Expression Simplification

SUMMARY

Expression simplification is a query optimization technique that transforms complex logical and arithmetic expressions into simpler, equivalent forms. This process reduces computational overhead and improves query execution efficiency by eliminating redundant operations and simplifying calculations before execution.

How expression simplification works

Expression simplification operates through a series of transformation rules that modify query expressions while preserving their logical equivalence. Common simplifications include:

Constant folding (pre-computing static expressions)
Boolean expression reduction
Algebraic simplification
Redundant predicate elimination

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Types of simplifications

Constant folding

Evaluates expressions with constant values at optimization time rather than execution time:

# Before simplification
WHERE column_a > 5 AND column_a > 3
# After simplification
WHERE column_a > 5

Boolean reduction

Simplifies complex boolean logic:

# Before simplification
WHERE (x AND TRUE) OR (y AND FALSE)
# After simplification
WHERE x

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Benefits for time-series queries

In time-series databases, expression simplification is particularly valuable when dealing with:

Complex date/time calculations
Range comparisons
Window function expressions
Aggregation chains

For example, a time-series query might be simplified from:

-- ⚠️ ANSI (requires QuestDB adaptation)
SELECT timestamp, value 
FROM metrics 
WHERE timestamp >= '2024-01-01' 
  AND timestamp < '2024-01-02'
  AND timestamp >= '2024-01-01'

To:

SELECT timestamp, value 
FROM metrics 
WHERE timestamp >= '2024-01-01' 
  AND timestamp < '2024-01-02'

Impact on query performance

Expression simplification contributes to query optimization in several ways:

Reduced CPU usage through fewer operations
Improved predicate pushdown opportunities
Enhanced partition pruning effectiveness
Better utilization of indexes

Integration with query optimization

Expression simplification works alongside other optimization techniques:

Cost-based optimizer decisions
Query planner strategies
Query rewrite operations

This integration ensures that simplified expressions contribute to overall query performance improvements while maintaining result accuracy.

Best practices

When working with expression simplification:

Write clear, logical expressions that the optimizer can understand
Avoid unnecessarily complex conditions
Use appropriate data types to enable optimization
Monitor query plans to verify simplification effectiveness

Common challenges

While powerful, expression simplification faces certain limitations:

Complex user-defined functions may resist simplification
Dynamic expressions might not be simplifiable at optimization time
Some domain-specific logic may require preservation of original form

Understanding these constraints helps in writing queries that can benefit from expression simplification while maintaining required functionality.