Abstract: Aspects of the disclosure relate to improved techniques for managing a data storage device (DSD) pool, and in particular the selecting of DSDs based on commands distribution and latencies among the command queues in the DSDs. In some aspects, a DSD may have multiple queues that enable the DSD to perform certain commands (e.g., write commands and/or read commands) in parallel. Thus, such DSD has various head-of-line blocking latencies based on which queue the command is directed to. A storage management device can reduce the command latency of the DSDs, for example, based on queue information (e.g., head-of-line blocking, parallel queue utilization, etc.) learned from the DSDs.

Abstract: Techniques for optimizing and deploying deep neural network (CNN) machine learning models for inference using static analysis are described. A method includes obtaining a deep neural network (DNN) machine learning (ML) model, generating an intermediate representation for the ML model, the intermediate representation including one or more nodes corresponding to one or more operators utilized by the ML model, identifying, for at least one node of the intermediate representation, an optimized schedule for at least one operator corresponding to the at least one node using a static analysis that is based on a hardware-specific cost model, generating an optimized intermediate representation using the optimized schedule that is optimized for execution on a hardware platform, and generating code corresponding to the ML model based at least in part on the optimized intermediate representation, wherein the code is specific to the hardware platform.

Abstract: The present disclosure provides a data management method and device based on IIoT, and an electronic device. The data management method comprises: generating a data acquisition instruction and sending the data acquisition instruction to an object platform, transmitting and storing raw data acquired by the object platform to a first general database; performing a first classification on the raw data to obtain a plurality of first data sets; storing the plurality of first data sets into a plurality of sub-databases, respectively, and transmitting and storing the plurality of first data sets to a second general database; performing a second classification on the first data sets based on function types of service sub-platforms to obtain a plurality of second data sets; and storing the plurality of second data sets into the sub-databases corresponding to different service sub-platforms based on a prioritization of the plurality of second data sets to realize data management.

Abstract: A system and method for combining data from disparate business intelligence systems and data sources. The method includes aggregating data in real-time across multiple, disparate data platforms of more than one third party, by mapping nonmatching data parameters used in the different platforms to a common data field. The business intelligence systems are queried to identify responsive data fields, which are then meshed in a translation and/or unification module into the common data field for display. The meshing of the data allows for efficient filtering according to user inputs. The system and method further include applications to allow users to create parameter mappings for the data meshing.

Abstract: Systems and methods are described for batch materialization of an incremental change data capture (CDC) changeset with full row changes. The primary keys are extracted from the incremental CDC changeset and an indication of the extracted primary keys are broadcast to a plurality of executors. The primary keys may be added to Bloom filter or a plurality of Bloom filters that are broadcast to the executors. Each executor filters a baseline data table based on the extracted primary keys to generate a baseline match dataframe with all primary keys matching the extracted primary keys, and a baseline unmatched dataframe with all primary keys not matching the extracted primary keys. Each executor receives full row changes from a partitioned incremental CDC changeset and combines the changes with the baseline unmatched dataframe to produce a final changed baseline data table.

Abstract: Provided herein are system, apparatus, device, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for generating an output indicating differences in the data stored in disparate data storage devices and/or for reconciling data stored in disparate data storage devices. In an embodiment, a server loads a first subset of a first set of data corresponding to one or more first columns and a second subset of a second set of data corresponding to one or more second columns into a data repository. The server identifies one or more differences between the first subset of data and the second subset of data in the data repository, and causes display of the one or more differences. The server may generate an output including the first and second sets of data, and a visual indicator indicating each of the one or more differences and causes display of the output.

Abstract: A method, apparatus, and product to provide a parser for property graph queries with precise error reporting and auto-completion based on information from property graph schemas. The approach generally comprises analysis of graph queries prior to their execution to identify issues prior to execution. In some embodiments, the approach includes any of: use of a property graph schema to determine whether names in a received property graph query exist within a corresponding property graph; determining whether the property graph query includes a comparison of mismatched data types; providing an autocomplete suggestion feature for assistance in resolving errors or corresponding to a cursor position within a query string; or evaluation of a property graph query to determine whether it would return an empty result. In some embodiments, property graph query analysis is performed using a context aware approach.

Abstract: Automated migration systems and methods are described for discovering and tracking a migration of legacy networked resources within a computer network environment. A network resource discovery application (app) implemented on a migration server executes, during an active migration session, a predefined migration query selected from one or more predefined migration queries customized based on corresponding migration types. The predefined migration query discovers a set of network dependencies of a legacy networked resource, corresponding to a migration type, and accessible on a computer network comprising a plurality of online network resources.

