统治人类
发表于 2025-3-28 16:37:38
https://doi.org/10.1007/978-1-4757-4067-7gas exploration and production, telecommunication, healthcare, agriculture, mining) and similarly in government (e.g., homeland security, smart cities, public transportation, accountable care). In developing several such applications over the years, we have come to realize that existing benchmarks f
FER
发表于 2025-3-28 19:24:36
https://doi.org/10.1007/978-0-387-76635-5cessing. In this paper, we propose a modified MapReduce architecture – MapReduce Agent (MRA) – that resolves those performance problems. MRA can reduce completion time, improve system utilization, and give better performance. MRA employs multi-connection which resolves error recovery with a Q-chaine
LUCY
发表于 2025-3-28 23:33:07
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hieroglyphic
发表于 2025-3-29 05:38:15
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prostate-gland
发表于 2025-3-29 11:02:00
An Approach to Benchmarking Industrial Big Data Applicationsgas exploration and production, telecommunication, healthcare, agriculture, mining) and similarly in government (e.g., homeland security, smart cities, public transportation, accountable care). In developing several such applications over the years, we have come to realize that existing benchmarks f
Cognizance
发表于 2025-3-29 11:26:35
The Emergence of Modified Hadoop Online-Based MapReduce Technology in Cloud Environmentscessing. In this paper, we propose a modified MapReduce architecture – MapReduce Agent (MRA) – that resolves those performance problems. MRA can reduce completion time, improve system utilization, and give better performance. MRA employs multi-connection which resolves error recovery with a Q-chaine
剥削
发表于 2025-3-29 15:44:41
Towards Benchmarking IaaS and PaaS Clouds for Graph Analyticshallenge for the process of benchmarking data-intensive services, namely the inclusion of the data-processing algorithm in the system under test; this increases significantly the relevance of benchmarking results, albeit, at the cost of increased benchmarking duration.
Corporeal
发表于 2025-3-29 22:52:29
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高度
发表于 2025-3-30 01:20:12
Towards a Complete BigBench Implementationases. It was fully specified and completely implemented on the Hadoop stack. In this paper, we present updates on our development of a complete implementation on the Hadoop ecosystem. We will focus on the changes that we have made to data set, scaling, refresh process, and metric.