querying

Querying is the act of requesting information from a database, information system, or search engine by specifying criteria that describe the data or documents sought. Queries express conditions, projections, and relationships, enabling targeted retrieval rather than bulk access. They can operate on structured data, unstructured text, or semi-structured formats, and may support filtering, sorting, grouping, and aggregation.

In databases and knowledge graphs, queries are written in specialized languages. Relational databases use SQL; SPARQL is used for RDF graphs; XML data may be addressed with XPath or XQuery; JSON data with JSONPath or proprietary APIs. NoSQL systems provide various query interfaces, from map-reduce paradigms to document or graph query languages. Queries also appear in application programming interfaces for data services.

Query processing typically follows parsing, validation, rewriting, optimization, and execution. A query parser checks syntax and semantics, while the optimizer selects an execution plan based on statistics, indexes, and data distribution. The executor runs the plan, possibly accessing disk storage, caches, and distributed nodes as needed.

Result handling involves projection or selection of fields, joins or unions, aggregation, and, for search engines, ranking. Information retrieval commonly uses scoring models and ranking algorithms to present the most relevant documents at the top. Users may refine queries through filters, operators, or query expansion and feedback loops.

Performance considerations include indexing, data model design, and query plan caching. Distributed querying and parallel execution improve scalability but introduce consistency and latency trade-offs. Security, access controls, and freshness requirements influence query design and results.