Schema Reference

Airfold uses ClickHouse data types and table engines as its foundation. This page covers the most commonly used types and engines.

Data Types

Basic Types

Type	Description
Int	Integer numbers (Int8, Int16, Int32, Int64)
Float	Floating-point numbers (Float32, Float64)
Decimal	Fixed-point numbers with configurable precision
String	Variable-length strings
JSON	Semi-structured JSON data with efficient storage

Date and Time

Type	Description
Date	Date values (YYYY-MM-DD)
DateTime	Date and time with timezone support
Time	Time values without date

Special Types

Type	Description
Enum	Enumerated values with named constants
UUID	Universally unique identifier

Composite Types

Type	Description
Array(T)	Array of elements of type T
LowCardinality(T)	Memory-optimized wrapper for low-cardinality data
Nullable(T)	Allows NULL values for type T

Aggregate Function Types

Type	Description
AggregateFunction	Stores intermediate state of aggregate functions
SimpleAggregateFunction	Simplified version for basic aggregations

Key Concepts

PARTITION BY

Partitioning

• Divides data into logical parts based on partition expression
• Enables efficient data management and query performance
• Common patterns: partition by date, month, or other logical groupings
• Allows for efficient data pruning and deletion

CREATE TABLE events (
    event_date Date,
    user_id UInt64,
    event_type String
) ENGINE = MergeTree()
PARTITION BY toYYYYMM(event_date)
ORDER BY (event_date, user_id)

Benefits of Partitioning:

• Faster queries when filtering by partition key
• Efficient data lifecycle management
• Parallel processing of partitions
• Simplified data maintenance operations

Reference

For detailed documentation on data types and table engines, refer to the official ClickHouse documentation:

• ClickHouse Data Types
• ClickHouse Table Engines