Abstract: Systems and methods for generating a machine-learning (ML) model for extracting information from one or more electronic documents, where the ML model can be used as a data object, which can be part of a database command or as part of a document information extraction process that is continuously running (e.g., document information extraction pipeline).

Abstract: A rules engine (RE) may operate in conjunction with a database providing functionality, such as transactional support in data access environments on behalf of tenants. The database may have a data repository accessible by multiple tenants, and tenants may have a private context. RE rules may be defined in the data repository having an extension point corresponding to an extension defined in the private context. Execution of database functionality may affect data defined in the database. Execution of RE rules corresponding to database functionality affects corresponding data associated with the RE. Various techniques, e.g., fact handles, event listeners, etc. may be used to coordinate tracking and synchronizing changes between RE data and/or the database. A flag or other indicator may signify state preservation between multiple calls to the database and/or the RE, e.g., to support analysis involving transactions having overlapping intermediary results such as results from performing data lookups.

Abstract: In an example embodiment, interactions among services in a service proxy are recorded in an interaction log. A service graph manager then parses the interaction log. The service graph manager reads each interaction and then processes the interaction to determine if it violates the rules. If so, the service graph manager reports the violation to the software developer and also recommends an action to remedy the violation. In an example embodiment, this recommendation takes the form of an indication of which files to modify to allow the service interaction (e.g., which rule(s) to modify to ensure that the service interaction is not a violation). The software developer can then approve the proposed action, which can then be automatically implemented to ensure that once the service is sent to a quality assurance environment there will be no rules violation from the corresponding interaction(s).

Abstract: An external function system can be implemented on a database to perform processing on one or more external network services. The external function system can comprise a particular external function for a particular external service, an outbound serializer function, and an inbound serializer function that are linked with the particular external function. The outbound serializer function can be configured to transform the data of a query from a database format to a different format of the particular external network service. The inbound deserializer function can be configured to receive data returned from the external service and transform the data to the format of the database.

Abstract: Some embodiments provide a program that receives a set of data for a first record in a first table. The set of data includes a set of values for a set of attributes. In a data loading process configured to load a subset of the set of data into a subset of a first set of columns in the first table, the program determines that a first column in a first set of columns does not belong in the subset of the first set of columns. The program generates the first record in the first table. The program generates a value for the first column in the first set of columns that refers to a second record in the second table configured to represent a defined type of record. The program stores the value in the first column in the first set of columns of the first record.

Abstract: In an approach to copying of table rows across logical nodes in a distributed database system comprising a plurality of logical nodes, for each logical node of a plurality of logical nodes, a connection is made to a current logical node of the plurality of logical nodes. One or more rows are selected from source nodes of the logical nodes to be stored in a target table on the current logical node, where the one or more rows are selected based on a distribution rule for distributing data in the distributed database system. The rows are stored into the target table, where the rows are pulled from the source nodes and stored in the current logical node.

Abstract: A computer-implemented method, system and computer program product for creating virtualized data assets. A copy of an extract, transform, load (ETL) or an extract, load, transform (ELT) job definition is created. Furthermore, a table function is created in which the table function is configured to trigger the execution of a copy of the ETL/ELT job definition, to read the resulting data from executing the copy of the ETL/ELT job definition and to return the resulting data (data sets), such as in a queue in a federation server. After receiving a query from a user based on a virtual view in which the query includes the ETL/ELT job definition, the table function is executed which triggers execution of the copy of the ETL/ELT job definition. Data sets are then produced by executing the copied ETL/ELT job definition, which is read and returned to the user in the virtual view.

Abstract: Systems, methods, and other embodiments associated with migrating key-value data to a relational database. A method comprises retrieving a namespace from a key-value store and querying the key-value store for a kind category associated with the namespace. The key-value store is accessed and data entities are retrieved that are associated with the kind category that is defined with the namespace identifier. Property names and associated property values are identified in the data entities. The method generates a relational database model including a table; assigns the namespace identifier as schema of the table and assigns the kind category as a table name; builds the table in the relational database model by defining a plurality of columns, wherein a column is defined for each different property name identified from the data entities; and migrates data from the data entities to rows in the table in the relational database model.

