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دسته بندی:
داده های بزرگ - big data
سال انتشار:
2018
عنوان انگلیسی مقاله:
BDWatchdog: Real-time monitoring and profiling of Big Data applications and frameworks
ترجمه فارسی عنوان مقاله:
BDWatchdog: نظارت بر زمان واقعی و چارچوب و پروفایل برنامه های کاربردی داده های بزرگ
منبع:
Sciencedirect - Elsevier - Future Generation Computer Systems, Corrected proof: doi:10:1016/j:future:2017:12:068
نویسنده:
Jonatan Enes *, Roberto R. Expósito, Juan Touriño
چکیده انگلیسی:
Current Big Data applications are characterized by a heavy use of system resources (e.g., CPU, disk)
generally distributed across a cluster. To effectively improve their performance there is a critical need
for an accurate analysis of both Big Data workloads and frameworks. This means to fully understand
how the system resources are being used in order to identify potential bottlenecks, from resource to
code bottlenecks. This paper presents BDWatchdog, a novel framework that allows real-time and scalable
analysis of Big Data applications by combining time series for resource monitorization and flame graphs
for code profiling, focusing on the processes that make up the workload rather than the underlying
instances on which they are executed. This shift from the traditional system-based monitorization to
a process-based analysis is interesting for new paradigms such as software containers or serverless
computing, where the focus is put on applications and not on instances. BDWatchdog has been evaluated
on a Big Data cloud-based service deployed at the CESGA supercomputing center. The experimental results
show that a process-based analysis allows for a more effective visualization and overall improves the
understanding of Big Data workloads. BDWatchdog is publicly available at http://bdwatchdog.dec.udc.es.
Keywords: Big data ، Monitoring ، Profiling ، Time series ، Flame graphs ، Process-based analysis
قیمت: رایگان
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