XML Query Processing and Optimization

Transcription

1 XML Query Processing and Optimization Bartley D. Richardson Department of Electrical & Computer Engineering and Computer Science University of Cincinnati December 16, 2005

2 Outline Background XML As A Data Model XML Overview OEM Overview Indexing Over XML B+, XR, and XB Trees DataGuides ToXin Constraint Sequencing XML Query Styles Proposed Research Characterize Parameters and Features Performance Study Create User Tools B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

3 Traditional Query Optimization SQL query travels through two levels of optimization Final product is an access plan for the query B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

4 Traditional Logical Optimization Query converted to relational algebra (RA) tree Transformations are performed on the tree Figure: RA Logical Optimization B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

5 Traditional Physical Optimization Takes into account file organization Chooses algorithms for operators Figure: RA Physical Optimization B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

6 XML Overview Syntactically similar to HTML Information stored in content as well as structure Data represented is self-describing Generally does not require outside schema Presents new challenges for query processing and optimization B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

7 XQuery Designed to meet requirements set by W3C for an XML query language Includes a well-defined grammar FLWR expressions (For, Let, Where, Return) No built-in optimization techniques Current version (XQuery 1.0) is extension of XPath 2.0 XQuery not used in proposal but will be leveraged as an acceptable interface to XML documents and used to extract information B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

8 XPath Simplest type of query in XML Expressions resemble UNIX directory structure Parent-child relationship denoted by a slash (/) Ancestor-descendant relationship denoted by a double-slash (//) Text in brackets ([ ]) acts as a filter on data to be returned XPath Example /bookstore/book[price>35]/title B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

9 XML Example FoodDrink XML Example <FoodDrink> <restaurant id= R001 > <name>chili s</name> <phone> </phone> <owner>g. Peppard</owner> </restaurant> <restaurant id= R002 > <name>maggiano s</name> <owner>g. Peppard</owner> <manager>crowley/manager> </restaurant> <bar id= B001 > <name>crowley</name> <style>irish</style> </bar> </FoodDrink> B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

10 OEM Overview XML data can be represented by the Object Exchange Model (OEM) [PGMW95] Self-describing Retains simplicity of relational models Allows flexibility of object-oriented models B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

11 OEM Representation Figure: Corresponding FoodDrink OEM Representation B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

12 Challenges for XML Query Processing/Optimization XML queries themselves are more complicated New kinds of indexes and traversal strategies Many kinds of indexes Many choices on how to store and traverse trees Results in more query execution strategies Complicated database statistics due to number of possibilities for tree shapes B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

13 Node Labeling Nodes of OEM must be labeled for B + -, XR-, and XB-trees Use extended preorder traversal [LM01] (an extension of Dietz s original numbering scheme [Die82]) Labels each node with a pair of numbers <order,size> Allows insertions to be made into the tree without need for global reordering B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

14 OEM Example with EPT Labeling Figure: OEM with Extended Preorder Traversal Node Labeling B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

15 B + -Trees Used in relational database systems to implement dynamic multilevel index [EN00] Does not require reorganization of entire file to maintain performance Due to hierarchical nature, used for processing XML structural joins Performance later improved upon by XR- and XB-trees B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

16 XR-Trees A B + -tree that is built on start points of element intervals Designed for strictly nested XML data Allows all ancestors and descendants for a given element to be identified optimally Lacks capability to handle highly recursive XML elements efficiently [LLHC04] B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

17 XB-Trees Combines structural features of both the B + -tree and R-tree Indexes pre-assigned intervals of elements in the tree (similar to one-dimensional R-tree) Constructs the index on start points of the intervals (similar to B + -tree) Main difference is that size value of <order,size> must be propagated up index Developed for use in processing holistic twig joins [BKS02] B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

18 A Sample XB-Tree Figure: Sample XB-tree B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

19 DataGuide Definition Concise and accurate summary of database structure [GW97] Dynamically generated Conforms to the data One OEM source database may have multiple DataGuides Use and effectiveness for indexing XML documents on their own has not been addressed Can be used in conjunction with other indexes VIndex (Value Index) LIndex (Link Index) BIndex (Parent/Child pairs) PIndex (Path Index) B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

20 DataGuide Example Figure: DataGuide for OEM Example B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

21 ToXin Developed within the ToX (Toronto XML Engine) project [RM01] Seeks to exploit overall path structure of XML databases in all stages of query processing Index consists of two main structures Value Index: stores XML nodes and corresponding values Path Index: Consists of index tree (a DataGuide) and set of instance tables (used to identify parent-child relationships) Includes redundant information (potentially costly for large databases) B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

