relate: https://github.com/milvus-io/milvus/issues/43687
We used to run the temporary analyzer and validate analyzer on the
proxy, but the proxy should not be a computation-heavy node. This PR
move all analyzer calculations to the streaming node.
---------
Signed-off-by: aoiasd <zhicheng.yue@zilliz.com>
issue: #44648
If the value is `null` during insertion, it will be omitted instead of
being filled with nil. Therefore, when performing checks, there’s no
need to retrieve data based on the valid offset.
Signed-off-by: Cai Zhang <cai.zhang@zilliz.com>
issue: #44800
This commit enhances the upsert and validation logic to properly handle
nullable Geometry (WKT/WKB) and Timestamptz data types:
- Add ToCompressedFormatNullable support for TimestamptzData,
GeometryWktData, and GeometryData to filter out null values during data
compression
- Implement GenNullableFieldData for Timestamptz and Geometry types to
generate nullable field data structures
- Update FillWithNullValue to handle both GeometryData and
GeometryWktData with null value filling logic
- Add UpdateFieldData support for Timestamptz, GeometryData, and
GeometryWktData field updates
- Comprehensive unit tests covering all new data type handling scenarios
Signed-off-by: Wei Liu <wei.liu@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: #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>
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>
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: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>
This PR make varchar & string array field max length exceeded error
message clearer. Also fixed a minor issue that error string format and
argument number not match.
Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
1. add nullable in model.Field
help to read nullable accurately.
2. check valid_data
a. if user pass default_value or the field is nullable, the length of
valid_data must be num_rows.
b. if passed valid_data, the length of passed field data must equal to
the number of 'true' in valid_data.
c. after fill default_value, only nullable field will still has
valid_data.
3. fill data in two situation
a. has no default_value, if nullable,
will fill nullValue when passed num_rows not equal to expected num_rows.
b. has default_value,
will fill default_value when passed num_rows not equal to expected
num_rows.
c. after fill data, the length of all field will equal to passed
num_rows.
#31728
---------
Signed-off-by: lixinguo <xinguo.li@zilliz.com>
Co-authored-by: lixinguo <xinguo.li@zilliz.com>
add sparse float vector support to different milvus components,
including proxy, data node to receive and write sparse float vectors to
binlog, query node to handle search requests, index node to build index
for sparse float column, etc.
https://github.com/milvus-io/milvus/issues/29419
---------
Signed-off-by: Buqian Zheng <zhengbuqian@gmail.com>
