Towards a physical XML independent XQuery/SQL/XML engine

Abstract

There has been a lot of research and industrial effort on building XQuery engines with different kinds of XML storage and index models. However, most of these efforts focus on building either an efficient XQuery engine with one kind of XML storage, index, view model in mind or a general XQuery engine without any consideration of the underlying XML storage, index and view model. We need an underlying framework to build an XQuery engine that can work with and provide optimization for different XML storage, index and view models. Besides XQuery, RDBMSs also support SQL/XML, a standard language that integrates XML and relational processing. There are industrial efforts for building hybrid XQuery and SQL/XML engines that support both languages so that users can manage and query both relational and XML data on one platform. However, we need a theoretical framework to optimize both SQL/XML and XQuery languages in one RDBMS. In this paper, we show our industrial work of building a combined XQuery and SQL/XML engine that is able to work and provide optimization for different kinds of XML storage and index models in Oracle XMLDB. This work is based on XML extended relational algebra as the underlying tuple-based logical algebra and incorporates tree and automata based physical algebra into the logical tuple-based algebra so as to provide optimization for different physical XML formulations. This results in logical and physical rewrite techniques to optimize XQuery and SQL/XML over a variety of physical XML storage, index and view models, including schema aware object relational XML storage with relational indexes, binary XML storage with schema agnostic path-value-order key XMLIndex, SQL/XML view over relational data and relational view over XML. Furthermore, we show the approach of leveraging cost based XML physical rewrite strategy to evaluate different physical rewrite plans.

Multi-model Database Management Systems - A Look Forward

“…For example, relational predicates over XMLTABLE() or JSON_TABLE() views can be written into XPATH/JSON PATH predicates directly navigating the native hierarchical storage of the underlying XML or JSON data [2]. Inversely, XPATH/JSON path query over the views constructed via SQL/XML or SQL/JSON generation functions over relational tables can be written into relational predicate over the underlying relational table storage [2,13]. Table 4 shows applying query rewrite transformation for Q2 and Q3 of Table 3.…”

Research and Implementation of XML Keyword Search Algorithm Based on Semantic Relatives

“…There are many research works on keyword-based search on the XML document, which typically include XRank [1], XKeyword [2], Schema-Free XQuery [3], XSEareh [4] and XKSearch [5], XSeek [6] and so on. In the modeling: XRank [1], XKewyord [2] uses graph-based XML document model, others use tree-based model, but their model is a simple modeling on the XML document schema, and the result set is set to the sub-tree(graph) containing the keyword on the document tree(graph), which is defined as LCA (Lowest Common Ancestor, LCA) (XRank), or its variants, such as SLCA (Smallest Lowest Common Ancestor, SLCA) (XKsearch), MLCA (Meaningful Lowest Common Ancestor, MLCA) (Schema-Free XQuery) and so on.…”

Binary XML storage and query processing in Oracle 11g

“…The index is designed to handle unstructured XML content (by means of a path-value storage) as well as structured content (by means of a property table). Query processing in the presence of these indexes is covered in [18]. In this section, we focus on query processing that leverages the binary XML format assuming that desired documents or fragments might have already been identified by the index.…”

“…We start by briefly introducing the techniques that rewrites XQuery queries into Binary XML specific operators and row sources (constructs that produce rows). A more comprehensive introduction to Oracle's approach to rewrite and normalization can also be found in [18]. Then we present our NFA-based streaming query processing and optimization techniques.…”