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检索条件"主题词=NoSQL databases"

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nosql vs relational database: A comparative study about the generation of the most frequent N-grams

NoSQL vs relational database: A comparative study about the ...

引用

International Conference on Systems and Informatics (ICSAI)

作者： Jardel Ribeiro Jonas Henrique Rodrigo Ribeiro Rosalvo Neto Department of Engineering Computer Federal University of Sao Francisco (Univasf) Juazeiro-BA Brazil

This study intends to help data mining developers to get better performance when obtaining the most frequent N-grams in Text Mining projects. The process of building new variables is one of the oldest and still challenging problems in Data Mining projects. The most frequent N-grams are commonly used as input variables in Text Mining projects. The N-grams represent the occurrence of N items in sequence in a given text. The items can be letters or words. This paper presents a performance comparison between the two main approaches of data storage, relational and nosql databases in the task of obtaining the most frequent N-grams. Validation of the study was executed using a database from a known benchmark from an international competition organized by PAN@CLEF 2013. The one-tailed paired t-test showed that nosql approach is statistically superior to the relational approach with a confidence level of 95%.

关键词： Relational databases nosql databases Text mining Tools XML

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An Empirical Comparison of MongoDB and Hive

An Empirical Comparison of MongoDB and Hive

引用

International Conference on Computing, Communication & Automation (ICCCA)

作者： Anurag Singh Chaudhary Kanika Singh Sanchi Kalra Parmeet Kaur Department of Computer Science and Information Technology Jaypee Institute of Information Technology Noida India

ISBN: (纸本)9781538669488

Most of the web and mobile applications today involve storage, processing and analysis of large datasets. The existing relational database systems are inadequate in handling the basic challenges introduced by these data-centric applications. This, consequently, has led to a new class of scalable and non-relational data management systems, referred to as nosql databases. nosql systems are characterized by their ability to scale horizontally and provide high availability. Apart from nosql, Hadoop framework and its constituent technologies are also synonymous with solutions for large data sets. This paper investigates the querying performance of a widely used nosql document store, MongoDB and compares its performance with respect to the Hadoop analytical language, Hive over a single node. The experimental results show that MongoDB yields a better performance than Hive for the considered dataset over a single node.

关键词： nosql databases Relational databases Data analysis Data models Structured Query Language Performance evaluation

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Big Data Integration Design for General Election in Indonesia

Big Data Integration Design for General Election in Indonesi...

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International Conference on Informatics and Computing (ICIC)

作者： Gede Karya Wikan Danar Sunindyo Benhard Sitohang Saiful Akbar Adi Mulyanto School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia Parahyangan Catholic University Bandung Indonesia PUI-PT Artificial Intelligence for Vision Natural Language Processing & Big Data Analytics (AI-VLB) Bandung Institute of Technology Bandung Indonesia

ISBN: (数字)9781728180472

ISBN: (纸本)9781728180489

The use of big-data analysis in elections in Indonesia has been started since the Governor Election of DKI-Jakarta in 2012 until the Presidential Election in 2019. However, its use is limited to using analytical sentiment to map support and predict election results using social-media data. We see that there is a great opportunity to use big data for a broader election, which is to facilitate the fulfillment of the information and analysis needs of all election stakeholders. But the main problem in using big-data is the integration of big data from various sources with a variety of different formats and large volumes, in addition to the issues of analysis and visualization. For this reason, in this paper, we propose a big-data integration design to meet the needs of elections in Indonesia. This big-data integration design was developed based on election regulations in Indonesia, knowledge of big-data, and the use of a nosql database to store unstructured data. The election big-data integration design that we propose includes (1) the information needs of each election stakeholder; (2) the potential for big-data in fulfilling the information needs of every election stakeholder; (3) big-data analysis architecture for elections; (4) big-data integration architecture for elections; (5) crawler architecture; and (5) technology architecture that can implement big-data integration design for elections. Currently, the implementation of this design is in progress in the P3MI-ITB research project.

关键词： Voting nosql databases Computer architecture Big Data Regulation Stakeholders Informatics

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Testing Spatial Data Deliverance in SQL and nosql Database Using NodeJS Fullstack Web App

Testing Spatial Data Deliverance in SQL and NoSQL Database U...

