ADT 2005 Lecture 10 Relational XQuery (Bomen, Bloemen

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ADT 2005Lecture 10Relational XQuery(Bomen,
Bloemen Tabellen)
Stefan Manegold Stefan.Manegold_at_cwi.nl http//www.
cwi.nl/manegold/
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XQuery Systems 2 Approaches

• Tree-based
• Tree is basic data structure
• Also on disk (if an XQuery DBMS)
• Navigational Approach
• Galax, Saxon, Flux, X-Hive, Tamino, eXist, ...
• Tree Algebra Approach
• TIMBER
• Relational
• Data shredded in relational tables
• XQuery translated into database query (e.g. SQL)

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The Challenge Comic Strip Finder

• Existing native XML/XQuery systems are built
  from scratch
• Galax, Saxon,
• X-Hive, Tamino,
• Re-inventing the wheel?
• Our approach
• Lets use the old rim, but make a new tyre
• Build XQuery system on top of an RDBMS
• Leverage mature relational technology
• to achieve efficient XQuery processing

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Architecture
Tyre
Rim
Steel
Aluminium
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Part I XML Storage in Relational Systems
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ltagt ltbgt ltcgt ltd/gt lte/gt lt/cgt
lt/bgt ltfgt ltg/gt lthgt lti/gt
ltj/gt lt/hgt lt/fgt lt/agt
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() post(v) pre(v) size(v) - level(v)
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pre(v) size(v)
post(v) - size(v)
() post(v) pre(v) size(v) - level(v)
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Replace pre / post by pre / size / level
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We replace pre / post by pre / size / level
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Part II Staircase Join Tree-Awareness for
Relational Systems
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Part III Beyond XPath XQuery on Relational
Systems
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Item Representation

• Item sequences, sequence order

Item
(10, x, lta/gt, 10) ?
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Iteration in XQuery Core
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Iteration in XQuery Core
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Loop Lifting
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Loop Lifting
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Loop Lifting
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Nested Scopes
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Nested Scopes
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Nested Scopes
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Nested Scopes
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Relating Scopes
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Evaluation in Scope S2
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Part IV MonetDB/XQuery
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European MonetDB/XQuery Team

• CWI, Amsterdam (Netherlands)
• Peter Boncz, Stefan Manegold, Sjoerd Mullender
• University of Twente (Netherlands)
• Maurice van Keulen, Jan Flokstra
• Technische Universität München (Germany)
• Torsten Grust, Jens Teubner, Jan Rittinger

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Architecture
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Science Research

• More research lead to more optimization
• Join Recognition
• Embedded XPath processing
• Order Awareness
• Various scientific publications

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Results Performance (1)
XMark benchmark, 110 MB MonetDB/XQuery vs.
X-Hive Galax
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Results Performance (2)
XMark benchmark, 1.1 GB MonetDB/XQuery vs.
X-Hive
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Results Scalability (3)

• Unsurpassed scalability
• Standard Opteron PC, 8GB RAM, 64-bit Linux
• Can process 11GB documents!
• Mostly linear scaling with document size

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Conclusions

• Relational approach
• Works
• Is fast
• Is scalable
• Crucial Optimizations
• Join recognition
• Embedded XPath processing
• Order awareness
• Research turned into open-source release

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Open Source Release References

• MonetDB Pathfinder on SourceForge
• Mozilla-like License
• MonetDB homepage
• http//monetdb.cwi.nl/
• Pathfinder homepage
• http//pathfinder-xquery.org/
• Developers website
• http//sf.net/projects/monetdb/

You are welcome to join the MonetDB/XQuery team!
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Part V Appendix
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