Abstract: Many computer applications comprise multiple threads of executions. Some client application requests are fulfilled by multiple cooperating processes. Techniques are disclosed for creating and managing memory namespaces that may be shared among a group of cooperating processes in which the memory namespaces are not accessible to processes outside of the group. The processes sharing the memory each have a handle that references the namespace. A process having the handle may invite another process to share the memory by providing the handle. A process sharing the private memory may change the private memory or the processes sharing the private memory according to a set of access rights assigned to the process. The private shared memory may be further protected from non-sharing processes by tagging memory segments allocated to the shared memory with protection key and/or an encryption key used to encrypt/decrypt data stored in the memory segments.

Abstract: In an approach to archive a digital twin in response to a determination to decommission its associated physical asset, a processor monitors for data sent from an Internet of Things (IoT) sensor associated in the physical asset. A processor determines that a pre-configured threshold is met. A processor reviews a digital twin agreement for the digital twin. A processor archives the digital twin.

Abstract: A write request is transmitted from a client to a metadata server (“MDS”), wherein the write request comprises an object identifier associated with a data object. An object store location for an object store is received from the MDS. A conditional write request is transmitted to the object store using the object store location, wherein the conditional write request includes the object identifier and the data object. A metadata response is received from the object store. The metadata response is determined to contain an object designator. A commit request is transmitted to the MDS, wherein the commit response includes the object designator.

Abstract: A technique involves normalizing identification of users (e.g., different customer organizations) across disparate local systems (e.g., different electronic platforms that provide different products and/or services). Such normalization of user identification enables a provider to accurately ascertain a particular user of multiple disparate local systems even when the multiple disparate local systems identify that user using different identification schemes. Accordingly, the provider is able to offer enhanced support to that user across the multiple disparate local systems. For example, with such normalization of user identification, the provider may employ a single authentication system across the various local systems thus enabling the user to authenticate via the same authentication process regardless of which local system the user attempts to access.

Abstract: A platform for processing event traces to generate clusters of journey maps for an interactive user display. The clustering can be implemented using a genetic process. The clustering can be implemented using a distance measures. Other clustering techniques can be used. The platform can use the clustering results to generate interactive dynamic visualizations with interactive selectable portions. The platform can integrate processing mining and journey maps to generate interactive dynamic visualizations.

Abstract: One or more techniques and/or systems for sending push notifications of content items to client devices are provided herein. For example, an input received from a user can be expanded to obtain an expanded user interest. Content items from a content source can be filtered based upon the expanded user interest to obtain a set of filtered content items. A push notification can be constructed to comprise one or more of the filtered content items from the set of filtered content items. The push notification can be sent to a client device of the user for display as a device alert notification. In an example, the filtered content items, within the push notification, may be ranked based upon a ranking metric.

Abstract: The present disclosure related to techniques for analyzing data from multiple different data sources to determine a relationship between the data (also referred to herein a “data relationship discovery”). The relationships between any two compared datasets may be used to determine one or more recommendations for merging (e.g., joining), or “blending,” the data sets together. Relationship discovery may include determining a relationship between a subset of data, such as a relationship between a pair of columns, or column pair, each column in a different dataset of the datasets that are compared. Given two datasets to process for relationship discovery, relationship discovery may identify and recommends a ranked subset of column pairs between two compared datasets. The ranked column pairs identified as a relationship may be useful for blending the datasets with respect to those column pairs.

Abstract: A directory deletion method and apparatus, and a storage server, where the directory deletion method includes receiving, by a storage server, a delete operation authentication request of a host, where the delete operation authentication request carries user information and information about a target directory, storing, by the storage server, the user information and returning a file identifier (FID) of the target directory to the host after authentication succeeds, sending, by the host to the storage server, a delete request carrying the FID, performing, by the storage server, verification on the file and the subdirectory using the user information, and deleting a successfully verified empty subdirectory and a successfully verified file. Hence, the directory deletion method and the apparatus, and the storage server improve directory deletion efficiency.

Abstract: The disclosure herein describes determining computing assets associated with a service. Metadata from one or more computing assets of a computing system is collected. One or more alias terms are identified in the collected metadata of the one or more computing assets, wherein the alias terms are associated with the service. Service association scores are generated for the one or more computing assets based on the identified one or more alias terms and a term-score mapping. Each service association score indicates a likelihood that a computing asset is used for a service. A subset of computing assets of the one or more computing assets is identified. The subset of computing assets includes computing assets with service association scores that exceed a service association threshold. Computing assets of the service are identified based on the identified subset, thereby reducing the need for manual identification of asset-service associations.

Abstract: Techniques are disclosed relating to creating an index for a database system. In one embodiment, a database system stores data within a plurality of fields in a data table, a subset of the data being associated with a particular one of the plurality of fields. The database system receives a request to index the data table based on the particular field and analyzes the subset of the data. In response to determining, based on the analyzing, that one or more duplicate values are present in the subset of data, the database system sets, in an index table having the particular field, an indication identifying which entries of the index table have a duplicate value for the particular field, and returns a response to the request that specifies the one or more duplicate values. In some embodiments, the response includes a user interface displaying one or more duplicates values.

