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Metrics for Measuring the Performance of the Mixed Workload CH-benCHmark

机译:衡量混合工作负荷性能的指标CH-benCHmark

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Advances in hardware architecture have begun to enable database vendors to process analytical queries directly on operational database systems without impeding the performance of mission-critical transaction processing too much. In order to evaluate such systems, we recently devised the mixed workload CH-benCHmark, which combines transactional load based on TPC-C order processing with decision support load based on TPC-H-like query suite run in parallel on the same tables in a single database system. Just as the data volume of actual enterprises tends to increase over time, an inherent characteristic of this mixed workload benchmark is that data volume increases during benchmark runs, which in turn may increase response times of analytic queries. For purely transactional loads, response times typically do not depend that much on data volume, as the queries used within business transactions are less complex and often indexes are used to answer these queries with point-wise accesses only. But for mixed workloads, the insert throughput metric of the transactional component interferes with the response-time metric of the analytic component. In order to address the problem, in this paper we analyze the characteristics of CH-benCHmark queries and propose normalized metrics which account for data volume growth.
机译:硬件体系结构的进步已开始使数据库供应商能够直接在运营数据库系统上处理分析查询,而又不会过多地限制关键任务事务处理的性能。为了评估这样的系统,我们最近设计了混合工作负载CH-benCHmark,它将基于TPC-C订单处理的事务负载与基于类似TPC-H的查询套件的决策支持负载组合在一个表中的同一表上并行运行单数据库系统。就像实际企业的数据量趋于随时间增加一样,这种混合工作负载基准测试的一个固有特征是,基准测试运行期间数据量会增加,这反过来又可能增加分析查询的响应时间。对于纯粹的事务负载,响应时间通常不那么依赖于数据量,因为在业务事务中使用的查询不太复杂,并且常常使用索引仅通过逐点访问来回答这些查询。但是对于混合工作负载,事务性组件的插入吞吐量度量会干扰分析组件的响应时间度量。为了解决该问题,在本文中,我们分析了CH-benCHmark查询的特征,并提出了归因于数据量增长的标准化指标。

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