XML/Relational mapping Introduction of the Main Challenges

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1 HELSINKI UNIVERSITY OF TECHNOLOGY November 30, 2004 Telecommunications Software and Multimedia Laboratory T Research Seminar on Digital Media (2-5 cr.): Autumn 2004: Web Service Technologies XML/Relational mapping Introduction of the Main Challenges Final version Authors Juha Sallinen (51133E) Hannes Tolvanen (51890B)

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3 XML/Relational Mapping Introduction of the Main Challenges Juha Sallinen, Hannes Tolvanen TKK, Telecommunications Software and Multimedia Laboratory Abstract XML has gained popularity as a data exchange format, but there does still not exist any single superior solution to manage persistent XML data. This paper gives an overview of the main challenges of mapping data in XML documents to a database management system using classical relational model and vice versa. Two basic mapping methods based on decomposition technique are introduced briefly and it's also introduced what they can be used for. 1 INTRODUCTION XML is a relatively new data exchange format, and the need to store XML documents persistently in a database has increased rapidly. However, the current implementations of the database management systems (DBMS) especially designed for XML purposes (called native XML DBMSs) have not been adopted into common use. One reason for this is, that there is not any de facto standard in the heterogeneous field of native XML DBMSs. Other reasons are the immaturity of the prevailing native XML database technology and the existence of efficient, well-working relational database systems, which have been in use for years. Native XML database technology seems to be in its emerging phase. By contrast, relational databases have been in use for decades, so they are extremely optimized to be efficient, usable and reliable. As a common scenario, many business applications of a company are using the same relational database, and some of them might take their input as XML. Some of the data sources of a database might as well use XML as their data exchange format. Thus, there must exist methods that map the data in XML documents to tables of a relational database, and and also methods that create XML presentations of the data in relational databases. These are called mapping methods. The rest of this paper is organized as follows. Next chapter gives a glimpse of the research work on the field when this paper was written. Chapter 3 presents the main dilemma of the mapping between XML and relational data models. In Chapter 4 the various XML data properties that have influence in the selection of the appropriate

4 mapping methods are studied. Chapter 5 describes different database usage models. In Chapter 6 two different mapping methods currently in use are presented. In discussion part in Chapter 7 these technologies are compared to each other. Conclusions are stated in Chapter Definition of The Research Problem Mapping the data from XML documents to relational model is complicated, because there is usually more than one feasible relational schema that could hold the data. According to (Salminen & Tompa, 2001), the major problem for applying traditional database technologies to XML data storage is the special characteristics of the XML data. This derives from the flexibility of the XML data format: An XML document can be highly structured and a DTD is not necessarily required, like it is with SGML. This means that XML documents can be arbitrary complex and differ a lot from each other. Conversely, relational databases are intended for the storage of strictly structured and homogeneous data. Storing loosely structured data in this kind of a database can easily result to an extremely complicated database schema. Therefore, there is a need for mapping methods that map the XML elements, attributes, comments and other information to relational tables, and vice versa. The selection of appropriate mapping method is not a trivial task. The characteristics of the data to be mapped play the main role in the selection process. This forms the basis of the research problem. 1.2 Objectives and Scope The study had two objectives. The first one was to identify the key issues and challenges related to the schema conversion problem, faced when optimal relational model schema is searched to hold given XML documents. The schema matching problem, which refers to the problem of finding correct mapping method when both of the schemas of source and destination are specified, is out of the scope of this study. Second objective of the study was to introduce two well-known and widely used mapping methods at the moment, based on composition approach introduced in Chapter 3, and also their applications. 1.3 Research Method The research was conducted as a literature study. The idea was to collect the main perceptions of the field from other recent research projects and draw conclusions based on them. 2 RELATED WORK There has been many research projects going on recently regarding to this topic. A number of methods dealing with the mapping problem between XML and relational data

5 models have been introduced each of which having its own purpose of usage, depending mainly on the characteristics of the data to be mapped. One of the newest methods on the time of writing this paper was ShreX (Amer-Yahia et al, 2004). Actually, ShreX is not just a mapping method. It is a comprehensive framework, which addresses other storage problems as well, like query translation from XML queries into SQL queries. The mapping in ShreX is based on annotations to an XML Schema. When talking about storing XML data in a relational database in broader sense and not just from the viewpoint of mapping, the findings in (Krishnamurthy et al, 2003) are interesting. Their research is based on the papers of the field published in recent years. The paper presents the state-of-the-art and the research field is still open. 3 MAPPING BETWEEN XML AND RELATIONAL DATA MODELS By default, distinct data models present the same information differently from each other. This means that transferring data between the source and destination that use different data models requires mapping methods, that do the conversion between these two presentations. This is also the case with XML and relational data models. 3.1 XML/Relational Impedance Mismatch Relational model requires the data to be highly structured. This means that data must be coherent and its structure is fixed and known beforehand. XML data model is more flexible and can be used to present also semi-structured data and mark-up text, like the chapters of a book, for example. Every book has its own structure of chapters. According to (Shanmugasundaram et. al, 2000), the difference between these two data models results from the fact that XML documents have tags and nested structure, whereas relational tables do not. This difference forms the basis of the problem named XML/relational impedance mismatch. It causes the most of the complexity of the mapping between these two data models. 3.2 Dichotomy of XML/Relational Mapping Methods According to (Draper, 2004), there are two fundamental ways to store XML data in a relational database: LOB representation and composed representation. LOB stands for Large Object. Using LOB representation means that one XML document is stored in one column of a row in relational table as whole instead of parsing the data into different columns according to XML tags. Of course, there is a need for at least one additional column for storage of the index (primary key) of the document. This kind of a mapping is easy to implement, but it does not take the full advantage of the features of the underlying relational database. For example, it is not possible to query the elements of XML documents using SQL. This is why the LOB

