A%20Performance%20Evaluation%20of%20Alternative%20Mapping%20Schemes%20for%20Storing%20XML%20Data%20in%20a%20Relational%20Database

1
A Performance Evaluation of Alternative Mapping
Schemes for Storing XML Data in a Relational
Database

• By
• Daniela Floresu
• Donald Kossmann

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Table of Contents

• Introduction
• Approaches to Store Semi-Structured Data
• Data Model for Semi-Structured Data
• Query Language and XML-QL
• Storing XML Data in Relational Database
• Mapping Attributes
• Mapping Values
• Evaluating the Mapping Schemes
• Conclusion

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Introduction

• August 3, 1999
• How XML data can be stored and Queried
• Presented alternative Mapping Schemes to Store
  XML data
• Performance experiments that analyze the
  tradeoffs of the schemes

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Approaches to Store Semi-Structured Data

• Special Purpose Database System
• Examples are Lore, Rufus and Strudel
• Store and retrieve xml data, using specially
  designed structures and indices
• Object Oriented Database
• Example is O2 or Objectsore
• Rich data modeling capabilities of OODMS are
  exploited
• Standard Relational Database System
• Data is mapped in tables of a relational schema

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Data Model for Semi-Structured Data

• Characteristics of Semi-Structured Data
• Schema is not given in advance, may be implicit
• Schema is relatively large and may be changing
  frequently
• Schema is descriptive rather than perspective
• Data is not strongly typed
• Simple graph data model similar to OEM model

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Data Model for Semi-Structured Data
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Query Language and XML-QL

• All query languages for semi-structure are based
  on labeled graph
• Features of Semi-Structure query language
• regular path expression
• ability to query the schema
• In addition, XML-QL restructuring mechanism

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Storing XML Data in Relational Database Mapping
Attributes

• Edge Approach
• Store all attributes in single table
• Edge(source, ordinal, name, flag, target)
• Indexing, Forward and backward traversals
• Variant of Edge approach is Store attributes
  name in separate table

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Storing XML Data in Relational Database Mapping
Attributes

• Attribute Approach
• All the attributes with the same name in one
  table
• Resembles to binary storage scheme proposed to
  stir semi-structure data
• Aname(source, ordinal, flag, target)
• Indexing

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Storing XML Data in Relational Database Mapping
Attributes

• Universal Table
• Single Universal table to store all attributes of
  XML document
• Universal(source, ordinaln1, flagn1,
  targetn1,..)

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Storing XML Data in Relational Database Mapping
Attributes

• Normalized Universal Table
• Multi-valued attributes are stored in separate
  Overflow tables
• UnivNorm(source, ordinaln1, flagn1,
  targetn1,..)
• Overflow(source, ordinal, flag, target),.

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Storing XML Data in Relational Database Mapping
Values

• Storing values in separate table
• Value table storing all integers, dates, and all
  strings
• Vtype(vid, value)

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Storing XML Data in Relational Database Mapping
Values

• Storing values together with attributes
• Column for each data type Inlining
• No flag is needed
• For indexing, on every value columns separately
  in addition to source and target

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Evaluating the Mapping Schemes

• Plan of Attack
• Size of Relational Database for each mapping
  scheme
• The time to bulkload the relational database
  given an XML document
• The time to reconstruct the XML document from the
  relational data
• The time to execute different classes of XML
  queries
• The time to execute different kinds of update
  functions

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Evaluating the Mapping Schemes

• Experimental Platform
• Commercial relational database system, installed
  on Sun Sparc Station 20 with
• Two 75 MHZ processors
• 128MB of main memory a disk that stores the
  database and intermediate results of query
  processing
• Machine runs on Solaris 2.6, with limited size of
  main memory buffer to 6.4MB
• Calls to relational database from the Java
  programs are implemented with JDBC

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Evaluating the Mapping Schemes

• Benchmark Specification
• Benchmark Database

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Evaluating the Mapping Schemes

• Benchmark Specification
• Benchmark Queries

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Evaluating the Mapping Schemes

• Benchmark Specification
• Update Functions

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Evaluating the Mapping Schemes

• Benchmark Specification
• Database Size

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Evaluating the Mapping Schemes

• Benchmark Specification
• Bulkloading Times

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Evaluating the Mapping Schemes

• Benchmark Specification
• Reconstructing the XML Document

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Evaluating the Mapping Schemes

• Benchmark Specification
• Running Times of the Queries

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Evaluating the Mapping Schemes

• Benchmark Specification
• Running Times of the Updates Functions

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Conclusion

• Relational database has following advantages
• Mature and Scale very well
• Traditional and Semi-structured data can co-exist
  in relational database
• RDBMS are capable of performing more complex XML
  queries on large database
• Disadvantages
• Very expensive to reconstruct the original XML
  data from relational database
• Components such as authorization and concurrency
  control need to be implemented outside RDBMS

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Conclusion (Contd)

• Alternative mapping schemes results shows
• Attribute tables for every attribute name that
  occurs in an XML document and inlining of values
  into these Attributes tables is the best approach