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International Conference on Science and Technology-Computer (ICST)

作者： Dany Laksono Department of Geodetic Engineering Faculty of Engineering Universitas Gadjah Mada Yogyakarta Indonesia

During the last decade, we saw an explosion of geospatial data being produced. Most of which coming from GPS-enabled devices available for general consumers. The large amount of geotagged data coined the term `Geospatial Big Data', indicating the semi-structured and unstructured nature of such data. SQL relational databases have been known in the past to handle geospatial data very well. However, the abundance of geospatial big data pushed forward the need for nosql database which is expected to perform better in terms of handling and storing geospatial big data. This paper discusses the quantitative comparison of performance between the SQL (i.e., PostGIS) and nosql (i.e., MongoDB) databases in handling geospatial big data. A NodeJS-based angular-framework web app was developed to test the real-world performance of MongoDB and PostGIS in handling a large amount of simulated geospatial data. A different number of points were generated for testing the geospatial data storing and loading capability of both the databases. The test was conducted by comparing the result of XHR (XML HTTP Request) of both databases in each case. The result showed that nosql database, i.e. MongoDB, performs better in loading big geospatial data compared to traditional SQL database using PostGIS.

关键词： Spatial databases Geospatial analysis nosql databases Testing Big Data Loading

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Hybrid Storage Architecture for Internet of Things

Hybrid Storage Architecture for Internet of Things

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Simpasio em Sistemas Computacionais (WSCAD-SSC)

作者： Braulio L.D.C. Junior Douglas D.J. de Macedo Edward David Moreno Mario A.R. Dantas Departament of Computer Science (DCOMP) Federal University of Sergipe (UFS) Sao Cristovao SE Brazil Department of Information Science (CIN) Federal University of Santa Catarina (UFSC) Florianopolis SC Brazil Department of Computer Science (DCC) Federal University of Juiz de Fora (UFJF) Juiz de Fora MG Brazil

ISBN: (纸本)9781728137735

Internet of Things (IoT) is part of our life. Some studies predict a considerable increase of up to 5 times on the number of connected devices by 2020. A significant challenge is how to manage this amount of data generated. In this paper, a hybrid storage architecture for IoT is proposed. The most used nosql databases types and two essential types of data of IoT sensors were selected. The results suggest that architecture is a feasible approach to address the ever-growing amount of data generated in IoT. Additionally, after an architecture evaluation, the results have shown that Redis achieved better overall performance.

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

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nosql Injection Detection Using Deep Neural Network and Principal Component Analysis of Injection Feature Vectors

NoSQL Injection Detection Using Deep Neural Network and Prin...

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International Conference on Computer, Control, Informatics and Its Applications (IC3INA)

作者： Irwin Santoso Soegiharto Abba Suganda Girsang Computer Science Department Binus Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department Binus Graduate Program - Master of Computer Science Binus Nusantara University Jakarta Indonesia

ISBN: (数字)9798331542313

ISBN: (纸本)9798331542320

nosql database has gained popularity in Big Data and other various applications for its simplicity and flexibility. The non-relational nature of nosql database such as MongoDB proves to improve development lifecycles and resources efficiency. However, security challenges arise along with increasing usage of nosql database, and nosql database is no exception to injection attacks. Machine learning proved to be an efficient method, as much has been researched. However, in the future there may be an increasing complexity of features that may prove costly to the model’s performance. Therefore, this research aims to utilize principal component analysis as dimensionality reduction and deep neural network as the classification method, to improve the security of nosql database. The text query is converted to feature vectors then further processed to reduce the input dimension of the deep neural network using PCA. The features used are based on previous research and various sources, and some are added after analyzing the dataset.10-fold cross validation is also applied to ensure that the model does not overfit the data, attempting to reduce bias to the result. The 10-fold cross validation model accuracy result is in average 97.44% with a standard deviation of 1.7%, and the testing results are 97.5% in accuracy,95.65% in precision, 91.67% in recall, and 93.61% in F1 score. Thus, it can be concluded that the usage of PCA on injection feature vectors can reduce complexity of the model.

关键词： Technological innovation nosql databases Artificial neural networks Vectors Complexity theory Security Informatics Standards Principal component analysis Testing

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A Feasible Schema Design Strategy for Amazon DynamoDB: A Nested Normal Form Approach

A Feasible Schema Design Strategy for Amazon DynamoDB: A Nes...

