Publication
Jumping the ORDER BY Barrier in Large-Scale Pattern Matching
Related concepts (34)
Regular expression
A regular expression (shortened as regex or regexp; sometimes referred to as rational expression) is a sequence of characters that specifies a match pattern in text. Usually such patterns are used by string-searching algorithms for "find" or "find and replace" operations on strings, or for input validation. Regular expression techniques are developed in theoretical computer science and formal language theory. The concept of regular expressions began in the 1950s, when the American mathematician Stephen Cole Kleene formalized the concept of a regular language.
Query language
A query language, also known as data query language or database query language (DQL), is a computer language used to make queries in databases and information systems. A well known example is the Structured Query Language (SQL). Broadly, query languages can be classified according to whether they are database query languages or information retrieval query languages. The difference is that a database query language attempts to give factual answers to factual questions, while an information retrieval query language attempts to find documents containing information that is relevant to an area of inquiry.
Tuple relational calculus
Tuple calculus is a calculus that was created and introduced by Edgar F. Codd as part of the relational model, in order to provide a declarative database-query language for data manipulation in this data model. It formed the inspiration for the database-query languages QUEL and SQL, of which the latter, although far less faithful to the original relational model and calculus, is now the de facto standard database-query language; a dialect of SQL is used by nearly every relational-database-management system.
Object–relational database
An object–relational database (ORD), or object–relational database management system (ORDBMS), is a database management system (DBMS) similar to a relational database, but with an object-oriented database model: objects, classes and inheritance are directly supported in database schemas and in the query language. In addition, just as with pure relational systems, it supports extension of the data model with custom data types and methods. An object–relational database can be said to provide a middle ground between relational databases and object-oriented databases.
Object–relational mapping
Object–relational mapping (ORM, O/RM, and O/R mapping tool) in computer science is a programming technique for converting data between a relational database and the heap of an object-oriented programming language. This creates, in effect, a virtual object database that can be used from within the programming language. In object-oriented programming, data-management tasks act on objects that combine scalar values into objects. For example, consider an address book entry that represents a single person along with zero or more phone numbers and zero or more addresses.
Visitor pattern
A visitor pattern is a software design pattern and separates the algorithm from the object structure. Because of this separation new operations can be added to existing object structures without modifying the structures. It is one way to follow the open/closed principle in object-oriented programming and software engineering. In essence, the visitor allows adding new virtual functions to a family of classes, without modifying the classes. Instead, a visitor class is created that implements all of the appropriate specializations of the virtual function.
Hash join
The hash join is an example of a join algorithm and is used in the implementation of a relational database management system. All variants of hash join algorithms involve building hash tables from the tuples of one or both of the joined relations, and subsequently probing those tables so that only tuples with the same hash code need to be compared for equality in equijoins. Hash joins are typically more efficient than nested loops joins, except when the probe side of the join is very small.
Data analysis
Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively.
Object–relational impedance mismatch
Object–relational impedance mismatch creates difficulties going from data in relational data stores (relational database management system [“RDBMS”]) to usage in domain-driven object models. Object-orientation (OO) is the default method for business-centric design in programming languages. The problem lies in neither relational nor OO, but in the conceptual difficulty mapping between the two logic models. Both are logical models implementable differently on database servers, programming languages, design patterns, or other technologies.
Data model
A data model is an abstract model that organizes elements of data and standardizes how they relate to one another and to the properties of real-world entities. For instance, a data model may specify that the data element representing a car be composed of a number of other elements which, in turn, represent the color and size of the car and define its owner. The corresponding professional activity is called generally data modeling or, more specifically, database design.