6 representation is not a very interesting choice, and the implementation based on it is therefore out of this study. In composed representation the data in XML document is shredded into columns of relational tables. This means that the data from elements, attributes etc. is distributed into appropriate columns into one or more tables in some way. This increases complexity of the mapping method, but enables the use of SQL query processing engine included in relational DBMS. It is also important to notice, that when composed representation is used, it is possible to get several different views of XML data using the same source data in relational database. It is also possible to use hybrid implementation of the two representations previously introduced. This simply means that some parts of an XML document are split to their own columns and some parts are stored as whole chunks of XML data strings. 3.3 Reverse Mapping To implement the functionalities of XML DBMS, relational DBMS or middleware interfaced to it must be able to publish XML view of the data stored in database. If the data can be represented using relational model, a respective schema in XML data model can be always found. 4 RELEVANT DATA CHARACTERISTICS As mentioned before, certain characteristics of the data to be stored (or retrieved) affect the selection of the mapping method. The most relevant ones are described briefly in this chapter. 4.1 Existence of Schema Definition If there exists no schema definition document that XML document can be validated against, there can be no guarantee that following documents will fit to the relational model schema, which was created in respect to the earlier documents of the same type. (Draper, 2004) states that LOB approach should be used always, when the schema of the XML data is not explicitly declared. This is because assumptions on the XML document schema that prove false later, might lead to seriously bad choices with database schema. 4.2 Stability of The Schema Schema definitions for XML document types might change with time. When there occurs changes in the schema of the document type, the database schema must be modified respectively to support the storage of XML data conforming to the new schema. Therefore it should be evaluated, what is the risk that XML schema will change, and how radical changes would be required to relational model schema. LOB approach eliminates the risk, but also with composed approach the changes can be minor.

7 4.3 Degree of Structure In this study, we categorize and define XML documents in respect to their degree of structure as in (Draper, 2004): Structured, semi-structured and marked-up text. It is possible to navigate a XML document containing structured data without examining its content, while semi-structured XML documents have variant substructures, so the content of those substructures must be known in advance so that navigation is possible. XML document categorized as marked-up text includes mixed content, which means that character data may appear not only inside the document elements but between the elements. Structured XML data with schema definition document can be usually easily composed into relations when the XML schema is known. 4.4 Depth and Width of the Document Structure The deeper the structure of an XML document is, the bigger is the maximum amount of nested elements. Depth of structure makes the mapping procedure more complicated, whereas width does not have this kind of an effect. It is much more simpler to map the elements on the same level (flat structure) than elements which are nested within each other. This is due to the fact that the nature of relational schema is flat, whereas XML data structure is tree-like and hierarchical. 4.5 Amount of Data The amount of data to be mapped can affect the speed of the mapping process. One XML document can contain a huge amount of data, and/or there can be a large number of separate XML documents. 5 DATABASE USAGE MODELS In selection of the optimal mapping strategy, the usage models of the database should be considered in addition to the data characteristics under mapping. Section 5.1 presents the reasoning why the queries that will be executed against the database data should be evaluated before deciding the mapping method. In Section 5.2 the concept of "hidden information" is introduced, and it's influence to the choice of optimal mapping method strategy is evaluated, in case the hidden information has to be preserved. 5.1 Queries on Data The usage spectrum of an XML database might vary from repository of XML documents to full-scale usage of database's features giving a good support for complex queries that aggregate data from different data sources. When making the decision between LOB and decomposition strategy, one should make an evaluation what are the most typical operations on data. If XML applications

