Abstract: A method for monitoring and managing heterogeneous vendor storage systems may include performing, by a management system, operations including: sending instructions to a vendor storage system among the heterogeneous vendor storage systems to cause the vendor storage system to generate a vendor answer file on the vendor storage system, sending instructions to the vendor storage system to copy vendor data from the generated vendor answer file to volatile memory of the management system, tracking and logging events associated with the copying of the vendor data, validating the copied vendor data based on the logged events, determining standardized reporting data from the validated vendor data in the volatile memory of the management system, saving the standardized reporting data in a data structure formatted for the heterogeneous vendor storage systems, receiving a user query regarding the saved standardized reporting data, and displaying the saved standardized reporting data in a user interface.

Abstract: Techniques are described herein for probabilistic monitoring of high-frequency, low-latency database queries. In some embodiments, a probabilistic query monitoring system periodically samples active database sessions. For example, the system may generate sample data every one second or at some other sampling rate for each database session that is currently active. The sample data may include a mapping between query identifiers to sample counter values that are extracted at different sample intervals. The system may then estimate performance metrics for the set of active database based on the counter values sampled across consecutive sample intervals.

Abstract: A method for processing one or more electronic documents for enhanced search includes defining a bounding box around each key and value of key-value pairs in a first schema file, tagging coordinates of a key corresponding to a first bounding box and coordinates of a value corresponding to a second bounding box in the first schema file. Furthermore, obtaining a first inference file, detecting coordinates of a key corresponding to a third bounding box, and determining coordinates of a fourth bounding box and the value of the first inference file that are determined by applying a normalization operation. Thereafter, extracting value encompassed by the fourth bounding box of the first inference file and automatically creating a searchable index of the first inference file with searchable key-value pairs. The method achieves an efficient and accurate clustering of data items with an accurate, meaningful, and formal objective function.

Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer-readable media for determining for a folder a file organization score and providing a free flow element based on the file organization score selectable to transition from providing a folder view to providing a free flow view. In some embodiments, the disclosed systems determine the file organization score indicating file organizational patterns associated with content items within the folder. Furthermore, based on receiving an indication of a selection of the free flow element, the disclosed systems transition from providing the folder view of the folder to providing the free flow view depicting graphical representations of the content items. Moreover, the graphical representations of the content items are arranged according to one or more content features associated with the content items.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium for intelligently buffering queries from a mobile application. In one aspect, the method may include receiving, by an application programming interface executing on a mobile device, multiple queries, from different software widgets executing on a mobile application, for data from a database stored on the mobile device, determining, by the application programming interface, a level of priority for each query of the multiple queries, providing, by the application programming interface, each of the multiple queries for storage in a data buffer until processing resources of the mobile device are available to process one or more of the multiple queries, and processing each query of the multiple queries against the database stored on the mobile device based on the assigned level of priority.

Abstract: In an example embodiment, a solution is provided in which an outbox table is added to each container in a database. Rather than perform an emit solely using the application instance alone (in response to a notification from the database that the underlying database action has been performed), or using an outside outbox table processor, an outbox table processor is integrated into the microservice application. When a database action is performed by the microservice application, that database action is written into the outbox table in the corresponding container in the database. Furthermore, whenever the outbox table processor determines that the state of the database has changed in a way that leads to an emit, it then reads the actions in the outbox table, issues an emit to notify one or more external systems of the actions, and deletes those actions from the outbox table.

Abstract: Example techniques for execution of query plans are described. In an example, a query plan may include a first sub-plan and a second sub-plan that are to provide the same output. One among the first sub-plan and the second sub-plan may be selected during execution of the query plan based on a runtime performance parameter of a component to be involved in execution of the first sub-plan and a runtime performance parameter of a component to be involved in execution of the second sub-plan.

Abstract: A system and methods for determining computer resource allocation, the system having a network communication interface configured to receive a query from a device, the query indicating a request to perform a processing operation on a portion of one or more data set. The system may also include data storage for data including historical information related to processing of data sets by back-end computer resources, and hardware processors configured to determine one or more scores associated with a query and based at least in part on the historical information. The system may determine a particular back-end computer resource with a highest score, provide a compute request to the particular back-end computer resource to perform a processing operation on a portion of one or more data sets, and store processing information related to the processing of the compute request by the particular back-end computer resource as historical information.

Abstract: A method for assigning data to similarity groups (sim-groups). The method includes: partitioning a data stream, originating from a data source, into stream chunks; for at least a first stream chunk of the stream chunks: initializing a first chunk bin-map for the first stream chunk; partitioning the first stream chunk into first chunk segments; updating the first chunk bin-map based on a chunk segment processing of the first chunk segments; computing, to obtain a first similarity distance set, a similarity distance between the first chunk bin-map and each sim-group bin-map in a first set of sim-group bin-maps; identifying a first sim-group corresponding to a first similarity distance in the first similarity distance set; and assigning the first stream chunk to the first sim-group.

Abstract: The invention relates to a computer-implemented method for managing multiple services in a DBMS. The services respectively are configured to process data that is stored in or is received for being stored in a database managed by the DBMS. The method comprises providing a service manager operatively coupled to the DBMS; registering the multiple services automatically and dynamically at runtime of the DBMS at the service manager; and automatically managing, by the service manager, dependencies between different ones of the multiple registered services.

