Compound treatment of chained declustered replicas using a parallel btree for high scalability and availability

  • Authors:

  • Min Luo;Akitsugu Watanabe;Haruo Yokota

  • Affiliations:

  • Department of Computer Science, Tokyo Institute of Technology, Meguro-ku, Tokyo, Japan;Department of Computer Science, Tokyo Institute of Technology, Meguro-ku, Tokyo, Japan;Department of Computer Science, Tokyo Institute of Technology, Meguro-ku, Tokyo, Japan and Global Scientific Information and Computing Center, Tokyo Institute of Technology, Meguro-ku, Tokyo Japan

  • Venue:
  • DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part II
  • Year:
  • 2010

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Abstract

Scalability and availability are key features of parallel database systems. To realize scalability, many dynamic load-balancing methods with data placement and parallel index structures on shared-nothing parallel infrastructure have been proposed. Data migration with range-partitioned placement using a parallel Btree is one solution. The combination of range partitioning and chained declustered replicas provides high availability while preserving scalability. However, independent treatment of the primary and backup data in each node results in long failover times. We propose a novel method for compound treatment of chained declustered replicas using a parallel Btree, called the Fat-Btree. In the proposed method, the single Fat-Btree provides access paths to both primary and backup data in all processor elements, which greatly reduces failover time. Moreover, it enables dynamic load balancing without physical data migration, and improves memory space utilization for processing the index. Experiments using PostgreSQL on a 160-node PC cluster demonstrate the effect.