"A hashing algorithm is used to organize an index into a sequence, where each indexed value is retrievable based on the result of the hash key value. Hash indexes are efficient with integer values, but are usually subject to overflow as a result of changes." (Gavin Powell, "Beginning Database Design", 2006)
"An index based on an ordered list of hash values." (Carlos Coronel et al, "Database Systems: Design, Implementation, and Management" 9th Ed., 2011)
"An index based on an ordered list of hash values." (Carlos Coronel & Steven Morris, "Database Systems: Design, Implementation, & Management" 11th Ed., 2014)
"A type of index intended for queries that use equality operators, rather than range operators such as greater-than or BETWEEN. It is available for MEMORY tables. Although hash indexes are the default for MEMORY tables for historic reasons, that storage engine also supports B-tree indexes, which are often a better choice for general-purpose queries. MySQL includes a variant of this index type, the adaptive hash index, that is constructed automatically for InnoDB tables if needed based on runtime conditions." (MySQL, "MySQL 8.0 Reference Manual Glossary")
[adaptive hash index:] "An optimization for InnoDB tables that can speed up lookups using - and IN operators, by constructing a hash index in memory. MySQL monitors index searches for InnoDB tables, and if queries could benefit from a hash index, it builds one automatically for index pages that are frequently accessed." (MySQL, "MySQL 8.0 Reference Manual Glossary")
"Hash indexes are file structures that can be used either to resolve queries by accessing the index instead of its underlying base table or to enhance access performance when they do not cover a query by providing a secondary access path to requested base table rows. They can either substitute for or point to base table rows." (Teradata)
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