Abstract: A terminal device uploads data to a storage device. The terminal device includes a processor and a memory storing instructions that cause the device to determine whether data to be uploaded is a file or a partial dataset being used by an application, determine whether one or more data objects created in a given format is included in the data to be uploaded determined to be the partial dataset, generate image data and a shared byte string from the data to be uploaded if the data objects created in the given format are included in the data to be uploaded, send the data to be uploaded to the storage device as shared data if the data to be uploaded is the file, and send the image data and the shared byte string to the storage device as the shared data if the data to be uploaded is the partial dataset.

Abstract: Embodiments of the present disclosure are directed a distributed storage system that supports query data. One embodiment provides, at a front-end node, a method comprising receiving a query regarding data stored in an object, obtaining information identifying data nodes at which blocks of the object are stored, sending, to a first data node, a query regarding data in a first block, and receiving results for the query regarding the data in the first block comprising an incomplete record. The method further comprises sending, to a second data node, a query regarding data in a second block comprising the incomplete record, the second block being stored on a different physical device than the first block, and receiving results for the query regarding the data in the second block. The method further comprises outputting the results for the queries regarding the data in the first block and the data in the second block.

Abstract: A method and system for handling asynchronous data streams in a multi-tenant system. The process includes receiving at least a first stream of data and a second stream of data by a rules engine, determining by pattern matching of the rules engine, whether data in the first stream or data in the second stream meet conditions of a rule defined by a tenant of the multi-tenant system, and implementing by the rules engine the rule including a set of actions to modify data from the second data stream, in response to the data in the first stream matching the conditions the rule.

Abstract: A system, method, and computer-readable medium are disclosed that generate staging data independently from the execution of control scripts, which process the staging data, improving the quality, efficiency, and speed of data processing systems. The staging data can be independently loaded, validated, and utilized across multiple control scripts, reducing redundancy in the loading of data and the overhead of executing separate data processing for each control script. The control scripts can be automatically validated, such as by verifying expected output data ranges. Additionally, the complexity of the control scripts can be reduced as the loading of data is not performed by the control scripts. The controls scripts can generate a variety of output data, such as an indication of impacted accounts, and provide notifications based on the output data. A variety of machine learning classifiers may automatically generate the staging data and validate the staging data and/or output data.

Abstract: A method for managing metadata for a transactional storage system include receiving a query request at a snapshot timestamp. The query request requests return of at least one data block from a plurality of data blocks. Each data block includes a corresponding write epoch timestamp and a corresponding conversion indicator indicating whether the data block is active or has been converted at a respective conversion timestamp. The method also includes setting a read epoch timestamp equal to the earliest one of the write epoch and determining whether any of the respective conversion timestamps occurring at or before the snapshot timestamp occur after the read epoch timestamp. The method also includes determining the at least one data block requested by the query request by scanning each of the data blocks including corresponding write epoch timestamps occurring at or after the read epoch timestamp.

Abstract: Predefined patterns are detected in streaming data being transmitted in a distributed computing system that contains a plurality of computing devices wherein the plurality of computing devices are collectively configured to execute a distributed software program. In one or more examples, a detection engine can be implemented on a computing device and can be configured to receive streaming data that is being transmitted between computing devices of the system. The detection engine can be further configured to analyze the streaming data to determine if the data matches one or more patterns that is specified by a watch point which can be converted into a happened before language expression. In one or more examples, the streaming data can be converted into an intermediate log file that is compared against patterns expressed by a regular expression and if a match is found, an alert can be generated.

Abstract: Controlling the timing of an execution of a database query for test purposes includes: receiving the database query, the database query comprising control code; the control code causing a database management system to control the timing of the execution of the database query within the database management system; executing the database query within the database management system.

Abstract: A computer server may receive an indication of a selected potential relationship and retrieve, from a use case configuration data store, an electronic record for that relationship. The first entity may then construct computer system configurations in accordance with use case parameters. The computer server may be used to evaluate the constructed computer system configurations, and an entity score result for the first entity may be stored into the use case configuration data store. The computer server may also retrieve, from a quality function deployment data store, an electronic record associated with the first entity and update a uniform scoring matrix by assigning weighted score values for the first entity in connection with a set of platform capabilities. An entity selection tool may be executed to automatically select a recommended entity based on the score results and scoring matrixes, and an indication of the recommended entity may be transmitted.

Abstract: An identification of a dynamic specification is received via a form for building an application. The dynamic specification is able to be utilized to execute one or more database queries to dynamically obtain a list of categories for different embedded screens of an automatically generated end-user application. The end-user application is configured to dynamically generate for a user interface of the end-user application a different selectable user interface element for each category of the list of categories dynamically obtained by executing the one or more database queries and upon selection of one of the selectable user interface elements, provide on the user interface a corresponding embedded screen of the different embedded screens.

