Abstract: Embodiments of the present disclosure relate to a method, an electronic device, and a computer program product for identifying a memory snapshot. The method includes determining, based on operation-related historical information for a plurality of memory snapshots, a probability that the plurality of memory snapshots are operated within a first time period. The method further includes, if the determined probability is less than a threshold associated with a duration of the first time period, identifying the plurality of memory snapshots for deletion. By use of the method, memory snapshots with a low probability of being operated in a future period of time can be identified, so that such memory snapshots are deleted to reduce usage of storage resources.

Abstract: An embodiment identifies a fileset used by an executing application. An embodiment generates, at a first time, a first snapshot of the fileset, the first snapshot comprising a first state of the fileset at the first time and a first indicator corresponding to the first state of the fileset. An embodiment selects, at a recovery time later than the first time, from a sequence of snapshots of the fileset including the first snapshot, a recovery snapshot, the recovery snapshot comprising a recovery indicator, wherein the recovery indicator has a difference from the first indicator that is higher than a threshold value. An embodiment restores, using the recovery snapshot, the fileset to a state other than the first state, the restoring resulting in a restored application.

Abstract: One example method includes generating first and second snapshots of a shared protection namespace of a backup storage device. The first snapshot includes a first working frozen copy of an active namespace and the second snapshot includes a second work working frozen copy of the active namespace. First and second point-in-time copies of the first and second working frozen copies are generated in the shared protection namespace. The first point-in-time copy includes first files extracted from the first working frozen copy and that are stacked in at least one first horizontal file. The second point-in-time copy includes the second files included in the second working frozen copy that are stacked in at least one second horizontal file. A retention lock is applied to the at least one first and second horizontal files.

Abstract: A method for identifying vehicle performance, including maintaining a database with clustered reference data based on first vehicle data, in which each cluster in the clustered reference data is associated with a cluster significant parameter being a cluster threshold indicative of the association of the corresponding cluster; collecting second vehicle data; identifying the second vehicle data with regards to the clusters of the clustered reference data by means of an associated significant parameter and a cluster threshold, and in response of not being able to classify the second vehicle data into a cluster of the clustered reference data, define the second vehicle data as an outlier; identifying vehicle performance based on the cluster identification and determined outlier of the second vehicle data.

Abstract: Systems, methods, and computer-readable media for generating responses to natural-language queries regarding items in unstructured documents are disclosed. An application instance that includes one or more machine learning models receives, from a subscriber computing system, a query and document comprising unstructured data. Based on the unstructured data, the application instance generates a searchable data structure using a machine learning model. A query response is generated by performing a semantic search on the searchable data structure. The query response is provided to a target application.

Abstract: Methods and systems described herein are directed to creating customized queries on data sets via selection of search elements based on meta-data from data set registrations. In some implementations, an automatic query system can register database elements with associated meta-data by receiving programming data objects, corresponding to database elements, with meta-data and adding the programming objects as selectable values for a user interface (UI). Each data object can define one or more elements for a table and/or column(s) within a table in a database. The automatic query system can provide the UI to a user to receive table and column selections. The automatic query system can select a root table to join the selected tables into, and generate a join query for the root table by inserting search string snippets, corresponding to selected tables and columns, into a query template.

Abstract: A method for a first set of processors and a second set of processors comprises, the first set of processors processing a set of queries, as a result of a change in utilization of the first set of processors, processing the set of queries using the second set of processors. The change in processors is independent of a change in storage resources, the storage resources shared by the first set of processors and the second set of processors.

Abstract: The present inventors devised techniques and technologies that streamline the protection of data stored on shared file storage e.g., on file servers, network-attached storage (NAS), share drives, network shares, etc., in a data storage management system. Some embodiments feature a proxy-less backup configuration in which backup services hosts are assigned to perform a secondary copy job, at job runtime, based on host attributes relative to the data source. Some embodiments are configured to, at job runtime, automatically resolve data paths to the source data, and automatically mount the data paths, rather than requiring data paths to be expressly pre-administered on all possible candidate backup machines. Some embodiments automatically protect data from shared file storage that was not expressly given a backup plan (“undefined” data) by applying default preferences for protecting undefined data.

Abstract: A method and apparatus for managing a set of storage resources for a set of queries is described. In an exemplary embodiment, a method provisions processing resources of an execution platform and provisions storage resources of a storage platform. The execution platform uses the storage platform, which is shared with the execution platform, to process the set of queries. The method changes a number of the storage resources provisioned for the storage platform based on a storage capacity utilization by the set of queries of the storage resources. The method changes the number of the storage resources independently to a change of the processing resources in the execution platform. The method processes the set of queries using the changed number of the storage resources provisioned for the storage platform.

Abstract: The subject technology receives, at a first execution node, a first transaction, the first transaction to be executed on linearizable storage. The subject technology determines whether the first execution node corresponds to a rank indicating a leader worker. The subject technology, in response to the first execution node corresponding to the rank indicating the leader worker, performs, by the first execution node, an initialization process for executing the first transaction. The subject technology broadcasts a first read timestamp associated with the first transaction to a set of execution nodes, the set of execution nodes being different than the first execution node. The subject technology executes, by the first execution node, at least a first operation from the first transaction.

