Abstract: A data search method based on a quantum simulated algorithm includes: creating a first search path according to a plurality of pieces of candidate data; obtaining a first processing function corresponding to the first search path, the first processing function comprising the plurality of coefficients, output values of the first processing function being determined by the first search path; traversing at least two value sets of the first search path; obtaining the output values of the first processing function based on a quantum simulated algorithm; respectively using, when the output values of the first processing function converge to a converging value, a plurality of values in a value set corresponding to the converging value as the values of the plurality of coefficients, to obtain a second search path; and searching for target data by using the second search path.

Abstract: A computer is to obtain specification concept graphs of nodes spec1, spec2, . . . , specm including concept nodes and relation nodes according to at least one of a plurality of digitized data from a plurality of computerized data sources forming a first set of evidences U and obtain concept graphs of nodes c?1, c?2, . . . , c?n including concept nodes and relation nodes for corresponding obtained plurality of information and knowledge (IKs) ?1, ?2, . . . , ?n forming a second set of evidences U. A subset of concept graphs of nodes is selected from c?1, c?2, . . . , c?n according to a computable measure of consistency, inconsistency and/or priority threshold between c?j in c?1, c?2, . . . , c?n to specification concept graph speck in spec1, spec2, . . . , specm. Knowledge fragments are generated for corresponding subset of concept graphs c?i1, c?i2, . . .

Abstract: A method for computer estimations based on statistical tree structures involves obtaining a statistical tree structure for reference elements. The statistical tree structure includes leaf nodes segmenting a statistic for a data label according to data features in the reference elements, and intermediate nodes connecting a first node to the leaf nodes. Each of the first node and the intermediate nodes provide a branching based on one of the data features. The method further includes obtaining target data, including values for the data features, and a value for the data label. The method also includes selecting the first node, associated with a first data feature, traversing the statistical tree structure to a leaf node by matching the values of the data features to the branching of the intermediate nodes, and assessing the value for the data label in the target data based on the statistic associated with the leaf node.

Abstract: A method, computer system, and a computer program product for managing a multi-vendor environment is provided. The present invention may include receiving a request to make a change to an aggregate computer system from a participant of the aggregate computer system. The present invention may include creating, in response to the request, a change block. The present invention may include receiving approval for the change block in accordance with an endorsement policy. The present invention may include adding the change block to a distributed ledger. The present invention may include monitoring a performance of the aggregate computer system.

Abstract: A data intake and query system may store raw machine data that includes location information. A client system may include a user interface for searching the data intake and query system. The user interface allows a user to define a field search query and to define one or more ad-hoc boundary regions on a map. A combined query is transmitted to the data intake and query system, the combined query including both the field search query and location search information that is based on the ad-hoc boundary regions. The data intake and query system runs the combined query and returns responsive results, which are displayed at the client user interface.

Abstract: This disclosure describes, in part, techniques for estimating frequency values of top contributors of a high cardinality data set in a computationally efficient manner. In one example, the techniques utilize a probabilistic data structure, such as a count-min-sketch, for identifying which contributors are the largest contributors to a particular metric. After identifying these largest contributors using the probabilistic data structure, the techniques may store the contributor IDs and the their respective estimated cumulative value (e.g., frequency counts) in a top-N list.

Abstract: Context dependent execution time prediction may be applied to redirect queries to additional query processing resources. A query to a database may be received at a first query engine. A prediction model for executing queries at the first query engine may be applied to determine predicted query execution time for the first query engine. A prediction model for executing queries at a second query engine may also be applied to determine predicted query execution time for the second query engine. One of the query engines may be selected to perform the query based on a comparison of the predicted query execution times.

Abstract: Systems, methods, and other embodiments associated with distributed primary identifier management in a multi-master database system are described. One embodiment includes adding a new master node to a system with a plurality of master nodes. Assigning a master node number to the new master node in relation to the plurality of master nodes. The master node number is converted into a binary value and a reverse bit order of the master node number is generated. The new master node is configured to assign primary identifiers within an address space to data objects, wherein the primary identifiers include the reverse bit order of the master node number to reduce collisions between the data objects.

Abstract: Systems and methods include determination, for each of a plurality of discrete features, of statistics based on a number of occurrences of each discrete value of the discrete feature in the data, determination of first summary statistics based on the determined statistics, determine of a dissimilarity for each discrete feature based on the first summary statistics and on the statistics determined for the discrete feature, determination of candidate discrete features based on the determined dissimilarities, determination, for each of the candidate discrete features, of second summary statistics based on values of a continuous feature associated with each discrete value of the candidate discrete feature, determination of a deviation score for each of the candidate discrete features based on the second summary statistics, and transmission of the candidate discrete features for display in association with the continuous feature based on the determined deviation scores.

