Declarative Database Query Language: Difference between revisions
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* [[Jeffrey F. Naughton]]. ([[2017]]). “[http://dl.acm.org/citation.cfm?id=3144574.3068610 Broadening and deepening query optimization yet still making progress: technical perspective].” In: [[ACM Communications]]. | * [[Jeffrey F. Naughton]]. ([[2017]]). “[http://dl.acm.org/citation.cfm?id=3144574.3068610 Broadening and deepening query optimization yet still making progress: technical perspective].” In: [[ACM Communications]]. | ||
** QUOTE: [[Query optimization]] is a [[fundamental problem]] in [[data management]]. Simply put, most [[database query language]]s are [[declarative]] rather than [[imperative]] — that is, they specify properties the answer should satisfy, rather than give an algorithm to compute the answer. The best known and most widely used database query language — [[SQL query language|SQL]] — is a prime example of a language for which [[database query optimization|optimization]] is essential. By "essential," I mean that database optimization is not a matter of shaving 10% or even a factor of 2x from a query's execution time. In database query evaluation, the difference between a good plan and a bad or even average plan can be multiple orders of magnitude — so successful query optimization makes the difference between a plan that runs quickly and one that never finishes at all. | ** QUOTE: [[Query optimization]] is a [[fundamental problem]] in [[data management]]. Simply put, most [[database query language]]s are [[declarative]] rather than [[imperative]] — that is, they specify properties the answer should satisfy, rather than give an algorithm to compute the answer. The best known and most widely used database query language — [[SQL query language|SQL]] — is a prime example of a language for which [[database query optimization|optimization]] is essential. By "essential," I mean that database optimization is not a matter of shaving 10% or even a factor of 2x from a query's execution time. In database query evaluation, the difference between a good plan and a bad or even average plan can be multiple orders of magnitude — so successful query optimization makes the difference between a plan that runs quickly and one that never finishes at all. | ||
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Latest revision as of 18:53, 1 August 2022
A Declarative Database Query Language is a database query language (to composed database queries) that is a declarative language.
- Context:
- It can (typically) specify properties the Database Query Answer should satisfy (rather than give an algorithm to compute the answer).
- Example(s):
- See: Imperative Database Query Language, Database Query Optimization.
References
2017
- Jeffrey F. Naughton. (2017). “Broadening and deepening query optimization yet still making progress: technical perspective.” In: ACM Communications.
- QUOTE: Query optimization is a fundamental problem in data management. Simply put, most database query languages are declarative rather than imperative — that is, they specify properties the answer should satisfy, rather than give an algorithm to compute the answer. The best known and most widely used database query language — SQL — is a prime example of a language for which optimization is essential. By "essential," I mean that database optimization is not a matter of shaving 10% or even a factor of 2x from a query's execution time. In database query evaluation, the difference between a good plan and a bad or even average plan can be multiple orders of magnitude — so successful query optimization makes the difference between a plan that runs quickly and one that never finishes at all.