cai.zhang 19346fa389
feat: Geospatial Data Type and GIS Function support for milvus (#44547)
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>
2025-09-28 19:43:05 +08:00
..

Milvus Go Client Test Framework

Overview

This is a comprehensive test framework for the Milvus Go Client, designed to validate various functionalities of the Milvus vector database client. The framework provides a structured approach to writing tests with reusable components and helper functions.

Framework Architecture

Directory Structure

/go_client/
├── testcases/           # Main test cases
│   ├── helper/          # Helper functions and utilities
│   │   ├── helper.go
│   │   ├── data_helper.go
│   │   └── collection_helper.go
│   ├── search_test.go   # Search functionality tests
│   ├── index_test.go    # Index management tests
│   └── ...
├── common/             # Common utilities and constants
└── base/               # Base infrastructure code

Key Components

  • Collection Preparation: Utilities for creating and managing collections
  • Data Generation: Tools for generating test data
  • Helper Functions: Common operations and validations
  • Test Cases: Organized by functionality

Writing Test Cases

Basic Test Structure

func TestYourFeature(t *testing.T) {
    // 1. Setup context and client
    ctx := hp.CreateContext(t, time.Second*common.DefaultTimeout)
    mc := createDefaultMilvusClient(ctx, t)

    // 2. Prepare collection
    prepare, schema := hp.CollPrepare.CreateCollection(
        ctx, t, mc,
        hp.NewCreateCollectionParams(hp.Int64Vec),
        hp.TNewFieldsOption(),
        hp.TNewSchemaOption(),
    )

    // 3. Insert test data
    prepare.InsertData(ctx, t, mc,
        hp.NewInsertParams(schema),
        hp.TNewDataOption(),
    )

    // 4. Execute test operations
    // ... your test logic here ...

    // 5. Validate results
    require.NoError(t, err)
    require.Equal(t, expected, actual)
}

Using Custom Parameters

  1. Collection Creation Parameters
fieldsOption := hp.TNewFieldsOption().
    TWithEnableAnalyzer(true).
    TWithAnalyzerParams(map[string]any{
        "tokenizer": "standard",
    })

schemaOption := hp.TNewSchemaOption().
    TWithEnableDynamicField(true).
    TWithDescription("Custom schema").
    TWithAutoID(false)
  1. Data Insertion Options
insertOption := hp.TNewDataOption().
    TWithNb(1000).           // Number of records
    TWithDim(128).           // Vector dimension
    TWithStart(100).         // Starting ID
    TWithMaxLen(256).        // Maximum length
    TWithTextLang("en")      // Text language
  1. Index Parameters
indexParams := hp.TNewIndexParams(schema).
    TWithFieldIndex(map[string]index.Index{
        common.DefaultVectorFieldName: index.NewIVFSQIndex(
            &index.IVFSQConfig{
                MetricType: entity.L2,
                NList:     128,
            },
        ),
    })
  1. Search Parameters
searchOpt := client.NewSearchOption(schema.CollectionName, 100, vectors).
    WithOffset(0).
    WithLimit(100).
    WithConsistencyLevel(entity.ClStrong).
    WithFilter("int64 >= 100").
    WithOutputFields([]string{"*"}).
    WithSearchParams(map[string]any{
        "nprobe": 16,
        "ef":     64,
    })

Adding New Parameters

  1. Define New Option Type
// In helper/data_helper.go
type YourNewOption struct {
    newParam1 string
    newParam2 int
}
  1. Add Constructor
func TNewYourOption() *YourNewOption {
    return &YourNewOption{
        newParam1: "default",
        newParam2: 0,
    }
}
  1. Add Parameter Methods
func (opt *YourNewOption) TWithNewParam1(value string) *YourNewOption {
    opt.newParam1 = value
    return opt
}

func (opt *YourNewOption) TWithNewParam2(value int) *YourNewOption {
    opt.newParam2 = value
    return opt
}

Best Practices

  1. Test Organization

    • Group related tests in the same file
    • Use clear and descriptive test names
    • Add comments explaining test purpose
  2. Data Generation

    • Use helper functions for generating test data
    • Ensure data is appropriate for the test case
    • Clean up test data after use
  3. Error Handling

    • Use common.CheckErr for consistent error checking
    • Test both success and failure scenarios
    • Validate error messages when appropriate
  4. Performance Considerations

    • Use appropriate timeouts
    • Clean up resources after tests
    • Consider test execution time

Running Tests

# Run all tests
go test ./testcases/...

# Run specific test
go test -run TestYourFeature ./testcases/

# Run with verbose output
go test -v ./testcases/...

# gotestsum
Recommend you to use gotestsum https://github.com/gotestyourself/gotestsum

# Run all default cases
gotestsum --format testname --hide-summary=output -v ./testcases/... --addr=127.0.0.1:19530 -timeout=30m

# Run a specified file
gotestsum --format testname --hide-summary=output ./testcases/collection_test.go ./testcases/main_test.go --addr=127.0.0.1:19530

# Run L3 rg cases
gotestsum --format testname --hide-summary=output -v ./testcases/advcases/... --addr=127.0.0.1:19530 -timeout=30m -tags=rg

# Run advanced rg cases and default cases
# rg cases conflicts with default cases, so -p=1 is required
gotestsum --format testname --hide-summary=output -v ./testcases/... --addr=127.0.0.1:19530 -timeout=30m -tags=rg -p 1

Contributing

  1. Follow the existing code structure
  2. Add comprehensive test cases
  3. Document new parameters and options
  4. Update this README for significant changes
  5. Ensure code quality standards:
    • Run golangci-lint run to check for style mistakes
    • Use gofmt -w your/code/path to format your code before submitting
    • CI will verify both golint and go format compliance