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In database management, an aggregate function or aggregation function is a function where multiple values are processed together to form a single summary statistic. (Figure 1) Entity relationship diagram representation of aggregation. Common aggregate functions include: Average (i.e., arithmetic mean) Count; Maximum; Median; Minimum; Mode ...
MongoDB provides three ways to perform aggregation: the aggregation pipeline, the map-reduce function and single-purpose aggregation methods. [40] Map-reduce can be used for batch processing of data and aggregation operations. However, according to MongoDB's documentation, the aggregation pipeline provides better performance for most ...
For example, think of A as Authors, and B as Books. An Author can write several Books, and a Book can be written by several Authors. In a relational database management system, such relationships are usually implemented by means of an associative table (also known as join table, junction table or cross-reference table), say, AB with two one-to-many relationships A → AB and B → AB.
The relationship between the aggregate and its components is a weak "has-a" relationship: The components may be part of several aggregates, may be accessed through other objects without going through the aggregate, and may outlive the aggregate object. [4] The state of the component object still forms part of the aggregate object. [citation needed]
A graph database (GDB) is a database that uses graph structures for semantic queries with nodes, edges, and properties to represent and store data. [1] A key concept of the system is the graph (or edge or relationship).
MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel and distributed algorithm on a cluster. [1] [2] [3]A MapReduce program is composed of a map procedure, which performs filtering and sorting (such as sorting students by first name into queues, one queue for each name), and a reduce method, which performs a summary ...
Bloom filters can be organized in distributed data structures to perform fully decentralized computations of aggregate functions. Decentralized aggregation makes collective measurements locally available in every node of a distributed network without involving a centralized computational entity for this purpose.
Note (1): Both function and procedure refer to internal routines written in SQL and/or procedural language like PL/SQL. External routine refers to the one written in the host languages, such as C, Java, Cobol, etc. "Stored procedure" is a commonly used term for these routine types. However, its definition varies between different database vendors.