Dataindex

Dataindex is a term used to describe a data structure or mechanism that enables fast retrieval of data by mapping search keys to their storage locations. In practice, data indexing is employed by databases, search engines, and analytics systems to reduce the cost of lookups and range queries.

Common index types include B-tree and hash indexes used in relational databases, which support equality and range queries; bitmap indexes for low-cardinality columns; inverted indexes used by full-text search to map terms to documents; spatial indexes such as R-trees for geographic queries. There are also clustered indexes, where the table data is stored in index order, and non-clustered indexes, which store pointers separately.

How indexing works: when an index is created on one or more fields, the system builds a data structure that stores the mapping from key values to physical addresses or pointers. Queries use the index to locate candidate records quickly and then retrieve the full rows. Index maintenance is required on writes, updates, or deletes; this can slow data modification but improves read performance.

Applications and trade-offs: indexes accelerate read-heavy workloads but incur storage overhead and write costs. Comprehensive indexing strategies may combine multiple indexes, see selectivity, and use statistics to optimize query plans. In distributed systems, indexes may be partitioned or replicated to support parallel queries and fault tolerance.

Limitations and best practices: avoid over-indexing; choose indexes with high selectivity; periodically reindex or update statistics; consider maintenance windows and effects on latency. Data indexing remains a balancing act between read performance, storage, and update costs.