Linux Journal Contents #87, July 2001
Linux Journal Issue #87/July 2001
Features
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Focus: Program Development
by Don Marti
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Debugging Memory on Linux
by Petr Sorfa
Sorfa provides some examples of multiple debugging methods.
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CVS: An Introduction
by Ralph Krause
Krause explains the workings and uses of this version control system.
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Create User Interfaces with Glade
by Mitch Chapman
Discover the joys of creating GUI apps with Glade and Python—Chapman shows us how.
Indepth
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Automating Firewall Log Scanning
by Leo Liberti
Liberti gives some clues for increasing security and saving time by automating log scanning.
Toolbox
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At the Forge Custom JSP Actions
by Reuven M. Lerner
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Cooking with Linux Programming Silence OUT!
by Marcel Gagné
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Paranoid Penguin Intrusion Detection for the Masses
by Mick Bauer
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GFX Linux at NAB
by Robin Rowe
Columns
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Linux in Education: Integrating a Linux Cluster into a Production High Performance Computing Environment
by Troy Baer
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Linux for Suits Whose Hand Is That in Your Pocket?
by Doc Searls
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Focus on Embedded Systems Linux at the Embedded Systems Conference
by Rick Lehrbaum
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Geek Law: Copyright Confusion
by Lawrence Rosen
Reviews
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KDevelop 1.4
by Petr Sorfa
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Catching up with KDE
by Robert Flemming
Departments
Strictly On-Line
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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| Designing Electronics with Linux | May 22, 2013 |
| Dynamic DNS—an Object Lesson in Problem Solving | May 21, 2013 |
| Using Salt Stack and Vagrant for Drupal Development | May 20, 2013 |
| Making Linux and Android Get Along (It's Not as Hard as It Sounds) | May 16, 2013 |
| Drupal Is a Framework: Why Everyone Needs to Understand This | May 15, 2013 |
| Home, My Backup Data Center | May 13, 2013 |
- Linux Systems Administrator
- New Products
- Senior Perl Developer
- Technical Support Rep
- UX Designer
- Web & UI Developer (JavaScript & j Query)
- Designing Electronics with Linux
- Dynamic DNS—an Object Lesson in Problem Solving
- Using Salt Stack and Vagrant for Drupal Development
- Making Linux and Android Get Along (It's Not as Hard as It Sounds)
Enter to Win an Adafruit Pi Cobbler Breakout Kit for Raspberry Pi

It's Raspberry Pi month at Linux Journal. Each week in May, Adafruit will be giving away a Pi-related prize to a lucky, randomly drawn LJ reader. Winners will be announced weekly.
Fill out the fields below to enter to win this week's prize-- a Pi Cobbler Breakout Kit for Raspberry Pi.
Congratulations to our winners so far:
- 5-8-13, Pi Starter Pack: Jack Davis
- 5-15-13, Pi Model B 512MB RAM: Patrick Dunn
- 5-21-13, Prototyping Pi Plate Kit: Philip Kirby
- Next winner announced on 5-27-13!
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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