Principle:Eventual Inc Daft Type Casting
| Knowledge Sources | |
|---|---|
| Domains | Data_Engineering, Data_Transformation |
| Last Updated | 2026-02-08 00:00 GMT |
Overview
Technique for converting expression values from one data type to another.
Description
Type casting transforms column values between compatible types (e.g., string to integer, float to int, timestamp to date). This is essential for data cleaning and ensuring type compatibility in downstream operations. Casting can be lossless (e.g., int32 to int64) or lossy (e.g., float to int, which truncates decimal places). Invalid casts (e.g., non-numeric string to integer) produce null values or errors depending on the implementation.
Usage
Use type casting when column types need conversion for compatibility with downstream operations or storage requirements. Common scenarios include converting string columns parsed from CSV to numeric types, narrowing integer widths for memory efficiency, converting timestamps to dates, or preparing columns for joins that require matching types.
Theoretical Basis
Type coercion follows a set of rules defining safe and lossy conversions between data types:
Type hierarchy (safe promotions):
int8 -> int16 -> int32 -> int64 -> float64
uint8 -> uint16 -> uint32 -> uint64
float32 -> float64
date -> timestamp
Lossy conversions:
float -> int (truncation)
string -> numeric (parsing, may fail)
timestamp -> date (time component dropped)
The cast operation applies element-wise to each value in the column, producing a new column of the target type with the same number of rows.