Search results
Results from the WOW.Com Content Network
Query optimization consists in determining from a query the most efficient manner (or manners) to execute it. Query optimization can be formalized as translating a relational calculus expression delivering an answer A into efficient relational algebraic expressions delivering the same answer A.
The result of the query is the set of tuples X 1 to X n that make the DRC formula true. This language uses the same operators as tuple calculus, the logical connectives ∧ (and), ∨ (or) and ¬ (not). The existential quantifier (∃) and the universal quantifier (∀) can be used to bind the variables.
An interesting property of these queries is that if we assume that the tuple variables range over tuples over the so-called active domain of the database, which is the subset of the domain that occurs in at least one tuple in the database or in the query expression, then the semantics of the query expressions does not change. In fact, in many ...
The relational algebra uses set union, set difference, and Cartesian product from set theory, and adds additional constraints to these operators to create new ones.. For set union and set difference, the two relations involved must be union-compatible—that is, the two relations must have the same set of attributes.
Conjunctive queries without distinguished variables are called boolean conjunctive queries.Conjunctive queries where all variables are distinguished (and no variables are bound) are called equi-join queries, [1] because they are the equivalent, in the relational calculus, of the equi-join queries in the relational algebra (when selecting all columns of the result).
The output of the problem is the set of answers to the query on the database. If the queries are Boolean queries, i.e., queries have a yes or no answer (for example, Boolean conjunctive queries) then the query evaluation problem is a decision problem. The query evaluation problem is usually posed for a specific class of queries and databases.
The magic sets algorithm takes a Datalog program and a query, and produces a more efficient program that computes the same answer to the query while still using bottom-up evaluation. [23] A variant of the magic sets algorithm has been shown to produce programs that, when evaluated using semi-naïve evaluation , are as efficient as top-down ...
If it does not equal 1, it replaces it with the string "Not one": « 1 == "One" "Not one" IFTE » IFT and IFTE will evaluate a program block given as one of its arguments, allowing a more compact form of conditional logic than an IF/THEN/ELSE/END structure. The following example pops an object from the bottom of the stack, and replaces it with ...