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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.
The set of query plans examined is formed by examining the possible access paths (e.g., primary index access, secondary index access, full file scan) and various relational table join techniques (e.g., merge join, hash join, product join). The search space can become quite large depending on the complexity of the SQL query. There are two types ...
(Top) 1 Wide. 2 Narrow. 3 Implementations. 4 See ... or long data is presented with one column containing all the values and another column listing the context of the ...
SQL includes operators and functions for calculating values on stored values. SQL allows the use of expressions in the select list to project data, as in the following example, which returns a list of books that cost more than 100.00 with an additional sales_tax column containing a sales tax figure calculated at 6% of the price.
A range query is a common database operation that retrieves all records where some value is between an upper and lower boundary. [1] For example, list all employees with 3 to 5 years' experience. Range queries are unusual because it is not generally known in advance how many entries a range query will return, or if it will return any at all.
The star schema is an important special case of the snowflake schema, and is more effective for handling simpler queries. [ 2 ] The star schema gets its name from the physical model's [ 3 ] resemblance to a star shape with a fact table at its center and the dimension tables surrounding it representing the star's points.
A query plan (or query execution plan) is a sequence of steps used to access data in a SQL relational database management system. This is a specific case of the relational model concept of access plans.
In order to calculate the average and standard deviation from aggregate data, it is necessary to have available for each group: the total of values (Σx i = SUM(x)), the number of values (N=COUNT(x)) and the total of squares of the values (Σx i 2 =SUM(x 2)) of each groups.