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Sphinx is configured to examine a data set via its Indexer. The Indexer process creates a full-text index (a special data structure that enables quick keyword searches) from the given data/text. Full-text fields are the resulting content that is indexed by Sphinx; they can be (quickly) searched for keywords. Fields are named, and you can limit ...
As of MySQL 5.7.8, August 2015, [41] MySQL supports a native JSON data type defined by RFC 7159. [42] MySQL Server 8.0 was announced in April 2018, [43] including NoSQL Document Store, atomic and crash safe DDL sentences and JSON Extended syntax, new functions, such as JSON table functions, improved sorting, and partial updates. Previous MySQL ...
In order to retrieve the desired data the user presents a set of criteria by a query. Then the database management system selects the demanded data from the database. The retrieved data may be stored in a file, printed, or viewed on the screen. A query language, like for example Structured Query Language (SQL), is used to prepare the queries.
JSON Schema specifies a JSON-based format to define the structure of JSON data for validation, documentation, and interaction control. It provides a contract for the JSON data required by a given application and how that data can be modified. [29] JSON Schema is based on the concepts from XML Schema (XSD) but is JSON-based. As in XSD, the same ...
A database shard, or simply a shard, is a horizontal partition of data in a database or search engine. Each shard may be held on a separate database server instance, to spread load. Some data within a database remains present in all shards, [a] but some appear only in a single shard. Each shard (or server) acts as the single source for this ...
The difference [contradictory] lies in the way the data is processed; in a key-value store, the data is considered to be inherently opaque to the database, whereas a document-oriented system relies on internal structure in the document in order to extract metadata that the database engine uses for further optimization.
SQL was initially developed at IBM by Donald D. Chamberlin and Raymond F. Boyce after learning about the relational model from Edgar F. Codd [12] in the early 1970s. [13] This version, initially called SEQUEL (Structured English Query Language), was designed to manipulate and retrieve data stored in IBM's original quasirelational database management system, System R, which a group at IBM San ...
Indexing and classification methods to assist with information retrieval have a long history dating back to the earliest libraries and collections however systematic evaluation of their effectiveness began in earnest in the 1950s with the rapid expansion in research production across military, government and education and the introduction of computerised catalogues.