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.github/workflows/deploy-antora.yml

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with:
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node-version: '20'
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cache: 'npm'
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cache-dependency-path: docs/package-lock.json
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- name: Install dependencies
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run: npm ci
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working-directory: docs
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- name: Build Antora site
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run: npm run build
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working-directory: docs
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- name: Upload artifact for GitHub Pages
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uses: actions/upload-pages-artifact@v3
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with:
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path: build/site
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path: docs/build/site
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deploy:
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name: Deploy to GitHub Pages

GUIDE_NEO4J_UC.md

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## Validated Test Results
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The following results are from running `full_uc_tests.py` against a Neo4j Aura instance:
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The following results are from testing against a Neo4j Aura instance:
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| Test | Status | Result |
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|------|--------|--------|
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---
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## Running the Test Suite
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A comprehensive test suite is available to validate your UC JDBC setup:
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```python
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# In Databricks notebook
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%run ./full_uc_tests
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# Or execute directly
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exec(open("/Workspace/path/to/full_uc_tests.py").read())
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```
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The test suite:
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- Loads configuration from Databricks Secrets
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- Creates/recreates the UC JDBC connection
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- Runs 12 tests covering all supported and unsupported patterns
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- Wraps all tests in try/except to prevent crashes
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- Provides detailed timing and results summary
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**Expected output:**
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```
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============================================================
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SUMMARY
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============================================================
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Total Tests: 12
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Passed: 9
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Failed: 0
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Expected Failures: 3
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Success Rate: 100% (excluding expected failures)
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Total Execution Time: 194.1s
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```
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---
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## References
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### Documentation
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- [Databricks Unity Catalog JDBC](https://docs.databricks.com/aws/en/connect/jdbc-connection)
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- [Spark JDBC Data Sources](https://spark.apache.org/docs/latest/sql-data-sources-jdbc.html)
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### Test Suite Files
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### Notebooks
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| File | Description |
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|------|-------------|
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| `uc-neo4j-test-suite/full_uc_tests.py` | Standalone Python test suite for Databricks |
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| `uc-neo4j-test-suite/neo4j_databricks_sql_translation.ipynb` | Full test notebook (Sections 1-8) |
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| `uc-neo4j-test-suite/neo4j_schema_test.ipynb` | Schema testing notebook (Sections 1, 3, 8) |
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| `uc-neo4j-test-suite/neo4j_databricks_sql_translation.ipynb` | UC JDBC connection and SQL-to-Cypher translation tests |
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| `uc-neo4j-test-suite/metadata_sync_delta.ipynb` | Metadata sync via materialized Delta tables |
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| `uc-neo4j-test-suite/metadata_sync_external.ipynb` | Metadata sync via External Metadata API |
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| `uc-neo4j-test-suite/federated_lakehouse_query.ipynb` | Federated query testing |
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| `uc-neo4j-test-suite/federated_views_agent_ready.ipynb` | Agent-ready federated views |
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### Additional Examples
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NEO4J_UC_INTEGRATION_REPORT.md

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## Prototype Validation: Query Patterns
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We ran a 12-test suite (`full_uc_tests.py`) against a live Neo4j Aura instance through the UC JDBC connection. Total execution time was approximately 194 seconds, with most time spent on connection initialization rather than query execution.
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We ran a 12-test suite against a live Neo4j Aura instance through the UC JDBC connection. Total execution time was approximately 194 seconds, with most time spent on connection initialization rather than query execution.
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### Passing Tests (9/9 supported patterns)
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README.md

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```
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neo4j-uc-integration/
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├── GUIDE_NEO4J_UC.md # Detailed usage guide
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├── uc-neo4j-test-suite/ # Databricks notebooks and test suite
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│ ├── full_uc_tests.py # Standalone Python test suite
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│ ├── neo4j_databricks_sql_translation.ipynb # Full test notebook
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│ └── neo4j_schema_test.ipynb # Schema testing notebook
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├── METADATA.md # Metadata synchronization design
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├── uc-neo4j-test-suite/ # Databricks notebooks
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│ ├── neo4j_databricks_sql_translation.ipynb # UC JDBC and SQL translation tests
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│ ├── metadata_sync_delta.ipynb # Metadata sync via Delta tables
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│ ├── metadata_sync_external.ipynb # Metadata sync via External Metadata API
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│ ├── federated_lakehouse_query.ipynb # Federated query testing
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│ └── federated_views_agent_ready.ipynb # Agent-ready federated views
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├── pyspark-translation-example/ # Local PySpark SQL translation tests
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├── sample-sql-translation/ # Spring Boot JDBC connectivity demo
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├── java-metadata-demo/ # Java JDBC metadata exploration
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Import notebooks from `uc-neo4j-test-suite/` to your Databricks workspace:
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1. **neo4j_databricks_sql_translation.ipynb** - Full test suite covering network, drivers, direct JDBC, and UC JDBC
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2. **neo4j_schema_test.ipynb** - Focused schema testing
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Or run the standalone test suite:
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```python
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# In a Databricks notebook
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%run ./full_uc_tests
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```
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1. **neo4j_databricks_sql_translation.ipynb** - UC JDBC connection and SQL-to-Cypher translation tests
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2. **metadata_sync_delta.ipynb** - Metadata sync via materialized Delta tables
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3. **metadata_sync_external.ipynb** - Metadata sync via External Metadata API
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### Local PySpark Tests
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sources:
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- url: .
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branches: HEAD
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start_path: docs
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start_path: .
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ui:
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bundle:

package.json renamed to docs/package.json

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"version": "1.0.0",
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"description": "Neo4j UC Integration - Federated Query Patterns Documentation",
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"scripts": {
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"convert-diagrams": "node docs/scripts/convert-excalidraw.js",
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"convert-diagrams": "node scripts/convert-excalidraw.js",
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"build": "antora antora-playbook.yml",
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"serve": "npx http-server build/site -p 8080 -o"
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},
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