Abstract: Methods and systems for providing a cost effective and robust security solution for shared files stored by file sharing software solutions are described herein. The methods and systems for generating a ledger associated with shared files, which may include scanning data received from applications associated with a number of client devices and from a cloud based scanner. An access manager may control file permissions granted to users based on requests for scan data from each user device requesting access to a shared file. A plurality of different scanning applications may provide data that is collected for each shared file to provide a diverse analysis of a shared file to increase user confidence in a file security status.

Abstract: Techniques are disclosed for providing an aggregate key performance indicator (KPI) that spans multiple services and is based on a priority value. The techniques may enable a user to select KPIs and to adjust weights (e.g., importance) associated with the KPIs. The weight of a KPI may affect the influence a value of the KPI has on the calculation of an aggregate KPI value. The techniques may also include the ability to create a correlation search using the selected KPIs and weights so that a notification may be generated when the aggregate KPI value exceeds a threshold.

Abstract: A method and a system import data into a table. The method includes providing the table with data identities and a primary key assigned to each of the data identities. A temporary copy of the table is provided and contains a data identity to be merged into the table. The table structure of the table and of the temporary copy is determined and the determined table structure is compared to the table structure of the temporary copy to decide which data identities have to be updated and/or imported. In the temporary copy a new column contains a final primary key of the related data identity for its transfer into the table. The data identities in the table that are present in the temporary copy are locked and an update function for the data identities having the same primary key in both the table and the temporary copy are executed.

Abstract: Technologies are disclosed for providing a common information model. Features include: detecting a scheduled time for a key performance indicator reflecting how a service provided by one or more entities is performing, entity definition information recording the association between the entities and its machine data, service definition information associating the entities that provide the service, and the KPI being defined by a search query, including a field identifier specified in a data model, the KPI derives a value from the machine data; performing the query in response to said detecting, including: associating values in the machine data having disparate field names in accordance with disparate schemas with the field identifier specified in the data model, and processing the associated values as semantically equivalent data instances. In doing so, values having the same semantic (or related semantics) can be used together despite being associated with disparate field names from disparate schemas.

Abstract: Application behavior is analyzed to determine relationships between data. Database objects accessed by an application are identified. Then, one or more relationships between the identified database objects are determined based on one or more from a group comprising statements of the application referring to the identified database objects and sets of the identified database objects accessed by different modules of the application.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for dynamic partition selection. One of the methods includes receiving a representation of a query plan generated for a query, wherein the query plan includes a dynamic scan operator that represents a first computing node obtaining tuples of one or more partitions of a table from storage and transferring the tuples to a second computing node that executes a parent operator of the dynamic scan operator. A partition selector operator is generated corresponding to the dynamic scan operator. A location in the query plan is determined for the partition selector operator. A modified query plan is generated having the partition selector operator at the determined location.

Abstract: Disclosed is a pesticide residue detection data platform based on high resolution mass spectrum, the Internet and data science, and a method for automatically generating a detection report. The platform includes allied laboratories, a detection result database of the allied laboratories, four basic sub-databases, a data collection system and an intelligent data analysis system. The intelligent analysis system reads data according to conditions set by a user, performs various statistical analyses according to a statistical analysis model, generates charts, obtains a comprehensive conclusion, and returns an analysis result to the client ends of the allied laboratories.

Abstract: The current document is directed to a virtual-log-file system that provides a browser-like display interface to users, enabling users to view the contents of log files. The virtual-log-file system assembles a virtual log file from the contents of one or more physical log files, applying filters and other processing to physical-log-file entries in order to generate the virtual-log-file entries logically contained within the virtual log file. The virtual-log-file system allows users to navigate, by scrolling, through the entries of the virtual log file, with additional virtual-log-file entries obtained from physical log files by the virtual-log-file system to support logical infinite scrolling in either direction.

Abstract: Techniques and technologies described herein can generate and provide identifiers, such as unique identifiers, for individual records of aggregate data. Such identifiers allow systems to cache and reuse individual records of aggregate data. Also, such identifiers can facilitate simpler analytic views of aggregate data.

Abstract: Methods, non-transitory computer readable media, and computing devices that receive data from a primary storage node. The data is stored in a primary volume within a primary composite aggregate hosted by the primary storage node. A determination is made when the data is tagged to indicate that the data is stored in the primary volume on a remote data storage device of the primary composite aggregate. The data is stored on another remote data storage device without storing the data in a local data storage device, when the determining indicates that the data is tagged to indicate that the data is stored in the primary volume on a remote data storage device of the primary composite aggregate. Accordingly, this technology allows data placement to remain consistent across primary and secondary volumes and facilitates efficient operation of secondary storage nodes by eliminating two-phase writes for data stored on cloud storage devices.

Abstract: A smart log file management device includes: a memory and a processor electrically connected to the memory, the processor being configured to: create a system log message containing information about an update to a folder or a file in the folder, if the folder or file is updated by a user terminal; create a user log message containing information about the user related to the update to the folder of file; and create a smart log message containing association analysis information which is statistical information obtained by analyzing either or both of the system log message and the user log message.

