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

1. Basic Queries: Start with JOIN and GROUP BY for fundamental data operations
2. Advanced Logic: Use CTE for complex query structures
3. Custom Functions: Implement UDF for specialized data processing
4. Performance: Leverage Query Profile for optimization insights
5. External Data: Integrate external sources with Dictionary

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