Abstract: Systems and methods for a programming language-agnostic data modeling platform that is both less resource intensive and scalable. Additionally, the programming language-agnostic data modeling platform allows for advanced analytics to be run on descriptions of the known logical data models, to generate data offerings describing underlying data, and to easily format data for compatibility with artificial intelligence systems. The systems and methods use a supplemental data structure that comprises logical data modeling metadata, in which the logical data modeling metadata describes the logical data model in a common, standardized language. For example, the logical data modeling metadata may comprise a transformer lineage of the logical data model.

Abstract: A device and method are described for a universal analytical data mart and data structure for same. The analytical data mart (ADM) associated data structure is designed to allow data from disparate sources to be integrated, enabling streamlined business intelligence, reporting and ad hoc analysis. Conceptually, the ADM enables analytics and business intelligence from multiple frames of reference including people, such as parties and actors including individuals and organizations, places, such as addresses with geographic information at various levels of view, objects, such as insured properties, automobiles and machinery, and events, milestones which happen at points in time and provide analytical/business value.

Abstract: A method includes detecting, by at least one hardware processor, an upload of a user application within a database system. The user application includes user-defined function (UDF) code. A plurality of dependencies of the user application is determined by the at least one hardware processor. A plurality of execution environments corresponding to the plurality of dependencies is generated by the at least one hardware processor. The plurality of execution environments is associated with a corresponding plurality of data types of the UDF. A database query is decoded. The database query specifies database data of a data type of the plurality of data types of the UDF. The database query is processed using at least one of the plurality of execution environments to generate results data. The at least one of the plurality of execution environments corresponds to the data type of the plurality of data types of the UDF.

Abstract: The present disclosure relates to methods and systems for querying data in a data repository. According to a first aspect, this disclosure describes a method of querying a database, comprising: receiving, at a computing device, a plurality of keywords; determining, by the computer device, a plurality of datasets relating to the keywords; identifying, by the computer device, metadata for the plurality of datasets indicating a relationship between the datasets by examining an ontology associated with the datasets; providing, by the computer device, one or more suggested database queries in natural language form, the one or more suggested database queries constructed based on the plurality of keywords and the metadata; receiving, by the computing device, a selection of the one or more suggested database queries; and constructing, by the computer device, an object view for the plurality of datasets based on the selected query and the metadata.

Abstract: In various embodiments, a data integration system is disclosed which enables incremental loads into a data warehouse by developing a data partitioning plan and selectively disabling and enabling indexes to facilitate incremental loads into fact tables.

Abstract: Aspects of the disclosure are directed to maintaining transaction consistency when using a columnar cache. The columnar cache can be initially loaded with all-visible data, and as the data gets modified, respective data is invalidated in the columnar cache. As more data gets invalidated in the columnar cache, respective data can be refreshed in the columnar cache. As part of the refresh, the latest all-visible data can be populated while the queries are still using the old data in the columnar cache. When all the queries transition to use the newly populated data, old data can be removed from the columnar cache. A query can use valid blocks of columnar cache and go to a row store for invalid blocks. When a query starts to use the columnar cache, a request can be submitted to asynchronously prefetch the invalid blocks from the row store.

Abstract: A computer-implemented method for efficient processing of pooled data shared by users of a cloud platform, the method includes the steps of uploading at least one dataset by a client device of a user to said cloud platform; calculating similarity scores indicating a degree of similarity between the current uploaded dataset and datasets previously uploaded by client devices of other users; and performing a procedure selected by a user on the cloud platform based on pooled data including the current dataset of the respective user and the datasets previously uploaded from client devices of other users stored in a database of the cloud platform having calculated similarity scores in relation to the current uploaded dataset of the respective user exceeding a configurable similarity score threshold, is provided.

Abstract: The present invention relates to summarizing cross-network user behavioral data. The summarizing cross-network user behavioral data may particularly include publishing the data to one or more data structures that become accessible to a server hosting an authorized domain when a user accesses the authorized domain.

Abstract: In accordance with an embodiment, described herein are systems and methods for data pipeline optimization with an analytic applications environment. The system can determine historical performance data or statistics associated with data pipeline processes recorded over a period of time. The system can automatically determine an order of running jobs associated with the flow of data, while honoring functional dependencies, to reduce or otherwise optimize an overall time to load data to a data warehouse. For example, the system can use the historical data to estimate a time for current or upcoming tasks, or organize various tasks to run in sequence and/or in parallel, to arrive at a minimum time to run an activation plan for one or more tenants. The described approach enables fine-grained monitoring of statistics of ongoing jobs, prediction of potential issues, and communication of alerts where appropriate to address such issues ahead of time.

