related: #45993
This commit extends nullable vector support to the proxy layer,
querynode,
and adds comprehensive validation, search reduce, and field data
handling
for nullable vectors with sparse storage.
Proxy layer changes:
- Update validate_util.go checkAligned() with getExpectedVectorRows()
helper
to validate nullable vector field alignment using valid data count
- Update checkFloatVectorFieldData/checkSparseFloatVectorFieldData for
nullable vector validation with proper row count expectations
- Add FieldDataIdxComputer in typeutil/schema.go for logical-to-physical
index translation during search reduce operations
- Update search_reduce_util.go reduceSearchResultData to use
idxComputers
for correct field data indexing with nullable vectors
- Update task.go, task_query.go, task_upsert.go for nullable vector
handling
- Update msg_pack.go with nullable vector field data processing
QueryNode layer changes:
- Update segments/result.go for nullable vector result handling
- Update segments/search_reduce.go with nullable vector offset
translation
Storage and index changes:
- Update data_codec.go and utils.go for nullable vector serialization
- Update indexcgowrapper/dataset.go and index.go for nullable vector
indexing
Utility changes:
- Add FieldDataIdxComputer struct with Compute() method for efficient
logical-to-physical index mapping across multiple field data
- Update EstimateEntitySize() and AppendFieldData() with fieldIdxs
parameter
- Update funcutil.go with nullable vector support functions
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
* **New Features**
* Full support for nullable vector fields (float, binary, float16,
bfloat16, int8, sparse) across ingest, storage, indexing, search and
retrieval; logical↔physical offset mapping preserves row semantics.
* Client: compaction control and compaction-state APIs.
* **Bug Fixes**
* Improved validation for adding vector fields (nullable + dimension
checks) and corrected search/query behavior for nullable vectors.
* **Chores**
* Persisted validity maps with indexes and on-disk formats.
* **Tests**
* Extensive new and updated end-to-end nullable-vector tests.
<sub>✏️ Tip: You can customize this high-level summary in your review
settings.</sub>
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: marcelo-cjl <marcelo.chen@zilliz.com>
1. Array.h: Add output_data(ScalarFieldProto&) overload for both Array
and ArrayView classes
2. Use std::string_view instead of std::string for VARCHAR and GEOMETRY
types to avoid extra string copies
3. Call Reserve(length_) before writing to proto objects to reduce
memory reallocations
a simple test shows those optimizations improve the Array of Varchar
bulk_subscript performance by 20%
issue: https://github.com/milvus-io/milvus/issues/45679
Signed-off-by: Buqian Zheng <zhengbuqian@gmail.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>
Related to #43592
When delete records are large, search pk one by one will result into
many `Pincells` call which creates lots of futures.
This patch make search pk execute in batch to reduce this cost.
Also add `GetAllChunks` API to utilize `PinAllCells` to reduce pins.
Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
issue: #41435
this is to prevent AI from thinking of our exception throwing as a
dangerous PANIC operation that terminates the program.
Signed-off-by: Buqian Zheng <zhengbuqian@gmail.com>
use meta to get chunked column memory size to avoid getting cells
actually from storage.
related: #39173
---------
Signed-off-by: shaoting-huang <shaoting.huang@zilliz.com>
Ref https://github.com/milvus-io/milvus/issues/42148
This PR mainly enables segcore to support array of vector (read and
write, but not indexing). Now only float vector as the element type is
supported.
---------
Signed-off-by: SpadeA <tangchenjie1210@gmail.com>
Signed-off-by: SpadeA-Tang <tangchenjie1210@gmail.com>
issue: https://github.com/milvus-io/milvus/issues/41435
this PR also makes HasRawData of ChunkedSegmentSealedImpl to return
based on metadata, without needing to load the cache just to answer this
simple question.
---------
Signed-off-by: Buqian Zheng <zhengbuqian@gmail.com>
Related to #39173
This PR:
- Upgrade milvus-storage commit to fix filesystem finalized issue
- Add bucket-name as prefix for all fs style access io
- Initial arrow fs on querynodes startup
- Fix timestamp access when loading sealed segment
---------
Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
issue: https://github.com/milvus-io/milvus/issues/41435
this PR is based on https://github.com/milvus-io/milvus/pull/41436.
Improvements include:
- Lazy Load support for Storage v1
- Use Low/High watermark to control eviction
- Caching Layer related config changes
- Removed ChunkCache related configs and code in golang
- Add `PinAllCells` helper method to CacheSlot class
- Modified ValueAt, RawAt, PrimitiveRawAt to Bulk version, to reduce
caching layer overhead
- Removed some unclear templated bulk_subscript methods
- CachedSearchIterator to store PinWrapper when searching on
ChunkedColumn, and removed unused contrustor.
---------
Signed-off-by: Buqian Zheng <zhengbuqian@gmail.com>
storage v2 chunked seal segment loading is based on caching layer. A
cell unit in storage v2 is a parquet row group in remote object storage,
containing all fields. Therefore, each field needs a proxy to do related
one field operations.
<img width="965" alt="Screenshot 2025-04-28 at 10 59 30"
src="https://github.com/user-attachments/assets/83e93a10-3b1d-4066-ac17-b996d5650416"
/>
related: #39173
---------
Signed-off-by: shaoting-huang <shaoting.huang@zilliz.com>
