XML query languages typically allow the specification of structural patterns using XPath. Usually, these structural patterns are in the form of trees (Tree-Pattern Queries-TPQs). Finding the occurrences of such patterns in an XML tree is a key operation in XML query evaluation. The multiple previous algorithms presented for this operation focus mainly on the evaluation of tree-pattern queries. Recently, requirements for flexible querying of XML data have motivated the consideration of query classes that are more expressive and flexible than TPQs for which efficient nonmain-memory evaluation algorithms are not known. In this paper, we consider a class of queries, called Partial Tree-Pattern Queries (PTPQs), which generalize and strictly contain TPQs. PTPQs represent a broad fragment of XPath which is very useful in practice. In order to process PTPQs, we introduce a set of sound and complete inference rules to characterize structural relationship derivation. We provide necessary and sufficient conditions for detecting query unsatisfiability and node redundancy. We also show that PTPQs can be represented as directed acyclic graphs augmented with the “same-path” constraints. In order to leverage existing efficient evaluation algorithms for less expressive classes of queries, we design two approaches that evaluate a PTPQ by decomposing it into a set of simpler queries: algorithm IndexTPQGen, exploits a structural summary of the XML data and evaluates a PTPQ by generating an equivalent set of TPQs and unioning their answers. Algorithm PartialPathJoin decomposes the PTPQ into partial-path queries, and merge-joins their solutions. We also develop PartialTreeStack, an original polynomial time holistic algorithm for PTPQs. To the best of our knowledge, this is the first algorithm to support the evaluation of such a broad structural fragment of XPath in the inverted lists evaluation model. We provide a theoretical analysis of our algorithm and identify cases where it is asymptotically optimal. An extensive experimental evaluation shows that it is more efficient, robust, and stable than the other two and it outperforms a state-of-the art XQuery engine on PTPQs.

Query processing techniques for XML data have focused mainly on tree-pattern queries (TPQs). However, the need for querying XML data sources whose structure is very complex or not fully known to the user, and the need to integrate multiple XML data sources with different structures have driven, recently, the suggestion of query languages that relax the complete specification of a tree pattern. In order to implement the processing of such languages in current DBMSs, their containment problem has to be efficiently solved.

Finding the occurrences of structural patterns in XML data is a key operation in XML query processing. Existing algorithms for this operation focus almost exclusively on path-patterns or tree-patterns. Requirements in flexible querying of XML data have motivated recently the introduction of query languages that allow a partial specification of path-patterns in a query. In this paper, we focus on the efficient evaluation of partial path queries, a generalization of path pattern queries. Our approach explicitly deals with repeated labels (that is, multiple occurrences of the same label in a query).

XML query languages typically allow the specification of structural patterns of elements. Finding the occurrences of such patterns in an XML tree is the key operation in XML query processing. Many algorithms have been presented for this operation. These algorithms focus mainly on the evaluation of path-pattern or tree-pattern queries. In this paper, we define a partial path-pattern query language, and we address the problem of its efficient evaluation on XML data.

The wide adoption of XML has increased the interest of the database community on tree-structured data management techniques. Querying capabilities are provided through tree-pattern queries. The need for querying tree-structured data sources when their structure is not fully known, and the need to integrate multiple data sources with different tree structures have driven, recently, the suggestion of query languages that relax the complete specification of a tree pattern. In this paper, we use a query language which allows partial tree-pattern queries (PTPQs). The structure in a PTPQ can be flexibly specified fully, partially or not at all. To evaluate a PTPQ, we exploit index graphs which generate an equivalent set of "complete" tree-pattern queries.In order to process PTPQs, we need to efficiently solve the PTPQ satisfiability and containment problems. These problems become more complex in the context of PTPQs because the partial specification of the structure allows new, non-trivial, structural expressions to be derived from those explicitly specified in a PTPQ. We address the problem of PTPQ satisfiability and containment in the absence and in the presence of index graphs, and we provide necessary and sufficient conditions for each case. To cope with the high complexity of PTPQ containment in the presence of index graphs,we study a family of heuristic approaches for PTPQ containment based on structural information extracted from the index graph in advance and on-the-fly. We implement our approaches and we report on their extensive experimental evaluation and comparison.

Nowadays, huge volumes of data, including scientific data, are organized or exported in tree-structured form. Querying capabilities are provided through tree-pattern queries. The need for integrating multiple data sources with different tree structures has driven, recently, the suggestion of query languages that relax the complete specification of a tree pattern. In this paper we adopt a query language with partially specified tree-pattern queries. A central feature of this type of queries is that the structure can be specified fully, partially, or not at all in a query. Important issues in query optimization require solving the query containment problem. We study the containment problem for partially specified tree-pattern queries. To support the evaluation of such queries, we use semantically rich constructs, called dimension graphs, which abstract structural information of the tree-structured data. We address the problem of query containment in the absence (absolute query containment) and in the presence (relative query containment) of dimension graphs, and we provide necessary and sufficient conditions for each type of query containment. We suggest a technique for relative query containment checking based on structural information extracted in advance from the dimension graph. Our approach is implemented and validated through extensive experimental evaluation.