22 ToXin Example Figure: Sample ToXin Tree and Tables B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

23 Constraint Sequencing Operates by encoding the entire tree at once [WM05] Index is built that allows selection of an object or path by matching subsequences Encoded information represented by adding prefixes (forward prefix) to value nodes that encode their path along the tree Similar to extended preorder traversal, but uses depth-first traversal of tree to assign the value order(x) Example Sequence <&1,&1&2,&1&2&5,&1&2&6,&1&2&7,... > <&1,&1&2,&1&2(Chili s),&1&2( ),&1&2(g. Peppard)... > B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

24 Constraint Sequencing Open Questions Challenges Encoding tree without introducing false hits or dismissals Authors have identified these problems and developed techniques to overcome Open Questions Appears efficient, but no full comparison to other indexing techniques Options for underlying data structure have not been investigated B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

25 Query Styles Overview Various styles of queries can be classified in traditional terms (Select, Project, Join) Select Simple Path Complex Path Project Value Object Join Structural Value-based B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

26 Query Styles Overview Various styles of queries can be classified in traditional terms (Select, Project, Join) Select Simple Path Complex Path Project Value Object Join Structural Value-based B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

27 Query Styles Overview Various styles of queries can be classified in traditional terms (Select, Project, Join) Select Simple Path Complex Path Project Value Object Join Structural Value-based B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

28 Query Styles Overview Various styles of queries can be classified in traditional terms (Select, Project, Join) Select Simple Path Complex Path Project Value Object Join Structural Value-based B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

29 Select: Simple Path Give me the phone number of Chili s. Chili s ]/phone B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

30 Select: Complex Path Give me the name of all restaurants owned by G. Peppard. G. Peppard ]/name B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

31 Project: Value Give me the name of all establishments. //name B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

32 Project: Object Give me all information about all restaurants. //restaurant B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

33 Join: Structural Give me the name of all restaurants owned by G. Peppard. G. Peppard ]/name B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

34 Join: Value-based Name of all places where manager name is the same as place name B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

35 Database Statistics Statistics kept for relational databases are straightforward Due to tree structure of XML, more parameters (statistics) to model for cost-based optimizers XML optimizer can start evaluating a path expression from any point in the path McHugh and Widom [MW99] identify salient features and develop a formal model More statistics may be necessary, but this model will be used as a starting point B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

36 Database Statistics - Model Statistics maintained for each subpath p with a length of at most k include the total number of atomic objects (for each atomic type) that are reachable via p, the minimum and maximum values (for each atomic type) of all atomic objects reachable via p, the total number of instances of path p ( p ), the total number of distinct objects reachable via p ( p d ), the total number of l-labeled subobjects reachable via p ( p l ), and the total number of l-labeled edges to any instance of p ( p l ). B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

37 Database Statistics - Fan In/Out Statistics can help describe the shapes of query trees presented to an XML database. Fan-out for any given path expression is computed by p p l p d Fan-in is computed by p pl p d. B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

38 Proposed Research Overview Our proposed research includes the following items Classification of XML query styles Investigation into possible tree shapes (database statistics) for XML documents and queries Performance study across all parameters Leverage performance study to create user tools B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

39 XML Query Styles Have a foundation to identify and classify XML query styles presented in the literature This allows for current and future research to be classified and referenced using a common framework As the area evolves, more styles may become necessary B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

40 Remaining Research Objectives of this research still remaining include: Determine if database statistics available are enough to effectively describe all tree shapes and distinguish trees from one another Conduct a performance study across all parameters (indexing techniques, data structures, query styles, tree shapes) Create user tools that take a wide, generic approach to automating query optimization B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

41 Remaining Research Objectives of this research still remaining include: Determine if database statistics available are enough to effectively describe all tree shapes and distinguish trees from one another Conduct a performance study across all parameters (indexing techniques, data structures, query styles, tree shapes) Create user tools that take a wide, generic approach to automating query optimization B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

42 Remaining Research Objectives of this research still remaining include: Determine if database statistics available are enough to effectively describe all tree shapes and distinguish trees from one another Conduct a performance study across all parameters (indexing techniques, data structures, query styles, tree shapes) Create user tools that take a wide, generic approach to automating query optimization B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

