Abstract: Various operations, functionalities and systems are described herein for backing up one or more node to an offsite location, restoring the one or more node from the offsite location, restoring the one or more node to a point-in-time (PIT) from the offsite location, cloning the one or more node from the offsite location, and cloning the one or more node to a PIT from the offsite location. Example operating contexts include one or more cluster of nodes running a NoSQL (Not only Structured Query Language) distributed database and backup, restore and/or cloning on those one or more cluster of nodes.

Abstract: Various operations, functionalities and systems are described herein for backing up one or more node to an offsite location, restoring the one or more node from the offsite location, restoring the one or more node to a point-in-time (PIT) from the offsite location, cloning the one or more node from the offsite location, and cloning the one or more node to a PIT from the offsite location. Example operating contexts include one or more cluster of nodes running a NoSQL (Not only Structured Query Language) distributed database and backup, restore and/or cloning on those one or more cluster of nodes.

Abstract: A system for exploring data receives the data from a database and indexes the data in a server. The system displays one or more selectable datasets from the indexed data, where the selected dataset includes one or more attributes. The system then sorts the one or more attributes by level of interestingness and displays the sorted attributes.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving queries, and for each received query: receiving data indicating resources identified by a search operation as being responsive to the query, wherein the search operation scores each of the resources based, in part, on features of the resource and the query, selecting a subset of the resources, determining, from the subset of resources and for each of the features of the resources and the query, an impact measure that measures the impact of the feature on the ranking of the resources that belong to the subset, adjusting the search operation based on the respective impact measures, and initiating the search operation to re-score the resources in the subset of resources based, in part, on the adjustment and to rank the subset of resources according to a second order that is different from the first order.

Abstract: A computer-implemented method for determining an index of an object in a sequence of objects. It is frequently needed to determine an index of an object in a sequence for example in order to request the next object in the sequence. Typically, databases do not include nested records that reference previous/next records. The method provides an improved process for determining an index of an object in a sequence of objects, which may also, in case of no exact match for requested object, provide an index of the object closest to the requested one.

Abstract: An approach is provided for managing a reorganization of a database object. Because a reorganization utility cannot acquire exclusive access to the object to complete the reorganization, determinations are made: an amount of transaction log records corresponding to active units of work using the database object is determined to be less than a first threshold; a sum of costs of SQL statements executed in the units of work is determined to be less than a second threshold; and a priority of the reorganization is determined to indicate a greatest priority among multiple priorities. Based on the determinations, (1) a reorganization lock providing exclusive access to the database object is acquired, (2) process(es) holding lock(s) on the database object experience a lockout error, a rollback of the process(es) is issued, and the lock(s) are released, and (3) the utility completes the reorganization based on the lock(s) being released.

Abstract: Conventionally, in addition to indexing, a synopsis of a base table of a database is used to skip and compress data. However, scanning of the entire synopsis for all queries is required, which takes a long time when the synopsis gets significantly big in a large data warehouse. A method for efficient data skipping and compression through vertical partitioning of data is provided to eliminate the cost of synopsis storage overhead while enabling the synopsis search functionality.

Abstract: A method is used in managing deletion of replicas of files. A request to delete a set of replicas of a file of a file system is received. A replica of the file represents a state of the file at a particular prior point in time. A destination replica is identified. A set of file system blocks shared between a replica of the set of replicas and the destination replica is de-allocated by updating metadata of the destination replica. File system blocks associated with the set of replicas are de-allocated. A subset of the file system blocks are de-allocated concurrently.

Abstract: A method, executed by an electronic apparatus, includes retrieving, in response to input of a character string by a user, conversion candidates associated with the input character string, each conversion candidate having a first rank. The method also includes displaying, when a plurality of the conversion candidates are present, the plurality of conversion candidates within a corresponding plurality of regions on a map wherein conversion candidates that have a higher first rank occupy larger regions on the map. A corresponding computer program product and corresponding computer systems are also disclosed herein.

Abstract: A query that requests a filter attribute is received by a database server from a remote application server that is associated with a calculation scenario that defines a data flow model including one or more calculation nodes. Subsequently, the database server instantiates the calculation scenario. As part of the instantiation, the calculation scenario is optimized by (i) pushing down a filter attribute from a first node to a lowest available child node, (ii) removing the filter attribute from the first node, and (iii) removing non-required join-attributes from the instantiated calculation scenarios. Thereafter, the operations defined by the calculation nodes of the instantiated calculation scenario can be executed to result in a responsive data set. Next, the data set is provided to the application server by the database server.

Abstract: Methods and systems are disclosed for real-time transactional database transformation implemented as part of a real-time transactional database management system.

Abstract: A method, executed by at least one processor, includes receiving a migration request for a plurality of files, assigning files of the plurality of files that are smaller than a selected size to one or more small-file secondary storage devices, assigning files of the plurality of files that are larger than the selected size to one or more large-file secondary storage devices, and initiating migration of the plurality of files from one or more primary storage devices to the secondary storage devices to which they are assigned. A corresponding computer program product and computer system are also disclosed herein.

Abstract: Disclosed aspects include managing an application bundle for processing a stream of tuples. The stream of tuples to be processed by a plurality of processing elements operating on a set of compute nodes is received. The stream of tuples is processed on a first compute node using the application bundle. A staleness factor with respect to the application bundle is detected by the first compute node. Based on a maintenance criterion related to both the application bundle and the plurality of processing elements, the application bundle is maintained on the first compute node.

Abstract: Herein is described a data-parallel algorithm for topic modeling in which the memory requirements are streamlined for implementation on a highly-parallel architecture, such as a GPU. Specifically, approximate counters are used in a large mixture model or clustering algorithm (e.g., an uncollapsed Gibbs sampler) to decrease memory usage over what is required when conventional counters are used. The decreased memory usage of the approximate counters allows a highly-parallel architecture with limited memory to process more computations for the large mixture model more efficiently. Embodiments describe binary Morris approximate counters, general Morris approximate counters, and Csrös approximate counters in the context of an uncollapsed Gibbs sampler, and, more specifically, for a Greedy Gibbs sampler.

Abstract: Herein is described a data-parallel algorithm for topic modeling on a distributed system in which memory and communication bandwidth requirements are streamlined for distributed implementation. According to embodiments, a distributed LDA Gibbs sampling algorithm shares approximate counter values amongst the nodes of a distributed system. These approximate counter values are repeatedly aggregated and then shared again to perform the distributed LDA Gibbs sampling. In order to maintain the shared counter values as approximate counter values of sixteen bits or less, approximate counter values are summed to produce aggregate approximate counter values. These small aggregate approximate counter values are shared between the nodes of the distributed system. As such, the addition of various types of approximate counters is described herein.