Xiaoyi Xu

Queen's University, Kingston, Ontario, Canada

Are you Xiaoyi Xu?

Claim your profile

Publications (2)0 Total impact

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Database management systems (DBMSs) use a main memory area as a buffer to reduce the number of disk accesses performed by a transaction. Some DBMSs divide the buffer area into a number of independent buffer pools and each database object (table or index) is assigned to a specific buffer pool. The tasks of configuring the buffer pools, which define the mapping of database objects to buffer pools and setting a size for each of the buffer pools, are crucial for achieving optimal performance. In this paper we describe an automated approach to multiple buffer pool configuration. Our approach, called BPCluster , analyses the characteristics of a given workload and partitions objects into buffer pools according to their access patterns and inherent characteristics. Similar objects are grouped into the same buffer pool, thus separating those objects that may conflict. A size configuration for the multiple buffer pools is determined using a greedy algorithm that attempts to minimize the cost of a logical read. A set of experimental results validate the approach and show that the configurations suggested by BPCluster outperform naïve configurations and, in most cases, perform as well as configurations suggested by an experienced database administrator.
    01/2006;
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Database Management Systems (DBMSs) use a main memory area as a buffer to reduce the number of disk accesses performed by a transaction. DB2 Universal Database divides the buffer area into a number of independent buffer pools and each database object (table or index) is assigned to a specific buffer pool. The tasks of configuring the buffer pools, which defines the mapping of database objects to buffer pools and setting a size for each of the buffer pools, is crucial for achieving optimal performance.Mapping database objects to buffer pools, which we refer to as the "buffer pool configuration problem", is the focus of this paper. Mapping database objects to buffer pools can be viewed as a partitioning problem, that is, we partition the database objects into groups where each group is assigned a separate buffer pool. The partitioning of objects is based on how the objects are used and on the inherent properties of objects. We present an approach to the configuration problem based on analyzing the access behaviour of a given database workload to the set of database objects. The approach is demonstrated with a typical OLTP workload.
    Proceedings of the 2002 conference of the Centre for Advanced Studies on Collaborative Research, September 30 - October 3, 2002, Toronto, Ontario, Canada; 01/2002