Related to #39173#41534
This pr fixes an issue that building mem index may report datatype not
match error when collection split fields into multiple groups
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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.
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Signed-off-by: Buqian Zheng <zhengbuqian@gmail.com>
support parallel loading sealed and growing segments with storage v2
format by async reading row groups.
related: #39173
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Signed-off-by: shaoting-huang <shaoting.huang@zilliz.com>
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>
Previously the grep with regex does not work and failed to match lots of
.cpp files
This PR:
- use "-E" flag to use regex match
- commit the fixed result of current cpp code
Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
issue: #38715
- Current milvus use a serialized index size(compressed) for estimate
resource for loading.
- Add a new field `MemSize` (before compressing) for index to estimate
resource.
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Signed-off-by: chyezh <chyezh@outlook.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.
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Signed-off-by: tasty-gumi <1021989072@qq.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>
Native support for Google cloud storage using the Google Cloud Storage
libraries. Authentication is performed using GCS service account
credentials JSON.
Currently, Milvus supports Google Cloud Storage using S3-compatible APIs
via the AWS SDK. This approach has the following limitations:
1. Overhead: Translating requests between S3-compatible APIs and GCS can
introduce additional overhead.
2. Compatibility Limitations: Some features of the original S3 API may
not fully translate or work as expected with GCS.
To address these limitations, This enhancement is needed.
Related Issue: #36212
issue: https://github.com/milvus-io/milvus/issues/36182
* improved `Column.h` to make the code much more readable and
maintainable, and added detailed comments.
* fixed an issue where `ArrayColumn::NumRows()` always returns 0 when
the mmap backing storage is a file.
* removed unused `ColumnBase` constructors and unnecessary members so we
don't get confused.
* Updated `test_chunk_cache.cpp` to make the tests parameterized: to
test both mmap enabled and disabled. Added sparse field in the test to
add coverage.
* re-enabled test `Sealed::GetSparseVectorFromChunkCache`.
* But 2 other disabled tests `Sealed::WarmupChunkCache` and
`Sealed::GetVectorFromChunkCache` remain disabled, there seems to be
errors. @bigsheeper PTAL.
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Signed-off-by: Buqian Zheng <zhengbuqian@gmail.com>
