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Compound Treatment of Chained Declustered Replicas Using a Parallel Btree for High Scalability and Availability

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Database and Expert Systems Applications (DEXA 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6262))

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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.

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Luo, M., Watanabe, A., Yokota, H. (2010). Compound Treatment of Chained Declustered Replicas Using a Parallel Btree for High Scalability and Availability. In: Bringas, P.G., Hameurlain, A., Quirchmayr, G. (eds) Database and Expert Systems Applications. DEXA 2010. Lecture Notes in Computer Science, vol 6262. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15251-1_4

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  • DOI: https://doi.org/10.1007/978-3-642-15251-1_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15250-4

  • Online ISBN: 978-3-642-15251-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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