Database cracking

Holger Pirk, Eleni Petraki, Stratos Idreos, Stefan Manegold, Martin Kersten
2014 Proceedings of the Tenth International Workshop on Data Management on New Hardware - DaMoN '14  
Database Cracking is an appealing approach to adaptive indexing: on every range-selection query, the data is partitioned using the supplied predicates as pivots. The core of database cracking is, thus, pivoted partitioning. While pivoted partitioning, like scanning, requires a single pass through the data it tends to have much higher costs due to lower CPU efficiency. In this paper, we conduct an in-depth study of the reasons for the low CPU efficiency of pivoted partitioning. Based on the
more » ... . Based on the findings, we develop an optimized version with significantly higher (single-threaded) CPU efficiency. We also develop a number of multi-threaded implementations that are effectively bound by memory bandwidth. Combining all of these optimizations we achieve an implementation that has costs close to or better than an ordinary scan on a variety of systems ranging from low-end (cheaper than $300) desktop machines to high-end (above $60,000) servers.
doi:10.1145/2619228.2619232 dblp:conf/damon/PirkPIMK14 fatcat:lzebgfgmkbad7na5cfmqu4j4gu