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It will also be clear that if we take the domain to be an infinite set, then the result of the query will also be infinite. To solve these problems we will restrict our attention to those queries that are domain independent, i.e., the queries that return the same result for a database under all of its schemas.
The search space can become quite large depending on the complexity of the SQL query. There are two types of optimization. These consist of logical optimization—which generates a sequence of relational algebra to solve the query—and physical optimization—which is used to determine the means of carrying out each operation.
In computing, the Halloween Problem refers to a phenomenon in databases in which an update operation causes a change in the physical location of a row, potentially allowing the row to be visited again later in the same update operation. This could even cause an infinite loop in some cases where updates continually place the updated record ahead ...
The skyline operator is the subject of an optimization problem and computes the Pareto optimum on tuples with multiple dimensions.. This operator is an extension to SQL proposed by Börzsönyi et al. [1] to filter results from a database to keep only those objects that are not worse in multiple dimensions than any other.
Object–relational impedance mismatch is a set of difficulties going between data in relational data stores and data in domain-driven object models. Relational Database Management Systems (RDBMS) is the standard method for storing data in a dedicated database, while object-oriented (OO) programming is the default method for business-centric design in programming languages.
We've gathered 50 delightfully unconventional products that prove solving life's everyday problems doesn't have to be boring. These aren't your standard household items; they're conversation ...
U.S. President-elect Donald Trump is making good on his threats to go after the media in court, with several recent lawsuits seeking damages against major publishers over what he describes as ...
In SQL, an INNER JOIN prevents a cartesian product from occurring when there are two tables in a query. For each table added to a SQL Query, one additional INNER JOIN is added to prevent a cartesian product. Thus, for N tables in an SQL query, there must be N−1 INNER JOINS to prevent a cartesian product.