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Instant Parallel Processing with Gearman
Instant Parallel Processing with Gearman
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1. Instant Parallel Processing with Gearman
So, what is Gearman?
Distinguishing features of Gearman
Overview of components
The conversation between the actors
Usecase – image processing
Quick Start – building your first components
Step 1 – running a server
Step 2 – downloading a client library
Your first client
Writing the client
Running your newly created client
Verifying that it was submitted
Step 3 – our first worker
Running your newly created worker
Step 4 – varying priorities
Step 5 – background tasks
And that's it
Top 5 features you need to know about
Job handling
Completed versus successful
Unique identifiers and coalescing
The client
The worker
Making it work
Scaling your system
Running multiple managers
Writing a client that supports multiple managers
Submitting jobs to multiple managers
Handling a manager being terminated
Processing jobs from multiple managers
MapReduce
The shared library
A simple program
The client
The worker
Parallelizing the pipeline
Scaling this solution
Processing a large data file
Providing job updates
Data updates
The worker
The client
Status updates
The worker
The client
Building a processing pipeline
Using multiple languages
Persistence engines
Why is this important?
Persistent versus non-persistent
How safe is safe?
People and places you should get to know
Client libraries
Community
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