url - Universität zu Lübeck

More documents

Recommendations

Info

159 The implementations of this work operate on top of the native XML database management systems Infonyte DB [55], that can be interpreted as a persistent DOM with a Java API interface so that it can be used by any Java class. Because the KeyX implementation uses only the XPath engine of Infonyte DB and its capability to assign unique identifiers to XML nodes, any other XML database management system that offers the same functionality can be used in principle. Therefore, the KeyX approach is independent of any particular database product. The results of this work have been published on four international conferences [44, 46, 47, 48], two workshops [43, 45] and two technical reports [41, 42] and can be used for the development of next-generation database management systems. Examples include new hybrid systems that unify relational and native XML paradigms like the SystemRX [11] from IBM. Although the aims of this project were achieved there are a multitude of points where further work can start: • So far only value comparisons with the operators =, ≠, , ≤, ≥ are supported. For a lot of scenarios a value comparison with substrings or regular expressions would make sense. For instance it might be useful to find all books with XML appearing somewhere in the title. In principle full text indexing methodologies from the relational world can be reused within the KeyX structure. • The intersection algorithms and the index maintenance algorithms may profit from the existence of schema information of the indexed data if available. We did not focus on data with a schema because XML database management systems have to support schemaless data in order not to restrict the capabilities and the expressiveness of the semistructured XML model. Having a schema information like a DTD or an XML schema the intersection problem may be easier because some combinations that cause an intersection are not enabled by the schema. On the other hand, a schema allows to define dependencies between elements (e.g. each book, that has a price has also a currency). If these dependencies are taken into account it is likely that the intersection problem is not getting easier. For XML data without a schema one could try to create a schema for the statistic DataGuide, that is a summary of the data • The statistic DataGuide is a first approach to summarize the frequency of elements and the selectivity of their values. In particular, the statistic DataGuide assumes that all elements are statistically independent. If some elements are statistically dependent (see example above) the estimation of the query execution time may lead to inaccuracies. Basically, statistic dependencies can arise for any two elements a and b, and even worse for any
160 CHAPTER 9. CONCLUSION AND FUTURE WORK combinations of arbitrary many elements a 1 ...a k . Therefore, there are exponentially many combinations to be checked for statistic dependency. Even if one is willing to spend this computational expenses there is the problem of storing the exponential many results - the factors that express the statistic dependence between elements. A first improvement may be to restrict the analysis on two elements and to store the factors only if a given threshold is exceeded. The time consuming analysis could take place when the database has a low working load. • So far, KeyX directly supports a major fragment of XPath expressions that allow to express most relevant queries. Advanced XPath features like functions (e.g. count(), sum()) are