Query Data in Databend
Databend supports standard SQL with ANSI SQL:1999 and SQL:2003 analytic extensions. This section covers query techniques, optimization tools, and advanced features for efficient data processing.
Core Query Features
| Feature | Description | Key Benefits |
|---|---|---|
| Common Table Expressions (CTE) | Define named temporary result sets with WITH clause | Improved query readability, reusable subqueries |
| JOIN | Combine data from multiple tables | Support for Inner, Outer, Cross, Semi, and Anti joins |
| GROUP BY | Group and aggregate data with extensions | CUBE, ROLLUP, and GROUPING SETS support |
| Sequence | Generate sequential numeric values | Auto-incrementing identifiers and counters |
Advanced Query Capabilities
| Feature | Type | Description | Use Cases |
|---|---|---|---|
| User-Defined Functions | Lambda & Embedded | Custom operations with Python, JavaScript, WebAssembly | Complex data transformations, custom business logic |
| External Functions | Cloud Feature | Custom operations using external servers | Scalable processing, external library integration |
| Dictionary | Data Integration | In-memory key-value store for external data | Fast lookups from MySQL, Redis sources |
| Stored Procedures | SQL Scripting | Reusable command sets with control flow | Multi-step operations, complex business logic |
Query Optimization & Analysis
| Tool | Purpose | Access Method | Key Features |
|---|---|---|---|
| Query Profile | Performance analysis | Databend Cloud Monitor | Visual execution plan, performance metrics |
| Query Hash | Query identification | SQL functions | Unique query fingerprinting, performance tracking |
GROUP BY Extensions
| Extension | Description | Best For |
|---|---|---|
| CUBE | All possible combinations of grouping columns | Multi-dimensional analysis |
| ROLLUP | Hierarchical subtotals and grand totals | Hierarchical reporting |
| GROUPING SETS | Custom grouping combinations | Flexible aggregation scenarios |
Quick Start Guide
- Basic Queries: Start with JOIN and GROUP BY for fundamental data operations
- Advanced Logic: Use CTE for complex query structures
- Custom Functions: Implement UDF for specialized data processing
- Performance: Leverage Query Profile for optimization insights
- External Data: Integrate external sources with Dictionary