Feat: unity catalog/delta lake integration#145
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beinan merged 7 commits intolance-format:mainfrom Mar 3, 2026
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Add SqlQuery and SqlEngine that let users run standard SQL directly against their datasets without requiring a GraphConfig. This is useful for data analytics workflows where users want explicit JOINs and aggregations against node/relationship tables. DataFusion handles SQL parsing and execution.
…r architecture
Add support for browsing and querying tables from Unity Catalog (OSS).
Inspired by Presto's connector SPI, the design cleanly separates:
- CatalogProvider trait: catalog metadata browsing (UC first, extensible
to Hive Metastore, AWS Glue, Iceberg REST Catalog)
- TableReader trait: format-specific data reading (Parquet + Delta Lake,
extensible to CSV, Iceberg, ORC)
- Connector struct: facade bundling catalog + readers
Key features:
- Full UC REST API client (list/get catalogs, schemas, tables, columns)
- UC type → Arrow type mapping (20 type mappings)
- ParquetTableReader via DataFusion register_parquet()
- DeltaTableReader via deltalake 0.29 (behind "delta" feature flag)
- Auto-register UC tables into SqlEngine via create_sql_engine()
- Python bindings: UnityCatalog, CatalogInfo, SchemaInfo, TableInfo
- 15 wiremock integration tests for UC REST client
- 12 type mapping unit tests
- 9 Python unit tests
Python API:
uc = UnityCatalog("http://localhost:8080/api/2.1/unity-catalog")
engine = uc.create_sql_engine("unity", "default")
result = engine.execute("SELECT * FROM my_table")
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Codecov Report❌ Patch coverage is 📢 Thoughts on this report? Let us know! |
- cargo fmt fixes across all new files - Replace EnumName::Variant with Self::Variant (clippy::unnecessary_structure_name_repetition) - Fix Python import sorting and line length (ruff)
…re, GCS)
- Add `storage_options` parameter to `TableReader::register_table()` trait
- `Connector::with_storage_options()` stores credentials and passes them
to table readers during registration
- `DeltaTableReader` uses `open_table_with_storage_options()` when
storage options are provided
- Enable deltalake cloud features: s3, azure, gcs
- Python: `UnityCatalog(url, storage_options={...})` accepts cloud creds
Usage:
uc = UnityCatalog(
"http://localhost:8080/api/2.1/unity-catalog",
storage_options={
"azure_storage_account_name": "myaccount",
"azure_storage_account_key": "...",
}
)
engine = uc.create_sql_engine("unity", "default")
Add examples for UnityCatalog browsing, create_sql_engine, and cloud storage options (S3, Azure, GCS) to both project and Python READMEs.
beinan
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Mar 3, 2026
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let's merge this pr first due to the urgent use cases
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Summary
SqlEngineCatalogProvider) and data format reading (TableReader)storage_optionsArchitecture
Inspired by Presto's connector SPI:
CatalogProvidertraitConnectorMetadata)TableReadertraitConnectorPageSourceProvider)ConnectorstructConnector)Extensibility:
CatalogProvider, reuses existing Delta/Parquet readersTableReader, works with any catalogPython API
```python
from lance_graph import UnityCatalog
Connect to Unity Catalog
uc = UnityCatalog("http://localhost:8080/api/2.1/unity-catalog")
Browse
catalogs = uc.list_catalogs()
tables = uc.list_tables("unity", "default")
table = uc.get_table("unity", "default", "marksheet")
print(table.columns())
Auto-register Delta + Parquet tables and query via SQL
engine = uc.create_sql_engine("unity", "default")
result = engine.execute("SELECT * FROM marksheet WHERE mark > 80")
Cloud storage support (S3, Azure, GCS)
uc = UnityCatalog(
"http://localhost:8080/api/2.1/unity-catalog",
storage_options={
"azure_storage_account_name": "myaccount",
"azure_storage_account_key": "...",
}
)
```
New files
SPI layer (`lance-graph-catalog`):
Implementation layer (`lance-graph`):
Python bindings (`lance-graph-python`):
Test plan