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Denormalization
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.S. K. Shin and G. L. SandersDenormalization strategies for data retrieval from data warehouses Decision Support Systems, 42(1):267-282, October 2006. It is often motivated by performance or scalability in relational database software needing to carry out very large numbers of read operations. Denormalization differs from the unnormalized form in that denormalization benefits can only be fully realized on a data model that is otherwise normalized. Implementation A normalized design will often "store" different but related pieces of information in separate logical tables (called relations). If these relations are stored physically as separate disk files, completing a database qu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Unnormalized Form
In database normalization, unnormalized form (UNF), also known as an unnormalized relation or non-first normal form (N1NF or NF2), is a database data model (organization of data in a database) which does not meet any of the conditions of database normalization defined by the relational model. Database systems which support unnormalized data are sometimes called non-relational or NoSQL databases. In the relational model, unnormalized relations can be considered the starting point for a process of normalization. It should not be confused with denormalization, where normalization is deliberately compromised for selected tables in a relational database. History In 1970, E. F. Codd proposed the relational data model, now widely accepted as the standard data model. At that time, office automation was the major use of data storage systems, which resulted in the proposal of many NF2 data models like the Schek model, Jaeschke models (non-recursive and recursive algebra), and the Nested Tabl ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Database Normalization
Database normalization or database normalisation (see spelling differences) is the process of structuring a relational database in accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It was first proposed by British computer scientist Edgar F. Codd as part of his relational model. Normalization entails organizing the columns (attributes) and tables (relations) of a database to ensure that their dependencies are properly enforced by database integrity constraints. It is accomplished by applying some formal rules either by a process of ''synthesis'' (creating a new database design) or ''decomposition'' (improving an existing database design). Objectives A basic objective of the first normal form defined by Codd in 1970 was to permit data to be queried and manipulated using a "universal data sub-language" grounded in first-order logic. An example of such a language is SQL, though it is one that Codd regarded as seriou ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Materialized View
In computing, a materialized view is a database object that contains the results of a query. For example, it may be a local copy of data located remotely, or may be a subset of the rows and/or columns of a table or join result, or may be a summary using an aggregate function. The process of setting up a materialized view is sometimes called materialization.Compare: This is a form of caching the results of a query, similar to memoization of the value of a function in functional languages, and it is sometimes described as a form of precomputation. As with other forms of precomputation, database users typically use materialized views for performance reasons, i.e. as a form of optimization. Materialized views which store data based on remote tables were also known as snapshots (deprecated Oracle terminology). In any database management system following the relational model, a view is a virtual table representing the result of a database query. Whenever a query or an update add ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
OLAP Cube
An OLAP cube is a multi-dimensional array of data. Online analytical processing (OLAP) is a computer-based technique of analyzing data to look for insights. The term ''cube'' here refers to a multi-dimensional dataset, which is also sometimes called a hypercube if the number of dimensions is greater than three. Terminology A cube can be considered a multi-dimensional generalization of a two- or three-dimensional spreadsheet. For example, a company might wish to summarize financial data by product, by time-period, and by city to compare actual and budget expenses. Product, time, city and scenario (actual and budget) are the data's dimensions. ''Cube'' is a shorthand for ''multidimensional dataset'', given that data can have an arbitrary number of ''dimensions''. The term hypercube is sometimes used, especially for data with more than three dimensions. A cube is not a "cube" in the strict mathematical sense, as the sides are not all necessarily equal. But this term is used widel ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Snowflake Schema
In computing, a snowflake schema is a logical arrangement of tables in a multidimensional database such that the entity relationship diagram resembles a snowflake shape. The snowflake schema is represented by centralized fact tables which are connected to multiple dimensions. "Snowflaking" is a method of normalizing the dimension tables in a star schema. When it is completely normalized along all the dimension tables, the resultant structure resembles a snowflake with the fact table in the middle. The principle behind snowflaking is normalization of the dimension tables by removing low cardinality attributes and forming separate tables. The snowflake schema is similar to the star schema. However, in the snowflake schema, dimensions are normalized into multiple related tables, whereas the star schema's dimensions are denormalized with each dimension represented by a single table. A complex snowflake shape emerges when the dimensions of a snowflake schema are elaborate, having ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Star Schema
In computing, the star schema is the simplest style of data mart schema and is the approach most widely used to develop data warehouses and dimensional data marts. The star schema consists of one or more fact tables referencing any number of dimension tables. The star schema is an important special case of the snowflake schema, and is more effective for handling simpler queries. The star schema gets its name from the physical model's", p. 708 resemblance to a star shape with a fact table at its center and the dimension tables surrounding it representing the star's points. Model The star schema separates business process data into facts, which hold the measurable, quantitative data about a business, and dimensions which are descriptive attributes related to fact data. Examples of fact data include sales price, sale quantity, and time, distance, speed and weight measurements. Related dimension attribute examples include product models, product colors, product sizes, geographic ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Third Normal Form
