Heinz Koeppl, Marc Hafner, et al.
BMC Bioinformatics
In database systems, the cost of data storage and retrieval are important components of the total cost and response time of the system. A popular mechanism to reduce the storage footprint is by compressing the data residing in tables and indexes. Compressing indexes efficiently, while maintaining response time requirements, is known to be challenging. This is especially true when designing for a workload spectrum covering both data warehousing and transaction processing environments. DB2 Linux, UNIX, Windows (LUW) recently introduced index compression for use in both environments. This uses techniques that are able to compress index data efficiently while incurring virtually no performance penalty for query processing. On the contrary, for certain operations, the performance is actually better. In this paper, we detail the design of index compression in DB2 LUW and discuss the challenges that were encountered in meeting the design goals. We also demonstrate its effectiveness by showing performance results on typical customer scenarios. © 2009 VLDB Endowment.
Heinz Koeppl, Marc Hafner, et al.
BMC Bioinformatics
Reena Elangovan, Shubham Jain, et al.
ACM TODAES
William Hinsberg, Joy Cheng, et al.
SPIE Advanced Lithography 2010
Anupam Gupta, Viswanath Nagarajan, et al.
Operations Research