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IEEE International Conference on Industrial Engineering and Engineering Management

作者： Wai Yin Mok The University of Alabama in Huntsville Huntsville USA

ISBN: (数字)9781538672204

ISBN: (纸本)9781538672211

Amazon DynamoDB is a next-gen nosql (Not only SQL), key-value and document database that delivers single-digit millisecond performance at any scale. As more complex web-based applications adopt DynamoDB, it is imperative to develop sound design strategies for DynamoDB schemas. Large-scale web-based applications often exhibit conflicting requirements. Hence, the research problem is to design the DynamoDB schemas of a given application with conflicting requirements such that the database must satisfy certain predetermined performance goals. In the era of relational databases, normal forms were developed to guide the schema design process. Past knowledge and experiences, we believe, are also applicable to DynamoDB schema design. Specifically, based upon Nested Normal Form and XML databases, this paper demonstrates the feasibility of a design strategy on DynamoDB schemas, particularly with the access patterns of the data in mind. Simulation further substantiates the feasibility of our approach.

关键词： Unified modeling language databases XML Data models Cloud computing nosql databases Relational databases

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Pinning Optimal DBDBs for User Delivered Sentiments

Pinning Optimal DBDBs for User Delivered Sentiments

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International Conference on Intelligent Computing and Control Systems

作者： Sai Jyothi Bolla T. Sudhir Department of Computer Science Sri Padmavathi Mahila Viswavidyalayam Tirupati India Department of Computer Science & Engineering Vasireddy Venkatadri Institute of Technology Guntur India

ISBN: (纸本)9781538628430;9781538628423

Handling data in this current era of Data Science is the biggest challenge. Most of the data practioners moved their path of research in understanding behavior of system. These behaviors are like sentiments;which are of many types;published and publishing in social networks. These sentiments are evolving at exponential level and becoming crucial for behavioral study of system. Analysis over such sentiments helps in prediction for increasing the profitable of the system. To do this, sentiments must be modelled. As sentiments are evolving explosively traditional approaches are not apt for modelling sentiments;as a result nosql databases were exploited for such applications. This paper emphasis on why DBDBs (Document Based databases), nosql databases;has gaining momentum for handling sentiments. To do this bulk number of sentiments over social networks are taken into interpretation;using MongoDB and CouchDB these sentiments are exploited for analysis.

关键词： DBDB Sentiments MongoDB CouchD nosql databases

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The Transformation of Relational Database to Wide Column Store Database

The Transformation of Relational Database to Wide Column Sto...

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International Symposium on Computer, Consumer and Control (IS3C)

作者： Jeang-Kuo Chen Wei-Zhe Lee Chaoyang University of Technology Taichung Taiwan

ISBN: (数字)9781728193625

ISBN: (纸本)9781728193632

Due to the popularity of big data applications, such as social networking, e-commerce, etc., companies need to quickly access huge amounts of data. Under such conditions, a relational database (RDB) cannot meet the demand, and more and more companies decide to switch to nosql database to maintain competitiveness. It's necessary to convert data from an RDB to a nosql database for the companies that have a lot of operation data in an RDB. Therefore, this paper proposes an algorithm to explore how to convert the schema of RDB into the ones of Wide Column Store DB (WCSDB), and how to import actual data from an RDB into a WCSDB.

关键词： Social networking (online) nosql databases Companies Relational databases Switches Big Data applications Business

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Basic nosql Injection Analysis And Detection On MongoDB

Basic NOSQL Injection Analysis And Detection On MongoDB

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International Conference on Advanced Computation and Telecommunication (ICACAT)

作者： Vrinda Sachdeva Sachin Gupta Department of CSE MVN University Palwal India

ISBN: (纸本)9781538653685

In recent years the usage of Information technology has unexpectedly increasing resulting in huge data generation. Many companies have taken initiative to use no relational database for managing the data. It has powerful function to manage big data. Huge amount of data has been generated every day. It possibly results in malicious information into the database. No sql database gaining popularity due to its powerful features like scalability, flexibility, faster data access and availability. In this paper, we will analyze the injection on nosql database. We also propose defense method by using php and java script. MongoDB is one of the most secure and powerful no sql database. In this paper we demonstrate, basic no sql injection attack and propose defense method to secure the no sql database. In this way, no sql database programmer be aware of the basic no sql injection attack mechanism and create a more secure database to store huge data.

关键词： nosql databases Malware Computer hacking SQL injection Companies

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