Data Systems Group at MIT

The case for learned index structures – part I 1/8/18

Whenever efficient data access is needed, index structures are the answer, and a wide variety of choices exist to address the different needs of various access patterns. For example, B-Trees are the best choice for range requests (e.g., retrieve all records in a certain time frame); Hash-maps are hard to beat in performance for single key look-ups; and Bloom filters are typically used to check for record existence. Because of their importance for database systems and many other applications, indexes have been extensively tuned over the past decades to be more memory, cache and/or CPU efficient [36, 59, 29, 11].

The case for learned index structures Kraska et al., arXiv Dec. 2017

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