55results about "Data merging" patented technology

Methods, computer program products, and systems are presented. The methods, computer program products, and systems can include, for example, processing multiple datasets using metadata, wherein the metadata can characterize relationships among datasets. In dependence on such metadata, production datasets can be, e.g., generated, versioned, and / or merged. The resulting production datasets can support subsequent computing uses such as analytics, machine learning, application testing, and / or enterprise processing.

A processor comprising storage, execution circuitry and a handling unit. The handling unit is configured to obtain operation data indicative of an operation to be executed using the execution circuitry. The execution circuitry is configured to operate over a multi-dimensional nested loop defining an operation space. The handling unit obtains a dimensional combination instruction and, in response, combines a plurality of dimensions of the operation space to obtain a local space dimension in an operation-specific local space as part of a procedure to map each operation block of a plurality of operation blocks in the operation space to a different respective local block in the local space dimension. The handling unit dispatches invocation data for the plurality of operation blocks to the execution circuitry. The invocation data for each respective operation block specifies a local space dimension range of a local block to be operated on for the respective operation block.

A hierarchy is a multi-level linked structure of nodes, wherein the hierarchy represents data relating to a set of one or more items to be processed. Where there are multiple input hierarchies, it may improve the efficiency of the processing of the items to merge the input hierarchies to form a merged hierarchy. The hierarchies are merged by identifying two or more sub-hierarchies within the input hierarchies which are to be merged, and determining one or more nodes of the merged hierarchy which reference nodes of the identified sub-hierarchies. The determined nodes of the merged hierarchy are stored and indications of the references between the determined nodes of the merged hierarchy and the referenced nodes of the identified sub-hierarchies are also stored. In this way, the merged hierarchy is formed for use in processing the items.

The present invention provides a data merging method and apparatus of a physical random access channel, and a storage medium. The method comprises: parsing task parameters of this PRACH data merging; reading PRACH data to be merged of an antenna from a PRACH data cache; carrying out, according to the task parameters, PRACH data merging between a plurality of antennas and / or RACH data merging in a PRACH of this antenna; and outputting the merged data to a shared cache.

Methods, systems, apparatuses, and non-transitory computer readable media for managing file generation and retention are provided. These systems may be used across a wide range of businesses to significantly automate the generation and storage of files. By utilizing nested file templates as described herein, example systems may increase the ease in which a file template may be generated, stored, retrieved, and retained. Moreover, by using the file retention storage system described below, example systems may simplify the process of ensuring files are retained for an appropriate amount of time and further assuring that files are deleted when they no longer need to be retained.

Performance of a collection of machines, arranged in a linear sequence of machines that form a linear communication orbit (LCO), is monitored. Multiple machines in the LCO receive, via the LCO, a set of rules (or various subsets of the same set of rules), each rule specifying one or a combination of conditions (e.g., a performance metric and corresponding criterion) for satisfying the rule, evaluate those rules with respect to locally occurring events and local processes, and store results of those evaluations in a local database. In response to a query sent to the machines via the LCO, each of the machines returns a report, including information identifying processes whose performance during the specified time period satisfies at least one rule in the set of one or more rules. Those reports are aggregated and used to generate a merged report reflecting performance information with respect to a set of machines.

The present disclosure generally relates to methods, systems, apparatuses, and non-transitory computer readable media for managing generated files. These systems may be of used across a wide range of businesses to significantly automate the generation, storage, and eventual deletion of files. In particular, embodiments of the present disclosure may comprise a server creating a file from a file template in response to a request from a client device. This request or the indicated file template may indicate when the file should be deleted. After the file is created, the server may store the first file and subsequently monitor for the occurrence of a relevant deletion-triggering event. If the server detects the occurrence of a deletion-triggering event, it may then delete the stored file. Thus, files are both retained for an appropriate amount of time and are deleted when they are no longer appropriate to keep.

Storage access for the merge operation is minimized. Multiple records from multiple input lists are merged. The merge includes: determining that one of the input lists has become empty; and, based on this determination, checking the controls dedicated to that input list. These controls determine how to proceed, such as whether to end the merge or continue.

A system and method are provided that store electronic data describing events that have occurred in a computing system, index the electronic data to create indexed data records; and store the indexed data records in computer memory as part of a flat data structure.

Embodiments of the present disclosure provide a file merging method for a real-time data lake, a device and a storage medium. The method comprises: obtaining characteristic information of a query task for a real-time data lake table and attribute information of files to be merged in the real-time data lake table; determining, based on the characteristic information of the query task and the attribute information of the files to be merged, whether to initiate a merging task; and in accordance with a determination that the merging task is initiated, merging the files to be merged.

