Heterogeneity-Aware Operator Placement in Column-Store DBMS

Abstract

Due to the tremendous increase in the amount of data efficiently managed by current database systems, optimization is still one of the most challenging issues in database research. Today’s query optimizer determine the most efficient composition of physical operators to execute a given SQL query, whereas the underlying hardware consists of a multi-core CPU. However, hardware systems are more and more shifting towards heterogeneity, combining a multi-core CPU with various computing units, e.g., GPU or FPGA cores. In order to efficiently utilize the provided performance capability of such heterogeneous hardware, the assignment of physical operators to computing units gains importance. In this paper, we propose a heterogeneity-aware physical operator placement strategy (HOP) for in-memory columnar database systems in a heterogeneous environment. Our placement approach takes operators from the physical query execution plan as an input and assigns them to computing units using a cost model at runtime. To enable this runtime decision, our cost model uses the characteristics of the computing units, execution properties of the operators, as well as runtime data to estimate execution costs for each unit. We evaluated our approach on full TPC-H queries within a prototype database engine. As we are going to show, the placement in a heterogeneous hardware system has a high influence on query performance.