Revision Control with Arch: Maintenance and Advanced Use
Setting up mirrors before long disconnected sessions is a lot like packing for a trip: you always forget the one thing you really needed. It would be frustrating to plug your laptop in to the light socket of your mountain cabin only to find that your checked-out copy of some crucial code came from an HTTP archive.
Fortunately, you can use some of the same techniques to move a checked-out copy to a new branch even if you can't reach the old read-only archive.
Alice checked out a copy of a project called bar while sitting in an Internet café in Chicago. On her return trip to California, she decides to work on the code. After another hour of prodigious efforts, she decides yet again that it is time to make her own branch in which to work.
Because the original archive is inaccessible, tagging off a branch is impossible. Fortunately, much of the changelog and history information is present in the checked-out tree, so Alice temporarily backs out her changes with tla undo and then forces the checked-out copy into her new branch:
$ tla archive-setup bar--train-ride--1.0 $ tla set-tree-version bar--train-ride--1.0 $ tla add-log-version bar--train-ride--1.0 $ tla import
Once this is done, Alice runs tla redo and then tla commit. Now the revision she grabbed in Chicago is bar--train-ride--1.0--base-0, and her changes are bar--train-ride--1.0--patch-1.
Although this method is not perfect, it still is possible to star-merge to and from the original branch without trouble. If Alice found her work on the bar project to be more involved, she most likely would merge with the upstream archive and make a proper branch when she found Internet access again.
You now know how to publish your archives to the Internet and how to work remotely with Arch. You even have a few tricks up your sleeve for when you make mistakes,
The third and final article in this series will show you how to administer a centralized official archive while retaining all of the benefits of Arch's distributed workings. You'll learn some tricks for scripting around your archives to create reports on development activity, as well as the creation of a test build infrastructure.
Nick Moffitt is a Linux professional living in the San Francisco Bay Area. He is the build engineer for the LNX-BBC Bootable Business Card distribution of GNU/Linux and the author of the GAR build system. When not hacking, he studies the history of urban public transportation.
Practical Task Scheduling Deployment
July 20, 2016 12:00 pm CDT
One of the best things about the UNIX environment (aside from being stable and efficient) is the vast array of software tools available to help you do your job. Traditionally, a UNIX tool does only one thing, but does that one thing very well. For example, grep is very easy to use and can search vast amounts of data quickly. The find tool can find a particular file or files based on all kinds of criteria. It's pretty easy to string these tools together to build even more powerful tools, such as a tool that finds all of the .log files in the /home directory and searches each one for a particular entry. This erector-set mentality allows UNIX system administrators to seem to always have the right tool for the job.
Cron traditionally has been considered another such a tool for job scheduling, but is it enough? This webinar considers that very question. The first part builds on a previous Geek Guide, Beyond Cron, and briefly describes how to know when it might be time to consider upgrading your job scheduling infrastructure. The second part presents an actual planning and implementation framework.
Join Linux Journal's Mike Diehl and Pat Cameron of Help Systems.
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With all the industry talk about the benefits of Linux on Power and all the performance advantages offered by its open architecture, you may be considering a move in that direction. If you are thinking about analytics, big data and cloud computing, you would be right to evaluate Power. The idea of using commodity x86 hardware and replacing it every three years is an outdated cost model. It doesn’t consider the total cost of ownership, and it doesn’t consider the advantage of real processing power, high-availability and multithreading like a demon.
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