My Open Source Debugging talk that I gave at JavaZone, Oslo, Norway last September is online and can be watched in Flash format or downloaded as an M4V file. If you were not able to catch this talk at either this venue, or any of the many NoFluffJustStuff.com stops that I gave this talk at last year, give it a try and let me know what you think of it.
When restoring from a backup, depending on the Mac-specific intelligence of your backup solution, or when copying files written by a 10.4 Mac, your Spotlight (Finder) Comments stored in the .DS_Store files might not survive the round trip. You’ll first notice this by the fact that your comments field or column is completely empty for files you know you previously tagged or made comments on.
Tiger and previous editions of Mac OSX store Spotlight comments in the .DS_Store file exclusively. Leopard and Snow Leopard on the other hand, claim to maintain backwards compatibility by storing the Spotlight Comments in both the .DS_Store and the new Extended File Attributes. I question this thinking though, because Mac OSX developer Steve Gehrman of the awesome PathFinder team says that Finder, while it writes both formats, still only reads back the .DS_Store ones. It seems to me that Apple would have changed Finder to read from the newer Extended Attributes as soon as they started writing to those in duplicate.
“On Mac OS X 10.4 Tiger, for example, .DS_Store files also contain the Spotlight comments of all the folder’s files, whereas Mac OS X 10.5 “Leopard” stores this information in Extended file attributes.”
Giving a tip of the hat to the similar-but-not-quite-what-I-wanted script that helped me get enough of the syntax working (using type alias instead of type file was tricky) get my own authored, I give you:
A MacOSXHints article, and the corresponding code
To solve this extended attributes vs. .DS_Store discrepancy, we only need to read (from the extended attributes) and reapply (thereby recreating the .DS_Store) the same comment. The solution is this AppleScript. Just highlight the files needing the treatment in Finder, then execute this script from the AppleScript Editor.
The result is that Finder (which reads only the .DS_Store files) and PathFinder (which only reads the extended attributes) can both now see the Spotlight Comments.
If you would like your Mac to automatically clean up the .DS_Store files it writes out to flash sticks and network drives, check out BlueHarvest, an interesting little utility app that fills this need.
Fonts, fonts, fonts. What’s this obsession? For those of us that share a passion for making presentation materials as comprehensible as possible for our students, sandwiched right between a great story and great delivery is a great font.
Once you’ve installed Microsoft Office, iWork, or Open Office, you’ll find that you’ve been granted a few (or possibly many) extra fonts installed into your operating system. This is a temptation you should approach carefully, just as you would the edge of a cliff. It is truly a time and design precipice you can fall off of into the abyss.
As you gradually approach this list of fonts, if you obsess over design like I do, you’ll let out an “Ooooooo” as if mesmerized by the quantity of selections you could make. A tool would be perfect here. Let me grant your wish with FontDoc for the Mac and WinFontsView for Windows.
Now, you have a tool to whittle that list of massive fonts down to size. Let me give you two facets that will chisel it down even further.
First, use a maximum of two Font Faces per presentation. I’ll allow for three if you make judicious use of a handwriting font.
One font should be interesting and story-relevant. It should mesh well with your photography and choice of color in the slides. I’d suggest you primarily use it for titles, strong statements and short phrases. It adds spice to your presentation. Feel the freedom to have fun with your title fonts. I’ve recently styled a presentation on Hadoop with an African theme. I used the Tribeca font in the title and custom rhinoceroses for the bullet points (yes, I used some bullets).
The second (primary) font should be highly legible. I can’t stress that enough. For the portions of your slide deck that people will need to read (and quickly, so they can return mental focus to you), readability is the critical point. I always suggest sticking with a very legible Sans Serif font, as does Garr Reynolds of Presentation Zen Design.
I don’t always obey this rule of Sans Serif in the body, sometimes to my own peril. Fortunately, local audiences in Denver are kind, and remind me that I need to change it back.
Hello Verdana. Really, I didn’t mean to cheat on you! It was just that Aquiline showed up looking so stylish and I just couldn’t help it.
The short list of Sans Serif fonts that I printed and put across the room is:
I’d suggest you do the same. Also put them up on a projector if you have access to one. Do white font on black. Do black font on white. Notice the affect each font’s nuances have on legibility. Throw up some ranking numbers next to each. That’s precisely what I did. And I asked a few folks to give me their rankings too.
The variant that I (and my scientifically font-polled friends) love the most, is Helvetica Neue. The beautiful part is that it comes preinstalled on many systems these days, but can also be purchased online if you are on a OS or office suite that doesn’t include it.
In the life of a font, you know you’ve arrived when a movie is made about you. Yes, a biographical movie about Helvetica, the font named after Switzerland’s classical name.
Lest you think this is a factor of Steve Jobs and his Apple design shop, I’ll let you in on the secret that this predates the personal computer by several decades. Max Miedinger was the designer behind this font all the way back in 1958!
Give any of these Sans Serif fonts a try (but lean towards Helvetica!) in your next presentation and be sure to gather design feedback from your audience. I think you’ll be pleasantly surprised!
Shameless plug: Keep an eye out in 2010 for the Presentation Patterns book from Neal Ford, Matthew McCullough and Nate Schutta for a complete recipe book with easily digestible presentation improvement hors d’oeuvres like this one.
I had the pleasure of hanging out with about 60 of my local friends at the Denver Java Users Group (DJUG to the locals) on Wednesday night and talking about Encryption on the JVM as well as Hadoop. I had the good fortune of having Andy Sautins of Returnpath.net, who’s an active user of Hadoop, field a few of the questions. I really appreciate the time a few of the folks spent giving me feedback on Speakerrate.com. For your future reference, below are the slides and sample source. Feedback and suggestions are always welcome at matthewm@ambientideas.com
Does your application transmit customer information? Are there fields of sensitive customer data stored in your DB? Can your application be used on insecure networks? If so, you need a working knowledge of encryption and how to leverage Open Source APIs and libraries to make securing your data as easy as possible. Encryption is quickly becoming a developer’s new frontier of responsibility in many data-centric applications.
In today’s data-sensitive and news-sensationalizing world, don’t become the next headline by an inadvertent release of private customer or company data. Secure your persisted, transmitted and in-memory data and learn the terminology you’ll need to navigate the ecosystem of symmetric and public/private key encryption.
Moore’s law has finally hit the wall and CPU speeds have actually decreased in the last few years. The industry is reacting with hardware with an ever-growing number of cores and software that can leverage “grids” of distributed, often commodity, computing resources. But how is a traditional Java developer supposed to easily take advantage of this revolution? The answer is the Apache Hadoop family of projects. Hadoop is a suite of Open Source APIs at the forefront of this grid computing revolution and is considered the absolute gold standard for the divide-and-conquer model of distributed problem crunching. The well-travelled Apache Hadoop framework is currently being leveraged in production by prominent names such as Yahoo, IBM, Amazon, Adobe, AOL, Facebook and Hulu just to name a few.
In this session, you’ll start by learning the vocabulary unique to the distributed computing space. Next, we’ll discover how to shape a problem and processing to fit the Hadoop MapReduce framework. We’ll then examine the incredible auto-replicating, redundant and self-healing HDFS filesystem. Finally, we’ll fire up several Hadoop nodes and watch our calculation process get devoured live by our Hadoop grid. At this talk’s conclusion, you’ll feel equipped to take on any massive data set and processing your employer can throw at you with absolute ease.