Performance Characterization of HTAP Workloads
Hybrid Transactional and Analytical Processing (HTAP) systems have become popular in the past decade. HTAP systems allow running transactional and analytical processing workloads on the same data and hardware. As a result, they suffer from workload interference. Despite the large body of existing work in HTAP systems and architectures, none of the existing work has systematically analyzed workload interference for HTAP systems.
In this work, we characterize workload interference for HTAP systems. We show that the OLTP throughput drops by up to 42% due to sharing the hardware resources. Partitioning the last-level cache (LLC) among the OLTP and OLAP workloads can significantly improve the OLTP throughput without hurting the OLAP throughput. The OLAP throughput is significantly reduced due to sharing the data. The OLAP execution time is exponentially increased if the OLTP workload generates fresh tuples faster than the HTAP system propagates them. Therefore, in order to minimize the workload interference, HTAP systems should isolate the OLTP and OLAP workloads in the shared hardware resources and should allocate enough resources to fresh tuple propagation to propagate the fresh tuples faster than they are generated.
Cite this item
Sirin, U., Dwarkadas, S., & Ailamaki, A. (2021). Performance Characterization of HTAP Workloads. 2021 Ieee 37Th International Conference on Data Engineering (Icde 2021), IEEE International Conference on Data Engineering, 1829–1834. https://doi.org/10.1109/ICDE51399.2021.00162
Click Copy to copy the citation, or select the text manually.
WOS:000687830800154
2021-01-01
Los Alamitos
978-1-7281-9184-3
IEEE International Conference on Data Engineering
1829
1834
REVIEWED
EPFL
| Event name | Event place | Event date |
ELECTR NETWORK | Apr 19-22, 2021 | |