Abstract: Disclosed herein are systems, methods, and devices for providing load unit recommendations. An example method includes monitoring queries executed by a database management system including a database object, determining an access frequency of the database object based upon the monitoring, and determining relative access counter information for the database object based on the access frequency. Subsequently, the method includes generating a sorted element based on the relative access counter information, determining threshold values based on threshold information and the sorted element, and determining a load unit for the database object based on the sorted element and the threshold values. The load unit indicates whether to load the whole database object, or only a portion thereof, into a main memory of the DBMS while accessing the database object.

Abstract: A computing device, including a processor configured to receive a plurality of database entries. The plurality of database entries may include a first portion organized according to a predefined database schema and a second portion not organized according to the predefined database schema. The processor may be further configured to generate an estimated database schema for the second portion and organize the second portion according to the estimated database schema. The processor may be further configured to determine at least one database entry included in the first portion that does not have the estimated data type indicated in the estimated database schema. The processor may be further configured to modify the estimated database schema such that the modified data type matches the estimated data type of the at least one database entry. The processor may be further configured to generate a database analytics model based on the modified database schema.

Abstract: Candidate data record prioritization for match processing includes identifying candidate records for use in match processing to determine records that match to an incoming record. The candidates are grouped into buckets according to bucket roles, with each bucket correlating to a bucket role, and with each bucket role being defined by a unique record attribute set. The method obtains an effectiveness score for each of the bucket roles. The scores are measures of effectiveness of the bucket roles in identifying candidates that match to incoming data records. The method establishes an order of priority in which to process the candidates by prioritizing the buckets into an order based on the effectiveness scores for the bucket roles. The process then commences match processing to process the candidates in the established order of priority where the match processing processes candidates of a higher priority bucket before processing candidates of lower priority buckets.

Abstract: Conditional processing based on data-driven filtering of records is described. A system stores a corresponding identifier in a data structure for each of a data manipulation action, an object, a filter field, a filter condition, and a process. The system receives a request to perform the data manipulation action for the object. The system determines, for each record based on the object, whether the filter field associated with a corresponding record satisfies the filter condition. The system identifies, for each record based on the object, a corresponding record as an included record that should be included for subsequent processing in response to a determination that the filter field associated with the corresponding record either satisfies the filter condition or does not satisfy the filter condition. The system executes the process on each included record.

Abstract: Systems and methods are provided for associating project entities with projects. In various implementations, user activity data is monitored based on sensor data from at least one user device associated with a user. From the monitored user activity data, entity features are determined of project entities corresponding to the user activity data. Time slots are extracted from the project entities. The time slots are clustered based the entity features of ones of the project entities corresponding to the time slots. The project entities are grouped into projects based on the clustered time slots. Project tags corresponding to the projects are applied to the project entities based on the grouping of the project entities. Content is personalized to the user based on the project tags applied to the project entities.

Abstract: Provided is a process including: obtaining network traffic logs; matching a set of a plurality of the user computing devices; obtaining an indicator of content to be measured for effectiveness in driving place visits; selecting from the network traffic logs records of network exchanges in which the indicator is present; obtaining a device identifier from each of the selected records; matching the obtained device identifiers to respective matching sets including the respective obtained identifier; obtaining respective mobile device identifiers from the respective matching sets; selecting from the network traffic logs records indicating communications from mobile computing devices identified by the obtained mobile device identifiers; obtaining geolocations from the records indicating communications from the mobile computing devices identified; determining that a subset of the records have geolocations that correspond to at least one of a set of geographic areas; and determining an effectiveness of the content i

Abstract: A device receives user interface interaction data that identifies an interaction that a user has with an interface that displays an image of a vehicle. The device generates, by using a data model to process at least a portion of the image, an array of vectors that includes one or more vectors relating to vehicle characteristics of the vehicle. The device assigns one or more weights to the one or more vectors based on the user interface action data. The device determines, based on a similarity analysis, similarity scores that indicate similarities between the array of vectors that include the one or more vectors that have been weighted and other arrays relating to the vehicles depicted in the images. The device selects a subset of the images based on the similarity scores and causes the subset of the images to be displayed.

Abstract: Technologies are described for facilitating transaction processing within a database environment that includes one or more processing units and a memory. A request for a database operation, such as a query, is received from a client. Execution statistics associated with the request are retrieved. At least some of the execution statistics are compared with one or more threshold values. Based on results of the comparing, the request is carried out with a first execution component or delegated to a second execution component. The request is executed and execution results are sent to the client.

Abstract: Various embodiments are generally directed to a dynamic, flexible acronym decoder. A user may submit a query via one of a plurality of user interfaces. Information describing the user may be received to generate a context vector for the user. The query may be processed against a database of terms using the context vector, a machine learning model, and content tags applied to terms in the database. Processing the queries against the database may return a result set, and the ML model may be used to compute a score for each result. The results may be ordered based on the scores and returned as responsive to the query.