Abstract: A document creation apparatus includes a first unit that acquires health data indicating a user health condition, a second unit that acquires at least one of consciousness data indicating user health consciousness, environment data indicating an environment related to user health, or knowledge data indicating a knowledge level related to the user health, a determination unit that determines a type of the user health based on a position of a point corresponding to the data acquired by the first unit and the second unit in a space spanned by bases, the bases being a vector having the health data, and at least one vector of a vector having the consciousness data, a vector having the environment data, or a vector having the knowledge data, and a creation unit that creates document data for a document to be presented to the user according to the type.

Abstract: SCAN operations for databases where scan time is dependent on a payload size consume too much memory space and computing time as payload sizes increase. A database table is configured to include an additional index mapping column that stores bitmaps related to the corresponding row of the table. Each bit in the bitmap corresponds to a column and indicates whether that column stores a value. Inclusion of an index column in a table decouples the time it takes to perform the SCAN operation on a column from the payload size of data stored in the column. The bitmaps stored in the index column are relatively small and uniform in size, so the SCAN operation on such a database requires only for the bitmap values of the applicable rows to be obtained from the index column and inspected.

Abstract: Methods, systems, devices, and computer-readable media for orchestrating the sharing of data between accounts that are hosted by a cloud-based data warehousing system on different cloud platforms or in different cloud regions of a cloud platform, and where such accounts may be associated with different organizations. Sharing of data in the multi-cloud platform and/or multi-cloud region environments may be facilitated by the on-demand creation of one or more data collection accounts.

Abstract: A network system to analyze a combined output of various input files from data-based applications. The system provides custom profiling of the data from each application based on an application of one or more sets of rules. The system stores the data from any other number of applications in a base level of granularity to allow direct comparison of the data from each application output. Because the data is stored at a same level of granularity, the data may be compared or processed regardless of the application from which the data is received. The system applies rules to compare the data across the applications to identify outliers, trends, or commonalities. The system may also search for and identify data fitting a specific rule across the applications to extract, modify, or label the data. The system provides a visualization of the data based on the rules applied.

Abstract: In accordance with an embodiment, described herein is a system and method for generating a data cube for analytics. A map-reduce program running in a data processing cluster can read each line of a source data, and generate a key-value pair for each of a plurality of data combinations in that line of data. Values paired with the same key can be aggregated to generate one or more frequency values or one or more aggregate values, for representing the result of a query on the source data. Each query result can be stored in an output file, and can be encapsulated into a data cube cached in a distributed file system of the data processing cluster. The data cube can map a query from a client application to an output file, and can return a pre-computed result in the output file from the data cube to the client application.

Abstract: A system and method for optimizing radiological workflow management and medical image review is disclosed. A preferred embodiment provides a system interoperable with various RIS and PACS systems and that provides efficient access to information, a dynamic prioritized worklist that constantly changes to address optimize distribution of studies and timely review. The novel system facilitates automated assignment, communication between physicians, technicians and radiologists regarding orders, radiographs, reports and studies. The system analyzes exam data, urgency and pendency times, among other things, to automatically determine an overall priority for each case. Cases are assigned for review in the most efficient time, resulting in optimal turnaround time and improved patient care.

Abstract: Methods, systems, apparatuses, devices, and computer program products are described. A system may identify, from an event log including log entries for a tenant of a multi-tenant database system, a pattern of log entries corresponding to main actions and satisfying a frequency threshold. The system may identify log entries associated with the pattern and corresponding to the main actions, detailed actions, or both. The system may retrieve data corresponding to a history field of a data object associated with the pattern and may determine at least a portion of a process flow for the data object according to the pattern and based on the log entries and the historical data. The process flow may include operations to perform using the data object. In some cases, the system may transmit, to a user device, an indication of the portion of the process flow for user review and implementation.

Abstract: A system, method, and computer-readable medium are disclosed that may 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 self-powered sensor node includes a printed wiring board connected to a patch. The printed wiring board includes a microcontroller, a transceiver, an antenna, and a power management module connected to supply electric power to the microcontroller. The patch comprises a metamaterial substrate and a piezoelectric element adhered to the metamaterial substrate. The piezoelectric element is connected to the power management module and to the microcontroller. The power management module is configured to store electric power received from the piezoelectric element. The microcontroller is configured to selectively convert electrical signals received from the piezoelectric element into sensor data and then command the transceiver to transmit the sensor data via the antenna. The metamaterial substrate has an auxetic kirigami honeycomb structure.

