BigDataBench-MT: A Benchmark Tool for Generating Realistic Mixed Data Center Workloads

TL;DR

BigDataBench-MT is a benchmark tool that generates realistic mixed workloads for data center evaluation by replaying actual traces and scaling workloads flexibly, addressing limitations of previous benchmarks.

Contribution

It introduces a novel benchmark tool that combines real workload traces with scalable workload generation for mixed data center workloads.

Findings

Enables realistic simulation of mixed workloads in data centers.

Provides a flexible, scalable workload generation mechanism.

Offers a visual interface for workload customization.

Abstract

Long-running service workloads (e.g. web search engine) and short-term data analysis workloads (e.g. Hadoop MapReduce jobs) co-locate in today's data centers. Developing realistic benchmarks to reflect such practical scenario of mixed workload is a key problem to produce trustworthy results when evaluating and comparing data center systems. This requires using actual workloads as well as guaranteeing their submissions to follow patterns hidden in real-world traces. However, existing benchmarks either generate actual workloads based on probability models, or replay real-world workload traces using basic I/O operations. To fill this gap, we propose a benchmark tool that is a first step towards generating a mix of actual service and data analysis workloads on the basis of real workload traces. Our tool includes a combiner that enables the replaying of actual workloads according to the workload traces, and a multi-tenant generator that flexibly scales the workloads up and down according to users' requirements. Based on this, our demo illustrates the workload customization and generation process using a visual interface. The proposed tool, called BigDataBench-MT, is a multi-tenant version of our comprehensive benchmark suite BigDataBench and it is publicly available from http://prof.ict.ac.cn/BigDataBench/multi-tenancyversion/.