Third normal form (3NF) is a database schema design approach for relational databases which uses normalizing principles to reduce the duplication of data, avoid data anomalies, ensure referential integrity, and simplify data management. It was defined in 1971 by Edgar F. Codd, an English computer scientist who invented the relational model for database management. A database relation (e.g. a database table) is said to meet third normal form standards if all the attributes (e.g. database columns) are functionally dependent on solely the primary key. Codd defined this as a relation in second normal form where all non-prime attributes depend only on the candidate keys and do not have a transitive dependency on another key. A hypothetical example of a failure to meet third normal form would be a hospital database having a table of patients which included a column for the telephone number of their doctor. The phone number is dependent on the doctor, rather than the patient, thus w ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Trade-off
A trade-off (or tradeoff) is a situational decision that involves diminishing or losing one quality, quantity, or property of a set or design in return for gains in other aspects. In simple terms, a tradeoff is where one thing increases, and another must decrease. Tradeoffs stem from limitations of many origins, including simple physics – for instance, only a certain volume of objects can fit into a given space, so a full container must remove some items in order to accept any more, and vessels can carry a few large items or multiple small items. Tradeoffs also commonly refer to different configurations of a single item, such as the tuning of strings on a guitar to enable different notes to be played, as well as an allocation of time and attention towards different tasks. The concept of a tradeoff suggests a tactical or strategic choice made with full comprehension of the advantages and disadvantages of each setup. An economic example is the decision to invest in stocks, which a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Complexity Of Constraint Satisfaction
The complexity of constraint satisfaction is the application of computational complexity theory on constraint satisfaction. It has mainly been studied for discriminating between tractable and intractable classes of constraint satisfaction problems on finite domains. Solving a constraint satisfaction problem on a finite domain is an NP-complete problem in general. Research has shown a number of polynomial-time subcases, mostly obtained by restricting either the allowed domains or constraints or the way constraints can be placed over the variables. Research has also established a relationship between the constraint satisfaction problem and problems in other areas such as finite model theory and databases. Overview Establishing whether a constraint satisfaction problem on a finite domain has solutions is an NP complete problem in general. This is an easy consequence of a number of other NP complete problems being expressible as constraint satisfaction problems. Such other problems ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Constraint Satisfaction
In artificial intelligence and operations research, constraint satisfaction is the process of finding a solution through a set of constraints that impose conditions that the variables must satisfy. A solution is therefore a set of values for the variables that satisfies all constraints—that is, a point in the feasible region. The techniques used in constraint satisfaction depend on the kind of constraints being considered. Often used are constraints on a finite domain, to the point that constraint satisfaction problems are typically identified with problems based on constraints on a finite domain. Such problems are usually solved via search, in particular a form of backtracking or local search. Constraint propagation are other methods used on such problems; most of them are incomplete in general, that is, they may solve the problem or prove it unsatisfiable, but not always. Constraint propagation methods are also used in conjunction with search to make a given problem si ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
PostgreSQL
PostgreSQL (, ), also known as Postgres, is a free and open-source relational database management system (RDBMS) emphasizing extensibility and SQL compliance. It was originally named POSTGRES, referring to its origins as a successor to the Ingres database developed at the University of California, Berkeley. In 1996, the project was renamed to PostgreSQL to reflect its support for SQL. After a review in 2007, the development team decided to keep the name PostgreSQL and the alias Postgres. PostgreSQL features transactions with Atomicity, Consistency, Isolation, Durability (ACID) properties, automatically updatable views, materialized views, triggers, foreign keys, and stored procedures. It is designed to handle a range of workloads, from single machines to data warehouses or Web services with many concurrent users. It is the default database for macOS Server and is also available for Windows, Linux, FreeBSD, and OpenBSD. History PostgreSQL evolved from the Ingres proj ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Oracle Database
Oracle Database (commonly referred to as Oracle DBMS, Oracle Autonomous Database, or simply as Oracle) is a multi-model database management system produced and marketed by Oracle Corporation. It is a database commonly used for running online transaction processing (OLTP), data warehousing (DW) and mixed (OLTP & DW) database workloads. Oracle Database is available by several service providers on-prem, on-cloud, or as a hybrid cloud installation. It may be run on third party servers as well as on Oracle hardware (Exadata on-prem, on Oracle Cloud or at Cloud at Customer). History Larry Ellison and his two friends and former co-workers, Bob Miner and Ed Oates, started a consultancy called Software Development Laboratories (SDL) in 1977. SDL developed the original version of the Oracle software. The name ''Oracle'' comes from the code-name of a CIA-funded project Ellison had worked on while formerly employed by Ampex. Releases and versions Oracle products follow a custom r ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
