To run AMD, you simply type amd at the prompt, providing the mount point(s) amd the map(s) on the command line. For example, if the map in listing 1 is named /etc/map.main, and a map named /etc/map.silly also exists, to execute AMD you would type:
amd /u /etc/map.main /silly /etc/map.silly
It is a good idea to include this statement in your rc files.
A number of options are available for the amd command. Two useful options are the ability to specify the NFS mount points and the timeout period. The program amq helps control AMD. For example, amq can force AMD to unmount a file system and to flush the cache (useful when debugging NFS problems). The man page for amq provides a complete description of all its capabilities.
Because AMD is just a front end to regular NFS, you have to worry about the same issues that you would when running NFS alone—you must ensure that exports and their options are correct. Explaining NFS is beyond the scope of this article; however, if you are unfamiliar with the basics of NFS, see the NFS Resources box on page FIXME.
Binaries and patches to port AMD to Linux may be obtained from sunsite and other sources (see sidebar). AMD has stayed relatively stable and bug free in the last few years; development is no longer active. AMD comes with excellent documentation.
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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
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- Next winner announced on 5-27-13!
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?