Abstract: A computer-implemented method can include identifying one or more candidate topics from a query. The method can generate, for each candidate topic, a candidate topic-answer pair that includes both the candidate topic and an answer to the query for the candidate topic. The method can obtain search results based on the query, wherein one or more of the search results references an annotated resource. For each candidate topic-answer pair, the method can determine a score for the candidate topic-answer pair for use in determining a response to the query, based on (i) an occurrence of the candidate topic in the annotations of the resources referenced by one or more of the search results, and (ii) an occurrence of the answer in annotations of the resources referenced by the one or more search results, or in the resources referenced by the one or more search results.

Abstract: A method, information processing system, and computer program storage product optimize the placement of database objects on a multiplicity of storage devices. A set of database objects are placed on a first storage device in a multiplicity of storage devices. Each storage device comprises differing characteristics. A query workload is run on the set of database objects that have been placed on the first storage device. Profiling information associated with the query workload that is running is collected. A subset of database objects is selected from the set of the database objects to be stored on a second storage device. The subset of database objects is stored on the second storage device and all remaining database objects in the set of database objects on the first storage device.

Abstract: A computer-implemented method can include identifying one or more candidate topics from a query. The method can generate, for each candidate topic, a candidate topic-answer pair that includes both the candidate topic and an answer to the query for the candidate topic. The method can obtain search results based on the query, wherein one or more of the search results references an annotated resource. For each candidate topic-answer pair, the method can determine a score for the candidate topic-answer pair for use in determining a response to the query, based on (i) an occurrence of the candidate topic in the annotations of the resources referenced by one or more of the search results, and (ii) an occurrence of the answer in annotations of the resources referenced by the one or more search results, or in the resources referenced by the one or more search results.

Abstract: A method, information processing system, and computer program storage product optimize the placement of database objects on a multiplicity of storage devices. A set of database objects are placed on a first storage device in a multiplicity of storage devices. Each storage device comprises differing characteristics. A query workload is run on the set of database objects that have been placed on the first storage device. Profiling information associated with the query workload that is running is collected. A subset of database objects is selected from the set of the database objects to be stored on a second storage device. The subset of database objects is stored on the second storage device and all remaining database objects in the set of database objects on the first storage device.

Abstract: A method, information processing system, and computer program storage product optimize the placement of database objects on a multiplicity of storage devices. A set of database objects are placed on a first storage device in a multiplicity of storage devices. Each storage device comprises differing characteristics. A query workload is run on the set of database objects that have been placed on the first storage device. Profiling information associated with the query workload that is running is collected. A subset of database objects is selected from the set of the database objects to be stored on a second storage device. The second storage device is a separate physical device from, and performs faster than, the first storage device. The subset of database objects is stored on the second storage device and all remaining database objects in the set of database objects on the first storage device.

Abstract: A method, system, and computer readable medium for collecting statistics associated with data in a database are disclosed. The computer readable medium implements 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: 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: 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 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: 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: 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: Providing consistency guarantees in a data stream processing engine is provided. 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: 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: 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 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 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.

Abstract: A method, information processing system, and computer program storage product optimize the placement of database objects on a multiplicity of storage devices. A set of database objects are placed on a first storage device in a multiplicity of storage devices. Each storage device comprises differing characteristics. A query workload is run on the set of database objects that have been placed on the first storage device. Profiling information associated with the query workload that is running is collected. A subset of database objects is selected from the set of the database objects to be stored on a second storage device. The second storage device is a separate physical device from, and performs faster than, the first storage device. The subset of database objects is stored on the second storage device and all remaining database objects in the set of database objects on the first storage device.