Load balancing and data placement for multi-tiered database systems

  • Authors:
  • Wen-Syan Li;Daniel C. Zilio;Vishal S. Batra;Calisto Zuzarte;Inderpal Narang

  • Affiliations:
  • Department of Computer Science, B2-250, IBM Almaden Research Center, 650 Harry Road, San Jose, CA 95120, USA;IBM Canada Ltd., 8200 Warden Ave Markham, Ont., Canada L6G 1C7;IBM India Research Lab., Block 1, IIT, New Delhi 110016, India;IBM Canada Ltd., 8200 Warden Ave Markham, Ont., Canada L6G 1C7;Department of Computer Science, B2-250, IBM Almaden Research Center, 650 Harry Road, San Jose, CA 95120, USA

  • Venue:
  • Data & Knowledge Engineering
  • Year:
  • 2007

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Abstract

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^(R) DB2^(R) Universal Database(TM) (DB2 UDB) and the IBM WebSphere^(R) 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.