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Automated Performance Management for the Big Data Stack

Anastasios Arvanitis, Shivnath Babu, Eric Chu, Adrian Popescu, Alkis Simitsis, Kevin Wilkinson
2019 Conference on Innovative Data Systems Research  
In this paper, we aim to bring attention to the performance management requirements that arise in big data stacks.  ...  This sample also covers the spectrum of choices for deploying the big data stack across on-premises datacenters, private cloud deployments, public cloud deployments, and hybrid combinations of these.  ...  The goal of this paper is to bring attention to the performance management requirements that arise in big data stacks.  ... 
dblp:conf/cidr/ArvanitisBCPSW19 fatcat:35mqpk66krakjnxk5ug234w63y

Cloud Based Big Data Infrastructure: Architectural Components And Automated Provisioning

Yuri Demchenko, Fatih Turkmen, Christophe Blanchet, Charles Loomis, Caees de Laat
2016 Zenodo  
The paper discusses importance of automation of all stages of the Big Data applications developments, deployment and management and refers to existing cloud automation tools and new developments in the  ...  the following components of the Big Data technologies: Big Data definition, Data Management including data lifecycle and data structures, Big Data Infrastructure (generically cloud based), Data Analytics  ...  The authors are thankful to the partners of the CYCLONE project and to the colleagues who collaborated on deploying selected bioinformatics applications in the CYCLONE testbed: Christian Baudet (Centre  ... 
doi:10.5281/zenodo.59159 fatcat:yxvau4m65vgkffgwwmy7nwrdmy

Research on the Application and Strategy of Logistics Stereo Warehouse in the Era of Big Data

Huijie Yang
2018 DEStech Transactions on Computer Science and Engineering  
The conclusion is that the big data analysis has certain guiding significance and reference value to the development direction of the application of logistics warehouse.1  ...  The research idea of this paper is: with the aid of big data tools, the paper analyzes the problems existing in the application of warehouse in logistics enterprises, and finds out the crux of the problem  ...  INTRODUCTION In the era of big data, many large logistics enterprises have begun to use automated three-dimensional warehouses.  ... 
doi:10.12783/dtcse/icmsie2017/18640 fatcat:72wnyy7qsneqnmmeeo35u3iklu

AI-Driven Digital Platform Innovation

Sergey A. Yablonsky
2020 Technology Innovation Management Review  
Evaluation, machine learning, information extraction, and data discovery of intangible AI/BD assets adds further value. • Measuring AI/Big Data Curation is the active management of data over its life cycle  ...  for effective usage based on the measurement of AI/BD assets to ensure it meets the necessary BD quality requirements for its effective usage. • AI Reporting and Interpreting/Big Data Storage denotes  ... 
doi:10.22215/timreview/1392 fatcat:nfwj4dbusjfyveagmdwh27qtqu

Docker container-based big data processing system in multiple clouds for everyone

Nitin Naik
2017 2017 IEEE International Systems Engineering Symposium (ISSE)  
Subsequently, it illustrates the automated provisioning of big data clusters using two popular big data analytics, Hadoop and Pachyderm (without Hadoop) including the Web-based GUI interface Hue for easy  ...  Therefore, this paper proposes the Docker container-based big data processing system in multiple clouds for everyone, which explores another potential dimension of Docker for big data analysis.  ...  The Pachyderm stack uses Docker containers, CoreOS and Kubernetes for cluster management.  ... 
doi:10.1109/syseng.2017.8088294 fatcat:pt2jynphvveivj2v27xsfjgdca

Automated machine learning: AI-driven decision making in business analytics [article]

Marc Schmitt
2022 arXiv   pre-print
It can also bridge the existing gap between supply and demand for ML experts and is a big step towards fully automated decisions in business analytics.  ...  The H2O AutoML framework was benchmarked against a manually tuned stacked ML model on three real-world datasets to test its performance, robustness, and reliability.  ...  AutoML is a big first step and might gradually evolve and extend to a fully automated decision engine.  ... 
arXiv:2205.10538v1 fatcat:jbvmn5bfgfailm7wy7edonccy4

Telco Data Analytics using Open-Source Data Pipeline: Detailed Architecture and Technology Stack

Abirami T
2021 International Journal for Research in Applied Science and Engineering Technology  
This research paper talks about different technology stacks using open source for telco big data analytics that are used to deploy various tools including data collection, data storage, data processing  ...  Open source for telco big data analytics enables sharp insights by enhancing problem discoverability and solution feasibility.  ...  The need for a robust big data analytics solution has never been more profound.  ... 
doi:10.22214/ijraset.2021.38644 fatcat:bkbofpbxxjh53lbncnu5lfblqi

D3.1 - Initial setup of policy aware Linked Data architecture and engine [article]

Bert Van Nuffelen (TF)
2017 Zenodo  
This document describes the deployment of a development environment based on the BDE platform with the semantification extensions  ...  Such components are also responsible for the automated synthesis of policies for derived data.  ...  The reasoning behind such as stack is that performing analytics is better done with regard to the semantics of the data and not the raw data representation.  ... 
doi:10.5281/zenodo.2543647 fatcat:nwvipaky2rdfpbutdstu2h25py

