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Transcript of Do you queue
Do you queue? Characteristics of scalabilityKevin Schroeder
Technology Evangelist
Zend Technologies
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• Kevin Schroeder Technology Evangelist for Zend
Programmer
Sys Admin
Author• IBM i Programmer’s Guide to PHP
• You want to do WHAT with PHP?
Race Ferraris on the weekend• My Honda has a dismal win record
About me
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I blog at eschrade.com
Follow us!(good things will happen to you)
Zend Technologies
http://twitter.com/zend
http://twitter.com/kpschrade (me!)
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Could your PHP apps benefit from being able to process data or execute
asynchronously?
Twtpoll results
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• Performance Execute logic apart from the main request (asynchronicity)
• Scalability The ability to handle non-immediate logic as resources are
available
Why would you want to queue?
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• People often say that performance and scalability are two completely different things.
This is inaccurate
• Performance is the speed by which a request is executed
• Scalability is the ability of that request to maintain its performance as load/infrastructure increases
Performance & Scalability
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• DON’T!!
• You are not Facebook
• You probably won’t be
• Don’t overcomplicate your problems by trying to be
So how do you scale to Facebook size?
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Typical anatomy of a PHP Application
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Presentation
Application Control
Database Access
Business Logic
Presentation
Application Control
Business Logic
Presentation
Bad for scala-bility!
9 | Apr 12, 2023
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Presentation
Database Access
Business Logic
Application Control
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Good for Scalabilit
y
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Defined tasks
Loose coupling
Resource discovery
What helps make software scalable?
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The Golden Rule of Scalability
“It can probably wait”
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• Pre-caching data
• Data analysis
• Data processing
• Pre-calculating (preparing data for the next request)
Data is “out of date” once it leaves the web server
Immediacy is seldom necessary
Asynchronous execution uses
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• A sledgehammer can hit a machine Scalability and High Availability are yin and yang
• A site that can’t keep running is not scalable
• A site that can’t scale will fail (if it gets really popular)
• Machines can be added and removed at will Not “cloudy” necessarily
• No single point of failure Data exists in at least two, preferably at least three, places
Characteristics
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• Waste disk space
• Control usage (don’t let users do anything they want)
• Pre-calculate as much as possible Calculate and cache/store
• Don’t scan large amounts of data
• Keep data processing off the front end servers
• Don’t just cache Don’t let it substitute for thought
Cache hit rates can be meaningless if you have hundreds of cache hits for a request
Considerations
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• Build a deployment mechanism with NO hardcoded values like directory or resource locations• Make as much as possible configurable/discoverable
• Decouple/Partition Don’t tie everything (relationships and such) into the
database
• Use queues/messaging Stomp interfaces are really good for PHP – Can also use
Java Bridge
Zend_Queue has several interfaces
• Try to use stateless interfaces (polling is more scalable than idle connections)
Considerations
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• Use Cron /w PHP CLI (probably shouldn’t do this)
• Use Gearman
• Use home-grown (don’t do this)
• Use pcntl_fork() (NEVER do this)
• Use Zend Server Job Queue
Options
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Gearman* Zend Server Job Queue
FreeLightweightOpen Source(mostly) language agnosticDistributed queuing
Ready to goIntegrates with Event MonitoringIntegrates with Code TracingRuns over a widely known protocolLoad distribution can be accomplished outside of the queue
Your only real options
* I am not an expert on Gearman. Corrections will be taken in the spirit that they are given.
Very cloud friendly
For obvious reasons, I will focus on Zend Server
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• Schedule jobs in the future
• Set recurring jobs
• Execute immediately, as resources are available (my fav)
• Utilize ZendJobQueue()
Using the Zend Server Job Queue
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Job Queue Architecture – Elastic Backend
Users!
Web Server /w
JQ
Web Server /w
JQ
Web Server /w
JQ
Web Server
Web Server
Web Server
Load B
ala
nce
r
• Pros Scale the backend as necessary
Default (easy) mechanism
• Cons Getting the job status requires using a DB
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Job Queue Architecture – Elastic Frontend
Users!
Web Server
Web Server
Web Server
Web Server /w
JQ
Web Server /w
JQ
Web Server /w
JQ
Load B
ala
nce
r
• Pros• Easy to communicate with the Job Queue server handling the job
Cons• Requires you to build your own interface
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• Create a task-handling controller
• Create an abstract task class Understands the Job Queue
Self contained• If Elastic Backend: connects to localhost
• If Elastic Frontend: connects to load balancer (my preferred), load balanced JQ servers manage themselves
• Execute the task, have it serialize itself and send it to send to the task handler
Kevin’s favorite way to implement it
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Q_Manager
Handles connecting to the queue and passing results back and forth
Q_JobAbstract
Abstract class that a job would be based off of
Q_Response
The response from the manager when a job is queued. Contains the server name and job number
Job_Scandir
The actual job that scans the directory
Job_ScandirResult
An object that represents the data found
Classes involved in the demo
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Create job and set data
Execute job• Job passes itself to the queue manager
• Manager serializes job
• Manager uses HTTP call through a load balancer to queue the job
• The queue on the other end returns the job id and server name
• Job ID and server name is passed to the client
Client polls the manager to get a completed job• When the job is returned pass the serialized version of the
executed job
Execution Flow
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Let’s write some code
(no I’m not copping out with slides. We’re all told to show our work in grade scool)
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Follow us!
Zend Technologies
http://twitter.com/zend
http://twitter.com/kpschrade (me!)
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Get this information and all the examples at eschrade.com…