not supported. XQuery expressions rely strongly on XPath for navigation and selection purposes, so that the KeyX approach can also be applied for the accelerated execution of XQuery expressions. Anyhow, because XQuery has a higher expressiveness than XPath, it might be interesting if and how KeyX can be extended in order to support XQuery more efficiently. For instance, XQuery has the concept of XML constructors embedding the selected element in a newly created XML structure. For frequently occurring Query expressions it might be profitable to precompute the embedding and store it in the KeyX search tree as return value. This way, KeyX would not only return the referenced element, but also its surrounding elements that are usually created by the XQuery constructors.
Page 1 and 2:
Aus dem Institut für Informationss
Page 3 and 4:
Acknowledgments I would like to tha
Page 5 and 6:
2 CONTENTS 4 Introduction to Recent
Page 7 and 8:
4 CONTENTS 10.3 XML Schema . . . .
Page 9 and 10:
6 CHAPTER 1. INTRODUCTION Due to th
Page 11 and 12:
8 CHAPTER 2. FUNDAMENTALS In contra
Page 13 and 14:
10 CHAPTER 2. FUNDAMENTALS data is
Page 15 and 16:
12 CHAPTER 2. FUNDAMENTALS XML supp
Page 17 and 18:
14 CHAPTER 2. FUNDAMENTALS 2.2 Docu
Page 19 and 20:
16 CHAPTER 2. FUNDAMENTALS be const
Page 21 and 22:
18 CHAPTER 2. FUNDAMENTALS plies th
Page 23 and 24:
20 CHAPTER 2. FUNDAMENTALS the stru
Page 25 and 26:
22 CHAPTER 2. FUNDAMENTALS 2.3 XML
Page 27 and 28:
24 CHAPTER 2. FUNDAMENTALS Axes for
Page 29 and 30:
26 CHAPTER 2. FUNDAMENTALS Node Tes
Page 31 and 32:
28 CHAPTER 2. FUNDAMENTALS //item[c
Page 33 and 34:
30 CHAPTER 2. FUNDAMENTALS 21 i f (
Page 35 and 36:
32 CHAPTER 2. FUNDAMENTALS FLWOR-Ex
Page 37 and 38:
34 CHAPTER 2. FUNDAMENTALS 21 22 {
Page 39 and 40:
36 CHAPTER 2. FUNDAMENTALS 1 2 3
Page 41 and 42:
38 CHAPTER 2. FUNDAMENTALS 2.5 XML
Page 43 and 44:
40 CHAPTER 2. FUNDAMENTALS the valu
Page 45 and 46:
42 CHAPTER 2. FUNDAMENTALS tables a
Page 47 and 48:
44 CHAPTER 2. FUNDAMENTALS signific
Page 49 and 50:
46 CHAPTER 3. FORMAL MODELS FOR XML
Page 51 and 52:
Page 53 and 54:
Page 55 and 56:
Page 57 and 58:
Page 59 and 60:
56 CHAPTER 4. INTRODUCTION TO RECEN
Page 61 and 62:
Page 63 and 64:
Page 65 and 66:
Page 67 and 68:
Page 69 and 70:
Page 71 and 72:
Page 73 and 74:
Page 75 and 76:
Page 77 and 78:
Page 79 and 80:
Page 81 and 82:
78 CHAPTER 5. THE KEY-ORIENTED XML
Page 83 and 84:
Page 85 and 86:
Page 87 and 88:
Page 89 and 90:
Page 91 and 92:
Page 93 and 94:
Page 95 and 96:
Page 97 and 98:
Page 99 and 100:
Page 101 and 102:
Page 103 and 104:
Page 105 and 106:
Page 107 and 108:
104 CHAPTER 6. THE INDEX SELECTION
Page 109 and 110:
106 CHAPTER 6. THE INDEX SELECTION
Page 111 and 112: 108 CHAPTER 6. THE INDEX SELECTION
Page 127 and 128: 124 CHAPTER 7. THE XML INDEX UPDATE
Page 151 and 152: 148 CHAPTER 8. KEYX IMPLEMENTATION
Page 161: 158 CHAPTER 9. CONCLUSION AND FUTUR
Page 165 and 166: 162 CHAPTER 10. APPENDIX 23 relKeyP
Page 167 and 168: 164 CHAPTER 10. APPENDIX Title: On
Page 169 and 170: 166 CHAPTER 10. APPENDIX Title: The
Page 171 and 172: 168 CHAPTER 10. APPENDIX
Page 173 and 174: 170 BIBLIOGRAPHY [12] Alberto Capra
Page 175 and 176: 172 BIBLIOGRAPHY [37] Roy Goldman a
Page 177 and 178: 174 BIBLIOGRAPHY [59] Raghav Kaushi
Page 179 and 180: 176 BIBLIOGRAPHY [84] David G. Mitc
Page 181 and 182: 178 BIBLIOGRAPHY [113] W3 Schools.
Page 183 and 184: 180 Index D, 78, 108, 110, 111, 144
Page 185 and 186: 182 INDEX Oracle XML DB, 41 Parent,
show all

url - Universität zu Lübeck

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?