SchemaTron (Incubating)
⚠️ This is an incubating project in draft status. APIs and functionality may change significantly between releases.
SchemaTron is a schema translation toolkit that converts between various schema formats and DataHub's native schema representation. It currently provides robust support for Apache Avro schema translation with a focus on complex schema structures including unions, arrays, maps, and nested records.
Modules
CLI Module
Command-line interface for converting schemas and emitting them to DataHub.
# Execute from this directory
../../../gradlew :metadata-integration:java:datahub-schematron:cli:run --args="-i cli/src/test/resources/FlatUser.avsc"
CLI Options
-i, --input: Input schema file or directory path-p, --platform: Data platform name (default: "avro")-s, --server: DataHub server URL (default: "http://localhost:8080")-t, --token: DataHub access token--sink: Output sink - "rest" or "file" (default: "rest")--output-file: Output file path when using file sink (default: "metadata.json")
Library Module
Core translation logic and models for schema conversion. Features include:
-
Support for complex Avro schema structures:
- Union types with multiple record options
- Nested records and arrays
- Optional fields with defaults
- Logical types (date, timestamp, etc.)
- Maps with various value types
- Enum types
- Custom metadata and documentation
-
Comprehensive path handling for schema fields
-
DataHub-compatible metadata generation
-
Schema fingerprinting and versioning
Example Schema Support
The library can handle sophisticated schema structures including:
- Customer profiles with multiple identification types (passport, driver's license, national ID)
- Contact information with primary and alternative contact methods
- Address validation with verification metadata
- Subscription history tracking
- Flexible preference and metadata storage
- Tagged customer attributes
Development
The project includes extensive test coverage through:
- Unit tests for field path handling
- Schema translation comparison tests
- Integration tests with Python reference implementation
Test resources include example schemas demonstrating various Avro schema features and edge cases.
Contributing
As this is an incubating project, we welcome contributions and feedback on:
- Additional schema format support
- Improved handling of complex schema patterns
- Enhanced metadata translation
- Documentation and examples
- Test coverage