Expression & Scalar Evaluation

The expression subsystem (src/expression/) powers column computations, predicates, and UPDATE assignments. It keeps expression trees approachable while demonstrating how they are evaluated during execution.

Responsibilities

• Store planner-produced expression trees (Expr) in a serializable, traversable enum.
• Bind column references, constants, and built-in functions.
• Evaluate expressions against Tuples at runtime, yielding ScalarValue.
• Provide type inference and casting so arithmetic/comparison operators remain well-typed.

Directory Layout

Concepts

Expr Enum

Expresses column refs, literals, comparisons, logical ops, arithmetic, and function invocations. Each variant implements ExprTrait::evaluate(&self, tuple) and returns a ScalarValue.

ScalarValue

Unified runtime value across types (int, bigint, bool, decimal, varchar, …). Includes cast_to(DataType) so results can be coerced to the target column type before writes.

Type Inference

Planner code invokes Expr::data_type(schema) to predict result types. Execution then casts when needed—e.g., UPDATE t SET a = b + 1 uses the column’s declared type for a.

Interactions

• Planner – builds Expr trees with bound columns; execution reuses them verbatim.
• ExecutionContext – exposes eval_expr and eval_predicate, wrapping expression evaluation plus boolean coercion (NULL becomes false for predicates).
• Optimizer – rules like constant folding traverse Expr trees and reuse ScalarValue arithmetic helpers.

Teaching Ideas

• Add a simple built-in function (length(expr)) to follow the pipeline from parsing to evaluation.
• Implement short-circuiting or full three-valued boolean logic and validate with sqllogictest.
• Instrument Expr::evaluate with tracing to visualise expression evaluation inside physical operators.