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Google Caffeine Drops MapReduce, Adds "Colossus"
An anonymous reader writes "With its new Caffeine search indexing system, Google has moved away from its MapReduce distributed number crunching platform in favor of a setup that mirrors database programming. The index is stored in Google's BigTable distributed database, and Caffeine allows for incremental changes to the database itself. The system also uses an update to the Google File System codenamed 'Colossus.'"
No, that's not it.
MapReduce is a sequence of batch operations, and generally, Lipkovits explains, you can't start your next phase of operations until you finish the first. It suffers from "stragglers," he says. If you want to build a system that's based on series of map-reduces, there's a certain probability that something will go wrong, and this gets larger as you increase the number of operations. "You can't do anything that takes a relatively short amount of time," Lipkovitz says, "so we got rid of it."
"[The new framework is] completely incremental," he says. When a new page is crawled, Google can update its index with the necessarily changes rather than rebuilding the whole thing.
There are still cases where Caffeine uses batch processing, and MapReduce is still the basis for myriad other Google services. But prior the arrival of Caffeine, the indexing system was Google's largest MapReduce application, so use of the platform has been significantly, well, reduced.
They're not still using MapReduce for the index. It's still supported in the framework for secondary computations where appropriate, and it's still used in some other Google services, but it's been straight-up replaced for the index. Colossus is not a new improved version of MapReduce, it's a completely different approach to maintaining the index.
Sorry, Colossus is the file system. Caffeine is the new computational framework.
I made the same error in several posts now...but Slashdot doesn't support editing. Oh well! Everyone reads the entire thread, right?
Colossus is also the name of the computers Bletchley Park used to crack the German Lorenz cipher.
http://en.wikipedia.org/wiki/Colossus_computer
Yes and no. With MapReduce, they were hitting Amdahl's Law. The speed limit of any concurrent system is defined by the speed of the slowest serial component. This is why IBM still makes money selling very fast POWER CPUs, when you can get the same speed on paper from a couple of much cheaper chips.
The old algorithm (massive oversimplifications follow) worked by indexing a small part of the web on each node, building a small index, and then combining them all in the last step. Think of a concurrent mergesort or quicksort - the design was (very broadly) similar.
The problem with this was that the final step was the one that updated the index. If one of the nodes failed and needed restarting, or was slow due to the CPU fan failing and the processor down-clocking itself, the entire job was delayed. The final step was largely serial (although it was actually done as a series of hierarchical merges) so this also suffered from scalability problems.
The new approach runs the partial indexing steps independently. Rather than having a separate step to merge them all, each one is responsible for merging itself into the database. This means that if indexing slashdot.org takes longer than expected then this just delays updates for slashdot.org, it doesn't delay the entire index update.
The jab at Microsoft in the El Reg article is particularly funny, because Google is now moving from a programming model created at MIT's AI labs to one very similar to the model created at Microsoft Research's Cambridge lab, in collaboration with Glasgow University.
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Hmmm. Bing has it, too - both hits I got on Google, I got there, as well.
http://www.bing.com/search?q=%22This+is+why+things+show+up+in+Google+days,+sometimes+weeks+ahead+of+the+other+search+engines%22&go=&form=QBLH&qs=n&sk=