Abstract: A computer system receives a database query to be executed against a database having a database table that stores records associated with keys. The database query specifies a set of conditional expressions that affect which ones of those records are returned. Based on the set of conditional expressions, the computer system derives a set of key ranges. The deriving can include representing the set of conditional expressions as a set of key spaces, performing a set of logical operations on pairs of those key spaces to reduce a number of key spaces in the set of key spaces, and converting the set of key spaces into the set of key ranges after performing the set of logical operations.

Abstract: A system and method for hierarchical database operation accelerator for scaling a single node database with a plurality of accelerator cards is provided, including: a host, receiving a query plan, generating a corresponding query operation and distributing them, receiving and processing aggregated execution results; a hierarchy accelerator module, which is connected to the host, receiving the query operation distributed and returning the aggregated execution results; the hierarchy accelerator module comprises a master accelerator card and at least one slave accelerator card, the slave accelerator card returns the execution results to the master accelerator card, by the master accelerator card completes the subsequent query operation which is aggregated and assigned by the execution results, returning the aggregated execution results to the host; the accelerator system having a multi-level storage architecture of accelerator chip on-chip cache, the accelerator card memory, the accelerator card storage, and the

Abstract: Data being identified includes a first portion of data and a second portion of data. Based on identifying the data, a data structure is generated. The data structure can include a first section having a first symbol associated with the first portion of data and a second symbol associated with the second portion of data. Further, the first section can include a first offset value corresponding to the first portion of data and a second offset value corresponding to the second portion of data. The data structure can include a second section with a plurality of pointers that reference at least a plurality of symbols including at least the first and second symbol. The data structure can be referenced to process one or more queries against the data.

Abstract: Embodiments are directed to systems, devices, methods, and techniques to determine words or word combinations of search engine queries and selected items corresponding to the words or word combinations. Embodiments also include applying a machine learning model to the word or word combinations and the selected items to determine a mapping between a word or word combination and a particular selected item, and updating attribute data in a web document with the word or word combination, wherein the web document is associated with the particular item such that a search including the word or word combination returns a result including the web document.

Abstract: A system for automated conversion and delivery of medical images. In an example implementation, a server is configured to retrieve a medical image file including medical data and metadata, in a medical data format, determine an output destination type based on the metadata, identify standardized format specifications based on the determined output destination type from the retrieved metadata, convert the medical data into a format compatible with the identified standardized format, and transmit an output message of the converted medical data to at least a recipient delivery address.

Abstract: Systems and techniques for managing data in a relational database environment and a non-relational database environment. Data in the relational database environment that is static and to be maintained beyond a preselected threshold length of time is identified. The data is copied from the relational database and stored in the data the non-relational database. Access to the data is provided from the non-relational database via a user interface that accesses both the relational database and the non-relational database.

Abstract: Providing Quality of Service (QoS) for replicating datasets including: receiving, by a target data repository from a source data repository, a checkpoint describing one or more updates to one or more datasets stored in the source data repository and the target data repository; adding, by the target data repository, the checkpoint to a first queue for checkpoints directed to one or more volumes in the target data repository, wherein the first queue is included in a plurality of queues for the target data repository; selecting, by the target data repository, one or more queues from the plurality of queues; and servicing an operation from each of the selected one or more queues.

Abstract: An intelligent clustering system has a dual-mode clustering engine for mass-processing and stream-processing. A tree data model is utilized to describe heterogenous data elements in an accurate and uniform way and to calculate a tree distance between each data element and a cluster representative. The clustering engine performs element clustering, through sequential or parallel stages, to cluster the data elements based at least in part on calculated tree distances and parameter values reflecting user-provided domain knowledge on a given objective. The initial clusters thus generated are fine-tuned by undergoing an iterative self-tuning process, which continues when new data is streamed from data source(s). The clustering engine incorporates stage-specific domain knowledge through stage-specific configurations. This hybrid approach combines strengths of user domain knowledge and machine learning power.

Abstract: A particular embodiment includes issuing a feature configuration template, such that a user configures, on a configuration interface, the content of the feature configuration template; receiving configuration content configured by the user for the feature configuration template and at least one set of time sequence data to generate at least one set of data feature values.

Abstract: A system for enterprise analytics may include a Machine Learning (“ML”) model data store containing at least one generic ML model and a fine-tuning data store containing prior natural language user requests and associated enterprise database queries generated by analysts. The system may also include an enterprise data store containing enterprise business data. A transformation framework may retrieve the generic ML model and fine-tune the model using the prior user requests and associated enterprise database queries to create a fine-tuned ML model. The framework may then receive a new natural language request from a user and use the fine-tuned ML model and new natural language request to automatically create a new enterprise analytics query. The new enterprise analytics query may then be executed to fetch enterprise analytics data from the enterprise data store. In some embodiments, an analytics chart may be automatically created and provided to the user.

