A Quantitative Summary of XML Structures
Byron Choi2006, Lecture Notes in Computer Science
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Abstract
Statistical summaries in relational databases mainly focus on the distribution of data values and have been found useful for various applications, such as query evaluation and data storage. As xml has been widely used, e.g. for online data exchange, the need for (corresponding) statistical summaries in xml has been evident. While relational techniques may be applicable to the data values in xml documents, novel techniques are requried for summarizing the structures of xml documents. In this paper, we propose metrics for major structural properties, in particular, nestings of entities and one-to-many relationships, of XML documents. Our technique is different from the existing ones in that we generate a quantitative summary of an xml structure. By using our approach, we illustrate that some popular real-world and synthetic xml benchmark datasets are indeed highly skewed and hardly hierarchical and contain few recursions. We wish this preliminary finding shreds insight on improving the design of xml benchmarking and experimentations.
Key takeaways
- The computation of our metrics of an xml document relies on the construction of the prefix tree of the document.
- The distributions of the number of a particular kind of star edges of a node, i.e. the previous metric, of our xml benchmark datasets have a large variance.
- However, these datasets are insufficient to show the benefits of algorithms for recursive xml datasets.
- xmark and dblp datasets appear popular in the xml research community, we found that the majority of these xml datasets are mild generalization of relations -not "tree-like".
- We derived statistics from a prefix tree of xml structures and used simple paths and star edges as the basis of our metrics.
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