On boosting holism in XML twig pattern matching using structural indexing techniques

Abstract

Searching for all occurrences of a twig pattern in an XML document is an important operation in XML query processing. Recently a holistic method T wigStack [2] has been proposed. The method avoids generating large intermediate results which do not contribute to the final answer and is CPU and I/O optimal when twig patterns only have ancestor-descendant relationships. Another important direction of XML query processing is to build structural indexes [3][8] [13][15] over XML documents to avoid unnecessary scanning of source documents. We regard XML structural indexing as a technique to partition XML documents and call it streaming scheme in our paper. In this paper we develop a method to perform holistic twig pattern matching on XML documents partitioned using various streaming schemes. Our method avoids unnecessary scanning of irrelevant portion of XML documents. More importantly, depending on different streaming schemes used, it can process a large class of twig patterns consisting of both ancestordescendant and parent-child relationships and avoid generating redundant intermediate results. Our experiments demonstrate the applicability and the performance advantages of our approach.

A bi-labeling based XPath processing system

“…To process tree queries that contain only descendant axes, algorithms with time complexity linear in the size of the input and output have been proposed [11]. Specialized indexes for optimizing joins over D-labels have also been designed [ 12,17,30,43]. The problem of optimizing joins translated from XQuery queries was studied [9], such as handling joins embedded in nested for-loops, recognizing join patterns in a way that is immune to syntactic variance in the query, and avoiding expensive sorting operations.…”

FMware: Middleware for Efficient Filtering and Matching of XML Messages with Local Data

“…Since in a streaming environment data itself is distributed and available in pieces, such holistic approaches, which are shown to work well for static XML data, are not applicable. Many existing (binary or holistic) structural join operators, including TwigStack, PathStack [19], iTwigJoin [20], Stack-Tree-Desc/Anc [21], EE/EA-Join [22], and TSGeneric [23], are specially designed variants of the standard sort-merge join algorithm: they require that the ancestor and descendant (a) AD labels (b) SES labels ViST-style SES-labeling of the same collection [26] lists be available in a structurally sorted order before the join operation can be performed ( Figure 4). Consequently, these sort-merge based schemes face the problems common in traditional sort-merge-joins: (a) they risk being blocking (for sorting the inputs) or (b) they constrain query plans to only those that can provide appropriately sorted inputs.…”

“…APEX [46] is similar to DataGuides and T-Indexes, but it only maintains frequent paths. [20] notes that a combination of XML indexing methods can be useful for improving stream-based processing of structural queries, since different schemes are better for different classes of XML twig patterns. Similarly, in (XDG) [28], node labels are indexed by a term index T-Index, which gives the sequence of all nodes with the same label in the XDG.…”

A Prime Number Approach to Matching an XML Twig Pattern including Parent-Child Edges

“…The labelling scheme must enable determination of all structural relationships by computation. In order to detect the twig patterns, previous algorithms need to access only the labels corresponding to the query nodes without traversing the original XML tree by utilizing a clustering mechanism called tag streaming where all elements with the same tag are grouped together (Chen et al, 2005). The alternative usually summarizes all paths in an XML document starting from the root.…”