After much trial and error, I was finally able to capture a video of our Didget Browser in action. The video was limited to only 5 minutes, so I had to move fast and could only show a few features, but it gives a good demonstration of the speed at which we can query any given Chamber populated with lots of Didgets.
You can watch the video at: www.screenr.com/XV17
The Didget Browser was running on a Windows 7 PC and was created using the open-source, cross-platform GUI library called Qt. It can easily be ported to the Linux and Mac OSX operating systems. It sits on top of our Didget Management System using its API to perform much of its work.
The PC I used was a 3 year old Gateway machine I bought at Costco for $500. It has an Intel Core 2 processor, 4 GB of DDR2 RAM, and a 750 GB HDD. This was not a high-end box even when I bought it, let alone now. If you are impressed with the speed at which we are able to perform queries and to display large lists of tag values, please keep in mind it is NOT due to speedy hardware.
Whenever we perform a query, we look at the metadata records for each Didget within the Chamber. This would be analogous to checking each iNode in an Ext3 file system when querying files. The same is true whenever we refresh the contents of the Status Tab. We look at each and every Didget metadata record and tally up a total of all the different categories displayed.
It is important to know that we do not have a separate database that we are querying like indexing services such as Apple's Spotlight or Microsoft's Windows Search do. Such databases can take hours to create and can easily become out of sync with the file metadata that they index.
Some of the query operations that we perform could be accomplished on a regular file system using command line utilities. For example, I can get a list of all .JPG files on my file system by entering the command:
C:>Dir *.jpg /s
The main difference is that on that same machine with the 500,000 files, this command takes nearly 3 minutes to complete. If my NTFS volume had 3 million files on it, the same command would take approximately 20 minutes to complete. Using the Didget Browser, we are able to accomplish the same task in under ONE second. In fact, we can get a list of all the JPG Photo Didgets in under one second even if there are 25 million of them.
The differences in speed between our system and conventional file systems is even more pronounced when we must do even more complicated queries. Try to find all .JPG photos in a file system that have two extended attributes attached with the key:values of Place=Hawaii and Event=Vacation. We can find all the Didgets with those two tags attached in just a couple of seconds. File systems (the ones that even support extended attributes) will require a very long time.