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检索条件"主题词=NoSQL Databases"

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Managing Big Data Using Specialized System Polar

Managing Big Data Using Specialized System Polar

引用

Siberian Symposium on Data Science and Engineering (SSDSE)

作者： Platonov, Y. Artamonova, E. Russian Acad Sci Siberian Branch AP Ershov Inst Informat Syst VLSI CAD Lab Novosibirsk Russia

ISBN: (纸本)9781538615935

In the research, the authors focus on the problem of a big data analytics: the fast search, reading and editing the data stored in systems operating with the data containing a great number (ex., about a billion) of records. The methods suggested in the current report have large opportunities of practical applications. The report extends the use of specialized databases. In particular, research was devoted to the use of Object Relational Mapping (ORM) technology for not relational databases. All operations were performed on specialized Polar system, the original implementation of Institute of Information Systems of Siberian Branch of the Russian Academy of Science. The authors have implemented complex ORM Polar system and performed the research to increase its efficiency. The suggested method of the disk space optimization provides significant accelerating of the data search for not-indexed fields. The original scheme of data placing in the Polar system for ORM solution considerably increases the overall performance of the generalized ORM Polar system. All received results were compared to the similar results received for some popular relational DBMS. The executed research confirmed prospects of Polar system use as DBMS for big data, and also proved the possibility of the effective use of ORM technology for it.

关键词： Polar RDF ORM nosql databases search indexing Big data

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Performance Evaluation of Container and Virtual Machine Running Cassandra Workload 3

Performance Evaluation of Container and Virtual Machine Runn...

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3rd International Conference of Cloud Computing Technologies and Applications (CloudTech)

作者： Shirinbab, Sogand Lundberg, Lars Casalicchio, Emiliano Blekinge Inst Technol Dept Comp Sci Karlskrona Sweden

ISBN: (纸本)9781538611159

Today, scalable and high-available nosql distributed databases are largely used as Big Data platforms. Such distributed databases typically run on a virtualized infrastructure that could be implemented using Hypervisorb ased virtualiz ation or Container-based virtualiz ation. Hypervisor-based virtualization is a mature technology but imposes overhead on CPU, memory, networking, and disk Recently, by sharing the operating system resources and simplifying the deployment of applications, container-based virtualization is getting more popular. Container-based virtualization is lightweight in resource consumption while also providing isolation. However, disadvantages are security issues and 110 performance. As a result, today these two technologies are competing to provide virtual instances for running big data platforms. Hence, a key issue becomes the assessment of the performance of those virtualization technologies while running distributed databases. This paper presents an extensive performance comparison between VMware and Docker container, while running Apache Cassandra as workload. Apache Cassandra is a leading nosql distributed database when it comes to Big Data platforms. As baseline for comparisons we used the Cassandra's performance when running on a physical infrastructure. Our study shows that Docker had lower overhead compared to the VMware when running Cassandra. In fact, the Cassandra's performance on the Dockerized infrastructure was as good as on the Non-Virtualized.

关键词： Cassandra Cloud computing Containers Docker nosql databases Virtual machine VMware Big Data Performance evaluation

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NAPP: Connecting Mentors and Students at Tecnico Lisboa 12th

NAPP: Connecting Mentors and Students at Tecnico Lisboa

引用

12th European Conference on Technology Enhanced Learning (EC-TEL)

作者： Veiga, Pedro Sardinha, Alberto Santos, Ana Moura Boura, Carla Univ Lisbon Inst Super Tecn Taguspk Ave Prof Dr Cavaco Silva P-2744016 Porto Salvo Portugal

ISBN: (纸本)9783319666105;9783319666099

In the past five years, a successful first-year mentoring programme at Tecnico Lisboa's Taguspark campus promoted by Nucleo de Apoio ao Estudante - Taguspark (NAPE-TP) was brought into play. Nevertheless, the relationship between mentors (mostly second-year students) and mentees (first-year students) tends to weaken after the first academic weeks of the semester. This problem can be addressed with the creation of a consistent and unique communication channel between all the parties involved in this programme This work presents NAPP, a novel mentoring software solution for first-year mentorship programmes, that enhances the communication between mentors and mentees while providing study guidance tools for mentees. NAPP is composed of two key components, a cross-platform mobile application and a web application that is used as a high level performance analysis tool by the programme's coordinator. These components were developed using state of the art technologies like the Ionic Framework using AngularJS, and the nosql databases CouchDB and PouchDB.

