Query Language Properties

Query Language Properties: Extended Formal Definitions

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Traditional Query Language Properties

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• Expressiveness: Indicates how powerful queries can be formulated in a given language. A language should be at least relationally complete.
• Closure: Requires that results of an operation are again elements of the data model.
• Adequacy: A query language is adequate if it uses all concepts of the underlying data model.
• Orthogonality: Requires that all operations may be used independently of the usage context.
• Safety: A query language is considered safe if every syntactically correct query returns a finite set of results (on a finite data set).

Extended Practical Properties

Resource-Bounded Safety

A query language is considered resource-bounded safe if, in addition to returning finite results, it provides guarantees about resource consumption within practical constraints:

• Time Complexity Bounds: The system can determine whether queries will complete within predefined time thresholds.
• Space Complexity Bounds: The system can predict whether memory/storage requirements will remain within available resources.
• Cardinality Prediction: The system can estimate result set size prior to execution.
• Resource Parameterization: The language allows for explicit specification of resource constraints as part of the query.

Semantic Cardinality Constraints

A query language is considered semantically constrained if it can express and enforce cardinality expectations based on domain-specific knowledge:

• Domain-Driven Cardinality: The system recognizes and enforces expected cardinality relationships based on real-world semantics (e.g., a person has exactly one birth date).
• Reasonable Bounds Detection: The system can identify queries that would violate expected cardinality patterns.
• Normalization Heuristics: Mechanisms to express when denormalization is acceptable versus when proper normalization is required.
• Cardinality Violation Handling: Methods to handle exceptional cases that legitimately violate typical cardinality expectations.

These extended definitions move beyond purely mathematical safety toward practical guarantees that reflect real-world data characteristics and resource constraints.