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: Provided are methods and systems for searching event sequences. An example method includes receiving a request including a sequence of queries, the sequence of queries including a first query and a second query, the second query succeeding the first query in the sequence; executing the first query over a first dataset to determine a first event; executing the second query over a second dataset to determine a second event, the second event occurring after the first event; and generating, in response to the request, a further sequence including the first event and the second event. The method may include executing the first query over the first dataset to determine a third event and verifying that the third event has occurred after the second event.

Abstract: In the general, the subject matter of the present disclosure relates to a data analysis tool that helps consumers, such as data scientists and engineers, understand datasets better. The disclosed data analysis framework/tool surfaces metrics to data consumers to visually inspect and understand large datasets more efficiently. In addition to the pre-computed and pre-collected metrics on given datasets or tables, the disclosed data analysis tool may also provide a way to detect various anomalies associated with the datasets.

Abstract: Task-dependent analysis of various types of data graphs is provided, based at least on generation of a random graph based on node embeddings corresponding to a data graph, and a graph feature matrix corresponding to the data graph based on a distance between the random graph and the data graph.

Abstract: An example method includes collecting, at a computing system of a data intake and query system, source data corresponding to an instance of a service hosted by a service provider, wherein the service provider hosts the service on a network of the service provider, identifying in the source data a set of metrics for the instance of the service, applying a machine learning model to the set of metrics to determine a classification for the set of metrics, generating, using the classification, a recommendation, wherein the recommendation relates to usage by the instance of the service of one or more physical resources of the service provider, and transmitting, for receipt by a client device, data comprising the recommendation, wherein the data enables display on the client device of a visualization comprising the recommendation.

Abstract: Systems and methods for managing a highly available distributed hybrid database comprising: a memory storing instructions; and one or more processors configured to execute the instructions to: receive a query from a user device to retrieve data from a distributed database comprising a source node, a first plurality of replica nodes, and a second plurality of replica nodes, wherein the source node and the first plurality of replica nodes form a transactional cluster, and wherein the second plurality of replica nodes forms an analytical cluster; determine whether to process the query using the transactional cluster or the analytical cluster based on one or more rules; translate the query into a first protocol that the determined cluster comprehends; select a replica node corresponding to the determined cluster; process the query using the selected replica node; and send data associated with results from processing the query to the user device.

Abstract: A plurality of music playlists created on a content sharing platform and having rankings are identified. A plurality of popular external search queries submitted via one or more search engine platforms external to the content sharing platform are identified. A subset of the plurality of music playlists that matches any of the plurality of popular external search queries is determined, and rankings of the determined subset of music playlists are improved. The personalized music recommendations for the user are created based on rankings of the plurality of music playlists, and the personalized music recommendations are provided for presentation to the user.

Abstract: The subject technology tracks a plurality of queries corresponding to a plurality of query plans based on join operations contained in each of the plurality of queries and a previous time of executing each query. The subject technology selects a first query plan among the plurality of query plans. The subject technology determines a value indicating an estimated improvement in execution time of the first query plan in comparison to a previous execution time of a previous query plan. The subject technology attempts to execute a first query using the first query plan. The subject technology determines that a second query plan selected among the plurality of query plans has a second estimated execution time that is less than an estimated execution time of the first query plan. The subject technology executes the first query corresponding to the first query plan at a subsequent time using the second query plan.

Abstract: One embodiment includes a method for extracting data views. The method includes steps for receiving data from several data sources and identifying raw fields from the received data. The process further includes steps for mapping the identified raw fields to common fields by determining similarities between a raw field and each of the common fields, identifying a target common field based on the determined similarities, and mapping the raw field to the target common field. The process further includes steps for extracting views of the received data based on the mapping of the identified raw fields to common fields.

Abstract: Optimizing database statements using a query compiler including receiving, by a query compiler from a client computing system, a state specification of a graphical user interface; compiling, by the query compiler, a database statement from the state specification, including: optimizing the database statement by repositioning, within the database statement, a limit clause such that the limit clause is processed by the database before at least one join clause; and sending, by the query compiler, the optimized database statement to a database on a cloud-based data warehouse.

Abstract: Aspects of the disclosure relate to multi-dimensional data tagging and reuse. A computing platform may receive first response data associated with responses to a first set of queries. Subsequently, the computing platform may apply data tags to the first response data, which may include tagging the first response data based on multiple dimensions. Then, the computing platform may prompt a user of a computing device from which the data originated to validate the data tags applied to the first response data. Next, the computing platform may analyze a second set of queries which may be associated with the same content type. Thereafter, the computing platform may generate second response data associated with responses to the second set of queries based on the data tags applied to the first response data and send the second response data in response to the second set of queries.