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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 ...
A popular window function, the Hann window. Most popular window functions are similar bell-shaped curves. In signal processing and statistics, a window function (also known as an apodization function or tapering function [1]) is a mathematical function that is zero-valued outside of some chosen interval. Typically, window functions are ...
The implementation of window function features by vendors of relational databases and SQL engines differs wildly. Most databases support at least some flavour of window functions. However, when we take a closer look it becomes clear that most vendors only implement a subset of the standard. Let's take the powerful RANGE clause as an example.
A partition of an interval being used in a Riemann sum. The partition itself is shown in grey at the bottom, with the norm of the partition indicated in red. In mathematics, a partition of an interval [a, b] on the real line is a finite sequence x 0, x 1, x 2, …, x n of real numbers such that a = x 0 < x 1 < x 2 < … < x n = b.
For example, all rows where the column Country is either Iceland, Norway, Sweden, Finland or Denmark could build a partition for the Nordic countries. Composite partitioning : allows for certain combinations of the above partitioning schemes, by for example first applying a range partitioning and then a hash partitioning.
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The SQL:2003 standard makes minor modifications to all parts of SQL:1999 (also known as SQL3), and officially introduces a few new features such as: [1] XML-related features ; Window functions; the sequence generator, which allows standardized sequences; two new column types: auto-generated values and identity-columns; the new MERGE statement
For example, when testing if the given interval [40 ,60) overlaps the intervals in the tree shown above, we see that it does not overlap the interval [20, 36) in the root, but since the root's low value (20) is less than the sought high value (60), we must search the right subtree. The left subtree's maximum high of 41 exceeds the sought low ...