Embodiment of the present disclosure provides method, apparatus, device and storage medium for data query. In the method, first data is obtained by a first device based on a request for a data query, where the request indicates a first data attribute to be classified and aggregated and at least a second data attribute and a third data attribute for classification, and the first data at least includes data associated with a second data attribute; and a third data fragment of a result of the data query is generated based on the first data fragment of the first data and the second data fragment of the second data received from the second device, where the second data at least includes data associated with the third data attribute, and the third data fragment includes an element corresponding to the first data attribute that is classified and aggregated based on at least the second data attribute and the third data attribute.

Techniques for computing matrix operations for arbitrarily large matrices on a limited size hybrid analog-digital matrix processor are described. Techniques for gain adjustment in a limited size hybrid analog-digital matrix processor are described that enable the system to achieve higher energy efficiency, greater physical density, and improved numerical accuracy. In some embodiments, these techniques maximize the prediction accuracy of GEMM-based convolutional neural networks using low-precision data representations.

Methods and apparatus to generate and display trends associated with a process control system are disclosed. An example apparatus includes memory, machine readable instructions, and processor circuitry to execute the instructions to generate a first graphical user interface. The first graphical user interface to include a graphical representation of a component in a process control system. The processor circuitry to generate a second graphical user interface. The second graphical user interface to include a chart region with a trend represented therein. The trend indicative of values of a process parameter of the process control system over a period of time. The processor circuitry to automatically generate the trend in the chart region in response to a graphical element being dragged and dropped from the first graphical user interface to the second graphical user interface.

A digital security system can store data associated with entities in resolver trees. If the digital security system determines that two resolver trees are likely representing the same entity, the digital security system can use a merge operation to merge the resolver trees into a single resolver tree that represents the entity. The single resolver tree can include a merge node indicating a merge identifier of the merge operation. Nodes containing information merged into the resolver tree from another resolver tree during the merge operation can be tagged with the corresponding merge identifier. Accordingly, if the merge operation is to be undone, for instance if subsequent information indicates that the entries are likely separate entities, the resolver tree can be unmerged and the nodes tagged with the merge identifier can be restored to a separate resolver tree.

The present invention provides a loyalty extraction machine, wherein “quadratic multiform separation” (QMS) is modified and executed multiplicatively in an even generalized way. In each execution, the characteristic of one single membership is either enhanced or reduced. This process is performed in turn to each membership. Thus, every sample data (or element) receives multiple classification results. Then, the multiple classification results are collected and analyzed by an “eclectic classifier” to reach a final decision. The combination of the generalized QMS and the eclectic classifier therefore develops the loyalty extraction machine. Moreover, a label called “loyalty type” of the element is introduced to describe the effectiveness of membership recognition with respect to a training set.

A data processing method, apparatus, device, and storage medium are provided. The method includes acquiring a data reading task; determining the target feature data from a data file stored in a target storage system based on the data reading task and metadata corresponding to the target storage system; reading the target feature data from the data file based on operation semantic information corresponding to the target feature data, and determining the read target feature data as the first target feature data; and merging the first target feature data to acquire target merged feature data in the case that the size of data volume of the read first target feature data meets a preset condition, and repeating the process of reading and merging the first target feature data until a completion of reading of the target feature data in the data file.

The present disclosure discloses a method, apparatus and device for generating a model and a storage medium. A method can include: acquiring sample resource features and sample labels; determining a first screening factor according to the sample resource features and the sample labels, and determining first resource features from the sample resource features according to the first screening factor; determining a second screening factor, and determining second resource features from the first resource features based on the second screening factor, and obtaining features of a target model based on the second resource features; and training a machine learning model, by taking the features of the target model as an input of the target model, and taking the sample labels corresponding to the features of the target model as an output of the target model, to obtain the trained target model.

Systems and methods for file sorting and de-duplication of files in a filesystem. A reverse path crawl may be performed followed by clustering files into file buckets. The clustering may be followed by one or more steps of combining file buckets based on one or more criteria. The merged content of the files in each file bucket may be analyzed and a similarity score may be calculated for each pair of files in the bucket. Based on the similarity score, the system may split each bucket into one or more dissimilar buckets. The dissimilar buckets may have a canonical file selected for each and a canonical file name created / chosen for said selected canonical file.

A data padding method comprises: determining a length of a space occupied by remaining data in the register; comparing the length of the space occupied; performing, when the length of the space occupied by the remaining data is less than the length of the unit input data, following operations: receiving a unit input data and storing it continuously with the remaining data in the register; determining a length of a unit output data to be output; intercepting a portion of data with a length of N words from data formed by padding the remaining data buffered in the register and the unit input data and starting from an address space of a lowest bit of the register, as the unit output data and outputting it; and shifting the data remaining in the register as a whole to an address space in the register starting from the lowest bit.

