Abstract: A system for shutting down a process of a database is provided. In some aspects, the system performs operations including tracking, during startup of a process, code locations of a process in the at least one memory. The operations may further include tracking, during runtime of the process and in response to the tracking the code locations, memory segments of the at least one memory allocated to the process. The operations may further include receiving an indication for a shutdown of a process. The operations may further include waking, in response to the indication, at least one processing thread of a plurality of processing threads allocated to a database system. The operations may further include allocating a list of memory mappings to the plurality of processing threads. The operations may further include freeing, by the first processing thread, the physical memory assigned to the processing thread by the memory mappings.

Abstract: Systems and methods include presentation of a subset of a result set of items received from a remote system, reception of a command to perform an operation on all items of the result set while presenting the subset, and determination, in response to the command, of whether a total number of items in the result set exceeds a threshold value. If it is determined that the total number of items in the result set exceeds the threshold value, a first request is transmitted to the remote system to perform the operation on all items of the result set, where the first request includes filter values associated with the result set. If it is determined that the total number of items in the result set does not exceed the threshold value, a second request is transmitted to the remote system to perform the operation on all items of the result set, where the second request includes an identifier of each item of the result set.

Abstract: The present disclosure involves systems, software, and computer implemented methods for automatically identifying table locations and table cell types of located tables. One example method includes receiving a request to detect tables. Features are extracted from an input spreadsheet and provided to a trained table detection model trained to predict whether worksheet cells are table cells or background cells and to a cell classification model that is trained to classify worksheet cells by cell structure type. The table detection model generates binary classifications that indicate whether cells are table cells or background cells. A contour detection process is performed on the binary classifications to generate table location information that describes at least one table boundary in the spreadsheet. The trained cell classification model generates a cell structure type classification for each cell that is included in a table boundary generated by the contour detection process.

Abstract: Techniques and solutions are provided for searching for documents upstream, downstream, or both upstream and downstream of a given document, and providing information about relationships between documents in the results. To help users understand relationships between documents, different “voices” can be used in a result display, such as an “active voice” being used for an upstream search and a “passive voice” being used for a downstream search. If desired, results can be limited or filtered, such as limiting a search to a particular relationship type or types, or providing a limit to an amount of indirection between documents. Disclosed techniques can provide more useful information about a document flow, and can reduce computing resources used in generating such displays.

Abstract: Methods, systems, and computer-readable storage media for receiving a first document including structured data and unstructured data, providing a first sub-document and a second sub-document, the first sub-document including the structured data of the first document, the second sub-document including the unstructured data of the first document, generating a prompt using the second sub-document and a second document, inputting the prompt to a LLM, receiving a response from the LLM, providing a calibrated first document by merging the response into the first sub-document, and processing the calibrated first document and the second document using a ML model to provide a prediction, the prediction indicating a matching class between the first document and the second document.

Abstract: The present disclosure involves systems, software, and computer implemented methods for integrated data privacy services. An example method includes receiving a request to initiate an aligned purpose disassociation protocol for a purpose for an object instance. Aligned purpose disassociation applications are identified that are each configured to indicate whether the application can disassociate the purpose from the object instance. Other applications are identified that area each configured to indicate whether the application can block the object instance. A can-disassociate query is sent to each of the aligned purpose disassociation applications. A can-block query is sent to each of the other applications. Can-disassociate responses are received from the aligned purpose disassociation applications. Can-block responses are received from the other applications. An aligned purpose disassociation decision is determined based on the can-disassociate responses and the can-block responses.

Abstract: Various examples are directed to systems and methods for evaluating an Application Program Interface (API) for interfacing an application to a database through a data model. A computing system may access a first view data structure associated with a first API call. The computing system may use a first view data structure to select a first table from the one or more tables, the first table being associated with the first API call, where the data model is described by a plurality of view data structures based on one or more tables at a database, including the first view data structure. The computing system may measure the API against a standard of performance for the API using a first performance double view data structure and a first performance double table.

Abstract: Methods, systems, and computer-readable storage media for receiving a first stream request, providing a first DAG representative of a data processing flow of the first stream request, comparing one or more DAGs representative of respective data processing flows of one or more running streams in a set of running streams to provide a set of comparison results, each running stream being processed by a computing machine of the stream computing system, and determining that the first stream request has a common portion with respect to a first running stream based on a first comparison result of the comparison results and, in response: providing the first stream request and the first comparison result to a computing machine that is processing the first running stream, the computing machine executing a stream merger that merges a non-common portion of the first stream request with the common portion within the first running stream.

