Query evaluation techniques for large databases
ACM Computing Surveys (CSUR)
Accurate modeling of the hybrid hash join algorithm
SIGMETRICS '94 Proceedings of the 1994 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Operating system support for database management
Readings in database systems (2nd ed.)
Database Systems Concepts
The Implementation of POSTGRES
IEEE Transactions on Knowledge and Data Engineering
Architecture-conscious database systems
Architecture-conscious database systems
Buffering databse operations for enhanced instruction cache performance
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
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The I/O performance of query processing can be improved using two complementary approaches: improve the buffer and the file system management policies of the DB buffer manager and the OS file system manager (e.g. page replacement), or improve the sequence of requests that are submitted to a file system manager and that lead to actual I/O's (block request sequences). This paper takes the latter approach. Exploiting common file system practices as found in Linux, we propose four techniques for permuting and refining block request sequences: Block-Level I/O Grouping, File-Level I/O Grouping, I/O Ordering, and Block Recycling. To manifest these techniques, we create two new plan operations, MMS and SHJ, each of which adopts some of the block request refinement techniques above. We implement the new plan operations on top of Postgres running on Linux, and show experimental results that demonstrate up to a factor of 4 performance benefit from the use of these techniques.