Updating the Pre/Post Plane in monetdb/xquery
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monetdb/xquery and the Pathfinder compiler are available in open-source: http:// monetdb.cwi.nl lar encoding used in monetdb/xquery, maps all document
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Updating the Pre/Post Plane in MonetDB/XQuery
Peter Boncz Stefan Manegold Jan Rittinger∗
University of Konstanz P.O. Box D 188 Konstanz, Germany CWI Kruislaan 413 Amsterdam, The Netherlands
{boncz,manegold}@cwi.nl
rittinge@inf.uni-konstanz.de
ABSTRACT
We outline an efficient ACID-compliant mechanism for structural inserts and deletes in relational XML document storage that uses a region based pre/size/level encoding (equivalent to the pre/post encoding). Updates to such node-numbering schemes are considered prohibitive (i.e. physical cost linear to document size), because structural updates cause shifts in all pre-numbers after the update point, and require updates of the size of all ancestors, such that the root of the tree becomes a locking bottleneck. We show how such locking can be avoided by updating the size of ancestors using deltaincrements, which are transaction-commutative operations. We also reduce the physical cost to the minimum (i.e. linear to update volume) by carefully exploiting the virtual column feature of MonetDB to store pre numbers (virtual columns are never materialized, and thus need not be updated). In our evaluation, we show the overhead of the update-feature in MonetDB/XQuery in terms of added XMark evaluation cost to stay within an acceptable limit (<30% on average).
1. INTRODUCTION
The MonetDB/XQuery system1 , allows to store schemafree XML documents in MonetDB and query them with XQuery. Figure 1 shows the system to consist of the Pathfinder XQuery-to-Relational Algebra compiler [5], and a small set of relational algebra extensions. Here, Pathfinder generates physical plans in MIL, the physical algebra on the binary relational model implemented by MonetDB [1]. Pathfinder currently supports almost the full XQuery standard, closely following the W3C Formal Semantics. MonetDB/XQuery is the first relational XQuery system we are aware of that fully supports both document and sequence order, XML schemas, and even recursive user-defined functions. MonetDB/XQuery also provides unsurpassed performance and
Work was supported by the DFG Research Training Group GK-1042 Explorative Analysis and Visualization of large Information Spaces. 1 MonetDB/XQuery and the Pathfinder compiler are available in open-source: http://monetdb.cwi.nl & http://pathfinder-xquery.org.
∗
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission of the authors. Informal Proceedings of the Second International Workshop
on XQuery Implementation, Experience, and Perspectives (XIME-P), June 16-17, 2005, Baltimore, MD, USA..
scalability: the combination of efficient nested XPath axis evaluation with loop-lifted staircase join, algebraic order optimizations, and join expression translation and optimization into relational join plans, allows it to e.g. obtain interactive response times on all XMark queries even for the 1 GB document size on a standard PC [2]. When comparing XML XQuery Pathfinder Compiler database solutions with − XQuery Parsing Client XQuery file-based management − Normalization − XML Schema Import of XML documents, − Core Generation − Core Simplification however, fast query XML − Type Checking performance is only − Core Optimization − MIL Generation one side of the story. MIL The main other reason Pathfinder Runtime Module MonetDB why XML databases − (Loop−lifted) Staircase Join Server are to be preferred over − XML Serialization − XML Shredding file-based XML document management, is MonetDB Kernel update support. FileFigure 1: MonetDB/XQuery based XML storage Architecture causes a full re-write of the entire document on each change, and does not provide any concurrency. Therefore, efficient and ACID-compliant XML document update functionality is an important selling point of XML database technology. Sticking to our approach of using relational technology to provide XML database functionality, the challenge of this paper is to map XML update requests, as formulated in a language like XUpdate [10], into update actions on the underlying relational XML document encoding. The particular encoding used in MonetDB/XQuery, maps all document nodes onto pre/post tuples (explained in Section 2.2). This XML document representation is exploited to full advantage when evaluating XPath steps efficiently, enabling cheap node order tests as well as significant positional node skipping in staircase join [6]. However, the naive implementation of this encoding poses two update performance challenges: (i) high physical update cost, and (ii) low granularity of transaction locking. Because of this, the pre/post plane is currently perceived to be a read-only representation of XML documents. The main contribution of this paper is to show that both challenges can actually be met, converting the pre/post plane into a suitable representation to implement dynamic updates that are both efficient and allow concurrency. In the evaluation, we show that the overhead of our update scheme on large instances of the XMark benchmark (up to 1.1 GB) is limited to about 30%, such that even under updates, MonetDB/XQuery is still highly efficient and scalable.
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