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| Author(s) |
Boncz, P., Grust, T., van Keulen, M., Manegold, S., Rittinger, J., Teubner, J. |
| Title |
MonetDB/XQuery: A fast XQuery processor powered by a relational engine |
| Abstract |
Relational XQuery systems try to reuse mature relational data management
infrastructures to create fast and scalable XML database
technology. This paper describes the main features, key contributions,
and lessons learned while implementing such a system. Its
architecture consists of (i) a range-based encoding of XML documents
into relational tables, (ii) a compilation technique that translates
XQuery into a basic relational algebra, (iii) a restricted (order)
property-aware peephole relational query optimization strategy,
and (iv) a mapping from XML update statements into relational
updates. Thus, this system implements all essential XML
database functionalities (rather than a single feature) such that we
can learn from the full consequences of our architectural decisions.
While implementing this system, we had to extend the state-of-theart
with a number of new technical contributions, such as looplifted
staircase join and efficient relational query evaluation strategies
for XQuery theta-joins with existential semantics. These contributions
as well as the architectural lessons learned are also deemed
valuable for other relational back-end engines. The performance
and scalability of the resulting system is evaluated on the XMark
benchmark up to data sizes of 11 GB. The performance section also
provides an extensive comparison of all major XMark results published
previously, which confirm that the goal of purely relational
XQuery processing, namely speed and scalability, was met. |
| Download |
BoGrke06.pdf |
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