Abstract: An apparatus is described that includes an execution unit to execute a first instruction and a second instruction. The execution unit includes input register space to store a first data structure to be replicated when executing the first instruction and to store a second data structure to be replicated when executing the second instruction. The first and second data structures are both packed data structures. Data values of the first packed data structure are twice as large as data values of the second packed data structure. The execution unit also includes replication logic circuitry to replicate the first data structure when executing the first instruction to create a first replication data structure, and, to replicate the second data structure when executing the second data instruction to create a second replication data structure.

Abstract: Transportable storage devices are communicatively coupled behind one or more dedicated “edge” data servers to take advantage of the benefits of the data servers and transportable storage devices while limiting their disadvantages. Each edge data server ingests data from one or more client devices and copies the data to one or more of the transportable storage devices for eventual transport to a cloud data center for upload to a cloud storage system. Multiple versions of a segment of data (e.g., of a file or a blob) are maintained at various points in the disclosed system and the disclosed technology ensures that the most recent version is the version ultimately stored on the cloud storage system.

Abstract: Adapting database queries from a common interface into conditions specific to database storage formats, optimization of a data model, and virtualization of query results from combined databases.

Abstract: Computer implemented methods for storing ad hoc relations between previously unrelated database objects assigned to different database structures using an electronic computing device are presented, the methods including: causing the electronic computing device to define at least three database structures: structure A, structure B and structure C, where each of the at least three database structures each includes a number of objects, where there exists at least one relation between objects of structure A and objects of structure B, and where there exists at least one relation between objects of structure B and objects of structure C; filtering data of structure A; accessing structure B using a first selected relation between structure A and structure B; storing information about filtering of structure A and information on a first selected path between structure A and structure B; filtering results obtained from structure B.

Abstract: Embodiments of the present disclosure relate to a data analysis system for grouping and enriching data items for presentation to an analyst through a user interface. Data items from one or more data sources are combined into memory-efficient clustered data structures, which may be stored as one or more data tables in a database. Analysis and scoring of those clustered data structures can be performed by utilizing various criteria or rules to generate scores, reports, alerts, or conclusions that may aid an analyst in evaluating the clustered data structures. The analysis and scoring may also be added to the clustered data structures which are stored as one or more data tables in a database. The analyst may be prompted to create a dossier format or specification and to additional enrichments to be performed on the raw data items in the clustered data structures.

Abstract: Systems and methods include determination, determine, for each of a plurality of discrete features, of statistics for each discrete value of the discrete feature based on values of a continuous feature associated with the discrete value, determination, for each discrete feature, of first summary statistics based on the statistics determined for each discrete value of the discrete feature, determination, for each discrete feature, of a dissimilarity based on the first summary statistics determined for the discrete feature and on the statistics determined for each discrete value of the discrete feature, determination of candidate discrete features of the discrete features based on the determined dissimilarities, the candidate discrete features comprising less than all of the discrete features, determination, for each of the candidate discrete features, of second summary statistics based on values of the continuous feature associated with each discrete value of the candidate discrete feature, determine of a devi

Abstract: Embodiments of the present invention are directed to validating extraction rules. In embodiments, a set of events for which field extraction is desired is obtained. Thereafter, an extraction rule is applied to the set of events to extract fields of the events. The application of the extraction rule can be monitored to determine that the applied extraction rule is invalid. Based on the applied extraction rule being invalid, a new extraction rule can be generated to apply to the set of events.

Abstract: Software-based technologies for improving structured data collection, presentation, validation, and workflow management processes are disclosed, including the use of interpretable configuration files to define data objects, generate object-level and sub-object-level specifications for a forms-based interface, validation processes and a workflow-based interface. A back-end integration component maps the data objects, validation and workflow processes, and interface specifications to portions of a back-end database system.

Abstract: An example operation may include one or more of receiving a request for trust information of an off-chain data source from a client, determining a category type of the off-chain data source from among a plurality of category types based on the request, retrieving a reliability value of the off-chain data source linked to one or more of an identity of the off-chain data source and the determined category type from a reliability database implemented via a distributed ledger shared among a plurality of peer nodes, and transmitting the retrieved reliability value linked to the category type to the client.

Abstract: In one example, a method includes receiving, at a cloud storage site, chunks that each take the form of a hash of a combination that includes two or more salts and a file object, and one of the salts is a retention salt shared by the chunks, monitoring a time period associated with the retention salt, when the time period has expired, removing the chunks that include the retention salt, and depositing the removed chunks in a deleted items cloud store.

Abstract: In one example, a method includes receiving, at a cloud storage site, chunks that each take the form of a hash of a combination that includes two or more salts and a file object, and one of the salts is a retention salt shared by the chunks, monitoring a time period associated with the retention salt, when the time period has expired, removing the chunks that include the retention salt, and depositing the removed chunks in a deleted items cloud store.