DSP: Schema Design for Non-Relational Applications

Imam, Abdullahi Abubakar; Basri, Shuib; Ahmad, Rohiza; Wahab, Amirudin Abdul; González-Aparicio, María Teresa; Capretz, Luiz Fernando; Alazzawi, Ammar K.; Balogun, Abdullateef Oluwagbemiga

doi:10.3390/sym12111799

Cited by 9 publications

(5 citation statements)

References 54 publications

(47 reference statements)

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“…From the Table 3, scenario 2 performs better than scenario 1 in all areas. This finding is similar to the proposed NoSql data modeling by [28]- [30]. The finding and suggestions from [31], [32] also related to this study's finding that a specific NoSql database requires detailed analysis for the performance and consistent access operations.…”

Section: Comparison Overviewsupporting

confidence: 87%

Cloud computing: google firebase firestore optimization analysis

Semma¹,

Ali²,

Saerozi³

et al. 2023

IJEECS

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Cloud computing is a new paradigm that provides end users with a secure, personalized, dynamic computing environment with guaranteed service quality. One popular solution is Google cloud firestore, a global-scale not only structured query language (NoSQL) document database for mobile and web apps. Recent research on cloud-based NoSQL databases often discusses the difference between them and SQL databases and their performance. However, using cloud-based NoSQL databases such as firestore is tricky without any scientific comparison methodology, and it needs analysis of how its particular systems work. This study aims to discover what is the best design that could be implemented to optimize data read cost, response size, and time regarding the cloud firestore database. In this study, we develop a grade point average (GPA)-report mocking application to assess data read based on our institution’s needs. This application consists of three functions. Add the graduated GPA and students’ names, and view the ten highest GPAs, GPA average, and total graduated students. The finding indicates that aggregating data on the client side or utilizing the Google cloud function trigger, then updating aggregation data in one transaction significantly reduces document read count (cost), response size, and time.

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Section: Comparison Overviewsupporting

confidence: 87%

Cloud computing: google firebase firestore optimization analysis

Semma¹,

Ali²,

Saerozi³

et al. 2023

IJEECS

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“…In [62], a storage method to improve the management of geochemical data is proposed; it consists of two levels, JSONification, where the data is converted using an existing library, and storage in the cloud. In [51], the authors developed a model whose architecture is made up of seven layers, which generates the scheme according to the user and system requirements, with the aim of managing data asymmetry. In [27], a method to select the most appropriate database model for polyglot persistence applications was developed, considering user requirements related to data handling.…”

Section: A Rq-1 What Are Nosql Database Modeling Procedures Based On ...mentioning

confidence: 99%

NoSQL Database Modeling and Management: A Systematic Literature Review

Aguilar Vera,

Naal Jácome,

Díaz Mendoza

et al. 2023

Rev. Fac. Ing.

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The NoSQL databases that emerged this century were created to solve the limitations of relational database systems due to the different types of data that have appeared for information processing. In this paper, we present the results of a secondary study carried out to find and synthesize the research made up to now on modeling processes, characteristics of the used types of data, and management tools for NoSQL Databases. Currently, four types are recognized and classified according to the data model they use: key-value, document-oriented, column-based, and graph-based. With this study, it was possible to identify that the most frequently type of NoSQL database model is that of documents because it offers greater flexibility and versatility compared to the other three models. Although it offers more complex search methods, in terms of data, column and document schemas are the ones that usually describe their characteristics. It was also possible to observe a trend in the use of the column-oriented model and the document-oriented model in the management tools, and, although they all comply with the basic functionalities, the differences lie in the way in which the information is stored and the way they can be accessed.

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“…For evaluation of ensuing SDP models, Accuracy, F-Measure, and Area under Curve (AUC) were selected. These evaluation metrics have been widely used and proven to be reliable in SDP studies [7,41,42].…”

Section: Performance Evaluation Metricsmentioning

confidence: 99%

Empirical Analysis of Rank Aggregation-Based Multi-Filter Feature Selection Methods in Software Defect Prediction

et al. 2021

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Selecting the most suitable filter method that will produce a subset of features with the best performance remains an open problem that is known as filter rank selection problem. A viable solution to this problem is to independently apply a mixture of filter methods and evaluate the results. This study proposes novel rank aggregation-based multi-filter feature selection (FS) methods to address high dimensionality and filter rank selection problem in software defect prediction (SDP). The proposed methods combine rank lists generated by individual filter methods using rank aggregation mechanisms into a single aggregated rank list. The proposed methods aim to resolve the filter selection problem by using multiple filter methods of diverse computational characteristics to produce a dis-joint and complete feature rank list superior to individual filter rank methods. The effectiveness of the proposed method was evaluated with Decision Tree (DT) and Naïve Bayes (NB) models on defect datasets from NASA repository. From the experimental results, the proposed methods had a superior impact (positive) on prediction performances of NB and DT models than other experimented FS methods. This makes the combination of filter rank methods a viable solution to filter rank selection problem and enhancement of prediction models in SDP.

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DSP: Schema Design for Non-Relational Applications

Cited by 9 publications

References 54 publications

Cloud computing: google firebase firestore optimization analysis

Cloud computing: google firebase firestore optimization analysis

NoSQL Database Modeling and Management: A Systematic Literature Review

Empirical Analysis of Rank Aggregation-Based Multi-Filter Feature Selection Methods in Software Defect Prediction

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