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

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Data Types

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Basic Types

TypeDescription
IntInteger numbers (Int8, Int16, Int32, Int64)
FloatFloating-point numbers (Float32, Float64)
DecimalFixed-point numbers with configurable precision
StringVariable-length strings
JSONSemi-structured JSON data with efficient storage

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Date and Time

TypeDescription
DateDate values (YYYY-MM-DD)
DateTimeDate and time with timezone support
TimeTime values without date

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Special Types

TypeDescription
EnumEnumerated values with named constants
UUIDUniversally unique identifier

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Composite Types

TypeDescription
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

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Aggregate Function Types

TypeDescription
AggregateFunctionStores intermediate state of aggregate functions
SimpleAggregateFunctionSimplified version for basic aggregations

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Key Concepts

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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

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Reference

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