Abstract: A system and method for managing data storage and data access with querying data in a distributed system without buffering the results of intermediate operations in persistent storage. The method includes pushing, by a first operator, as a result of executing a query plan, an intermediate result to a plurality of secondary operators. Processing of the intermediate result by the plurality of secondary operators is delayed to coordinate generation of a plurality of second results based on beginning a final consumption operation of the plurality of second results.

Abstract: Embodiments described herein provide systems and methods for a customized search platform that provides users control and transparency in their searches. The system may use a ranker and parser to utilize input data and contextual information to identify search applications, sort the search applications, and present search results via user-engageable elements. The system may also use input from a user to personalize and update search results based on a user's interaction with user-engageable elements.

Abstract: Methods and systems for use in a storage network to prioritize storage units for data storage operations. In various examples, a device obtains data storage cost information relating to the storage network and resource utilization information for a plurality of storage unit sets. The device also determines pending resource demand information for storage units of each of the plurality of storage unit sets. The device further groups, based on at least one of the resource utilization information or the data storage cost information, the storage units into an underutilized resource group and an over utilized resource group and selects, based on at least one of the resource utilization information or the pending resource demand information, a storage unit set of the plurality of storage unit sets for storing new data. The device further issues high priority write access information to storage units of the selected storage unit set.

Abstract: Systems and methods for calculating the virality of a content item are disclosed herein. First data is collected relating to a first content item and second data is collected relating to a second content item. The first and second data are used to plot a continuous probability distribution and using the continuous probability distribution, a virality score is calculated for a third content item. In response to the virality score being greater than a first threshold, the third content item is classified as likely to be viral and the third content item is queued for auto-publishing.

Abstract: Methods, systems, and computer-readable media are disclosed herein that conduct security penetration testing. In accordance with embodiments, a security extension is run in a web browser in order to record a user interface workflow and to generate a test script of the user interface workflow. The test script is executed in an application in order to perform penetration testing of the user interface workflow, in some embodiments. Based on the outcomes of the penetration testing, a security report may be generated in order to identify one or more security vulnerabilities in the user interface workflow.

Abstract: Minimizing queries by sending first query/ies, including query parameter/s having first query parameter value/s respectively, to a database, and receiving therefrom, response/s to the first query/ies respectively; and using at least the query/ies and response/s to compute a model which approximates the database's behavior, the behavior including generating responses pursuant to queries received. The model serves as current model, unless/until replaced by a later computed model. The method may iterate as follows at least once: selecting query/ies, more distant from the first query's query parameter/s than query/ies not selected; sending the selected query/ies to the database and using a received database's response, and the selected query/ies, and query-response pair/s already used, to compute another model of the database's behavior which serves as current model, unless and until replaced by a later computed model.

Abstract: A method of generating and storing metadata in a data processing system includes defining metadata sets of process definition metadata based on a process definition of the data processing system. The metadata sets include a first set of metadata corresponding to a processing step of the data processing system, a second set of metadata corresponding to a processing step successor, and a third set of metadata corresponding to a data object that is produced or consumed by the processing step in the data processing system. The method further includes executing one or more steps of the data processing system according to the process definition and generating runtime metadata during an execution of the one or more data processing system steps. The method further includes storing the runtime metadata and forming a metadata data store that integrates the runtime metadata and the metadata sets of process definition metadata.

Abstract: The present disclosure relates to a system, method, and computer program for extracting large customer data volumes at high speed from an external multi-tenant SaaS environment. The system identifies a plurality of customer data objects to be extracted from the multi-tenant SaaS environment. The system creates an extraction plan for extracting the identified data objects, which includes identifying characteristics of each data object to be extracted, creating a plurality of extraction groups, determining an extraction frequency and extraction mode, determining a scope of data extraction, assigning an API to each extraction group, identifying extraction parameters, determining a degree of parallelism, and creating an extraction plan. The system displays the extraction plan in a user interface and enables a user to edit the extraction plan.

