Structural Join Research Articles

Research of XML Structural Join Based on the Cone Three-dimensional Coding

Research of XML Structural Join Based on the Cone Three-dimensional Coding

Improvement of XML Structural Join Algorithm with Weaving Multi-documents

Improvement of XML Structural Join Algorithm with Weaving Multi-documents

Structural Join Algorithm of XML Query Based on Exhaustive Dynamic Programming

Using the advantages of exhaustive dynamic programming algorithm, on the basic ideas of the global optimal solution is derived based on local optimal solution, this paper propose a new structural selection join algorithm. The algorithm connects to the sub-tree, and then connects to the structure of the whole. Though not guaranteed optimal solution, this algorithm can improve much in the time complexity, reduce the search space and improve efficiency.

XML Structural Join Based on Extended Region Coding

XML has become a standard technology in exchange of a wide variety of data on web and internet for its structure, label, portability and expansibility. To efficiently query XML documents has been the primary urgent task. At the present time, most of XML index and query are based on encoding the XML document tree, so all kinds of XML encoding schemes are proposed, and region coding is the mainstream coding and used most commonly, such as Dietz coding, Li-Moon coding, Zhang coding, Wan coding, etc. The paper proposes an extended region coding based on region coding. Preorder XML document tree, and take preorder numerical orders of a node's all descendants as the region. When carrying out structural join, if preorder numerical order of a node is in this region, structural relation can be ensured. So this extended region coding can help effectively judge structural relation and the XML document tree needn’t be traversed. Furthermore, the better structural join algorithms of XML path queries have received considerable attention recently, and some researchers have proposed some fine algorithms to solve the problem. Stack-Tree-Desc algorithm is one of these fine algorithms, it need separately scan ancestor list and descendant list one time to decide ancestor/descendant structural relation, but some unneeded join nodes still be scanned. For this reason, if some element nodes of ancestor list and descendant list which don’t need participate in structural join can be jumped, the query efficiency is enhanced. Therefore, based on Stack-Tree-Desc algorithm an improved algorithm which introduces index structure to avoid scanning unwanted nodes, so ordered scanning is unnecessary, the consuming time of query shortens accordingly. And this improved algorithm can quickly judge structural relation based on extended region coding presented in this paper. Experiment is conducted to test the effectiveness of the extended region coding and the Indexed Stack-Tree-Desc algorithm. Experiment results show that the method in this paper is effective.

Fiber processing of queries on hierarchical data

This paper is dealing with fiber processing of XPath queries. We make use of the Structural Join (SJ) method that we modify so as to achieve an improved number of page fetches containing input data. The fiber aggregation based composition, defined in this paper, allows local optimization of individual search steps taking advantage either of input low cardinality or high selectiveness of parent-child join.

OXML: an Object XML Database Supporting Rich Media Indexing and Retrieval

There are countless animation movies available nowadays throughout the Internet. Rich media (including Flash and PowerPoint) presentations are increasingly gaining widespread usage, particularly in the domains of e-learning and digital entertainment. In order to allow these animation movies to be queried efficiently, in this article we present OXML - an Object XML database for storing and retrieving animation movies. After converting the movies into XML format, OXML stores the resultant XML data into a native object-oriented database. To enhance the retrieval of such XML objects, an indexing technique known as Structural Join Index Hierarchy (SJIH) is then applied to the OXML database. A detailed cost model for query execution through SJIH is developed. Our experimental studies on accessing Flash movies using SJIH has demonstrated performance advantageous when compared with other indexing techniques.

A Fast Structural Join Algorithm Based on Partitioning

Structural join is the core part of XML queries and has a significant impact on the performance of XML queries.Several structural join algorithms have been proposed such as Stack-Tree and XR-tree.This paper studies to solve the problem of structural join by partitioning.It first extends the relationships between nodes to the relationships between partitions and get some observations and properties about the relationships between partitions that can be exploited for improving the performance of the structural join algorithms.This paper then proposes a new partition-based structural join method and two optimized methods based on the properties derived from these observations.Extensive experiments show that the performance of the proposed algorithms is better than that of Stack-Tree and XR-tree algorithms.In order to store the partitioning results,the authors design a simple but efficient index structure.The experimental result shows that the index structure has less maintenance overhead than XR-tree.

Structural Join and Staircase Join Algorithms of Sibling Relationship

The processing of XML queries can result in evaluation of various structural relationships. Efficient algorithms for evaluating ancestor-descendant and parent-child relationships have been proposed. Whereas the problems of evaluating preceding-sibling-following-sibling and preceding-following relationships are still open. In this paper, we studied the structural join and staircase join for sibling relationship. First, the idea of how to filter out and minimize unnecessary reads of elements using parent's structural information is introduced, which can be used to accelerate structural joins of parent-child and preceding-sibling-following-sibling relationships. Second, two efficient structural join algorithms of sibling relationship are proposed. These algorithms lead to optimal join performance: nodes that do not participate in the join can be judged beforehand and then skipped using B+-tree index. Besides, each element list joined is scanned sequentially once at most. Furthermore, output of join results is sorted in document order. We also discussed the staircase join algorithm for sibling axes. Studies show that, staircase join for sibling axes is close to the structural join for sibling axes and shares the same characteristic of high efficiency. Our experimental results not only demonstrate the effectiveness of our optimizing techniques for sibling axes, but also validate the efficiency of our algorithms. As far as we know, this is the first work addressing this problem specially.

An Index for Supporting XML Structural Join Efficiently and Effectively—CATI

An Index for Supporting XML Structural Join Efficiently and Effectively—CATI

Structural Join Algorithm for Sequential Regular Path Expressions

XML queries employ regular path expressions to find structural patterns within XML documents. The operation of structural join is a crucial part of XML query processing. Existing approaches reduce complex join expressions to several binary structural joins. It implies generation of superfluous intermediate data. In this paper, we propose a new structural join algorithm, called sequence join algorithm, for sequential regular path expressions. It exploits information about position of the elements in the document to skip generation of the redundant intermediate lists. The algorithm performs merge of several input lists of nodes in one pass. Experimental results prove the structural join algorithm is better than multiple binary join algorithm for queries of both small and large cardinality.