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: #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>
issue: #42942
This pr includes the following changes:
1. Added checks for index checker in querycoord to generate drop index
tasks
2. Added drop index interface to querynode
3. To avoid search failure after dropping the index, the querynode
allows the use of lazy mode (warmup=disable) to load raw data even when
indexes contain raw data.
4. In segcore, loading the index no longer deletes raw data; instead, it
evicts it.
5. In expr, the index is pinned to prevent concurrent errors.
---------
Signed-off-by: sunby <sunbingyi1992@gmail.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 #43660
This patch reduces the unwanted offset&ts entries having same timestamp
of delete record. Under large amount of upsert, this false hit could
increase large amount of memory usage while applying delete.
The next step could be passing a callback to `search_pk_func_` to handle
hit entry streamingly.
Signed-off-by: Congqi Xia <congqi.xia@zilliz.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>
Related to #42640
The search/query plan holded a reference to schema, which could be
destructed after schema change. This PR make plan hold a shared ptr to
it fixing dangling reference problem under concurrent read & schema
change.
This PR also remove field binlog check for loading index for old segment
with old schema may have binlog lack.
Signed-off-by: Congqi Xia <congqi.xia@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 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>
Related to #39718Fixesmilvus-io/pymilvus#2771
This PR:
- Make AsyncRetrieve task triggers "schema check" logic as well
- Rename `AddField` related methods to align with code standard
Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
Related to #39718
This PR:
- Add reopen logic for growing & sealed segments
- Lazy reopen when schema version increases
- Add FinishLoad api for loading progress
---------
Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
support parallel loading sealed and growing segments with storage v2
format by async reading row groups.
related: #39173
---------
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>
issue: https://github.com/milvus-io/milvus/issues/35528
If the query data type does not match the index type, fall back to a
brute-force search
---------
Signed-off-by: sunby <sunbingyi1992@gmail.com>
https://github.com/milvus-io/milvus/issues/35528
This PR adds json index support for json and dynamic fields. Now you can
only do unary query like 'a["b"] > 1' using this index. We will support
more filter type later.
basic usage:
```
collection.create_index("json_field", {"index_type": "INVERTED",
"params": {"json_cast_type": DataType.STRING, "json_path":
'json_field["a"]["b"]'}})
```
There are some limits to use this index:
1. If a record does not have the json path you specify, it will be
ignored and there will not be an error.
2. If a value of the json path fails to be cast to the type you specify,
it will be ignored and there will not be an error.
3. A specific json path can have only one json index.
4. If you try to create more than one json indexes for one json field,
sdk(pymilvus<=2.4.7) may return immediately because of internal
implementation. This will be fixed in a later version.
---------
Signed-off-by: sunby <sunbingyi1992@gmail.com>
This PR splits sealed segment to chunked data to avoid unnecessary
memory copy and save memory usage when loading segments so that loading
can be accelerated.
To support rollback to previous version, we add an option
`multipleChunkedEnable` which is false by default.
Signed-off-by: sunby <sunbingyi1992@gmail.com>