43 Current XML Optimization Work We are aware of two projects that perform XML query optimization Timber: System proposed out of University of Michigan Stanford: Similar project out of Stanford University Both projects are limited to their own local indexing research Do not provide a wide enough scope for a general XML query optimizer Some of their work may be able to be leveraged on our proposed research B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

44 Questions Questions? B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

45 Extended Preorder Traversal There are three conditions placed on the values for order and size. 1 For tree node y and its parent x, [order(y), order(y) + size(y)] contained in [order(x), order(x) + size(x)] 2 For two sibling nodes x and y, order(x) + size(x) < order(y) if x is predecessor of y in preorder traversal 3 For any node x, size(x) y size(y) for all y s that are a direct child of x. B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

46 References I Serge Abiteboul, Peter Buneman, and Dan Suciu. Data on the Web. Morgan Kaufmann Publishers Inc., ANSI. American National Standards Institute: The database language SQL. Document ANSI X3.135, Nicolas Bruno, Nick Koudas, and Divesh Srivastava. Holistic twig joins: Optimal xml pattern matching. In Proceedings of the 2002 ACM SIGMOD International Conference on Management of data, pages , Madison, Wisconsin, USA, June B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

47 References II R. G. G. Cattell, Douglas K. Barry, Dirk Bartels, Mark Berler, Jeff Eastman, Sophie Gamerman, David Jordan, Adam Springer, Henry Strickland, and Drew Wade. The Object Database Standard: ODMG 2.0. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, E. F. Codd. A relational model of data for large shared data banks. Communications of the ACM, 13(6): , B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

48 References III Shu-Yao Chien, Zografoula Vagena, Donghui Zhang, and Vassilis J. Tsotras. Efficient structural joins on indexed xml documents. In Proceedings of the 28th International Conference on Very Large Data Bases (VLDB 02), pages , Hong Kong, China, August Paul F. Dietz. Maintaining order in a linked list. In Proceedings of the 14th Annual ACM Symposium on Theory of Computing (STOC 82), pages , San Francisco, CA, United States, May B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

49 References IV Ramez Elmasri and Shamkant B. Navathe. Fundamentals of Database Systems. Addison-Wesley, 3rd edition, Roy Goldman and Jennifer Widom. Dataguides: Enabling query formulation and optimization in semistructured databases. In Proceedings of 23rd International Conference on Very Large Data Bases (VLDB 97), pages , San Francisco, CA, USA, August Su Cheng Haw and G. S. V. Radha Krishna Rao. Query optimization techniques for XML databases. International Journal of Information Technology, 2(1):97 104, B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

50 References V Haifeng Jiang, Hongjun Lu, Wei Wang, and Beng Chin Ooi. XR-Tree: Indexing XML data for efficient structural joins. In Proceedings of the 19th International Conference on Data Engineering (ICDE 03), pages , Bangalore, India, March Hanyu Li, Mong-Li Lee, Wynne Hsu, and Chao Chen. An evaluation of xml indexes for structural join. SIGMOD Record, 33(3):28 33, September Quanzhong Li and Bongki Moon. Indexing and querying XML data for regular path expressions. In Proceedings of the 27th International Conference on Very Large Data Bases (VLDB 01), pages , San Francisco, CA, United States, September B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

51 References VI Jason McHugh and Jennifer Widom. Query optimization for XML. In The VLDB Journal, pages , Edinburgh, U.K., September Yannis Papakonstantinou, Hector Garcia-Molina, and Jennifer Widom. Object exchange across heterogeneous information sources. In Proceedings of the 11th International Conference on Data Engineering (ICDE 95), pages , Taipei, Taiwan, March IEEE Computer Society. B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

52 References VII Flavio Rizzolo and Alberto O. Mendelzon. Indexing XML data with ToXin. In Proceedings of the 4th International Workshop on the Web and Databases (WebDB 2001), pages 49 54, Santa Barbara, CA, USA, May Haixun Wang and Xiaofeng Meng. On the sequencing of tree structures for xml indexing. In Proceedings of the 21st International Conference on Data Engineering (ICDE 05), pages , Tokyo, Japan, April B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57

53 References VIII Yuqing Wu, Jignesh Patel, and H. Jagadish. Structural join order selection for XML query optimization. In Proceedings of the 19th International Conference on Data Engineering (ICDE 03), pages , Bangalore, India, March Extensible Markup Language (XML). XPath amoeller/xml/linking/xpath20.html. XQuery 1.0: An XML Query Language. B. Richardson (ECECS-UC) XML Query Processing and Optimization December 16, / 57