Large-scale Incremental Processing Using Distributed Transactions and Notifications

This is definitely worth reading:

Large-scale Incremental Processing Using Distributed Transactions and Notifications: “Updating an index of the web as documents are crawled requires continuously transforming a large repository of existing documents as new documents arrive. This task is one example of a class of data processing tasks that transform a large repository of data via small, independent mutations. These tasks lie in a gap between the capabilities of existing infrastructure. Databases do not meet the storage or throughput requirements of these tasks: Google’s indexing system stores tens of petabytes of data and processes billions of updates per day on thousands of machines. MapReduce and other batch-processing systems cannot process small updates individually as they rely on creating large batches for efficiency.

We have built Percolator, a system for incrementally processing updates to a large data set, and deployed it to create the Google web search index. By replacing a batch-based indexing system with an indexing system based on incremental processing using Percolator, we process the same number of documents per day, while reducing the average age of documents in Google search results by 50%. Links: [abstract] [pdf] [search]

(Via Recent Google Publications (Atom).)

I built an incremental indexer while at Feedster, albeit on a much smaller scale, we had a 10 minute turn around time for newly crawled stuff which wasn’t too shabby I think.



Open Source Search Conference

Just came across this on Steve Arnold’s weblogLucid Imagination is sponsoring an open source search conference in Boston, MA on October 7-8, 2010 at the Hyatt Harborside:

The first-ever conference focused on addressing the business and development aspects of open source search will take place October 7-8, 2010 at the Hyatt Harborside in Boston.

Dubbed Lucene Revolution due to the sponsor, Lucid Imagination, the commercial company dedicated to Apache Lucene technology. This inaugural event promises a full, forward-thinking agenda, creating opportunities for developers, technologists and business leaders to explore the benefits that open source enterprise search makes possible.

In addition to in-depth training provided by Lucid Imagination professionals, there will be two days of content rich talks and presentations by Lucene and Solr open source experts. Working on the program will be Stephen E. Arnold, author and consultant.

Those interested in learning more about the conference and submitting a proposal for a talk can navigate to The deadline for submissions is June 23, 2010. Individuals are encouraged to submit proposals for papers and talks that focus on categories including enterprise case studies, cloud-based deployment of Lucene/Solr, large-scale search, and data integration.

The Lucene Revolution conference comes just after success of sold-out Apache Lucene EuroCon 2010 in Prague, also sponsored by Lucid Imagination, the single largest gathering of open source search developers to date.

Need to Focus the Meaning of “NoSQL”

Great post by Adam Ferrari titled Let’s not let “NoSQL” go the way of “Web 2.0” on the new to focus the definition of “NoSQL” lest it turns into the term “Web 2.0” which has become pretty much meaningless since meaning everything:

As part of a team focused on enterprise-oriented information access problems, which are a different beast from wide area data stores, I don’t apply the “NoSQL” label to what we’re doing. At our core, we’re targeting different problem spaces. And I have a huge amount of respect for what the NoSQL movement is doing. For example, the work being done on consistency models like the Vogels paper I mentioned above is big league computer science that is making large contributions to the ways that technology can play bigger and more helpful roles in our lives. I’d just hate to see the “NoSQL” label go the way of “Web 2.0,” a moniker that rapidly came to mean everything and so nothing at all.

MapReduce Book Draft

This is well worth taking a look at if you are interested in MapReduce/Hadoop and IR:

An updated draft of the upcoming book, Data-Intensive Text Processing with MapReduce by Jimmy Lin and Chris Dyer is available.

The book isn’t finished, but it still has interesting material. It emphasizes algorithms for processing text with Mapreduce: co-occurrence analysis, inverted index construction, and the EM algorithm applied to estimating parameters in HMMs.

You can also see Jimmy’s cloud computing course (spring 2010) and the Ivory search engine.

Cloud Platform Choices

Good article over on ArsTechnica about Cloud Platform Choices, well worth reading if for no other reason than to keep up with what is going on in that space:

Cloud computing is one of the most hyped technology concepts in recent memory, and, like many buzzwords, the term “cloud” is overloaded and overused. A while back Ars ran an article attempting to clear some of the confusion by reviewing the cloud’s hardware underpinnings and giving it a proper definition, and in this article I’ll flesh out that picture on the software side by offering a brief tour of the cloud platform options available to development teams today. I’ll also discuss these options’ key strengths and weaknesses, and I’ll conclude with some thoughts about the kinds of advances we can expect in the near term. In all, though, it’s important to keep in mind that what’s presented here is just a snapshot. The cloud is evolving very rapidly—critical features that seem to be missing today may be standard a year from now.

Why The Name NoSQL Is Meaningless (To Me)

The ‘NoSQL’ movement has gotten quite popular lately and with good reason, it is breaking new ground on distributed, scalable storage.

But the name ‘NoSQL’ really bugs me, because SQL is just a query language, it is not a storage technology. This is well illustrated in “InnoDB is a NoSQL database”, which I will quote below:

As long as the whole world is chasing this meaningless “NoSQL” buzzword, we should recognize that InnoDB is usable as an embedded database without an SQL interface. Hence, it is as much of a NoSQL database as anything else labeled with that term. And I might add, it is fast, reliable, and extremely well-tested in the real world. How many NoSQL databases have protection against partial page writes, for example?

It so happens that you can slap an SQL front-end on it, if you want: MySQL.

Another thing, it is probably better to say what you are for rather than what you are against, much more constructive. Time to get a new name/acronym I think.

Updated December 18th, 2009 – I am seeing that NoSQL is being renamed to mean Not Only SQL, which I think is much better.

exit() Rather Than free()

I have to admit that I had a bit of a reaction to this post, apologies for quoting more than 50% of the post here but here goes:

See, developers are perfectionists, and their perfectionism also includes the crazy idea that all memory has to be deallocated at server shutdown, as otherwise Valgrind and other tools will complain that someone leaked memory. Developers will write expensive code in shutdown routines that will traverse every memory structure and deallocate/free() it.

Now, guess what would happen if they wouldn’t write all this expensive memory deallocation code.

Still guessing?

OS would do it for them, much much much faster, without blocking the shutdown for minutes or using excessive amounts of CPU. \o/

I am really uncomfortable with the approach of using free() for memory cleanup for the obvious reason that it is usually much, much cheaper to keep a process running than to shut it down and restart it on a regular basis. The other reason is that to rely on free() for memory cleanup is just poor hygiene.

Reminds me of the days of SunOS where common wisdom said that restarting a server once a week was a good idea to keep the memory leaks in check.