Post on 11-Aug-2020
COMP9321 Web Application Engineering
Improving Performance
1 COMP9321, 16s1, Week 10
http://webapps.cse.unsw.edu.au/webcms2/course/index.php?cid=2442
Dr. Basem Suleiman
Service Oriented Computing Group, CSE, UNSW Australia
Semester 1, 2016, Week 10
Review…
Performance
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Performance
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Scalability
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Why does performance and scalability matter ?
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Architectural Considerations
(Network)
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Architectural Considerations - Network
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http://www.cs.cornell.edu/courses/cs519
Architectural Considerations - Network
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https://devcentral.f5.com
Architectural Considerations - Network
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By Kanoha - Own work, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=7868809
Content Delivery (or Distribution) Network (CDN): an interconnected series of
servers that cache, store, and distribute web content to end-users simultaneously
based on their proximity (geographical distribution)
Single server distribution CDN scheme of distribution
Architectural Considerations - Network
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http://www.cdnreviews.com/what-is-cdn/
Content Delivery (or Distribution) Network (CDN): an interconnected series of
servers that cache, store, and distribute web content to end-users simultaneously
based on their proximity (geographical distribution)
Architectural Considerations
(Servers)
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Architectural Considerations - Server
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Architectural Considerations - Server
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Architectural Considerations - Server
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General Techniques for Improving
Performance and Scalability
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General Techniques for Improving Performance and Scalability
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1. Caching and Replication
2. Parallelism
3. Redundancy
4. Asynchrony
5. Resource Pooling
General Techniques for Improving Performance and Scalability
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1. Caching and Replication
General Techniques for Improving Performance and Scalability
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2. Parallelism
More on implementing multi-thread applications in Java https://docs.oracle.com/javase/tutorial/collections/streams/parallelism.html
General Techniques for Improving Performance and Scalability
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3. Redundancy
General Techniques for Improving Performance and Scalability
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4. Asynchrony
General Techniques for Improving Performance and Scalability
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5. Resource Pooling
Improving Performance using HTTP features
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Improving Performance using HTTP features
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Improving Performance using HTTP features
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Improving Performance using HTTP features
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Improving Performance using HTTP features
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Improving Performance using HTTP features
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Improving Performance using HTTP features
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Improving Performance using HTTP features
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AJAX = Asynchronous JavaScript and XML
• Update a web page without reloading the page
• Request data from a server - after the page has loaded
• Receive data from a server - after the page has loaded
• Send data to a server - in the background
Improving Performance using HTTP features
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Improving Database Access
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Improving Database Access
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Improving Database Access
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Improving Database Access
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Improving Database Access
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Improving Database Access
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Improving Database Access
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Improving Database Access
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Improving Database Access
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Improving Database Access
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JOINT queries
Improving Database Access
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JOINT queries
Improving Database Access
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INSERT operation
Improving Database Access
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INSERT operation
Improving Database Access
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Improving Database Access
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Improving Database Access
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Characteristics of Scalability
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Characteristics of Scalability
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Characteristics of Scalability
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Characteristics of Scalability
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https://blog.twitter.com/2011/twitter-search-is-now-3x-faster
• Inefficiencies Twitter’s former Ruby-on-Rails front-end servers
• The front ends ran a fixed number of single-threaded rails worker
processes, each of which did the following:
• parsed queries
• queried index servers synchronously
• aggregated and rendered results
• The model of synchronous request processing uses Twitter’s CPUs
inefficiently
• Over time, significant technical debt in Ruby code base was accrued,
making it hard to add features and improve the reliability of our search
engine..
Characteristics of Scalability
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More details on the case study and the Blender implementation: https://blog.twitter.com/2011/twitter-search-is-now-3x-faster
Blender addresses these issues by:
• Creating a fully asynchronous aggregation service. No thread waits on
network I/O to complete
• Aggregating results from back-end services, for example, the real-time,
top tweet, and geo indices
• Elegantly dealing with dependencies between services. Workflows
automatically handle transitive dependencies between back-end services
Scaling and
Request Load Balancing
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Scaling & Request Load Balancing
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Types of Scaling:
Scaling & Request Load Balancing
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Types of Scaling:
Scaling & Request Load Balancing
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Request Load Balancing for Horizontal Scaling
Scaling & Request Load Balancing
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Request Load Balancing for Horizontal Scaling
Scaling & Request Load Balancing
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Scaling & Request Load Balancing
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Scaling & Request Load Balancing
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Scaling & Request Load Balancing
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Scaling & Request Load Balancing
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Scaling & Request Load Balancing
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Scaling & Request Load Balancing
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Application-Level Load Balancing with Stateless Logic
Scaling & Request Load Balancing
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Application-Level Load Balancing with Stateless Logic
Scaling & Request Load Balancing
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http://www.ibm.com/developerworks/java/library/j-jtp07294/index.html
Application-Level Load Balancing with Stateless Logic
Scaling & Request Load Balancing
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Scaling Databases - Replication
Scaling & Request Load Balancing
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Scaling Databases - Replication
Scaling & Request Load Balancing
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Scaling Databases - Replication
Scaling & Request Load Balancing
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Scaling Databases - Replication
Scaling & Request Load Balancing
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Scaling Databases - Replication
References
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• Building Scalable and High-performance Java Web Applications by Greg Barish,
Addison Wesley
• Building Scalable Web Sites by Cal Henderson, O’Reilly Books
• Gregor Roth, ”Server load balancing architectures”, JavaWorld, October 2008
• http: //www.javaworld.com/javaworld/jw-10-2008/jw-10-load-balancing-1.html
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