Jasmine: Exploring the Dependency-Aware Execution on Distributed Shared Memory

Abstract

Distributed shared memory abstraction can coordinate a cluster of machine nodes to empower performance-critical queries with the scalable memory space and abundant parallelism. But to deploy the query under such an abstraction, the general execution model just makes operators expressed as multiple subtasks and sequentially schedule them in parallel, while neglecting those vital dependencies between subtasks and data. In this paper, we conduct the in-depth researches about the issues (i.e., low CPU Utilization and poor data locality) raised by the ignorance of dependencies, and then propose a dependency-aware query execution model called Jasmine, which can (i) help users explicitly declare the dependencies and (ii) take these declared dependencies into the consideration of execution to address the issues. We invite our audience to use the rich graphical interfaces to interact with Jasmine to explore the dependency-aware query execution on distributed shared memory.