標題: Titlebook: Big Data Benchmarking; 5th International Wo Tilmann Rabl,Kai Sachs,Hans-Arno Jacobson Conference proceedings 2015 Springer International Pu [打印本頁] 作者: expenditure 時間: 2025-3-21 19:22
書目名稱Big Data Benchmarking影響因子(影響力)
書目名稱Big Data Benchmarking影響因子(影響力)學科排名
書目名稱Big Data Benchmarking網絡公開度
書目名稱Big Data Benchmarking網絡公開度學科排名
書目名稱Big Data Benchmarking被引頻次
書目名稱Big Data Benchmarking被引頻次學科排名
書目名稱Big Data Benchmarking年度引用
書目名稱Big Data Benchmarking年度引用學科排名
書目名稱Big Data Benchmarking讀者反饋
書目名稱Big Data Benchmarking讀者反饋學科排名
作者: Yag-Capsulotomy 時間: 2025-3-21 23:27 作者: 半導體 時間: 2025-3-22 04:09 作者: 勉強 時間: 2025-3-22 05:01
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/185634.jpg作者: 彩色的蠟筆 時間: 2025-3-22 11:41
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.作者: 高爾夫 時間: 2025-3-22 16:03 作者: indoctrinate 時間: 2025-3-22 18:40
Conference proceedings 2015n Potsdam, Germany, in August 2014..The 13 papers presented in this book were carefully reviewed and selected from numerous submissions and cover topics such as benchmarks specifications and proposals, Hadoop and MapReduce - in the different context such as virtualization and cloud - as well as in-memory, data generation, and graphs..作者: 移動 時間: 2025-3-22 21:57
Big Data Benchmarking978-3-319-20233-4Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: nitroglycerin 時間: 2025-3-23 03:57 作者: maculated 時間: 2025-3-23 08:13
,The Poincaré-Bendixson Theorem,e objects contain embedded technology allowing them to interact with the external environment. In other words, when objects can sense and communicate, it changes how and where decisions are made, and who makes them. In the coming years, the Internet of Things is expected to be much larger than the internet and world-wide web that we know today.作者: Circumscribe 時間: 2025-3-23 12:05
Asymptotically Autonomous Vector Fields,ases. 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.作者: 名字 時間: 2025-3-23 14:07 作者: FADE 時間: 2025-3-23 21:33
,The Poincaré-Bendixson Theorem,ardware and software technologies in terms of performance, price-performance and energy efficiency. Continuing its commitment to bring relevant benchmarks to industry, the Transaction Processing Performance (TPC) formed the Big Data committee to develop set of industry standards, and announced its f作者: 連鎖,連串 時間: 2025-3-24 00:54 作者: addict 時間: 2025-3-24 06:18 作者: TIGER 時間: 2025-3-24 09:40
https://doi.org/10.1007/978-1-4757-4067-7industrial operations and physical systems are generating ever increasing volumes of data of many different types. At the same time, advances in computing, storage, communication, and big data technologies are making it possible to collect, store, process, analyze and visualize enormous volumes of d作者: Aspirin 時間: 2025-3-24 12:05 作者: obeisance 時間: 2025-3-24 18:31 作者: innate 時間: 2025-3-24 20:41 作者: CRUE 時間: 2025-3-25 00:01 作者: 名字的誤用 時間: 2025-3-25 03:39 作者: Individual 時間: 2025-3-25 07:41 作者: 果仁 時間: 2025-3-25 14:32
Review of Semiconductor Physics,s processes and their involved master and transactional data objects. The interactions are correlated in controlled ways to enable non-uniform distributions for data and relationships. For benchmarking data integration, the generated data is stored in two interrelated databases. The dataset can be a作者: 飛鏢 時間: 2025-3-25 19:02
https://doi.org/10.1007/978-0-387-76635-5ring to the new standards requires industry commitment and collaboration. In this paper, we discuss the problems we observe in the current practices of benchmarking, and present our proposal for bringing standardization in the SQL-on-Hadoop space.作者: 急性 時間: 2025-3-25 20:18
Springer Optimization and Its Applicationsmpanies have no need to reveal sensible data but yet developers have access to important development artifacts. We demonstrate our approach by generating a customized test set with medical information for developing SAP’s healthcare solution.作者: 使腐爛 時間: 2025-3-26 02:10
Benchmarking SQL-on-Hadoop Systems: TPC or Not TPC?ring to the new standards requires industry commitment and collaboration. In this paper, we discuss the problems we observe in the current practices of benchmarking, and present our proposal for bringing standardization in the SQL-on-Hadoop space.作者: 雇傭兵 時間: 2025-3-26 05:19 作者: 細微的差異 時間: 2025-3-26 12:03 作者: 考博 時間: 2025-3-26 16:23
0302-9743 ed from numerous submissions and cover topics such as benchmarks specifications and proposals, Hadoop and MapReduce - in the different context such as virtualization and cloud - as well as in-memory, data generation, and graphs..978-3-319-20232-7978-3-319-20233-4Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 留戀 時間: 2025-3-26 18:46
https://doi.org/10.1007/978-1-4757-3745-5influence the performance of CPU bound and I/O bound workloads. Based on our observations, we identify three important factors that should be considered when configuring and provisioning virtualized Hadoop clusters.作者: Monotonous 時間: 2025-3-27 00:57
0302-9743 on Big Data Benchmarking, WBDB 2014, held in Potsdam, Germany, in August 2014..The 13 papers presented in this book were carefully reviewed and selected from numerous submissions and cover topics such as benchmarks specifications and proposals, Hadoop and MapReduce - in the different context such as作者: N斯巴達人 時間: 2025-3-27 02:31
,The Poincaré-Bendixson Theorem,enchmark draft we attempt to bridge the gap by challenging analytical platforms to answer complex queries on structured business data while leveraging the elastic infrastructure of the cloud to satisfy performance requirements.作者: 百科全書 時間: 2025-3-27 08:00 作者: exclamation 時間: 2025-3-27 11:39
Benchmarking Elastic Query Processing on Big Dataenchmark draft we attempt to bridge the gap by challenging analytical platforms to answer complex queries on structured business data while leveraging the elastic infrastructure of the cloud to satisfy performance requirements.作者: 多山 時間: 2025-3-27 14:01 作者: electrolyte 時間: 2025-3-27 19:56 作者: crockery 時間: 2025-3-28 01:16
,The Poincaré-Bendixson Theorem,me, Hadoop file system API compatible systems and MapReduce layers. The TPCx-HS can be used to asses a broad range of system topologies and implementation methodologies, in a technically rigorous and directly comparable, vendor-neutral manner.作者: BILL 時間: 2025-3-28 06:07 作者: 鴕鳥 時間: 2025-3-28 09:30 作者: Gratulate 時間: 2025-3-28 12:05
Benchmarking Virtualized Hadoop Clustersinfluence the performance of CPU bound and I/O bound workloads. Based on our observations, we identify three important factors that should be considered when configuring and provisioning virtualized Hadoop clusters.作者: 統(tǒng)治人類 時間: 2025-3-28 16:37
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作者: FER 時間: 2025-3-28 19:24
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作者: LUCY 時間: 2025-3-28 23:33 作者: hieroglyphic 時間: 2025-3-29 05:38 作者: prostate-gland 時間: 2025-3-29 11:02
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作者: Cognizance 時間: 2025-3-29 11:26
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作者: 剝削 時間: 2025-3-29 15:44
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.作者: Corporeal 時間: 2025-3-29 22:52 作者: 高度 時間: 2025-3-30 01:20
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.
