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: #44212
Implement search/query storage usage statistics in go side(result
reduce), only record storage usage in vector search C++ path. Need to be
implemented in query c++ path in next prs.
---------
Signed-off-by: chasingegg <chao.gao@zilliz.com>
Signed-off-by: marcelo.chen <marcelo.chen@zilliz.com>
Co-authored-by: marcelo.chen <marcelo.chen@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>
