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  • The Avengers

    Almer S. Tigelaar 11 / 05 / 2012

    Marvel teased us with the release of this film near the end of various previously released super hero flicks like Captain America and Iron Man 2. This would be the movie that unites all the super heroes from the Marvel universe. Well actually, only those that had not been previously licensed to other studios. Hence, you will not find characters from X-Men, Spiderman, or the Fantastic Four in this movie. Director Joss Whedon brings back fond memories of creative television series like Firefly and Dollhouse, but what does he make of a 220 million blockbuster production?

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  • Hugo

    Almer S. Tigelaar 06 / 03 / 2012

    Hugo is based on a relatively recently released (2007) award winning book by Brian Selznick. It is not surprising that the film rights to the books were quickly sold, and certainly not by the least of directors either: Martin Scorsese. He has a career spanning decades and has directed a string of movies in recent years which I liked, among which are Shutter Island, The Departed and Gangs of New York. However, those were admittedly all in different, less family friendly, genres. So, I went to Hugo hoping to be pleasantly surprised.

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  • How long would it take to read Wikipedia?

    Almer S. Tigelaar 21 / 02 / 2012

    Wikipedia has become the de facto encyclopedia on the Internet. A traditional encyclopedia spans many textbook volumes which would take any normal person ages to read. Few people would likely engage in such an endeavor. However, since Wikipedia is readily accessible: should you take up the challenge?

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Almer S. Tigelaar » Graduation Committees

Koen Lavooij: Near-real Time Statistics Gathered from a Continuous and Voluminous Data Mutation Stream

Almer S. Tigelaar 17 / 02 / 2010, 15:45

Near-real Time Statistics Gathered from a Continuous and Voluminous Data Mutation Stream
by Koen Lavooij

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Abstract
The amount of digital data is growing fast. Providing that information as a service is not enough, with the amount of information available. To support the users in finding information, supporting systems have been developed to extract specific information from a large amount of stored data.

Finding or extracting interesting information is as least as important as providing the original data. The “collective intelligence? of a large number of users can be used to order the information. The ordered information is of much greater value when compared to the unordered information, because it provides the user with an overview of interesting and less interesting information.
Current database systems are not able to provide ranked information by analyzing a massive amount of user feedback (e.g. clicks) within a short period of time. Therefore, the systems update the answers periodically.

In this thesis, a Stream Processing Engine (SPE) is being adapted. The modified SPE accepts a stream of mutations to a virtual data storage as opposed a stream of tuples. The newly created system exploits the properties of statistical functions in order to efficiently aggregate live statistics over a large stream of mutations.
The newly created system is able to provide answers to a small set of continuous queries. The answers to the queries will be continuously maintained, instead of recalculated. Therefore, the system is able to provide the answers to the continuous queries instantly and with low latency for a large number of users.

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