8 interfaced to database require views on data that are transformations of the source data or anything more complex, the database engine can be used to speed up queries if the decomposition strategy is chosen. LOB strategy is an obvious choice when requests are limited to retrieval of stored XML documents. Respectively, decomposition strategy is an obvious choice if queries generally collect summary data from the element. 5.2 Preservation of Hidden Information By hidden information we mean the information in XML documents that is not implicitly defined in data or meta data. That is, the order of tags, white spaces and every other information of that kind. If the hidden information is vital, the mapping method must take care of storing it to relational tables in some way. For example, in the case of a product catalog, the order of the elements containing the color and price of a certain product is not relevant. In contrast, the order of chapters in a book must be preserved when storing them in a database. There could be an index column in the table of chapters, for instance. If we want to reproduce exactly the same XML document we stored in relational database earlier, all the hidden information must be stored. Usually this is not the case. The more hidden information is needed, the more complex becomes the mapping method. 6 TWO WIDELY USED MAPPING METHODS As mentioned in Chapter 3, the dichotomy of the mapping methods between XML and relational data model means that XML documents can be stored in relational tables as whole (as LOBs), or the data in the documents can be extracted to rows and columns of a relational table (composed representation). The LOB representation is the most trivial way to put XML documents into tables. By contrast, composed representations can be extremely complex, depending on the the composition method that is used and the XML schema that is mapped. This chapter describes two well-know mapping methods based on composition, that are both used in many XML-enabled relational DBMS products. 6.1 Table-Based Mapping Table-based mapping is the simplest possible mapping method based on composition. It models an XML document as a single relational table or set of tables. This means that XML documents to be mapped must have a certain structure. This structure is illustrated in Listing 1. <Tables> <Table_1> <Row> <Column_1>...</Column_1>... <Column_n>...</Column_n>

9 </Row>... </Table_1>... <Table_n> <Row> <Column_1>...</Column_1>... <Column_m>...</Column_m> </Row>... </Table_n> </Tables> Listing 1. Required structure of XML document in table-based mapping (Bourret, 2001). The root node represents the whole database. The child nodes of the root are mapped into tables. Next sub-nodes are the rows of the tables, and the child nodes of them are considered as column values of the respective row. The drawback of the table-based mapping method is that it can be aplied only to documents conforming the format showed in Listing 1 (Bourret, 2002). The applications for table-based mapping method are therefore very limited. One very popular use for the table-based mapping method is of serializing relational database's data for transfer to other RDBMS:s. Data in relational database can be very easily exported to XML document conforming to XML schema the method supports, as well as imported back to database. XML Documents, whose orginal data source is not a relational database, seldom conform the schema the table-based mapping method supports, so more sophisticated mapping methods have to be used in other usage models than data transfer between databases. 6.2 Object-Relational Mapping In object-relational mapping XML document is modeled as a tree of objects. Basically it means that complex element types are mapped to classes and primitive data types to scalar properties of the classes. Object-relational mapping is executed in two steps. At first, the mapping must be done from XML schema to objects. After that, objects are mapped into relational schema of the database. Listing 2 clarifies the idea of the method. XML Objects Tables ============= ============ =============== Table A <A> object A { <B>bbb</B> B = "bbb" B C D <C>ccc</C> <=> C = "ccc" <=> <D>ddd</D> D = "ddd"

10 </A> } bbb ccc ddd Listing 2. Simple example of object-relational mapping (Bourret, 2001). The XML document in listing 2 could have been as well decomposed using table-based mapping method resulting to the exactly same relational model schema. The objectrelational mapping method however includes support for almost all document types introduced earlier in the study. However, it's not a good choise if document includes mixed content, or hidden information of the document has to be reserved (Bourret, 2001). 7 DISCUSSION The obvious problem with table-based mapping is that it can be applied only for XML documents with a very simple structure. This is not the case with loosely structured (mark-up text) XML documents, which can be very heterogeneous and contain mixed content. However, compared to the object-relational mapping the implementation of table-based mapping method is very straightforward. It can be used for highly structured, data-centric data, like forms with fixed fields in addition to data originated from relational databases. 8 CONCLUSION In this paper we have introduced the basic dilemma of the mapping between XML and relational data models. We have presented the crucial data characteristics and data usage models, which have impact to the selection of the appropriate mapping method. Finally, two well-known mapping methods were described and compared with each other from the viewpoint of data characteristics and their usage models. The fundamental point of the paper was to make the reader understand the fact that XML data can be always stored to relational database, and relational data can be always published as XML documents, but in the point of view of data managebility, some usage models just cause much more trouble than others if the database schema/xml schema for mapping has to be declared explicitly by the user.

11 REFERENCES Amer-Yahia S.; Du F.; Freire J A Comprehensive Solution to the XML-to- Relational Mapping Problem. In WIDM 04, November 12-13, 2004, Washington, DC, USA. Bourret R Mapping DTDs to Databases. pub/a/2001/05/09/dtdtodbs.html Draper D Mapping between XML and Relational Data. Addison Wesley. Florescu D. and Kossman D A Performance Evaluation of Alternative Mapping Schemes for Storing XML Data in a Relational Database. Rapport de Recherche No. 3680, INRIA, a.pdf Krishnamurthy R.; Kaushik R.; Naughton J. F XML-SQL query translation literature: The state of the art and open problems. In Proceedings of the International XML Database Symposium (XSym), Salminen A. and Tompa F. Wm Requirements for XML Document Database Systems. In Proceedings of the 2001 ACM Symposium on Document engineering, Atlanta, Georgia, USA, Shanmugasundaram J.; Shekita E.; Barr R.; Carey M.; Lindsay B.; Pirahesh H.; Reinwald B Efficiently Publishing Relational Data as XML Documents. In Proceedings of the 26th International Conference on Very Large Databases (VLDB), Cairo, Egypt, Ronald Bourret, 2002: XML And Databases,