Abstract: In various example embodiments, a system and method for versioning data in an unstructured data store are presented. The method includes generating a first record in the unstructured data store based on a version of a second record in the unstructured data store. The method further includes initializing a parent version identifier of the first record based on the version of the second record. The method further includes comparing the parent version identifier of the first record to a version identifier of the second record. The method further includes determining whether the first record is consistent based on the comparison.

Abstract: A method and system for computer processes and data structures is described that define an environment for monitoring tasks that together constitute a project, where such processes utilize a scripting language to define certain functions that may relate data from one part of a project to another.

Abstract: A server receives a query identifying one or more attributes of an entity. The server accesses a set of candidate templates for answering the query based on the one or more attributes of the entity, each candidate template having one or more fields, wherein each field is associated with at least one constraint. The server obtains a set of information that answers the query and selects a template from the set of candidate templates, where the selected template has a maximum number of fields with constraints that are satisfied by the set of information. The server then generates a phrase by adding the set of information to the one or more fields of the selected template, such that the phrase comprises an answer to the query. Finally, the server communicates the phrase to a client device.

Abstract: Methods, systems, and devices for data retention handling are described. In some data storage systems, data objects are stored in a non-relational database schema. The system may support configurable data retention policies for different tenants, users, or applications. For example, a data store may receive retention requests, where the retention requests may specify deletion or exportation actions to perform on records contained within data objects. The data store may determine retention rules based on these retention requests, and may periodically or aperiodically evaluate the rules to determine active actions to perform. To improve the efficiency of the system, the data store may aggregate the active actions (e.g., according to the dataset to perform the actions on), and may generate work items corresponding to the aggregate actions. A work processor may retrieve these work items and may efficiently perform the data retention actions on datasets stored in the data object store.

Abstract: Systems, methods, and devices for batch ingestion of data into a table of a database. A method includes determining a notification indicating a presence of a user file received from a client account to be ingested into a database. The method includes identifying data in the user file and identifying a target table of the database to receive the data in the user file. The method includes generating an ingest task indicating the data and the target table. The method includes assigning the ingest task to an execution node of an execution platform, wherein the execution platform comprises a plurality of execution nodes operating independent of a plurality of shared storage devices collectively storing database data. The method includes registering metadata concerning the target table in a metadata store after the data has been fully committed to the target table by the execution node.

Abstract: In some examples, natural language processing (NLP) and artificial intelligence based searching may include identifying named entities in text from a corpus of documents. References in the text may be resolved with the identified named entities. Links between the named entities may be determined, and a bi-direction rootless graph may be generated. Semantic relationships may be determined from text of the named entities, and blacklist keywords may be identified. Machine learning classification may be performed based on a pair of the named entities and a blacklist keyword. A classification may be determined based on the pair of named entities and the blacklist keyword, and a rule may be identified that specifies which named entity in the pair is to be flagged. Further, a node in the graph may be flagged based on an association with the named entity identified according to the rule.

Abstract: Embodiments generally relate transforming data for a target schema. In some embodiments, a method includes receiving input data, where the input data includes a plurality of segments, and where the segments include a plurality of source fields containing target data. The method further includes characterizing the input data based at least in part on a plurality of predetermined metrics, where the predetermined metrics determine a structure of the input data. The method further includes mapping the target data in the source fields of the segments to a plurality of target fields of a target schema based at least in part on the characterizing. The method further includes populating the target fields of the target schema with the target data from the source fields based at least in part on the mapping.

Abstract: Windowed queries with event-based open times are described for use in data analytics for streaming data. A window semantic may be used to define windowed queries of an analytics application that, when executed against an incoming data stream, open a window at a time when a first event associated with a grouping key is received by a windowed query. The window remains open for a predefined duration specified in the windowed query, and query results may be generated based on any events associated with the grouping key that are received while the window remains open. After a lapse of the predefined duration, the window closes, and the query results may be output in association with the window.

Abstract: A system and method for determining the extent of beneficial ownership of a target business by populating a database structure wherein businesses and ownership relationships between the business are represented by nodes and links. Steps include querying the database to establish the related ownership links; analyzing the query to determine ownership loops; de-looping the ownership relationships; and calculating the percentage ownership of each of the beneficial owners of the target business based on de-looped ownership relationships. A computer readable non-transitory storage medium stores instructions of a computer program, which when executed by a computer system results in performance of steps of the method. A system architecture having features uniquely suited to the task is also disclosed.

Abstract: Systems and methods for presenting ranked search results on an interactive graphical user interface based on a semantic matching platform that is configured to apply an ontology are disclosed. In one aspect, a computer system comprising one or more computer readable storage devices configured to store a plurality of computer-executable instructions, a semantic matching platform, one or more network communication systems, and one or more hardware computer processors in communication with the one or more computer readable storage devices to execute the plurality of computer-executable instructions to cause the system to receiving search criteria from a user device, parse the search criteria, determine and rank matched search results, and generating instructions for presentation of a portion of the ranked search results on an interactive graphical user interface configured to be displayed on the user device.

