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First Page: select only the first {rows} rows, depending on the type of database; Next Page: select only the first {rows} rows, depending on the type of database, where the {unique_key} is greater than {last_val} (the value of the {unique_key} of the last row in the current page)
Had the engine loaded the rows using a table scan, it would then have to perform the additional work of sorting the returned rows. In some extreme cases - e.g. the statistics maintained by the database engine indicate that the table contains a very small number of rows - the optimizer may still decide to use a table scan for this type of query:
In SQL, a window function or analytic function [1] is a function which uses values from one or multiple rows to return a value for each row. (This contrasts with an aggregate function, which returns a single value for multiple rows.) Window functions have an OVER clause; any function without an OVER clause is not a window function, but rather ...
In a database, a table is a collection of related data organized in table format; consisting of columns and rows. In relational databases, and flat file databases, a table is a set of data elements (values) using a model of vertical columns (identifiable by name) and horizontal rows, the cell being the unit where a row and column intersect. [1]
A common table expression, or CTE, (in SQL) is a temporary named result set, derived from a simple query and defined within the execution scope of a SELECT, INSERT, UPDATE, or DELETE statement. CTEs can be thought of as alternatives to derived tables ( subquery ), views , and inline user-defined functions.
A database table can be thought of as consisting of rows and columns. [1] Each row in a table represents a set of related data, and every row in the table has the same structure. For example, in a table that represents companies, each row might represent a single company. Columns might represent things like company name, address, etc. In a ...
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The same may not be true of B-tree: B-tree requires a tree node for every approximately N rows in the table, where N is the capacity of a single node, thus the index size is large. As BRIN only requires a tuple for each block (of many rows), the index becomes sufficiently small to make the difference between disk and memory.