Abstract: A method for receiving paths information of a file system (FS) that is stored in a storage system, the method includes (a) receiving a request to receive paths information of at least part of the FS; wherein the request is received at a request point in time (PIT); (b) determining a current path name information of the at least part of the FS, wherein the determining is based on: (i) a FS paths data structure that includes path name information that is updated up to a last update PIT, and (ii) FS paths change information that is indicative of FS path names changes introduced between the last update PIT and the request PIT; wherein the FS paths change information associates at least one of excluded FSEs and included FSEs for each direct or indirect ancestor FSE of any FSE that had its path name changed between the last update PIT and the request PIT; and (c) generating a response to the request, wherein the generating of the response comprises using the current FS path name information of the FS.

Abstract: A cardinality query associated with a specific attribute is received. One or more in-scope attribute cardinality partitions is enforced on session record analytics. Vertical data compression is performed to eliminate a time dimension. Horizontal data compression is performed to eliminate one or more out-of-scope attributes. One or more like in-scope session records is aggregated. Magnitudes of each in-scope attribute of each enforced cardinality partition are summed. The sum is returned as a response to the cardinality query.

Abstract: One example method includes generating, by a data backup server agent that is hosted by a backup client computing system, backup data files from data stored at the backup client computing system. The backup data files are written to a temporary folder in a staging location of a backup storage server. A determination is made of if an attempt to move the temporary folder has failed. A failure is indicative that the backup storage server is operating in a retention lock mode. Each of the plurality of backup data files are moved individually from the temporary folder to a final folder in a final location of the backup storage server when it is determined that the attempt to move the temporary folder has failed.

Abstract: Methods, systems, and apparatus, for providing map data that causes a user device to display a map of an area that includes a physical entity location and a access locations for the physical entity, wherein the physical entity location is indicated by an icon of a first type and each access location is indicated by an icon of a second type that is different from the icon of the first type.

Abstract: A system for extracting and providing information from a source document includes a memory and a processor. The memory stores data associated with the source document. The processor is configured to classify the source document as a determined document type from a plurality of document types. The processor extracts data from the source document based at least in part upon the determined document type and store that extracted data as a first extracted data in the memory. When a request for information is received, the processor then determines if the first extracted data includes all the requested information and if it does not, the processor extracts second extracted data from the image file and stores the second extracted data along with the first extracted data and the image file in the memory. The requested information is then provided to the requesting process from the first and second extracted data.

Abstract: A query including a time range can be received. The query can be processed to determine data associated with the time range of the query. Cached data can be analyzed to identify a first block of data including metadata identifying a first timestamp associated with the time range of the query. A communication can be generated to include the first timestamp associated with the first block of data. Based on the communication, a second block of data can be received with metadata identifying a second timestamp associated with the time range of the query. A query result can be generated to include the first block of data and the second block of data.

Abstract: An example method includes receiving and preprocessing a query request prior to execution of a query. Through preprocessing, a probability that execution of the query would yield a result set similar to at least a portion of results stored in a repeated query result repository is obtained. In response to the probability satisfying a probability threshold, a portion of results is retrieved from the repository. The example method further includes causing transmission of a response to the query request, the response comprising the portion of results.

Abstract: A method for accessing information. The information is received by a computer system from sources for distribution to client computer systems. A piece of the information received from the sources without temporal data is identified by the computer system. The temporal data for the piece of the information based on a policy is identified by the computer system. The temporal data is associated with the piece of the information by the computer system, enabling analyzing the information by a client computer system with increased accuracy.

Abstract: Systems and methods provide a first group of computation modules configured to provide back-end compute resources for a first type of computation module by back-end compute resources. Systems and methods provide a second group of computation modules that are configured to provide back-end compute resources for a second type of computation module wherein the first and second type of computation modules are of different types. In some examples, methods and systems identify the type of computation module needed by each of a plurality of queries associated with different types of client applications based on computation module type data associated with each query and route each of the plurality of queries to an appropriate computation module within the first or second computation modules based on the computation module type data.

Abstract: Systems, methods, and machine-readable storage devices provide for identifying a user dataset on a distributed database. The system includes generating a similarity score dataset that indicates a similarity between the user dataset and a plurality of datasets of other users of the distributed database. The system generates a plurality of overlap queries that are configured to output overlap datasets between the user dataset and one or more of the plurality of datasets. The system further generates a results dataset by applying one or more of the plurality of overlap queries to a joined dataset comprising data from the user dataset and one of the plurality of datasets of other users on the distributed database.