Abstract: The embodiments of the disclosure provide a dada shuffling method, apparatus and device, a computer-readable storage medium and product. The method comprises: acquiring a data shuffling request; acquiring a shuffling request parameter linked list associated with the at least one data to be shuffled based on the data shuffling request; performing a merging operation on shuffling request parameters in the shuffling request parameter linked list according to the data amount of the data segment corresponding to the shuffling request parameter and memory buffer information to obtain at least one target request parameter; and caching the data to be shuffled corresponding to the at least one target request parameter to a predetermined remote direct memory access network card; and distributing respectively data segments associated with at least one data to be shuffled cached in the remote direct memory access network card to a target server of the data segment.

Abstract: Improved techniques for management of memory (or memory management) for computing systems and environments are disclosed. The improved techniques are especially well suited for computing systems that operate in highly complex and/or demanding computing environments (e.g., massively parallel database systems that may be required to process many complex database queries in parallel. Memory can be managed dynamically at run time to determine and designate one of multiple memories that are available for execution of executable components (e.g., database queries, Opcodes of a Virtual Machine). In addition, memory can be managed dynamically at run time to effectively reuse memory locations of a memory (e.g., stack memory) being used for execution of one or more executable components (e.g., Opcodes of a Virtual Machine) at run time when the memory is being actively used to execute the one or more executable components.

Abstract: Case management systems and techniques are disclosed. In various embodiments, a trait definition is received that associates with a case node comprising a case model an object associated with an external system, e.g., a document or other content object and/or a business or other software object. The trait definition is used to bind respective instances of the object to corresponding instances of the case node in case instances created based on the case model.

Abstract: Provided herein is a method of storing an incoming dataset in a data mesh. The method may include a plurality of steps. The steps may include associating a metadata tag with a classifying feature and a storage instruction in a (first) relational database. The steps may include scanning incoming datasets to identify datasets characterized by the classifying feature. The steps may include tagging an incoming dataset to generate a tagged dataset. The steps may include storing the tagged dataset in the data mesh, according to the storage instruction. The steps may include associating, in a second relational database, the metadata tag with the initial storage location. The steps may include modifying the storage instruction. The steps may include storing the incoming dataset an additional time in the data mesh, according to the modified storage instruction.

Abstract: Systems and methods for generating min-increment counting bloom filters to determine count and frequency of device identifiers and attributes in a networking environment are disclosed. The system can maintain a set of data records including device identifiers and attributes associated with device in a network. The system can generate a vector comprising coordinates corresponding to counter registers. The system can identify hash functions to update a counting bloom filter. The system can hash the data records to extract index values pointing to a set of counter registers. The system can increment the positions in the min-increment counting bloom filter corresponding to the minimum values of the counter registers. The system can obtain an aggregated public key comprising a public key. The system can encrypt the counter registers using the aggregated shared key to generate an encrypted vector. The system can transmit the encrypted vector to a networked worker computing device.

Abstract: A coupling table search device 530 includes: input means 531 that receives an input of a coupling index from a coupling index storage unit 520; search plan generation means 532 that calculates, for each coupling index, the number of results that is the number of couplable record pairs estimated in a case where a record in a target column is found using the coupling index for each similarity function, and generates a search plan that defines a use order of the coupling index in descending order of the calculated number of results; and record search means 533 that searches for a record in the target column by using the coupling index in the order defined in the search plan, and specifies the external table in which records whose number is equal to or larger than a predetermined threshold have been found as a coupling table.

Abstract: A method for establishing an externally verifiable proof of work as immutable evidence of computational work completed by a mining node to generate a private data output, the proof of work for use in appending a block record to a blockchain comprises receiving, from a data broker server, a data package comprising signal information to be kept private by the mining node. The method further comprises analyzing the data package to convert the signal information to a corresponding private data output. In response to analyzing the data package, the method further comprises generating metadata characteristic of the analysis. The method further comprises using a cryptographic commitment scheme to generate a metadata commitment value for the data package. The method further comprises communicating the metadata commitment value and the validation data to a commitment database server operable to permit external access for use in providing an externally verifiable proof of work.

Abstract: A visual search system includes a computing device, where the computing device includes an image processing engine for generating a feature vector representing a user-selected object in an image. The computing device also includes, an object detection engine for locating one or more objects in the image and for determining a category of a user-selected object from objects in the image, where the object detection engine uses the category to generate a plurality of attributes for the user-selected object. The computing device further includes a product data store for storing a plurality of tables storing one or more attributes associated with a category of the user-selected object. The computing device additionally includes an attribute generation engine for generating a plurality of attribute options and an attribute matching engine for comparing attributes and attribute options of the user-selected object with attributes and attribute options of visually similar products and images.

Abstract: An automated method and apparatus are provided for comparing a first database and a second database that are intended to be kept in synchronization with each other. Applications process changes that are posted to the first database and the second database. Changes made to the first database are applied to the second database, and vice-versa. Changes made to the first database resulting from changes posted to the first database are collected into a first change log. Changes made to the second database resulting from changes posted to the second database are collected into a second change log. Representations of the changes that correspond to the same respective changes in the change logs are compared with each other. Corrective action is performed when the comparison indicates that the corresponding representations of the changes in the first change log and the second change log do not match.

Abstract: Various embodiments for a disk-based merge for hash maps are described herein. An embodiment operates by identifying a plurality of hash maps with a plurality of disjunctions, ordering the one or more entries in each disjunction based on the hash value, and assigning an index value to each data value based on the ordering. The hash values of each of the entries may be moved to memory and compared for a particular disjunction. A data value with a lower hash value as determined based on the comparison is selected and stored in a merged hash map. The process is repeated until all the data values have been compared. A query is received, and processed based on the merged hash map.