A fast index for semistructured data

The most promising and dominant data format for data processing and representation on the Internet is the semistructured data form termed XML. XML data has no fixed schema; it evolved and is self describing which results in management difficulties compared to, for example, relational data. It is therefore a major challenge for the database community to design query processing techniques and storage methods that can retrieve semistructured data efficiently. In this paper, we present a querying scheme for semistructured data views of relational form. The proposed technique stores element-paths, attributes, contents of the element paths and attributes, and XML processing instructions in a dynamic relational structure termed as Multi-XML-Data-Structure (MXDS).

Lecture Notes in Computer Science, 1999

XML queries are based on path expressions which are composed of some elements connected to each other in a tree pattern structure, called Query Tree Pattern (QTP). Thus, the core operation of XML query processing is finding all instances of QTP in the XML document. A number of methods are offered for QTP matching, but they process too many elements in XML document while most of them have no opportunity to participate in the final result. The exiting techniques have lots of limitations and disadvantages that are illustrated in detail in Chapter III. In this thesis, the author proposes a novel method which doesn't blindly processes elements of the document. The author abstracts structural relationships inside the XML documents to evaluate the XML queries. In contrast to the existing methods, in the proposed method only elements which have a chance to produce a result are processed and those which are definitely not part of any final result are ignored. An XML query is either a cha...

Advances in Database Technology - EDBT 2004, 2004

In this paper we present HOPI, a new connection index for XML documents based on the concept of the 2-hop cover of a directed graph introduced by Cohen et al. In contrast to most of the prior work on XML indexing we consider not only paths with child or parent relationships between the nodes, but also provide space-and time-efficient reachability tests along the ancestor, descendant, and link axes to support path expressions with wildcards in our XXL search engine. We improve the theoretical concept of a 2-hop cover by developing scalable methods for index creation on very large XML data collections with long paths and extensive cross-linkage. Our experiments show substantial savings in the query performance of the HOPI index over previously proposed index structures in combination with low space requirements.

Proceedings 2004 VLDB Conference, 2004

As XML usage grows for both data-centric and document-centric applications, introducing native support for XML data in relational databases brings significant benefits. It provides a more mature platform for the XML data model and serves as the basis for interoperability between relational and XML data. Whereas query processing on XML data shredded into one or more relational tables is well understood, it provides limited support for the XML data model. XML data can be persisted as a byte sequence (BLOB) in columns of tables to support the XML model more faithfully. This introduces new challenges for query processing such as the ability to index the XML blob for good query performance. This paper reports novel techniques for indexing XML data in the upcoming version of Microsoft® SQL Server™, and how it ties into the relational framework for query processing.

2003

With the growing importance of XML in data exchange, much research has been done in providing flexible query facilities to extract data from structured XML documents. In this paper, we propose ViST, a novel index structure for searching XML documents. By representing both XML documents and XML queries in structure-encoded sequences, we show that querying XML data is equivalent to finding subsequence matches. Unlike index methods that disassemble a query into multiple sub-queries, and then join the results of these sub-queries to provide the final answers, ViST uses tree structures as the basic unit of query to avoid expensive join operations. Furthermore, ViST provides a unified index on both content and structure of the XML documents, hence it has a performance advantage over methods indexing either just content or structure. ViST supports dynamic index update, and it relies solely on B + Trees without using any specialized data structures that are not well supported by DBMSs. Our experiments show that ViST is effective, scalable, and efficient in supporting structural queries.

Journal of Computing and Information Technology

Querying nested data has become one of the most challenging issues for retrieving desired information from the Web. Today diverse applications generate a tremendous amount of data in different formats. These data and information exchanged on the Web are commonly expressed as nested representation such as XML, JSON, etc. Unlike the traditional database system, they do not possess a rigid schema. In general, the nested data is managed by storing data and its structures separately which significantly reduces the performance of data retrieving. Ensuring efficiency of processing queries which locates the exact positions of the elements has become a big challenging issue. There are different indexing structures which have been proposed in the literature to improve the performance of the query processing on the nested structure. Most of the past researches on nested structure concentrate on the structure alone. This paper proposes new index structure which combines siblings of the terminal nodes as one path which efficiently processes twig queries with less number of lookups and joins. The proposed approach is compared with some of the existing approaches. The results also show that they are processed with better performance compared to the existing ones. ACM CCS (2012) Classification: → Information systems → Data management systems → Query language Information systems → World Wide Web → Web searching and information discovery → Web search engines → Web indexing

The explosive growth of XML has led to an increasing need for scalable XML retrieval systems. Our XML retrieval system, the SQLGenerator, stores XML of any schema in a fixed schema relational database and supports a fullfeatured semistructured query language, XML-QL, through optimized translation of its semantics to relational SQL queries. This paper examines the scalability of this approach with respect to increasing data size. We index four XML collections ranging in size from 500MB to 2GB that were generated using a standard XML generator, XBench. We then compare the execution times of 11 standard XBench queries, covering a wide range of semistructured query features, whose semantics were directly translatable from their original XQuery language to XML-QL. Although it is difficult to estimate the theoretical baseline for scalability of these query features in an RDBMS, many of the queries' runtimes grow linearly with respect to the size of the document collection.

2004

Abstract Path expressions are ubiquitous in XML processing languages. Existing approaches evaluate a path expression by selecting nodes that satisfies the tag-name and value constraints and then joining them according to the structural constraints. We propose a novel approach, next-of-kin (NoK) pattern matching, to speed up the node-selection step, and to reduce the join size significantly in the second step.

Indexing XML data to facilitate query processing has been a popular subject of study in recent years. Most of previous studies can be classified into three categories: path indexing, node indexing and sequence-based indexing. Many of them cannot answer both single-path and branching queries with various value predicates very efficiently. In this paper, we propose a novel compact tree (Ctree) structure, which provides not only concise path summaries but also detailed element relationships, and a configurable index scheme based on data statistics. We develop an efficient Ctree-based method for processing a tree structure query with various value constraints. Efficiency of our method is achieved by: (1) summarizing a large database into a condensed structure view to prune irrelevant search space; (2) evaluating a tree structure query directly without expensive join operations; (3) using Ctree properties such as trivial groups and bi-direction to reduce query processing time; (4) using ...