关键词： Mentoring program Student support systems Mobile application nosql databases

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Graph Database for Recipe Recommendations

Graph Database for Recipe Recommendations

引用

International Conference on Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions)

作者： Vasvi Bajaj Rajat Bhusan Panda Chetna Dabas Parmeet Kaur Jaypee Institute of Information Technology Noida India

ISBN: (纸本)9781538646939

Graph databases represent a paradigm shift from relational databases with a strong support for “ relationships”. As compared to relational databases which compute relationships at runtime, graph databases persist relationships for fast querying and data retrieval. This work presents a recipe recommender as a graph database, Neo4j application. Given any set of ingredients, this application recommends a variety of recipes with the help of a data set containing thousands of ingredients. Further based on availability of ingredients with a user, this application helps discover the list of possible dishes with these ingredients. In order to implement this application, ingredients and recipes have been crawled from cookery based websites using Python scripts. The crawled data has been inserted into the Neo4j database and subsequently inter-relationships between ingredients and recipes nodes have been analyzed. Execution of self designed queries has verified the time-efficiency of the proposed approach.

关键词： Relational databases Crawlers nosql databases Social networking (online) Recommender systems Big Data

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Towards a Hybrid Storage Architecture for IoT

Towards a Hybrid Storage Architecture for IoT

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IEEE Symposium on Computers and Communications (ISCC)

作者： L. D. C. Braulio Edward David Moreno Douglas D. J. de Macedo Diego Kreutz Mario A. R. Dantas Federal University of Sergipe (UFS) Federal University of Santa Catarina (UFSC) Federal University of Pampa (UNIPAMPA) Federal University of Juiz de Fora (UFJF)

Internet of Things (IoT) is becoming part of our daily life. Indeed, studies predict a sharp market growth by 2020. One of the challenges of this fast-growing market is how to store and manage the amount of non-structured data generated by IoT devices. In this paper, we propose a hybrid storage architecture for IoT for addressing scalability, performance, and heterogeneity issues. We selected three of the most commonly used nosql databases (Redis, MongoDB, and Cassandra) to perform the first evaluation of our architecture. Our results suggest that the hybrid storage architecture is a feasible and promising approach to address some of the issues related to the ever-growing amount of data generated by IoT devices. Additionally, our findings also show that Redis achieves a better overall performance for the two chosen types of data, namely scalar and positional.

关键词： Memory Logic gates nosql databases Computer architecture Performance evaluation Internet of Things

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Big Data Storage for a Health Predictive System

Big Data Storage for a Health Predictive System

引用

International Symposium in Sensing and Instrumentation in IoT Era (ISSI)

作者： João Rala Cordeiro Octavian Postolache Instituto de Telecomunicações IT-IUL Instituto Universitário de Lisboa ISCTE-IUL Lisbon Portugal

When referring to health data processing and management quickly comes across the challenge for storing this kind of information. This article resumes the research for a storage model able to support a baby's multimodal healthcare predictive system, which our team is developing. We have took a structured approach where we define the data characteristics, the systems requirements and most significant operations required to our “business”. Understanding relational and non-relational approaches, and differences between nosql database categories we have defined what we consider the best approach for our scenario, is this case a mix of document and extensible record stores. Finally we analyze the different available technologies/platforms on this categories and how they can support our system requirements.

关键词： Indexes Distributed databases nosql databases Pediatrics XML Big Data

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Uncovering the Evolution History of Data Lakes 5

Uncovering the Evolution History of Data Lakes

引用

IEEE International Conference on Big Data (IEEE Big Data)

作者： Klettke, Meike Awolin, Hannes Stoerl, Uta Mueller, Daniel Scherzinger, Stefanie Univ Rostock Rostock Germany Univ Appl Sci Darmstadt Germany OTH Regensburg Regensburg Germany

ISBN: (纸本)9781538627150

Data accumulating in data lakes can become inaccessible in the long run when its semantics are not available. The heterogeneity of data formats and the sheer volumes of data collections prohibit cleaning and unifying the data manually. Thus, tools for automated data lake analysis are of great interest. In this paper, we target the particular problem of reconstructing the schema evolution history from data lakes. Knowing how the data is structured, and how this structure has evolved over time, enables programmatic access to the lake. By deriving a sequence of schema versions, rather than a single schema, we take into account structural changes over time. Moreover, we address the challenge of detecting inclusion dependencies. This is a prerequisite for mapping between succeeding schema versions, and in particular, detecting nontrivial changes such as a property having been moved or copied. We evaluate our approach for detecting inclusion dependencies using the MovieLens dataset, as well an adaption of a dataset containing botanical descriptions, to cover specific edge cases.