Abstract: A computing device generates and displays a data visualization in a data visualization user interface. The data visualization includes a plurality of visual data marks representing data from a data source. The computing device detects a first user input to select a visual data mark of the plurality of visual data marks. In response to detecting the first user input, the computing device identifies a first aggregated data value, for the visual data mark, corresponding to a first data field in the data source. The computing device retrieves a first disaggregated set of data rows corresponding to the first aggregated data value, from a first table, in the data source, containing the first data field. The computing device displays, in the data visualization user interface, a plurality of data rows from the first disaggregated set of data rows.

Abstract: A method for automatically selecting input for a smart city application includes determining data schema for a data lake locally stored at a local smart city platform instance and determining aggregate statistical information of data corresponding to a data schema concept. The determined data schema and aggregate statistical information are sent to a global matcher with an identifier of the application. An input matching is received, from the global matcher, for the application, wherein the input matching provides, for each respective input of the application, a respective data schema concept. Data corresponding to the respective data schema concept for each respective input of the data-driven application is provided as input to the application. The input matching is determined using a trained quality of service (QOS) scoring function trained to minimize a QoS error of aggregated QoS scores against a ground-truth QoS score computed from predictive accuracy and/or user feedback.

Abstract: Implementations relate to techniques for providing context-dependent search results. The techniques can include receiving a query and background audio. The techniques can also include identifying the background audio, establishing concepts related to the background audio and obtaining terms related to the concepts related to the background audio. The techniques can also include obtaining search results based on the query and on at least one of the terms. The techniques can also include providing the search results.

Abstract: The present disclosure provides a multi-task deep Hash learning-based retrieval method for massive logistics product images. According to the idea of multi-tasking, Hash codes of a plurality of lengths can be learned simultaneously as high-level image representation. Compared with single-tasking in the prior art, the method overcomes shortcomings such as waste of hardware resources and high time cost caused by model retraining under single-tasking. Compared with the traditional idea of learning a single Hash code as an image representation and using it for retrieval, information association among Hash codes of a plurality of lengths is mined, and the mutual information loss is designed to improve the representational capacity of the Hash codes, which addresses the poor representational capacity of a single Hash code, and thus improves the retrieval performance of Hash codes.

Abstract: A computer system may send an async version of a file to a client, with the async version of the file comprising a uniform resource identifier for the file, a secret key for accessing the file, one or more filter parameters, and at least one of metadata of the file or a sample of data of the file. A portion of the data of the file may be excluded from the async version. The computer system may receive a request for additional data of the file from the client, with the request comprising a parameter value for the filter parameter(s), and then generate a requested version of the file based on the request, including at least a portion of the data of the file in the requested version based on the parameter value. The computer system may then send the requested version of the file to the client component.

Abstract: A technique of calculating evaluation values regarding anonymity for a table obtained by anonymizing an arbitrary table is provided. An anonymity evaluation apparatus includes an evaluation target table generation part configured to generate a first evaluation target table of p×L including L records which are sets of values of p master attributes different from each other from a table to be anonymized of M×N and generate a second evaluation target table of p×L by anonymizing the p master attributes in the first evaluation target table from an anonymized table of M×N by anonymizing the p master attributes in the table to be anonymized, where M is the number of attributes, N is the number of records, p is the number of master attributes, and L is the number of sets of values of p master attributes which are different from each other.

Abstract: In some embodiments, techniques for identifying one or more species in an undifferentiated environmental sample comprising a plurality of nucleic acid sequences are provided. One or more indices that represent a plurality of reference nucleic acid sequences may be provided, and data may be received comprising digital representations of respective nucleic acid sequences. The respective nucleic acid sequences may be aligned, if possible, using the indices. A respective alignment ration may be calculated for each one of the reference nucleic acid sequences, based on the number of nucleic acid sequences aligned to the respective reference nucleic acid sequence and the total number of nucleic acid sequences in the received data.

Abstract: In an embodiment, a computer-implemented method includes receiving a query from a client and determining a query plan for the query. The query plan comprises one or more query operators for executing at least a portion of the query on a database. The method also includes sending the one or more query operators to one or more computing nodes for the one or more computing nodes to execute the one or more query operators on one or more data fragments of the database. In this example, each computing node of the one or more computing nodes hosts a respective data fragment of the one or more data fragments. Further, the method includes detecting an error in executing a first query operator by a first computing node on a first data fragment, and sending, in response to detecting the error, the first query operator to a replacement computing node for executing on the first data fragment hosted by the spare computing node.

Abstract: The present invention generally relates to the field of automated functional testing, and, more particularly, to a method and system for validation of calculation code against calculation specification. Currently the validation is done manually which is time consuming and effort intensive. Embodiments of present disclosure provide an automated method of validation by generating a schema from the calculation specification, retrieving data based on the schema, executing the intermediate calculations, and comparing the result with the output from the calculation code. The method requires minimal manual input and is a fast, simple, resilient and low-code/no-code technique that can be extended to support any type of calculation code and calculation specifications with minimal or no change.

Abstract: The present invention relates to an implementation method for graphic-blockchain-orientated hybrid consensus, at least comprising: calling at least one module to generate a new data block and broadcast it; calling at least one module to check and validate the received new block based on predetermined rules; calling at least one module to generate a void block; and calling at least one module to update a committee member list. The existing graphic blockchain can only achieve probabilistic consensus, yet the present invention achieves deterministic consensus on graphic blockchain for the first time, thereby reaching consensus faster. The present invention decouples generation and consensus of blocks for the first time, so that the two parts can be designed separately in a modularized manner. The present invention provides the first totally decentralized hybrid consensus algorithm in the graphic blockchain. This is unachievable to many existing graphic blockchain such as IOTA and Obyte.