DataGuides: Enabling Query Formulation and Optimization in Semistructured Databases
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
XMark: a benchmark for XML data management
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Parallelization of XPath queries using multi-core processors: challenges and experiences
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Generating efficient execution plans for vertically partitioned XML databases
Proceedings of the VLDB Endowment
Partitioning XML documents for iterative queries
Proceedings of the 16th International Database Engineering & Applications Sysmposium
Partial Evaluation for Distributed XPath Query Processing and Beyond
ACM Transactions on Database Systems (TODS)
HadoopXML: a suite for parallel processing of massive XML data with multiple twig pattern queries
Proceedings of the 21st ACM international conference on Information and knowledge management
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In this demo we will showcase a research prototype for processing queries and updates on large XML documents. The prototype is based on the idea of statically and dynamically partitioning the input document, so to distribute the computing load among the machines of a Map/Reduce cluster. Attendees will be able to run predefined queries and updates on documents conforming to the XMark schema, as well as to submit their own queries and updates.