关键词： nosql databases schema version extraction evolution operations integrity constraints inclusion dependencies

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Defining a nosql document database of accessible transport routes 10

Defining a NoSQL document database of accessible transport r...

引用

EEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)

作者： Vela, Belen Maria Cavero, Jose Caceres, Paloma Sierra, Almudena Cuesta, Carlos E. Rey Juan Carlos Univ Escuela Tecn Super Ingn Informat Mostoles 28933 Spain

ISBN: (纸本)9781538630662

Transport is one the aspects that most critically affects the population's life conditions, particularly in the case of those people with various special mobility needs. In spite of the existence of numerous Websites that provide information about public transport services, there is a lack of open data regarding accessible public transportation systems. We are, therefore, working on the development of a technological framework for the processing, management and exploitation of open data, with the goal of promoting accessibility to city public transport, which is taking place within the framework of the Access@city project. In this paper we specifically focus on the problem of designing the nosql document database with which to manage the information concerning accessible routes obtained by means of crowdsourcing techniques.

关键词： Transport Accesibility Big Data nosql databases Document Database Design

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Graph databases: Neo4j Analysis 19

Graph Databases: Neo4j Analysis

引用

19th International Conference on Enterprise Information Systems (ICEIS)

作者： Guia, Jose Soares, Valeria Goncalves Bernardino, Jorge Polytech Coimbra ISEC Rua Pedro Nunes Coimbra Portugal Univ Fed Paraiba Informat Ctr Joao Pessoa Paraiba Brazil Univ Coimbra CISUC Ctr Informat & Syst Coimbra Portugal

ISBN: (纸本)9789897582479

The volume of data is growing at an increasing rate. This growth is both in size and in connectivity, where connectivity refers to the increasing presence of relationships between data. Social networks such as Facebook and Twitter store and process petabytes of data each day. Graph databases have gained renewed interest in the last years, due to their applications in areas such as the Semantic Web and Social Network Analysis. Graph databases provide an effective and efficient solution to data storage and querying data in these scenarios, where data is rich in relationships. In this paper, it is analyzed the fundamental points of graph databases, showing their main characteristics and advantages. We study Neo4j, the top graph database software in the market and evaluate its performance using the Social Network Benchmark (SNB).

关键词： Graph databases nosql databases Neo4j

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Integrating Big Data technologies in a dynamic environment EIAH dedicated to e-learning systems based on cloud infrastructure 17

Integrating Big Data technologies in a dynamic environment E...

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2nd International Conference on Computing and Wireless Communication Systems (ICCWCS)

作者： Dahdouh, K. Dakkak, Ahmed Oughdir, Lahcen Univ Sidi Mohamed Ben Abdellah FPT Dept Math Phys & Informat LSI Taza Morocco

ISBN: (纸本)9781450353069

Online learning has experienced a lot of change, largely as a result of a number of technological Innovations. Newer e-learning (online learning) authoring tools have been developed, and more sophisticated Learning Management Systems (LMSs) have been deployed. Nowadays, e-learning systems have evolved exponentially. The emergence of new information and communication technologies, also with the development of new models of learning and new pedagogical concepts, which causes many problems such as the gigantic volume of data generated by e-learning platform, the large number of learners and the diversity of educational content. In this context, Big Data is a promising paradigm because of its permanent scalability and opportunities that offer to e-learning professionals in terms of data collection, storage, analysis, processing, optimization and representation of data. This article presents the Big Data concept, its characteristics, and focuses in particular on the integration of it in a dynamic environment dedicated to e-learning systems, and how Big Data impacts the future of e-learning. Moreover, it proposes a new approach for E-learning systems based on big data technologies in a cloud infrastructure. Furthermore this work explores the benefits and advantages of Big Data for e-learning professionals and how Big Data can improve the online learning experience.

关键词： Big Data Cloud computing E-learning Online learning Learner Learning Management Systems (LMS) nosql databases Hadoop MapReduce Spark Cassandra mongoDB

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