Load balancing and data placement for multi-tiered database systems

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• 作者：Wen-Syan Li ; Daniel C. Zilio ; Vishal S. Batra ; Calisto Zuzarte ; Inderpal Narang
• 关键词：OLAP ; Materialized views ; Data placement ; Performance ; Caching
• 刊名：Data and Knowledge Engineering
• 出版年：2007
• 期刊代码：44_0169023x
• 类别：cp
• 出版时间：September 2007
• 卷：62
• 期：3
• 页码：523-546
• 文件大小：1637 K

摘要

A materialized view or Materialized Query Table (MQT) is an auxiliary table with precomputed data that can be used to significantly improve the performance of a database query. A Materialized Query Table Advisor (MQTA) is often used to recommend and create MQTs. The state-of-the-art MQTA works in a standalone database server where MQTs are placed on the same server as that in which the base tables are located. The MQTA does not apply to a federated or scaleout scenario in which MQTs need to be placed on other servers close to applications (i.e. a frontend database server) for offloading the workload on the backend database server. In this paper, we propose a Data Placement Advisor (DPA) and load balancing strategies for multi-tiered database systems. Built on top of the MQTA, DPA recommends MQTs and advises placement strategies for minimizing the response time for a query workload. To demonstrate the benefit of the data placement advising, we implemented a prototype of DPA that works with the MQTA in the IBM^® DB2^® Universal Database™ (DB2 UDB) and the IBM WebSphere^® Information Integrator (WebSphere II). The evaluation results showed substantial improvements of workload response times when MQTs are intelligently recommended and placed on a frontend database server subject to space and load characteristics for TPC-H and OLAP type workloads.