Greenplum

TLDR

Demand for enterprise data warehouse solutions that support both real‑time OLTP queries and long‑running OLAP workloads is rising, yet Greenplum has traditionally been limited to OLAP with poor OLTP performance. This paper aims to transform Greenplum into a hybrid system that can handle both OLTP and OLAP workloads while preserving ACID properties and minimizing performance overhead. The authors address bottlenecks such as restrictive locking and two‑phase commit, introduce a global deadlock detector, adopt one‑phase commit for single‑segment updates, and implement a resource‑group model to separate OLTP and OLAP workloads. Benchmarks on TPC‑B and CH‑benCHmark show the proposed enhancements improve OLTP performance without compromising OLAP performance.

Abstract

Demand for enterprise data warehouse solutions to support real-time Online Transaction Processing (OLTP) queries as well as long-running Online Analytical Processing (OLAP) workloads is growing. Greenplum database is traditionally known as an OLAP data warehouse system with limited ability to process OLTP workloads. In this paper, we augment Greenplum into a hybrid system to serve both OLTP and OLAP workloads. The challenge we address here is to achieve this goal while maintaining the ACID properties with minimal performance overhead. In this effort, we identify the engineering and performance bottlenecks such as the under-performing restrictive locking and the two-phase commit protocol. Next we solve the resource contention issues between transactional and analytical queries. We propose a global deadlock detector to increase the concurrency of query processing. When transactions that update data are guaranteed to reside on exactly one segment we introduce one-phase commit to speed up query processing. Our resource group model introduces the capability to separate OLAP and OLTP workloads into more suitable query processing mode. Our experimental evaluation on the TPC-B and CH-benCHmark benchmarks demonstrates the effectiveness of our approach in boosting the OLTP performance without sacrificing the OLAP performance.