SQL Reference
This section provides a comprehensive reference for SQL support in Spice.ai, including syntax, data types, operators, functions, and system features. The reference is organized by topic for ease of navigation.
Table of Contents
SELECT Syntax
- WITH Clause
- SELECT Clause
- FROM Clause
- WHERE Clause
- JOIN Clause
- GROUP BY Clause
- HAVING Clause
- UNION Clause
- ORDER BY Clause
- LIMIT Clause
- EXCLUDE and EXCEPT Clause
Subqueries
- Subquery Operators
- SELECT Clause Subqueries
- FROM Clause Subqueries
- WHERE Clause Subqueries
- HAVING Clause Subqueries
- Subquery Categories
EXPLAIN
Information Schema
AI Functions
Operators and Literals
Scalar Functions
- Math Functions
- Conditional Functions
- String Functions
- Binary String Functions
- Regular Expression Functions
- Time and Date Functions
- Array Functions
- Struct Functions
- Map Functions
- Hashing Functions
- Union Functions
- Other Functions
Spark-compatible scalar functions such as array, bit_get, date_add, like, and parse_url follow the semantics documented in the Spark SQL built-in function reference.
Aggregate Functions
JSON Functions and Operators
Search
Prepared Statements
DML (Data Manipulation Language)
Data Types
Spice uses Apache Arrow data types internally. For data type compatibility with accelerators, see [Data Type Reference(../datatypes/index.md). Common SQL types include:
| SQL Type | Description |
|---|---|
INT, BIGINT | Integer types |
FLOAT, DOUBLE | Floating-point types |
VARCHAR, TEXT | String types |
BOOLEAN | Boolean type |
TIMESTAMP | Timestamp with nanosecond precision |
DATE | Date type |
DECIMAL | Arbitrary precision numeric |
Use CAST(expression AS type) or expression::type to convert between types.
Refer to each section for detailed syntax, supported features, and examples.
