Performance Characterization of HTAP Workloads
Performance Characterization of HTAP Workloads
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DOI：
10.1109/icde51399.2021.00162
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发表时间：
2021-04
期刊：
影响因子：
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通讯作者：
Utku Sirin;S. Dwarkadas;A. Ailamaki
中科院分区：
文献类型：
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作者：
Utku Sirin;S. Dwarkadas;A. Ailamaki
混合事务和分析处理(HTAP)系统在过去十年中变得流行起来。HTAP系统允许在相同的数据和硬件上运行事务和分析处理工作负载。因此，他们会受到工作负载干扰。尽管已有大量的HTAP系统和体系结构的工作，但没有一项现有工作系统地分析了HTAP系统的工作负载干扰。结果表明，由于共享硬件资源，OLTP吞吐量下降了42%。在OLTP和OLAP工作负载之间划分末级缓存(LLC)可以在不损害OLAP吞吐量的情况下显著提高OLTP吞吐量。由于共享数据，OLAP吞吐量显著降低。如果OLTP工作负载生成新的元组的速度快于HTAP系统传播它们的速度，则OLAP执行时间将呈指数级增加。因此，为了将负载干扰降到最低，HTAP系统应该隔离共享硬件资源中的OLTP和OLAP负载，并分配足够的资源用于新鲜元组传播，以使新鲜元组的传播速度快于它们的生成。
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.