The Sensible Sharing Approach to a Scalable, High-Performance Database System

Exploiting parallelism has become the key to building high-performance database systems. Several approaches to building database systems that support both inter and intra-query parallelism have been proposed. These approaches can be broadly classified as either Shared Nothing (SN) or Shared Everything (SE). Although the SN approach is highly scalable, it requires complex data partitioning and tuning to achieve good performance whereas the SE approach suffers from non-scalability. We propose a sensible sharing approach which combines the advantages of both SN and SE. We propose an architecture, and data partitioning and scheduling strategies that promote sensible sharing. We analyze the performance and scalability of our approach and compare with that of a SN system. We find that for a variety of workloads and data skew our approach performs and scales at least as well as a SN system that uses the best possible data partitioning strategy