Agent skill
Teradata HNSW Vector Search
Approximate nearest neighbor search using HNSW algorithm
Install this agent skill to your Project
npx add-skill https://github.com/teradata-labs/claude-cookbooks/tree/main/skills/analytics/td-hnsw
SKILL.md
Teradata HNSW Vector Search
| Property | Value |
|---|---|
| Skill Name | Teradata HNSW Vector Search |
| Description | Approximate nearest neighbor search using HNSW algorithm |
| Category | Vector Search |
| Primary Function | HNSW |
| Framework | MLE |
| - Minimum Version: Teradata 20.00 |
Core Capabilities
- Automated table structure analysis via DBC.ColumnsV
- Dynamic SQL generation for HNSW
- Complete workflow from data preparation to results interpretation
- Data quality validation and preprocessing guidance
- Parameter optimization and tuning
Key Parameters
- IDColumn: Unique vector identifier
- TargetColumns: Column(s) containing vector data
- M: Connections per layer (default 16)
- EfConstruction: Build-time search width (default 200)
- DistanceMetric: 'COSINE', 'EUCLIDEAN', 'INNERPRODUCT'
- TopK: Number of nearest neighbors to return (Predict)
- EfSearch: Search-time accuracy parameter (Predict)
Use Cases
- Semantic similarity search
- Recommendation systems
- Image/document retrieval
- RAG (Retrieval-Augmented Generation)
- Duplicate detection
Example Usage
-- HNSW execution
SELECT * FROM HNSW (
ON {USER_DATABASE}.{VECTOR_TABLE} AS InputTable
USING
IDColumn ('{ID_COLUMN}')
TargetColumns ('{VECTOR_COLUMN}')
M (16) -- Neighbors per layer
EfConstruction (200) -- Construction search size
DistanceMetric ('COSINE') -- 'COSINE','EUCLIDEAN','INNERPRODUCT'
) AS dt;
Scripts Included
Core Analytics Scripts
table_analysis.sql: Automatic table structure discoverypreprocessing.sql: Data preparation and feature engineeringmodel_training.sql: HNSW executionevaluation.sql: Results analysis and metricscomplete_workflow_template.sql: End-to-end workflow
Utility Scripts
data_quality_checks.sql: Comprehensive data validationparameter_tuning.sql: Parameter optimizationdiagnostic_queries.sql: Results diagnostics and interpretation
Best Practices
- Always run table_analysis.sql first to understand your data structure
- Validate data quality before executing the analytical function
- Use parameter_tuning.sql to find optimal configuration
- Review diagnostic_queries.sql output for model/results validation
Limitations
- Requires Teradata Vantage 20.00+ with ClearScape Analytics
- Input data must meet function-specific requirements
- Results depend on data quality and parameter configuration
Teradata HNSW Vector Search - ClearScape Analytics skill for Teradata Vantage
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