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>
fix: #29757
In previous code, `ColumnBasedInsertMsgToInsertData` adds empty field if
the insertMsg parameter does not have the column schema defined. This
may lead to unexpected behavior of caller functions.
This PR:
- Add column missing check
- Add column length check
- Generate BlobInfo for ColumnBasedInsertMsgToInsertData result
---------
Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
Benchmark Milvus with https://github.com/qdrant/vector-db-benchmark and
specify the datasets as 'deep-image-96-angular'. Meanwhile, do perf
profiling during 'upload + index' stage of vector-db-benchmark and see
the following hot spots.
39.59%--github.com/milvus-io/milvus/internal/storage.MergeInsertData
|
|--21.43%--github.com/milvus-io/milvus/internal/storage.MergeFieldData
| |
| |--17.22%--runtime.memmove
| |
| |--1.53%--asm_exc_page_fault
| ......
|
|--18.16%--runtime.memmove
|
|--1.66%--asm_exc_page_fault
......
The hot code path is in storage.MergeInsertData() which updates
buffer.buffer by creating a new 'InsertData' instance and merging both
the old buffer.buffer and addedBuffer into it. When it calls golang
runtime.memmove to move buffer.buffer which is with big size (>1M), the
hot spots appear.
To avoid the above overhead, update storage.MergeInsertData() by
appending addedBuffer to buffer.buffer, instead of moving buffer.buffer
and addedBuffer to a new 'InsertData'. This change removes the hot spots
'runtime.memmove' from perf profiling output. Additionally, the 'upload
+ index' time, which is one performance metric of vector-db-benchmark,
is reduced around 60% with this change.
Signed-off-by: Cathy Zhang <cathy.zhang@intel.com>
