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A Performance Evaluation of Alternative Mapping Schemes for Storing XML Data in a Relational Database By Daniela Floresu Donald Kossmann Presented by:

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1 A Performance Evaluation of Alternative Mapping Schemes for Storing XML Data in a Relational Database By Daniela Floresu Donald Kossmann Presented by: Intakhab Mehboob Khan

2 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

3 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

4 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

5 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

6 Data Model for Semi-Structured Data

7 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

8 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

9 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

10 Storing XML Data in Relational Database [Mapping Attributes] Universal Table –Single Universal table to store all attributes of XML document –Universal(source, ordinal n1, flag n1, target n1,…..)

11 Storing XML Data in Relational Database [Mapping Attributes] Normalized Universal Table –Multi-valued attributes are stored in separate Overflow tables – UnivNorm(source, ordinal n1, flag n1, target n1,…..) –Overflow(source, ordinal, flag, target),….

12 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)

13 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

14 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

15 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

16 Evaluating the Mapping Schemes Benchmark Specification –Benchmark Database

17 Evaluating the Mapping Schemes Benchmark Specification –Benchmark Queries

18 Evaluating the Mapping Schemes Benchmark Specification –Update Functions

19 Evaluating the Mapping Schemes Benchmark Specification –Database Size

20 Evaluating the Mapping Schemes Benchmark Specification –Bulkloading Times

21 Evaluating the Mapping Schemes Benchmark Specification –Reconstructing the XML Document

22 Evaluating the Mapping Schemes Benchmark Specification –Running Times of the Queries

23 Evaluating the Mapping Schemes Benchmark Specification –Running Times of the Updates Functions

24 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

25 Conclusion (Cont’d) 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


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