No Silver Bullet: Boosting GaussDB Performance on the 30TB TPC-H Workload

2026-08-28

AI Summary

本文通过采用流水线执行模型、更快的节点间数据交换等方法，提升了GaussDB在30TB TPC-H复杂分析工作负载上的性能，超出最佳已发表结果40%。

Abstract

GaussDB is Huawei's premier database system, designed for large-scale deployments and the most demanding workloads. It is a distributed shared-nothing system, capable of handling all types of workloads. This paper outlines a series of modifications to GaussDB aimed at improving its performance on large-scale and complex analytical workloads. After these changes, its performance on the TPC-H workload exceeded the best published result by 40% at 30 TB. The key enhancements to achieve this elite performance include adopting a pipeline execution model, a faster and more scalable inter-node data shuffle, exploiting a unified bus and unified remote memory access. We also expanded the support of cost-based Bloom filter placement and implemented several Bloom filter streaming strategies, enabling their use across nodes.

Problem

• GaussDB
• performance
• TPC-H workload
• large-scale

Innovation

• pipeline execution model
• inter-node data shuffle
• unified bus and remote memory access
• cost-based Bloom filter placement
• Bloom filter streaming strategies