Abstract: Techniques for estimating items (e.g., data item or objects) frequencies in large data sets are disclosed. For example, a technique for determining items and their frequencies at multiple levels of interest in a collection of nested bags includes the following steps. A hierarchy of a plurality of levels of nested bags and the levels of interest are inputted. Among the plurality of levels, a subset of bags is sampled from at least one level. At each level of interest, the frequency is counted of each distinct item in the bags obtained in the sampling step. At each level of interest, the item frequencies obtained in the counting step are extrapolated based on sampling ratios associated with the sampling step. At each level of interest, the items are sorted according to their frequencies obtained from the extrapolating step and those items with highest frequencies are retained. A bag may refer to one or more subsets or groups of data items or objects. Also, a bag may, itself, contain one or more other bags.

Abstract: Techniques are provided for automatically rewriting a relational-to-hierarchical mapping into one or more modified mappings. In this way, clients that prefer or require different portions of the mapping-defined data are supported. For example, in one aspect of the invention, a technique for modifying a relational-to-hierarchical mapping in accordance with at least one user query includes the following steps/operations. At least one query associated with a query language that supports a hierarchical data structure is obtained. Further, at least one relational-to-hierarchical mapping for use in translating data associated with a relational data structure into data associated with the hierarchical data structure is obtained. Then, the at least one relational-to-hierarchical mapping is modified based on the at least one query such that data specifically relevant to the at least one query may be generated in accordance with the modified relational-to-hierarchical mapping.

Abstract: A tagging tree that defines a hierarchical output data structure and relational database query operations that retrieve the data to be included in each hierarchical section is accepted and processed. A query optimizer analyzes the tagging tree to determine database query operations that can be combined into a single query command. An outer-union query command is generated to allow efficient combination of multiple query commands, some of which are predicates to others. The tagging tree is modified to replace the database queries that were combined into the outer-union query to extract data from the results set produced by the outer-union query as opposed to submitting queries to the database manager. The optimized queries can be reused an arbitrary number of times to leverage the optimizing resources that were used in their creation.

Abstract: Tagging trees are generated and used to facilitate transforming data from relational databases into hierarchical formats, such as in XML documents. Tagging trees contain both XML hierarchical structure information as well a query information that is needed to access different data sources, e.g., databases, to retrieve the information to be placed in the hierarchical structure. A designer optionally creates a mapping script that specifies the transformation from relational databases to the hierarchical format. A tagging tree is created by either parsing that mapping script or by other means. A runtime environment then processes the tagging tree by a depth first traversal. The runtime environment is able to be configured to output a hierarchical data object, such as an XML document, or pipelined to control, for example, SAX processing.

Abstract: A method, a system and recording medium for maintaining the order of nodes in a hierarchical document. The method may select the maximum and the minimum number of children for each node, build an auxiliary ordered tree having at least as many leaves as atoms within the hierarchical document based upon the selected maximum and minimum number of children for each node, attach the atoms to the leaves of the auxiliary ordered tree, and label each of the nodes in the auxiliary ordered tree.

Abstract: A system, method and computer readable medium for translating data in a hierarchical data structure to a relational data structure is disclosed. The method on an information processing system includes reading a hierarchical data abiding to a hierarchical data structure for holding data and traversing the hierarchical data structure using a tree traversal algorithm. The method further includes generating, in accordance with an external mapping script, a mapping for translating data from the hierarchical data structure to a relational data structure. The method further includes reading a hierarchical data structure including data and translating the data of the hierarchical data structure to the relational data structure using the mapping and using a depth-first traversal algorithm.