A partitioning framework for Cassandra NoSQL database using Rendezvous hashing

Elghamrawy, Sally M.; Hassanien, Aboul Ella

doi:10.1007/s11227-017-2027-5

Cited by 12 publications

(8 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Figure 5 shows the number of proposals related to each type of fragmentation. Articles [ 1 , 2 , 3 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 ] focus on horizontal fragmentation; while [ 7 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 ] consider vertical partitioning, [ 67 , 68 , 69 , 70 , 71 , 72 ,…”

Section: Discussionmentioning

confidence: 99%

“…The most relevant work in the category “Fragmentation of Multimedia Databases” is [ 1 ] since it has been cited in several papers ([ 26 , 32 , 40 , 41 , 55 , 67 , 73 ]); in contrast, the most influential method in the category “Dynamic Fragmentation” is [ 70 ] because it has motivated a number of approaches ([ 28 , 29 , 30 , 31 , 32 , 35 , 52 , 56 , 60 , 66 , 69 , 70 , 75 , 77 , 79 , 91 ]); in the category “Fragmentation for NOSQL DBMS”, the article that has attracted more attention is [ 63 ]; finally, [ 25 ] is the most cited work in the category “Other Types of Fragmentation” ([ 23 , 26 , 27 , 32 ]).…”

Section: Discussionmentioning

confidence: 99%

“…Figure 4 shows a bar graph that relates the number of articles to the publisher; most of the articles are concentrated in the Springer publishing house. Springer’s articles primarily addressed vertical ([ 22 , 24 , 25 , 26 , 32 , 33 , 34 , 36 ]) and horizontal ([ 1 , 43 , 46 , 47 , 51 , 55 , 58 , 59 , 63 , 66 ]) fragmentation, 18 of 26 articles. Only one article considers both fragmentation and CBIR ([ 1 ]).…”

Section: Classification Of Research Papersmentioning

confidence: 99%

“…Elghamrawy in [ 59 , 63 ] proposed an Adaptive Rendezvous Hashing Partitioning Module (ARHPM) for Cassandra NoSQL databases. To evaluate the proposed module, Cassandra was modified incorporating the partitioning module and a series of experiments was carried out to validate the load balancing of the proposed module using the Yahoo Cloud Serving Benchmark.…”

Section: Description Of the Set Of Work By Categorymentioning

confidence: 99%

See 3 more Smart Citations

Application of Dynamic Fragmentation Methods in Multimedia Databases: A Review

Castro-Medina

Rodríguez-Mazahua

López-Chau

et al. 2020

Entropy

View full text Add to dashboard Cite

Fragmentation is a design technique widely used in multimedia databases, because it produces substantial benefits in reducing response times, causing lower execution costs in each operation performed. Multimedia databases include data whose main characteristic is their large size, therefore, database administrators face a challenge of great importance, since they must contemplate the different qualities of non-trivial data. These databases over time undergo changes in their access patterns. Different fragmentation techniques presented in related studies show adequate workflows, however, some do not contemplate changes in access patterns. This paper aims to provide an in-depth review of the literature related to dynamic fragmentation of multimedia databases, to identify the main challenges, technologies employed, types of fragmentation used, and characteristics of the cost model. This review provides valuable information for database administrators by showing essential characteristics to perform proper fragmentation and to improve the performance of fragmentation schemes. The reduction of costs in fragmentation methods is one of the most desired main properties. To fulfill this objective, the works include cost models, covering different qualities. In this analysis, a set of characteristics used in the cost models of each work is presented to facilitate the creation of a new cost model including the most used qualities. In addition, different data sets or reference points used in the testing stage of each work analyzed are presented.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Classification Of Research Papersmentioning

confidence: 99%

Section: Description Of the Set Of Work By Categorymentioning

confidence: 99%

See 2 more Smart Citations

Application of Dynamic Fragmentation Methods in Multimedia Databases: A Review

Castro-Medina

Rodríguez-Mazahua

López-Chau

et al. 2020

Entropy

View full text Add to dashboard Cite

show abstract

“…In practice, this means that the system tolerates those network partitions while it remains available, despite using one of those CAP-constrained and convergent models. The key for ensuring this is to have a good data sharding approach, and there has been a fruitful line of research in that area [43,44,45,46,47,48,49].…”

Section: Convergence-based Relationsmentioning

confidence: 99%

CAP Theorem: Revision of Its Related Consistency Models

Muñoz-Escoí

Juan-Marín

García-Escrivá

et al. 2019

The Computer Journal

View full text Add to dashboard Cite

The CAP theorem states that only two of these properties can be simultaneously guaranteed in a distributed service: (i) consistency, (ii) availability, and (iii) network partition tolerance. This theorem was stated and proved assuming that "consistency" refers to atomic consistency. However, multiple consistency models exist and atomic consistency is located at the strongest edge of that spectrum.Many distributed services deployed in cloud platforms should be highly available and scalable. Network partitions may arise in those deployments and should be tolerated. One way of dealing with CAP constraints consists in relaxing consistency. Therefore, it is interesting to explore the set of consistency models not supported in an available and partition-tolerant service (CAP-constrained models). Other weaker consistency models could be maintained when scalable services are deployed in partitionable systems (CAP-free models). Three contributions arise: (1) multiple other CAPconstrained models are identified, (2) a borderline between CAP-constrained and CAP-free models is set, and (3) a hierarchy of consistency models depending on their strength and convergence is built.

show abstract

An H2O’s Deep Learning-Inspired Model Based on Big Data Analytics for Coronavirus Disease (COVID-19) Diagnosis

Elghamrawy

2020

Studies in Big Data

View full text Add to dashboard Cite

The outbreak of coronavirus diseases has rabidly spread all over the world. The World Health Organization (WHO) has announced that coronavirus COVID-19 is an international pandemic. Big Data analytics tools must handle and analyse the massive amount of big medical data, generated daily, quickly due to the fact that time is very significant issue in healthcare applications. In addition, several deep learning algorithms are used along with big data analysis processes to help in detecting COVID-19 outbreaks and predicting their worldwide spread. Many researchers developed their models to diagnosis COVID-19 using Computed Tomography (CT) or X-ray imaging. This chapter presents a detailed discussion of Deep Learning and Big Data Analytics effects in containment of the disease. In addition, an H2O's Deep-Learning-inspired model based on Big Data analytics (DLBD-COV) is proposed for early diagnosis of COVID-19 cases using CT or Xray images. The proposed diagnosis model is build based on the machine learning framework (H2O) for scalable processing. The Generative Adversarial Networks (GAN) and the Convolutional Neural Networks (CNNs) are used and their classification results are compared. The experimental results emphasize the superiority of DLBD-COV when using H 2 O framework for scalable COVID19 classification. The results obtained, using a dataset with thousands of real data and images, show encouraging performance using the automated feature extraction of deep learning techniques used in DLBD-COV. Keywords Coronavirus disease (COVID-19) • CT imaging • X-Ray • Big data analytics • H 2 O • Deep learning technique • Generative adversarial networks (GAN) • Convolutional neural networks (CNNs)

show abstract

A partitioning framework for Cassandra NoSQL database using Rendezvous hashing

Cited by 12 publications

References 22 publications

Application of Dynamic Fragmentation Methods in Multimedia Databases: A Review

Application of Dynamic Fragmentation Methods in Multimedia Databases: A Review

CAP Theorem: Revision of Its Related Consistency Models

An H2O’s Deep Learning-Inspired Model Based on Big Data Analytics for Coronavirus Disease (COVID-19) Diagnosis

Contact Info

Product

Resources

About