Abstract: Techniques are disclosed for querying for members in multiple groups. A list of unique members in the multiple groups may be received in response to the query. An example methodology implementing the techniques may include generating a group contexts dictionary and a job stack. The group contexts dictionary may include group context objects, each group context object associated with a group within a domain. The job stack may include one or more group context hashset keys, wherein a group context hashset key identifies a group context object. The method may include retrieving one or more group context hashset keys from the job stack and, for each retrieved group context hashset key, traversing a group associated with a group context object identified by a group context hashset key to determine membership information of the group, and generating a list of unique members by removing duplicate entries in the membership information.

Abstract: Embodiments of a data processing system comprises a first database including first records and a second database including second records. The data processing system may also comprise a processor configured to execute instructions to receive a first filter item comprising a first criterion and a second filter item comprising a second criterion and identify, in the first and second records, at least one record that meets the first criterion of the first filter item. The instructions may update the at least one record to include a unique identifier and generate a third database including third records by identifying, in the first and second records, records that include the unique identifier. The instructions may cause a comparison of a rubric of historical linkage features with the third records to identify an element of historical linkage between the at least one record and the third records and generate an event notification including the element of historical linkage.

Abstract: Examples include bypassing a portion of an analytics workflow. In some examples, execution of an analytics workflow may be monitored upon receipt of a raw data and the execution may be interrupted at an optimal bypass stage to obtain insights data from the raw data. A similarity analysis may be performed to compare the insights data to a stored insights data in an insights data repository. Based, at least in part, on a determination of similarity, a bypass operation may be performed to bypass a remainder of the analytics workflow.

Abstract: Various examples are directed to systems and methods for utilizing local identifiers in a distributed database system. A database management system server may receive first execution unit data describing a first execution unit of a first database query. The first execution unit data may comprise first operand data describing a set of operands for the first execution unit. The database management system server may determine that the first operand data describes at least one operand from a first partition and at least one operand from a second partition. The database management system server may generate a first set of local identifiers describing rows at the first partition and a first set of local identifiers describing rows at the second partition. The database management system server may execute the first execution unit based at least in part on the first set of local identifiers describing rows at the first partition and the first set of local identifiers describing rows at the second partition.

Abstract: In one aspect, data replication processes include setting a minimum snap set creation interval, a maximum snap set creation interval, and a recovery time threshold (RTT). An aspect further includes creating snap sets during a synchronous replication process based on the snap set creation intervals and the RTT. The snap set creation further includes monitoring an amount of data changes since the last snap set creation, monitoring throughput statistics between a source and target system, and estimating an amount of time to replicate the data changes to the target system based on the data changes and throughput statistics. Upon determining the time to replicate the data changes reaches the RTT and the time since the last snap set creation passes the minimum interval, the snap set creation includes creating a next snap set, storing the next snap set at the source, and replicating the next snap set at the target.

Abstract: A mood score calculation apparatus has a memory device that stores a manipulation history of a user on a predetermined device and a arithmetic device that classifies the manipulation history into any one of a verbal task and a spatial task on the basis of a predetermined algorithm, calculates the user's mood score on the basis of a relative relationship between the manipulation histories for each of the verbal task and the spatial task specified in the classification, and outputs information on the mood score into a predetermined output target.

Abstract: A portion of a graph dataset is generated for each computing node in a distributed computing system by, for each subject vertex in a graph, recording for the computing node an offset for the subject vertex, where the offset references a first position in an edge array for the computing node, and for each edge of a set of edges coupled with the subject vertex in the graph, calculating an edge value for the edge based on a connected vertex identifier identifying a vertex coupled with the subject vertex via the edge. When the edge value is assigned to the first position, the edge value is determined by a first calculation, and when the edge value is assigned to position subsequent to the first position, the edge value is determined by a second calculation. In the computing node, the edge value is recorded in the edge array.

Abstract: Systems, methods, and devices for batch ingestion of data into a table of a database. A method includes determining a notification indicating a presence of a user file received from a client account to be ingested into a database. The method includes identifying data in the user file and identifying a target table of the database to receive the data in the user file. The method includes generating an ingest task indicating the data and the target table. The method includes assigning the ingest task to an execution node of an execution platform, wherein the execution platform comprises a plurality of execution nodes operating independent of a plurality of shared storage devices collectively storing database data. The method includes registering metadata concerning the target table in a metadata store after the data has been fully committed to the target table by the execution node.

Abstract: Various methods and systems for monitoring files in a computer system are provided. In this regard, aspects of the invention facilitate file monitoring without file handle use, as it pertains to file monitoring and tailing, thereby mitigating file handle locking conflicts. In various implementations, information for the monitored files is obtained from the kernel using a filter driver in the I/O path. When the filter driver detects write operations being performed on monitored files, file-write data is copied and placed in a kernel buffer, where it can be pulled by a user mode monitoring process and fed to a monitoring application. As such, there is no need for coordination between the monitoring process and the user mode processes of other third-party applications writing data to monitored files.

Abstract: A search apparatus encodes a plurality of elements, each of which is a unit of encoding, stored in a plurality of items, in a file that includes a plurality of records each including the plurality of items separated by delimiters, with use of an encoding dictionary indicating corresponding relationships between the elements and codes. Further, the search apparatus generates an index that associates the elements with positions of the respective elements in the file. Then, the search apparatus generates mask information indicating a range of a specific search target item among the plurality of items, in the file. The search apparatus searches for one or more element strings satisfying a search condition, from among search target elements that are indicated by the index as being within the range of the search target item indicated in the mask information, based on the search condition.