As you know, SIGMOD is ACM’s Special Interest Group on Management of Data. SIGMOD holds the annual conference that is regarded as one of the best conference in computer science. Besides, SIGMOD organizes a programming contest in parallel with the ACM SIGMOD conference. Below description is the call for the programming contest of this year. The programming contest’s subject of this year seems very interesting! The task is to implement a simple distributed query executor built on top of last year’s main-memory index. The environment on which contestants will test their implementation may be provided by Amazon. If you are interested in this programming contest, try that. You can get further information from here (
A programming contest is organized in parallel with the ACM SIGMOD 2010 conference, following the success of the first annual SIGMOD programming contest organized last year. Student teams from degree-granting institutions are invited to compete to develop a distributed query engine over relational data. Submissions will be judged on the overall performance of the system on a variety of workloads. A shortlist of finalists will be invited to present their implementation at the SIGMOD conference in June 2010 in Indianapolis, USA. The winning team, to be selected during the conference, will be awarded a prize of 5,000 USD and will be invited to a one-week research visit in Paris. The winning system, released in open source, will form a building block of a complete distributed database system which will be built over the years, throughout the programming contests.
ACM SIGMOD Conference 2009 was held in Providence, Rhode Island from June 29 through July 2. Then, the electronic proceedings are available online. Among many nice papers, I tried to choose some interesting papers as follows:
MapReduce & Hadoop
- “A Comparison of Approaches to Large Scale Data Analysis,” Andrew Pavlo, Samuel Madden, David DeWitt, Michael Stonebraker, Alexander Rasin, Erik Paulson, Lakshmikant Shrinivas and Daniel Abadi.
Some of the authors are members of vertica, a parallel database. Prof. Dwitt strongly attacked MapReduce (MapReduce: A major step backwards, MapReduce II). So, I wonder how did they benchmark both architectures.
- “Minimizing the Communication Cost for Continuous Skyline Maintenance,” Zhenjie Zhang, Reynold Cheng, Dimitris Papadias, Anthony K. H. Tung.
- “Scalable Skyline Computation Using Object-based Space Partitioning,” ZHANG Shiming, Nikos Mamoulis, David Cheung.
- “Kernel-Based Skyline Cardinality Estimation,” Zhenjie Zhang, Yin Yang, Ruichu Cai, Dimitris Papadias, Anthony and K. H. Tung.
Since I first met the skyline problem, I have been always interested in skyline queries. Considering multi-criteria, Skyline queries retrieve the best tuples among multi-dimensional objects.
Graph Query Processing
- “3-HOP: A High-Compression Indexing Scheme for Reachability Query,” Ruoming Jin, Yang Xiang, Ning Ruan, and Dave Fuhry.
Rechability query is to compute whether two given vertices are rechable, or not. Rechability query is one of the most fundamental operations in graph querying. it can be usually used in a primitive operation for complex graph queries.
RDF Query Processing
- “Scalable Join Processing on Very Large RDF Graphs,” Thomas Neumann and Gerhard Weikum.
The issue with which I’m primarily concerned is RDF query processing. As linked data are gaining attention, this issue will be more dealt with in the database community.
Spatial Query Processing
- “Quality and Efficiency in High Dimensional Nearest Neighbor Search,” Yufei Tao, Ke Yi, Cheng Sheng and Panos Kalnis.
- “Continuous Obstructed Nearest Neighbor Queries in Spatial Databases,” Yunjun Gao and Baihua Zheng.
- “A Revised R*-tree in Comparison with Related Index Structures,” Norbert Beckmann and Bernhard Seeger.
While I was taking M.S. program, I studied many spatial query processing issues. Hence, I try to keep in touch with recent spatial database issues.
They are seem to be very interesting. Later, I will post paper reviews about above papers.