A method for data processing is described. The method may include retrieving, from a cloud storage environment accessible to a data management system (DMS), two or more observability data sets associated with a set of time intervals within a selected time range. The observability data sets may contain a set of time-partitioned data blocks that include tracing data associated with operations performed by one or more nodes of a node cluster of the DMS during the selected time range. The method may further include merging the tracing data by selecting a first subset of overlapping time-partitioned data blocks, omitting a second subset of the overlapping time-partitioned data blocks, and retaining one or more non-overlapping time-partitioned data blocks. The method may further include transmitting data corresponding to a visualization of the merged tracing data.

A method and system for processing datasets having a number of data points are described. A portion of the dataset is received and processed in parallel. A view on a display is updated to include a first section of the portion of the dataset after the first section completes processing but before a remainder of the portion of the dataset completes processing. In some aspects, the portion of the dataset can include up to one million or more data points. In some aspects, if a change from the view to a second view is received before processing has completed, an unusable part of the dataset is discarded and / or a reusable part of the dataset that has completed processing is reused for the second view. In some aspects, columns of different dataset may be correlated and / or processed data is provided such that the processed data may be rapidly rendered.

The present disclosure generally relates to methods, systems, apparatuses, and non-transitory computer readable media for managing file generation and retention. These systems may be of used across a wide range of businesses to significantly automate the generation and storage of files. By utilizing nested file templates as described below, systems of the present disclosure may increase the ease in which a file template may be generated. Moreover, by using the file retention storage system described below, system of the present disclosure may simplify the process of ensuring files are retained for an appropriate amount of time and further assuring that files are deleted when they no longer need to be retained.

The present disclosure generally relates to methods, systems, apparatuses, and non-transitory computer readable media for managing file generation and retention. These systems may be of used across a wide range of businesses to significantly automate the generation, storage, and eventual deletion of files. In particular, embodiments of the present disclosure may centralize storage of generated files on a first server. A second server may be connected to the first server so as to seamlessly display certain information about these stored files. This displayed information may allow a user of the second server to seamlessly access these stored files while simultaneously avoiding transmitting the files to the second server itself. By doing so, the first server maintains control over the first file and may, according to the retention policy specified at the file's creation, ensure that the file is deleted after the appropriate amount of time.

Sorting data in memory is a fundamental computation that facilitates a wide range of search and query problems, aids in the construction and manipulation of data structures, and can improve the spatial and temporal locality of data and computation. Oftentimes, merge-based designs are used for sorting data, where a block sorting pass is performed followed by merging passes that produce increasingly larger sorted sublists until only a single list remains. While conventional merge-based designs can support multiple (K) merge operations in a single pass, a balance must be struck since there exists a point where K-scaling is no longer profitable. The present disclosure provides an alternative merge-based design in which data is merged using a single feed-forward data path.

The present disclosure generally relates to methods, systems, apparatuses, and non-transitory computer readable media for managing file generation and retention. These systems may be of used across a wide range of businesses to significantly automate the generation and storage of files. By utilizing nested file templates as described below, systems of the present disclosure may increase the ease in which a file template may be generated. Moreover, by using the file retention storage system described below, system of the present disclosure may simplify the process of ensuring files are retained for an appropriate amount of time and further assuring that files are deleted when they no longer need to be retained.

An online system enables large language models (LLMs) to perform analytics on large datasets that exceed the LLM's context window by employing a recursive merge-sort prompting approach. Upon receiving a free-text analysis request from a user, the system generates an initialization prompt for the LLM to create a merge prompt template. The dataset is recursively divided into portions, which may be equal or semantically segmented subsets, and each portion is analyzed by the LLM. If a portion still exceeds the context window, the recursive process continues on its subsets. Outputs from each analysis are merged using a merge prompt template, which may include fields for outputs, data, and descriptions of subsets. The merge prompt template is used to generate a merge prompt, which is provided to the LLM to synthesize a final response.

Disclosure is made of methods, apparatus and system for clustering processes for use by a cloud platform. Process clustering may include receiving traffic data transmitted and received between each pair of processes in a set of processes. A matrix may be generated based on the traffic data, the matrix including a row and a column for each process in the set of processes. The matrix may be hierarchically clustered based on the traffic data, the hierarchical clustering outputting a plurality of clusters, each cluster including one or more processes in the set of processes. The plurality of clusters may then be merged into a set of merged clusters of processes.

A computing system merges data sets associated with user groups a combined data set. Each data set is associated with a unique user group. The combined data set is associated with a target user group including subsets of the user groups. The computing system performs steps including: configuring data content of each data set of the multiple data sets into the target data format; automatically evaluating the data sets to automatically postulate whether one or more users of the target user group are common to more than one of the subsets of users; and automatically transmitting a notification signal to the one or more agent device upon at least one of: postulating one or more users of the target user group are common to more than one of the subsets of users; and completion of generating the combined data set in the target data.