Report on the Sixth International Workshop on Cloud Data Management (CloudDB 2014)

Shuai Ma, Xiaofeng Meng, Fusheng Wang
2014 SIGMOD record  
KEYNOTE TALKS The two keynote talks covered topics on big data processing systems and on big data uses and architecture integrating high performance computing and the Apache stack, respectively. • The  ...  Further, all the participants agreed that many open challenges remain open for cloud data management, such as big data management in the cloud and cloud data security and privacy.  ... 
doi:10.1145/2694413.2694426 fatcat:smzllaoumvh3pfq257meg2bcj4

Resistive Computation: A Critique

Hamid Mahmoodi, Sridevi Srinivasan Lakshmipuram, Manish Arora, Yashar Asgarieh, Houman Homayoun, Bill Lin, Dean M. Tullsen
2014 IEEE computer architecture letters  
a Good Fit for the Big Data Workloads?".  ...  § Big Data Computing o Big data computing, algorithms for energy-efficient acceleration of Big Data o Deep machine learning and data mining acceleration on heterogeneous platforms o Emerging big data  ...  PRESENTATIONS/INVITED TALKS/TUTORIALS Internship Position, Mahab Ghods Company, Tehran, Iran Ø Design of HMI for management information system server and client application.  ... 
doi:10.1109/l-ca.2013.23 fatcat:kvh7nh56r5dmtfo57kxjhttdc4

Architecture and Design for Regression Test Framework to Fuse Big Data Stack

Shashank Saxena
2017 International Journal for Research in Applied Science and Engineering Technology  
Architecture and design for validation components fused to big data stack to cook the desired results for functional validations. II.  ...  Rest of the paper will talk about quality measures for big data validation.  ...  Design for Regression Framework which fuses big data stack for functional and data flow analysis illustrated below in the Fig3.  ... 
doi:10.22214/ijraset.2017.8050 fatcat:mprq2mip3zhghne4w3nggyzugy

Big Data, Simulations and HPC Convergence [chapter]

Geoffrey Fox, Judy Qiu, Shantenu Jha, Saliya Ekanayake, Supun Kamburugamuve
2016 Lecture Notes in Computer Science  
We discuss convergence software built around HPC-ABDS (High Performance Computing enhanced Apache Big Data Stack) and show how one can merge Big Data and HPC (Big Simulation) concepts into a single stack  ...  Two major trends in computing systems are the growth in high performance computing (HPC) with in particular an international exascale initiative, and big data with an accompanying cloud infrastructure  ...  We thank Dennis Gannon for comments on an early draft.  ... 
doi:10.1007/978-3-319-49748-8_1 fatcat:u4rxtm3jzbacpeg7elwhzad454

TurboVG: A HW/SW co-designed multi-core OpenVG accelerator for vector graphics applications with embedded power profiler

Shuo-Hung Chen, Hsiao-Mei Lin, Ching-Chou Hsieh, Chih-Tsun Huang, Jing-Jia Liou, Yeh-Ching Chung
2011 16th Asia and South Pacific Design Automation Conference (ASP-DAC 2011)  
Hardware/Software Components Hardware/Software integration is a big challenge because of the data transportation!!  ...  • Multi-core accelerator can meet requirements of higher resolution screen -Duo-core: 951 seqs/s in Full HD (1920x1080), -Single core: 1200 seqs/s in VGA (640x480) Design Features to Overcome the Performance  ... 
doi:10.1109/aspdac.2011.5722315 dblp:conf/aspdac/ChenLHHLC11 fatcat:27agqbojcrfkhfbyvbthbfjrde

Test Driven Development in OWOW's Full-stack Web Development

Albert Edwillian Pratomo, Erik Van der Schriek, Thomas Van der Veen
2020 JIRAE (International Journal of Industrial Research and Applied Engineering)  
OWOW separates its full-stack web development into back-end and front-end. OWOW had done some automated testing in back-end, but none in front-end.  ...  This was not ideal because the quality of web apps developed could not be easily and thoroughly ensured. OWOW believes Test Driven Development (TDD) might be the solution for the situation.  ...  Research Back-end Back-end development is an aspect of full-stack development which processes data and interacts with the database.  ... 
doi:10.9744/jirae.4.2.46-50 fatcat:nqnct3drobaxdimkl5j3jsry54

Extremely optimizing software applications on Cloud and HPC solutions [article]

Maria Carbonell, Joao Pita Costa
2021 Zenodo  
SODALITE provides application for developers and infrastructure operators with tools that abstract their application and infrastructure requirements to enable simpler and faster development, deployment  ...  In addition, the stack implements semantic modelling for the database, with the end to offer an appealing and complete system for developers who are specialized in complex systems, managing big amounts  ...  The European number one in Big Data, Cybersecurity, High Performance Computing and Digital Workplace.  ... 
doi:10.5281/zenodo.4467851 fatcat:6bz2uyertzbydb2xol4kotoeom
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