Abstract: An import job associated with a data store update is inspected and schemas associated with target data tables that are to be updated with update data are analyzed. Referential integrity issues associated with foreign keys in the target tables are identified in the update data. The update data is broken into three portions, a first portion that is guaranteed to not have a referential integrity issue, a second portion this is known to have a referential integrity issue, and a third portion that cannot be determined at this stage of processing. The import job is modified to update the corresponding target tables with the first portion of the update data while the second and third portions are not updated to the target data base tables but a custom message is recorded in fields associated with the second and third portions that describes the issue for subsequent review/resolution.

Abstract: The present disclosure relates to computer-implemented methods, software, and systems for exchanging metadata between applications. One example method includes providing a metadata service defining a service metadata model for exposing metadata of data objects defined at one or more applications. A connection to a data source associated with a first application is established from a separate application to acquire the metadata from the data source for one or more data objects related to the first application. In response to establishing the connection, a view of content from the data source is provided that includes a list of entities from the service metadata model. A query defined based on the list of entities is received for acquiring metadata associated with the one or more identified entities. The query is evaluated at a backend of the first application and the metadata for the identified entities from the data source is provided.

Abstract: A computing system to generate models of managed devices and applications in an Internet of Things (IOT) system by identifying each endpoint in the managed devices and applications capable of transmitting or receiving the data and defining flows for data from the endpoints in sensors to endpoints of IOT servers via endpoints of the programmable edge device applications. The computing system can develop a data flow map to define a connectivity of the programmable edge device applications to the sensors and the servers in the IOT system for exchanging the data from the sensors to the servers in the IOT system via the programmable edge device applications. The computing system can prompt configuration of the managed devices and applications in the IOT system based on the data flow map, which implements the connectivity of the programmable edge device applications to the sensors and to servers in the IOT system.

Abstract: Query planning in a distributed database that includes a table partitioned into shards according to a sharding criterion and distributed to database instances includes receiving a data-query. The data-query includes a “distinct count” clause on a first column and a “group by” clause on least a second column. A query plan is formulated to include respective instructions for converting, at at least some of the database instances, distinct values of the first column grouped by values of the second column into a count of the distinct values grouped by the values of the second column to obtain respective intermediate results; instructions for receiving the respective intermediate results from at least a subset of the at least some of the database instances; and instructions for concatenating the respective intermediate results using a summing operation to obtain the first “distinct count” of the first column grouped by the second column.

Abstract: Methods and systems are used for providing a generic data state transfer interface to the state of data and information for a reporting system. As an example, a generic data status request is received, by a generic data source access function of a backend source system, from a reporting system. In response to the generic data status request being received, a first set of notifications is retrieved, by the generic data source access function, from a first source database. Each notification of the first set of notifications to each corresponding target notification of a set of target notifications in a generic data status response is mapped, by the generic data source access function, using a customizable mapping function based on a specific application of a plurality of applications in each notification. The generic data status response is transmitted, by the generic data source access function, to the reporting system.

Abstract: Methods for performing a query operation on a database comprise selecting a connection to the database from a plurality of connections to the database, the connections being arranged within a data structure and each having a predetermined number of query slots; waiting for a query slot to be available on the selected connection; in response to determining that the predetermined number of query slots include at least one available query slot, accessing one of the at least one available query slots; reordering the plurality of connections within the data structure; causing the query operation to execute at least partially using the accessed query slot; and releasing the accessed query slot.

Abstract: Methods, systems, devices, and computer-readable media used by a cloud data management system for collecting data from accounts hosted by a cloud-based data warehousing system on different cloud platforms or in different cloud regions of a cloud platform. Collection of data in the multi-cloud platform and/or multi-cloud region environments may be facilitated by the on-demand creation of one or more data collection accounts. Based on the collected data, one or more data warehouse resources not managed by the cloud data management system may be discovered, configured, and onboarded to the cloud data management system.

Abstract: Enhanced techniques applicable to a ray tracing hardware accelerator for traversing a hierarchical acceleration structure are disclosed. The traversal efficiency of such hardware accelerators are improved, for example, by transforming a ray, in hardware, from the ray's coordinate space to two or more coordinate spaces at respective points in traversing the hierarchical acceleration structure. In one example, the hardware accelerator is configured to transform a ray, received from a processor, from the world space to at least one alternate world space and then to an object space in hardware before a corresponding ray-primitive intersection results are returned to the processor. The techniques disclosed herein facilitate the use of additional coordinate spaces to orient acceleration structures in a manner that more efficiently approximate the space occupied by the underlying primitives being ray-traced.