ACM Computing Surveys (CSUR)
The state of the art in distributed query processing
ACM Computing Surveys (CSUR)
Volcano— An Extensible and Parallel Query Evaluation System
IEEE Transactions on Knowledge and Data Engineering
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
A survey of peer-to-peer content distribution technologies
ACM Computing Surveys (CSUR)
A taxonomy of Data Grids for distributed data sharing, management, and processing
ACM Computing Surveys (CSUR)
Interpreting the data: Parallel analysis with Sawzall
Scientific Programming - Dynamic Grids and Worldwide Computing
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Neptune: scalable replication management and programming support for cluster-based network services
USITS'01 Proceedings of the 3rd conference on USENIX Symposium on Internet Technologies and Systems - Volume 3
Dryad: distributed data-parallel programs from sequential building blocks
Proceedings of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems 2007
Bigtable: a distributed storage system for structured data
OSDI '06 Proceedings of the 7th symposium on Operating systems design and implementation
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Click-stream data warehousing has emerged as a monumental information management and processing challenge for commercial enterprises. Traditional solutions based on commercial DBMS technology often suffer from poor scalability and large processing latencies. One of the main problems is that click-stream data is inherently collected in a distributed manner, but in general these distributed click-stream logs are collated and pushed upstream in a centralized database storage repository, creating storage bottlenecks. In this paper, we propose a design of an ad-hoc retrieval system suitable for click-stream data warehouses, in which the data remains distributed and database queries are rewritten to be executed against the distributed data. The query rewrite does not involve any centralized control and is therefore highly scalable. The elimination of centralized control is achieved by supporting a restricted subset of SQL, which is sufficient for most click-stream data analysis. Evaluations conducted using both synthetic and real data establish the viability of this approach.