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Denormalization is a strategy used on a previously-normalized database to increase performance. In computing, denormalization is the process of trying to improve the read performance of a database, at the expense of losing some write performance, by adding redundant copies of data or by grouping data.
Snowflake schema used by example query. The example schema shown to the right is a snowflaked version of the star schema example provided in the star schema article. The following example query is the snowflake schema equivalent of the star schema example code which returns the total number of television units sold by brand and by country for 1997.
Star schema used by example query. Consider a database of sales, perhaps from a store chain, classified by date, store and product. The image of the schema to the right is a star schema version of the sample schema provided in the snowflake schema article.
Query rewriting is a typically automatic transformation that takes a set of database tables, views, and/or queries, usually indices, often gathered data and query statistics, and other metadata, and yields a set of different queries, which produce the same results but execute with better performance (for example, faster, or with lower memory use). [1]
For this example it is assumed that each book has only one author. A table that conforms to the relational model has a primary key which uniquely identifies a row. In our example, the primary key is a composite key of {Title, Format} (indicated by the underlining):
The sixth normal form is currently as of 2009 being used in some data warehouses where the benefits outweigh the drawbacks, [9] for example using anchor modeling.Although using 6NF leads to an explosion of tables, modern databases can prune the tables from select queries (using a process called 'table elimination' - so that a query can be solved without even reading some of the tables that the ...
It is a hybrid approach encompassing the best of breed between 3rd normal form (3NF) and star schema. The design is flexible, scalable, consistent and adaptable to the needs of the enterprise" [ 11 ] Data vault's philosophy is that all data is relevant data, even if it is not in line with established definitions and business rules.
A relational schema R is in Boyce–Codd normal form if and only if for every one of its functional dependencies X → Y, at least one of the following conditions hold: [5] X → Y is a trivial functional dependency (Y ⊆ X), X is a superkey for schema R. [5]