Abstract: A method, system, and computer readable medium for collecting statistics associated with data in a database are disclosed. The method comprises determining an amount of memory needed to collect statistics for data associated with a defined data type in a relational database. The defined data type is based upon a mark-up language using a tree structure with one or more root-to-node paths therein. The amount of memory is allocated as determined for collecting the statistics for the data of the defined data type. A statistics collection is performed for the data of the defined data type in a single pass through the database and within the amount of memory which has been allocated. The performing includes at least determining a total number of instances of at least one path-identifier associated with a given value within a given set of documents.

Abstract: Illustrative embodiments provide a computer-implemented method for hybrid push/pull of continuous structured query language queries. The computer-implemented method receives stream input, wherein the stream input comprises events of interest, builds and a state machine and stream plans, based on an original query, and replicates the stream input. Responsive to a push sub-query trigger, the computer-implemented method submits a pull sub-query to the database to produce a result, and sends the result to a requester.

Abstract: Disclosed are a system, method, and computer readable medium for collecting statistics associated with data in a database. The method comprises determining an amount of memory needed to collect statistics for data associated with a defined data type in a relational database. The defined data type is based upon a mark-up language using a tree structure with one or more root-to-node paths therein. The amount of memory as determined is allocated for collecting the statistics for the data of the defined data type. A statistics collection is performed for the data of the defined data type in a single pass through the database and within the amount of memory which has been allocated.

Abstract: Disclosed are a method for collecting statistics associated with data in a database. The method comprises determining an amount of memory needed to collect statistics for data associated with a defined data type in a relational database. The defined data type is based upon a mark-up language using a tree structure with one or more root-to-node paths therein. The amount of memory as determined is allocated for collecting the statistics for the data of the defined data type. A statistics collection is performed for the data of the defined data type in a single pass through the database and within the amount of memory which has been allocated.

Abstract: Techniques are disclosed for selecting a delete-safe compression method for a plurality of delta encoded data values (e.g., delta encoded integers or deltas). For example, a computer-implemented method for selecting an optimal delete-safe compression algorithm from among two or more compression algorithms for use on a plurality of delta encoded data values includes the following steps. The maximum number of data values eliminated by each of the two or more compression algorithms is computed. For the plurality of delta encoded data values to be compressed, the minimum size of the plurality of delta encoded data values before compression thereof is computed. A delete-safe threshold value is computed based on the minimum size of the plurality of delta encoded data values. Then, the compression algorithm is selected from the two or more compression algorithms that achieves the delete-safe threshold value.

Abstract: Techniques are disclosed for encoding a variable length structure such that it facilitates forward and reverse scans of a list of such structures as needed. While the techniques are applicable to a wide variety of applications, they are particularly well-suited for use with structures such as those found in compressed database indexes. For example, a computer-implemented method for processing one or more variable length data structures includes the following steps. Each variable length data structure is obtained. Each variable length structure comprises one or more data block. A variable length encoding process is applied to the one or more blocks of each variable length data structure which comprises setting a continuation data value in each block to a first value or a second value, wherein the setting of the continuation data values enables bi-directional scanning of each variable length structure.

Abstract: A system, method, and computer readable medium for optimizing throughput of a stream processing system are disclosed. The method comprises analyzing a set of input streams and creating, based on the analyzing, an input profile for at least one input stream in the set of input streams. The input profile comprises at least a set of processing requirements associated with the input stream. The method also comprises generating a search space, based on an initial configuration, comprising a plurality of configurations associated with the input stream. A configuration in the plurality of configurations is identified that increases throughput more than the other configurations in the plurality of configurations based on at least one of the input profile and system resources.

Abstract: A system for providing consistency guarantees in a data stream processing engine. Consistency tracking information is attached to data streams coming into the data stream processing engine. The consistency tracking information is propagated through a plurality of streaming operators that process the data streams within the data stream processing engine. Then, the propagated consistency tracking information is used to detect a consistent state in an output stream.

Abstract: A system, method, and computer readable medium for preserving information in time variant data schemas are disclosed. The method includes determining if at least one modification request associated with a database schema has been received. In response to the modification request being received, a metadata table associated with the database schema is updated to include at least one entry associated with the modification request. The entry identifies an instance in time when an action associated with the modification request was performed.

