Load Balancing for Multi-tiered Database Systems through Autonomic Placement of Materialized Views

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

  • Affiliations:
  • IBM Almaden Research Center;IBM Canada Ltd.;IBM India Research Lab;IBM Almaden Research Center;IBM Canada Ltd.;IBM Almaden Research Center

  • Venue:
  • ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
  • Year:
  • 2006

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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. AMaterialized 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 theMQTA in the IBM® DB2® Universal Database^TM (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 at a frontend database server subject to space and load characteristics for TPC-H and OLAP type workloads.