Cherry-pick from master
pr: #45018#45030
Related to #44761
Refactor proxy shard client management by creating a new
internal/proxy/shardclient package. This improves code organization and
modularity by:
- Moving load balancing logic (LookAsideBalancer, RoundRobinBalancer) to
shardclient package
- Extracting shard client manager and related interfaces into separate
package
- Relocating shard leader management and client lifecycle code
- Adding package documentation (README.md, OWNERS)
- Updating proxy code to use the new shardclient package interfaces
This change makes the shard client functionality more maintainable and
better encapsulated, reducing coupling in the proxy layer.
Also consolidates the proxy package's mockery generation to use a
centralized `.mockery.yaml` configuration file, aligning with the
pattern used by other packages like querycoordv2.
Changes
- **Makefile**: Replace multiple individual mockery commands with a
single config-based invocation for `generate-mockery-proxy` target
- **internal/proxy/.mockery.yaml**: Add mockery configuration defining
all mock interfaces for proxy and proxy/shardclient packages
- **Mock files**: Regenerate mocks using the new configuration:
- `mock_cache.go`: Clean up by removing unused interface methods
(credential, shard cache, policy methods)
- `shardclient/mock_lb_balancer.go`: Update type comments
(nodeInfo → NodeInfo)
- `shardclient/mock_lb_policy.go`: Update formatting
- `shardclient/mock_shardclient_manager.go`: Fix parameter naming
consistency (nodeInfo1 → nodeInfo)
- **task_search_test.go**: Remove obsolete mock expectations for
deprecated cache methods
Benefits
- Centralized mockery configuration for easier maintenance
- Consistent with other packages (querycoordv2, etc.)
- Cleaner mock interfaces by removing unused methods
- Better type consistency in generated mocks
---------
Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
issue: #43427
This pr's main goal is merge #37417 to milvus 2.5 without conflicts.
# Main Goals
1. Create and describe collections with geospatial type
2. Insert geospatial data into the insert binlog
3. Load segments containing geospatial data into memory
4. Enable query and search can display geospatial data
5. Support using GIS funtions like ST_EQUALS in query
6. Support R-Tree index for geometry type
# 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.Now only support brutal search
7. **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: Yinwei Li <yinwei.li@zilliz.com>
Signed-off-by: Cai Zhang <cai.zhang@zilliz.com>
Co-authored-by: ZhuXi <150327960+Yinwei-Yu@users.noreply.github.com>
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>
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>
Related to #39718
After support add field with dynamic fields enabled, the masked dynamic
field shall be able to return with `$meta["name"]`
---------
Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
feat: Add support for modifying max capacity of array fields
This commit adds support for modifying the max capacity of array fields
in the `alterCollectionFieldTask` function. It checks if the field is an
array type and then validates and updates the max capacity value. This
change improves the flexibility of array fields in the collection.
Issue: https://github.com/milvus-io/milvus/issues/41363
---------
Signed-off-by: Xianhui.Lin <xianhui.lin@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>
The fields and partitions information are stored and fetched with
different prefixes in the metadata. In the CreateCollectionTask, the
RootCoord checks the existing collection information against the
metadata. This check fails if the order of the fields or partitions info
differs, leading to an error after restarting Milvus. To resolve this,
we should use a map in the check logic to ensure consistency.
related: https://github.com/milvus-io/milvus/issues/40955
---------
Signed-off-by: shaoting-huang <shaoting.huang@zilliz.com>
after the pr merged, we can support to insert, upsert, build index,
query, search in the added field.
can only do the above operates in added field after add field request
complete, which is a sync operate.
compact will be supported in the next pr.
#39718
---------
Signed-off-by: lixinguo <xinguo.li@zilliz.com>
Co-authored-by: lixinguo <xinguo.li@zilliz.com>
proxy to always remove pk field from output field when forwarding
request to QN, and if user requested pk, fill it from IDs.
issue: https://github.com/milvus-io/milvus/issues/40833
---------
Signed-off-by: Buqian Zheng <zhengbuqian@gmail.com>
Related to #38275
This PR move sync created partition step to proxy to avoid potential
logic deadlock when create partition happens with target segment change.
Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
issue: #37665#37631#37620#37587#36906
knowhere has add default nlist value, so some invalid param test ut with
no nlist param will be valid.
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>
Related to #37183
Utilize proxy metacache for `HasCollection` request, if collection
exists in metacache, it could be deducted that collection must exist in
system.
Signed-off-by: Congqi Xia <congqi.xia@zilliz.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>