Abstract: A computer-implemented method is provided for performing key lookups. The method comprises accessing a header of a given one of a plurality of nodes in a tree-based data index structure. The given node comprises the header and a plurality of partitions. Each partition comprises at least one key. The header of the given node comprises a selected key from each of a selected plurality of the partitions. The method also comprises choosing, using a search key, a selected key in the header. The method further comprises accessing a partition corresponding to the chosen selected key and selecting, using the search key, one of the at least one keys in the accessed partition. The selected one of the at least one keys can be used to access another of the plurality of nodes. Yet additional methods, apparatus, and program products are disclosed.

Abstract: A system, method, and computer readable medium for optimizing throughput of a stream processing system are disclosed. The method comprises analyzing a set of input streams and creating, based on the analyzing, an input profile for at least one input stream in the set of input streams. The input profile comprises at least a set of processing requirements associated with the input stream. The method also comprises generating a search space, based on an initial configuration, comprising a plurality of configurations associated with the input stream. A configuration in the plurality of configurations is identified that increases throughput more than the other configurations in the plurality of configurations based on at least one of the input profile and system resources.

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: A method for collecting statistics associated with data in a database are disclosed. The method comprises determining an amount of memory needed to collect statistics for data associated with a defined data type in a relational database. The defined data type is based upon a mark-up language using a tree structure with one or more root-to-node paths therein. The amount of memory is allocated as determined for collecting the statistics for the data of the defined data type. A statistics collection is performed for the data of the defined data type in a single pass through the database and within the amount of memory which has been allocated. The performing includes at least determining a total number of instances of at least one path-identifier associated with a given value within a given set of documents.

Abstract: A system for determining relationships between hierarchically structured schema components and their effects on and content of tuples, includes: analyzing the hierarchically structured schema with user-supplied mappings and finding elements or attributes mapped to a same relational table; determining relationships between the elements or attributes to be either a one-to-one relationship or a one-to-many relationship based on an information set in the hierarchically structured schema; recording the relationships; and processing a hierarchically structured document against the recorded relationships and generating tuples accordingly. The constructs of a hierarchically structured schema that may affect the cardinality between the attributes of a relation, and thus the contents of the tuples, are considered. A relationship between the hierarchically structured schema model and a relational model is established.

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 method, information processing system, and computer readable medium for modifying at least one data warehouse schema based on detected changes in an associated observation model are disclosed. The method includes determining if at least one new observation model has been created. The method also includes determining if at least one existing observation model is associated with the new observation model. In response to the existing observation model being associated with the new observation model, at least one changed attribute is identified by comparing the new observation model and the existing observation model. A set of files associated with the existing observation model is updated to reflect the changed attribute between the new observation model and the existing observation model.

Abstract: A method, information processing system, and computer readable medium for modifying at least one data warehouse schema based on detected changes in an associated observation model are disclosed. The method includes determining if at least one new observation model has been created. The method also includes determining if at least one existing observation model is associated with the new observation model. In response to the existing observation model being associated with the new observation model, at least one changed attribute is identified by comparing the new observation model and the existing observation model. A set of files associated with the existing observation model is updated to reflect the changed attribute between the new observation model and the existing observation model.

Abstract: A computer implemented method, data processing system, and computer usable program code are provided for accessing unique hierarchical data. A tree structure for a document is analyzed. A determination is made as to whether a set of unique paths exist in the tree structure. Responsive to an existence of the set of unique paths, a unique path identifier is assigned to each of the set of unique paths to create a set of unique path identifiers and assigned unique path pairs. Then, the unique path identifier and a node address for the unique hierarchical data for each of the set of unique path identifiers and assigned unique path pairs is stored into a header in the document disk page.

Abstract: A method and computer program for processing structured documents follows a processing framework that enables generation of events corresponding to instance document elements and events corresponding to definition components in a single serial process. The process comprises creating a graph data structure in which nodes of the graph represent components of a document definition. The process further involves reading an instance document conforming to the document definition, identifying elements of the document that correspond to nodes of the graph, identifying a path between nodes of the graph that correspond to elements of the document, and traversing the path to generate a start event when moving from a parent node to a child node and an end event when moving from a child node to a parent node.

Abstract: A method and system that allows efficient shredding of large instances of hierarchical data structures into relational data structures. Large instances of hierarchical data structures, which are able to be larger than the random access storage of a computer used to shred them into relational data structures, are incrementally shredded into a temporary storage. When the amount of data shredded into the temporary storage reaches or exceeds a predetermined commit count, the data in the temporary storage is transferred to a relational data structure maintained by a relational database manager. A Document Type Description annotation is provided to allow the end user to specify execution order for SQL commands and to specify commit count values.