Abstract: Systems and methods that allow examination of response data collected from content providers and provide for classification and routing according to the classification. The process of classification employs an unsupervised, or partially unsupervised, Machine Learning classifier model for identifying data collection responses that contains no data, mangled data, or a block, for assigning a classification correspondingly and for feeding the classification decision back to a data collection platform.

Abstract: The present invention provides a seeded news event clustering and retrieval system configured to first create a candidate data set of documents, second create a set of initial clusters based on nearness or duplicate similarity status, and third create an aggregate cluster by merging initial clusters with seed documents. The invention generates top-level clusters for news events based on an editorially supplied topical label or “seed” component and generates sub-topic-focused clusters based on algorithm. The system uses an agglomerative clustering algorithm to gather and structure documents into distinct result sets.

Abstract: A method may include maintaining first data structure with records organized in a first hierarchy, and maintaining a second data structure with records organized in a second hierarchy. The method may additionally include receiving a change request for the value stored in the first record. The change request may be received from a parent in the second data structure of the first record. The method may further include sending a notification to the parent in the first data structure that the parent in the second data structure is attempting to change the first record.

Abstract: Techniques for automated query retry in a database platform include decoding, by at least one hardware processor, a query directed to database data from a client account of a database platform. The method further includes decoding, by the at least one hardware processor, an indication that execution of the query on at least one computing node of the database platform results in a failed execution. The method further includes configuring a processing loop with continuous retry executions of the query on the at least one computing node based on the indication. The method further includes exiting the processing loop based on detecting a retry execution of the continuous retry executions results in at least one successful execution of the query. The method includes logging each attempt to execute the query during the continuous retry executions in a query status log until the at least one successful execution of the query.

Abstract: A computer comprising one or more processors and memory may implement multiple threads performing mutually exclusive lock acquisition operations on disjoint ranges of a shared resource each using atomic compare and swap (CAS) operations. A linked list of currently locked ranges is maintained and, upon entry to a lock acquisition operation, a thread waits for all locked ranges overlapping the desired range to be released then inserts a descriptor for the desired range into the linked list using a single CAS operation. To release a locked range, a thread executes a single fetch and add (FAA) operation. The operation may be extended to support simultaneous exclusive and non-exclusive access by allowing overlapping ranges to be locked for non-exclusive access and by performing an additional validation after locking to provide conflict resolution should a conflict be detected.

Abstract: The disclosed embodiments include a method performed by a data intake and query system. The method includes receiving a search query by a search head, defining a search process for applying the search query to indexers, delegating a first portion of the search process to indexers and a second portion of the search process to intermediary node(s) communicatively coupled to the search head and the indexers. The first portion can define a search scope for obtaining partial search results of the indexers and the second portion can define operations for combining the partial search results by the intermediary node(s) to produce a combination of the partial search results. The search head then receives the combination of the partial search results, and outputs final search results for the search query, where the final search results are based on the combination of the partial search results.

Abstract: Adaptable internet-of-things (IoT) computing systems and methods are disclosed for improved and flexible declarative control of streaming data, such as Big Data, in compute intense environments. A declarative scripting engine determines an input data stream based on a first declarative statement defining input data stream variable(s) of a declarative scripting language in declarative scripting module(s). The input data stream is bound to a stream controller and is ingested into computer memory. The declarative scripting engine generates a snapshot data stream based on a second declarative statement in the declarative scripting module(s), and is derived from the input data stream. A stream model is defined, where a listener entity comprising an event is triggered based on the input data stream or the snapshot data stream as ingested into the stream model.

Abstract: An example operation may include one or more receiving notifications from one or more monitoring agents, each notification comprising a monitoring agent identifier, one or more configuration changes, and a timestamp corresponding to each configuration change, identifying incremental configuration changes that may require a disaster recovery retest, requesting a partial disaster recovery retest comprising the incremental configuration changes, the partial disaster recovery retest providing test coverage for a subset of a full disaster recovery test plan, and providing a request to a blockchain network to store information for the received notifications to a shared ledger of the blockchain network.

Abstract: Techniques for automated query retry in a database platform include assigning by at least one hardware processor a first execution of a query directed to database data to a first execution node of a plurality of execution nodes of an execution platform. The first execution node uses a first set of configurations during the first execution. The techniques further include determining that the first execution of the query by the first execution node results in a failed execution. The query is transferred to a second execution node of the plurality of execution nodes. A second execution of the query at the second execution node is caused. The second execution node uses a second set of configurations during the second execution. A cause of the failed execution at the first execution node is determined based on a result of the second execution of the query at the second execution node.

Abstract: Methods and devices for simplifying data collected from assets are provided. An example method involves obtaining raw data from a data source at an asset, determining that a data logging trigger is satisfied by determining that a recently obtained point in the raw data differs from a corresponding predicted point predicted by extrapolation based on previously saved points included in one or more previously generated simplified sets of data by an amount of extrapolation error that is limited by an upper bound that is fixed as the raw data is collected over time, and, when the data logging trigger is satisfied, performing a dataset simplification algorithm on the raw data to generate a simplified set of data.