A hybrid data structure for dense keys in in-memory database systems
Name
714212509-MIT.pdf
Description
Full printable version
Size
7.87 MB
Format
Adobe PDF
Checksum (MD5)
7f11a807f46d5d40244d3b3bd921b251
Author(s)
Muñiz Navarro, José Alberto
Advisor(s)
Samuel Madden.
Date Issued
2010
Publisher
Massachusetts Institute of Technology
Abstract
This thesis presents a data structure which performs well for in-memory indexing of keys that are unevenly distributed into clusters with a high density of keys. This pattern is prevalent, for example, in systems that use tables with keys where one field is auto-incremented. These types of tables are widely used. The proposed data structure consists of a B+ Tree with intervals as keys, and arrays as values. Each array holds a cluster of values, while the clusters themselves are managed by the B+ Tree for space and cache efficiency. Using the H-Tree as an in-memory indexing structure for an implementation of the TPC-C benchmark sped up the transaction processing time by up to 50% compared to an implementation based on B+Trees, and showed even more dramatic performance gains in the presence of few and large clusters of data.
Description
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 71-72).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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