Linux Journal Contents #156, April 2007
Linux Journal Issue #156/April 2007
Features
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Single Packet Authorization
by Michael Rash
Want something better than port knocking?
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eCryptfs: a Stacked Cryptographic Filesystem
by Mike Halcrow
How does your filesystem security stack up?
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Multi-Category Security in SELinux in Fedora Core 5
by Russell Coker
Not in the military and still want SELinux?
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PacketFence
by Ludovic Marcotte and Dominik Gehl
An open-source solution to manage your security.
Indepth
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Need for Speed: PS3 Linux!
by Dave Taylor
It's a miracle; it's a dog.
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The OpenSSH Protocol under the Hood
by Girish Venkatachalam
What's SSH all about?
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Starting a Linux Firewall from Scratch
by Dinil Divakaran
How do you start using iptables?
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Time-Zone Processing with Asterisk, Part II
by Matthew Gast
What is a good time to call?
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Use Inkscape and XSLT to Create Cross-Platform Reports and Forms
by Chad Files
Dynamic forms using Inkscape with XSLT
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Extract and Parse ODF Files with Python
by Kamran Husain
Want to use Python to dissect an ODF file?
Columns
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Reuven Lerner's At the Forge
Dojo Events and Ajax
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Marcel Gagné's Cooking with Linux
Security for Your Data—It's Totally Mondo!
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Dave Taylor's Work the Shell
Displaying Image Directories in Apache
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Mick Bauer's Paranoid Penguin
Linux Firewalls for Everyone
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Jon maddog Hall's Beachhead
The Outer Banks
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Doc Searls' Linux for Suits
Why an iPhone When We Can Make Our Own OpenPhone?
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Nicholas Petreley's /var/opinion
Do Not Forget What People Fetch
Quick Takes
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MySQL Deserves a Double Take
by Reuven M. Lerner
In Every Issue
Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
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| Non-Linux FOSS: libnotify, OS X Style | Jun 18, 2013 |
| Containers—Not Virtual Machines—Are the Future Cloud | Jun 17, 2013 |
| Lock-Free Multi-Producer Multi-Consumer Queue on Ring Buffer | Jun 12, 2013 |
| Weechat, Irssi's Little Brother | Jun 11, 2013 |
| One Tail Just Isn't Enough | Jun 07, 2013 |
| Introduction to MapReduce with Hadoop on Linux | Jun 05, 2013 |
- Containers—Not Virtual Machines—Are the Future Cloud
- Non-Linux FOSS: libnotify, OS X Style
- Lock-Free Multi-Producer Multi-Consumer Queue on Ring Buffer
- Linux Systems Administrator
- RSS Feeds
- Introduction to MapReduce with Hadoop on Linux
- Validate an E-Mail Address with PHP, the Right Way
- New Products
- Weechat, Irssi's Little Brother
- Tech Tip: Really Simple HTTP Server with Python
Featured Jobs
| Linux Systems Administrator | Houston and Austin, Texas | Host Gator |
| Senior Perl Developer | Austin, Texas | Host Gator |
| Technical Support Rep | Houston and Austin, Texas | Host Gator |
| UX Designer | Austin, Texas | Host Gator |
| Web & UI Developer (JavaScript & j Query) | Austin, Texas | Host Gator |
Free Webinar: Hadoop
How to Build an Optimal Hadoop Cluster to Store and Maintain Unlimited Amounts of Data Using Microservers
Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
Some of key questions to be discussed are:
- What is the “typical” Hadoop cluster and what should be installed on the different machine types?
- Why should you consider the typical workload patterns when making your hardware decisions?
- Are all microservers created equal for Hadoop deployments?
- How do I plan for expansion if I require more compute, memory, storage or networking?




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