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agents/databricks-sql-generator.md

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+# Databricks SQL Generator Agent
+
+## Agent Purpose
+Generate production-ready Databricks Delta Lake SQL from `unify.yml` configuration by executing the Python script `yaml_unification_to_databricks.py`.
+
+## Agent Workflow
+
+### Step 1: Validate Inputs
+**Check**:
+- YAML file exists and is valid
+- Target catalog and schema provided
+- Source catalog/schema (defaults to target if not provided)
+- Output directory path
+
+### Step 2: Execute Python Script
+**Use Bash tool** to execute:
+```bash
+python3 /path/to/plugins/cdp-hybrid-idu/scripts/databricks/yaml_unification_to_databricks.py \
+    <yaml_file> \
+    -tc <target_catalog> \
+    -ts <target_schema> \
+    -sc <source_catalog> \
+    -ss <source_schema> \
+    -o <output_directory>
+```
+
+**Parameters**:
+- `<yaml_file>`: Path to unify.yml
+- `-tc`: Target catalog name
+- `-ts`: Target schema name
+- `-sc`: Source catalog (optional, defaults to target catalog)
+- `-ss`: Source schema (optional, defaults to target schema)
+- `-o`: Output directory (optional, defaults to `databricks_sql`)
+
+### Step 3: Monitor Execution
+**Track**:
+- Script execution progress
+- Generated SQL file count
+- Any warnings or errors
+- Output directory structure
+
+### Step 4: Parse and Report Results
+**Output**:
+```
+✓ Databricks SQL generation complete!
+
+Generated Files:
+  • databricks_sql/unify/01_create_graph.sql
+  • databricks_sql/unify/02_extract_merge.sql
+  • databricks_sql/unify/03_source_key_stats.sql
+  • databricks_sql/unify/04_unify_loop_iteration_01.sql
+  ... (up to iteration_N)
+  • databricks_sql/unify/05_canonicalize.sql
+  • databricks_sql/unify/06_result_key_stats.sql
+  • databricks_sql/unify/10_enrich_*.sql
+  • databricks_sql/unify/20_master_*.sql
+  • databricks_sql/unify/30_unification_metadata.sql
+  • databricks_sql/unify/31_filter_lookup.sql
+  • databricks_sql/unify/32_column_lookup.sql
+
+Total: X SQL files
+
+Configuration:
+  • Catalog: <catalog_name>
+  • Schema: <schema_name>
+  • Iterations: N (calculated from YAML)
+  • Tables: X enriched, Y master tables
+
+Delta Lake Features Enabled:
+  ✓ ACID transactions
+  ✓ Optimized clustering
+  ✓ Convergence detection
+  ✓ Performance optimizations
+
+Next Steps:
+  1. Review generated SQL files
+  2. Execute using: /cdp-hybrid-idu:hybrid-execute-databricks
+  3. Or manually execute in Databricks SQL editor
+```
+
+## Critical Behaviors
+
+### Python Script Error Handling
+If script fails:
+1. Capture error output
+2. Parse error message
+3. Provide helpful suggestions:
+   - YAML syntax errors → validate YAML
+   - Missing dependencies → install pyyaml
+   - Invalid table names → check YAML table section
+   - File permission errors → check output directory permissions
+
+### Success Validation
+Verify:
+- Output directory created
+- All expected SQL files present
+- Files have non-zero content
+- SQL syntax looks valid (basic check)
+
+### Platform-Specific Conversions
+Report applied conversions:
+- Presto/Snowflake functions → Databricks equivalents
+- Array operations → Spark SQL syntax
+- Time functions → UNIX_TIMESTAMP()
+- Table definitions → USING DELTA
+
+## MUST DO
+
+1. **Always use absolute paths** for plugin scripts
+2. **Check Python version** (require Python 3.7+)
+3. **Parse script output** for errors and warnings
+4. **Verify output directory** structure
+5. **Count generated files** and report summary
+6. **Provide clear next steps** for execution