Regression based performance modeling and provisioning for NoSQL cloud databases

Farias, Victor A. E. de; Sousa, Flávio R. C.; Maia, José Gilvan Rodrigues; Gomes, João P. P.; Machado, Javam C.

doi:10.1016/j.future.2017.08.061

Cited by 16 publications

(8 citation statements)

References 12 publications

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“…Опубліковані результати показують, що залежно від сценарію використання, умов розгортання, використовуваного навантаження та налаштувань бази даних, будь-яка база даних NoSQL може перевершити інші за певними показниками. Однак треба відмітити [9][10][11], що існуючі наукові доробки як правило не враховують взаємозалежність між узгодженістю інформації та продуктивністю реплікованих нереляційних баз даних, а також не досліджують, як параметри узгодженості впливають на затримку виконання операцій читання та запису.…”

Section: вступunclassified

Research consistency and perfomance of nosql replicated databases

Karpenko¹,

Tarasyuk²,

Gorbenko³

2021

A.I.S.

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This paper evaluates performance of distributed fault-tolerant computer systems and replicated NoSQL databases and studies the impact of data consistency on performance and throughput on the example of a three-replicated Cassandra cluster. The paper presents results of heavy-load testing (benchmarking) of Cassandra cluster’s read and write performance which replicas were deployed on Amazon EC2 cloud. The presented quantitative results show how different consistency settings affect the performance of a Cassandra cluster under different workloads considering two deployment scenarios: when all cluster replicas are located in the sane data center, and when they are geographically distributed across different data centers (i.e. Amazon availability zones). We propose a new method of minimizing Cassandra response time while ensuring strong data consistency which is based on optimization of consistency settings depending on the current workload and the proportion between read and write operations.

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Section: вступunclassified

Research consistency and perfomance of nosql replicated databases

Karpenko¹,

Tarasyuk²,

Gorbenko³

2021

A.I.S.

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“…The cloud environment helps us in handling and storing these multiple data in the cloud. This storage is supported and the functionality is enhanced by NoSql [9] databases. The better processing is supported here, since more comfortable the data for storage, then more better the data are taken and processed for efficient usage.…”

Section: Related Workmentioning

confidence: 99%

“…Based on the model the evaluation is performed. The other trend is EHR [10], the Electronic Health Record. For the generation of EHR, the data are available from wearable devices and then stored for processing.…”

Section: Related Workmentioning

confidence: 99%

Semantic web service-based messaging framework for prediction of fitness data using Hadoop distributed file system

Sethuraman

Sasiprabha

2019

Automatika

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Big data is coined as word of mouth in this era due to the generation of huge volume of data every second from multiple sources like logs, web sources, and sensors, electrical and electronic devices. The manipulation is performed over the injected data and is termed as Data Processing Segment. In this proposed paper the data are obtained from the wearable devices with attributes like calories, weight, fat, step count, sleep, BMI and so on. The obtained data is stored in HDFS in a persistence manner. The component Kafka acts as a queue for the real time data and regulates the data before storing in HDFS. Now Apache Spark does the streaming of data. Here the data are cleaned, applied the Machine Learning Algorithms (KNN Classifier) to obtain the model, by splitting the cleaned data into Training data and Testing Data. Now the obtained predicted result is sent to Web service Telephony ontology, which in turns communicates with ontology service repository consisting of cloud telephony services ontology and fitness activity ontology through OWL API. The classified and predicted value is analysed and intimated to the users through visualization graphs, SMS, IVR and e-mail.

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“…The reported results show that depending on the use case scenario, deployment conditions, current workload and database settings any NoSQL database can outperform the others. Other recent related works, such as [11,12,13], investigate the measurement-based performance prediction of NoSQL data stores. However, the studies mentioned above, do not analyse an interdependency between consistency and performance, that is in the very nature of such distributed database systems and do not study how consistency settings affect database latency.…”

Section: Introductionmentioning

confidence: 99%

Interplaying Cassandra NoSQL Consistency and Performance: A Benchmarking Approach

Gorbenko

Romanovsky

Tarasyuk

2020

Communications in Computer and Information Science

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This experience report analyses performance of the Cassandra NoSQL database and studies the fundamental trade-off between data consistency and delays in distributed data storages. The primary focus is on investigating the interplay between the Cassandra performance (response time) and its consistency settings. The paper reports the results of the read and write performance benchmarking for a replicated Cassandra cluster, deployed in the Amazon EC2 Cloud. We present quantitative results showing how different consistency settings affect the Cassandra performance under different workloads. One of our main findings is that it is possible to minimize Cassandra delays and still guarantee the strong data consistency by optimal coordination of consistency settings for both read and write requests. Our experiments show that (i) strong consistency costs up to 25% of performance and (ii) the best setting for strong consistency depends on the ratio of read and write operations. Finally, we generalize our experience by proposing a benchmarking-based methodology for run-time optimization of consistency settings to achieve the maximum Cassandra performance and still guarantee the strong data consistency under mixed workloads.

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Regression based performance modeling and provisioning for NoSQL cloud databases

Cited by 16 publications

References 12 publications

Research consistency and perfomance of nosql replicated databases

Research consistency and perfomance of nosql replicated databases

Semantic web service-based messaging framework for prediction of fitness data using Hadoop distributed file system

Interplaying Cassandra NoSQL Consistency and Performance: A Benchmarking Approach

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