Performance Evaluation of MongoDB on Amazon Web Service and OpenStack
2018 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE credits
Student thesis
Abstract [en]
Context
MongoDB is an open-source, scalable, NoSQL database that distributes the data over many commodity servers. It provides no single point of failure by copying and storing the data in different locations. MongoDB uses a master-slave design rather than the ring topology used by Cassandra. Virtualization is the technique used for accessing multiple machines in a single host and utilizing the various virtual machines. It is the fundamental technology, which allows cloud computing to provide resource sharing among the users.
Objectives
Studying and identifying MongoDB, Virtualization on AWS and OpenStack. Experiments were conducted to identify the CPU utilization associated when Mongo DB instances are deployed on AWS and physical server arrangement. Understanding the effect of Replication in the Mongo DB instances and its effect on MongoDB concerning throughput, CPU utilization and latency.
Methods
Initially, a literature review is conducted to design the experiment with the mentioned problems. A three node MongoDB cluster runs on Amazon EC2 and OpenStack Nova with Ubuntu 16.04 LTS as an operating system. Latency, throughput and CPU utilization were measured using this setup. This procedure was repeated for five nodes MongoDB cluster and three nodes production cluster with six types of workloads of YCSB.
Results
Virtualization overhead has been identified in terms of CPU utilization and the effects of virtualization on MongoDB are found out in terms of CPU utilization, latency and throughput.
Conclusions
It is concluded that there is a decrease in latency and increases throughput with the increase in nodes. Due to replication, increase in latency was observed.
Place, publisher, year, edition, pages
2018.
Keywords [en]
MongoDB, Virtualization, performance evaluation, AWS, OpenStack
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:bth-16856OAI: oai:DiVA.org:bth-16856DiVA, id: diva2:1238384
Subject / course
DV2572 Master´s Thesis in Computer Science
Educational program
DVADA Master Qualification Plan in Computer Science
Presentation
2018-05-30, J1620, Blekinge Institute of Technology, Karlskrona, 09:00 (English)
Supervisors
Examiners
2018-08-152018-08-132019-08-05Bibliographically approved