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>
See also #34746
This PR add segment level field in response of
`GetPersistentSegmentInfo` and `GetQuerySegmentInfo`
---------
Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
issue: #34357
Go Parquet uses dictionary encoding by default, and it will fall back to
plain encoding if the dictionary size exceeds the dictionary size page
limit. Users can specify custom fallback encoding by using
`parquet.WithEncoding(ENCODING_METHOD)` in writer properties. However,
Go Parquet [fallbacks to plain
encoding](e65c1e295d/go/parquet/file/column_writer_types.gen.go.tmpl (L238))
rather than custom encoding method users provide. Therefore, this patch
only turns off dictionary encoding for the primary key.
With a 5 million auto ID primary key benchmark, the parquet file size
improves from 13.93 MB to 8.36 MB when dictionary encoding is turned
off, reducing primary key storage space by 40%.
Signed-off-by: shaoting-huang <shaoting.huang@zilliz.com>
issue: #34123
Benchmark case: The benchmark run the go benchmark function
`BenchmarkDeltalogFormat` which is put in the Files changed. It tests
the performance of serializing and deserializing from two different data
formats under a 10 million delete log dataset.
Metrics: The benchmarks measure the average time taken per operation
(ns/op), memory allocated per operation (MB/op), and the number of
memory allocations per operation (allocs/op).
| Test Name | Avg Time (ns/op) | Time Comparison | Memory Allocation
(MB/op) | Memory Comparison | Allocation Count (allocs/op) | Allocation
Comparison |
|---------------------------------|------------------|-----------------|---------------------------|-------------------|------------------------------|------------------------|
| one_string_format_reader | 2,781,990,000 | Baseline | 2,422 | Baseline
| 20,336,539 | Baseline |
| pk_ts_separate_format_reader | 480,682,639 | -82.72% | 1,765 | -27.14%
| 20,396,958 | +0.30% |
| one_string_format_writer | 5,483,436,041 | Baseline | 13,900 |
Baseline | 70,057,473 | Baseline |
| pk_and_ts_separate_format_writer| 798,591,584 | -85.43% | 2,178 |
-84.34% | 30,270,488 | -56.78% |
Both read and write operations show significant improvements in both
speed and memory allocation.
Signed-off-by: shaoting-huang <shaoting.huang@zilliz.com>
XuanYang-cn
Ted Xu
zhenshan.cao
Hao Tan
cai.zhang
wei liu
congqixia
shaoting-huang
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Buqian Zheng