
writing, and cache block management.
5. **Query Operators**: Implement simple display and support for filter
queries. Initially, focus on filtering based on spatial relationships
for a single column of geospatial literal values, providing parsing and
execution for query expressions.
6. **Client Modification**: Enable the client to handle user input for
geospatial data and facilitate end-to-end testing.Check the modification
in pymilvus.
---------
Signed-off-by: tasty-gumi <1021989072@qq.com>
issue: #35922
add an enable_tokenizer param to varchar field: must be set to true so
that a varchar field can enable_match or used as input of BM25 function
---------
Signed-off-by: Buqian Zheng <zhengbuqian@gmail.com>