Abstract: Systems include reception of a plurality of tags associated with a first job board and, for each of the plurality of tags, one or more values associated with the first job board, input of each of the plurality of tags to a first neural network to determine a field of a job posting system associated with the tag, wherein the first neural network is trained based on a plurality of mappings from fields of the job posting system to tags associated with a plurality of job boards, input of each of the one or more values of each of the plurality of tags to a second neural network to determine an item of the job posting system associated with the value, wherein the second neural network is trained based on a plurality of mappings from items of the job posting system to values associated with the plurality of job boards, creation of first mappings from each of the plurality of tags associated with the first job board to the determined field associated with the tag, creation of second mappings from each of the one or m

Abstract: The present disclosure relates to computer-implemented methods, software, and systems for importing metadata between applications. One example method includes obtaining, at a data warehouse application, metadata for relevant entities in response to a query defined for querying metadata from a metadata source associated with a source application. A service at the source application is queried to identify a set of programming interfaces associated with the relevant entities for acquiring data objects corresponding to the obtained metadata from the source application. Instructions are generated that can be used to configure the database associated with the data warehouse application to acquire a data object based on executing a call to a corresponding programming interface. The generated instructions are provided to the database to configure the database to automatically execute the call to acquire the data object from the source application.

Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. In response to receiving a request from a client device for an overall score for an entity, the program retrieves a first set of data associated with the entity and a second set of data associated with the entity. The program further uses a first computational model to generate a first score based on the first set of the data. The program also uses a second computational model to generate a second score based on the second set of data. The program further determines the overall score for the entity based on the first score and the second score.

Abstract: A computer-implemented method can instantiate a net graph based on one or more existing bills of materials for one or more known entities. The net graph includes a plurality of interconnected nodes representing different objects included in the one or more known entities, and the one or more existing bill of materials define relationship between the objects. The method can determine carbon footprint values of the objects represented by the nodes, collect vectors of object features and carbon footprint values corresponding to selected nodes in the net graph, train a machine learning model using the collected vectors of object features and the carbon footprint values corresponding to the selected nodes, receiving a request associated with a target entity different from the one or more known entities, and responsive to the request, generate an estimated carbon footprint value for the target entity based on the machine learning model.

Abstract: Techniques and solutions are provided for obtaining a suggested configuration for a configurable object. Typically, a particular object and object configuration are recommended based on technical characteristics of the object. However, a user or process wishing to obtain a recommendation may be more familiar with their operational requirements. Disclosed techniques can include an overall solutions category containing solutions of different solutions category subtypes. Sets of requirements attributes and configuration (technical) attributes can be defined for the solutions category. In some cases, a first machine learning model is trained using input values for the requirements attributes and the configuration attributes, and is used to recommend a particular solution in response to a set of input requirement attribute values.

Abstract: A computer-implemented method can receive a message sent from a source entity, perform first pre-processing operations for verifying validity of the message, perform second pre-processing operations for determining a category of the message, extract metadata from the message, generate an enriched message comprising the metadata and the determined category, perform post-processing operations for classifying the enriched message into one of a plurality of event types, broadcast the enriched message to a message broker, and routing, by the message broker, the enriched message to one or more target entities registered an event type into which the message is classified.

Abstract: Techniques and solutions are provided for obtaining a suggested configuration for a configurable object. Typically, a particular object and object configuration are recommended based on technical characteristics of the object. However, a user or process wishing to obtain a recommendation may be more familiar with their operational requirements. Disclosed techniques can include an overall solutions category containing solutions of different solutions category subtypes. Sets of requirements attributes and configuration (technical) attributes can be defined for the solutions category. In some cases, a first machine learning model is trained using input values for the requirements attributes and the configuration attributes, and is used to recommend a particular solution in response to a set of input requirement attribute values.

Abstract: A computer-implemented method can include registering a new version of an application programming interface (API) with an API registry, transforming the new version of the API to a first knowledge graph, comparing the first knowledge graph to a second knowledge graph to determine a difference graph, and sending the difference graph to selected entities who have subscribed to the API registry. The second knowledge graph can be transformed from a prior version of the application programming interface. The difference graph connects the second knowledge graph to the first knowledge graph and identifies changes from the second knowledge graph to the first knowledge graph.

Abstract: A knowledge accelerator platform automatically builds and maintains a knowledge index of assets stored across a plurality of sources to allow consolidated searching of assets in the plurality of sources. The platform automatically processes the assets to extract metadata information and record labels for each asset in the index, without storing the content of an asset itself in the index, where a semantic dictionary maps labels to terminology in different domains. The knowledge accelerator platform further provides an internal user interface that allows internal users to evaluate the knowledge contained in the assets at a high level and thus identify knowledge gaps that can be mitigated, and promote quality assets within targeted user communities. The knowledge accelerator platform also provides an external user interface that recommends assets to users based on various factors such as their experience, status, and domain interests.

Abstract: A computer-implemented method can include generating a first knowledge graph from a first version of an application programming interface (API), generating a second knowledge graph from a second version of the API, identifying changes from the second knowledge graph to the first knowledge graph, and generating a difference graph based on the identified changes from the second knowledge graph to the first knowledge graph. The difference graph connects the second knowledge graph to the first knowledge graph via one or more revision edges, which represent the identified changes from the second knowledge graph to the first knowledge graph.

Abstract: Techniques and solutions are provided for obtaining a suggested configuration for a configurable object. Typically, a particular object and object configuration are recommended based on technical characteristics of the object. However, a user or process wishing to obtain a recommendation may be more familiar with their operational requirements. Disclosed techniques can include an overall solutions category containing solutions of different solutions category subtypes. Sets of requirements attributes and configuration (technical) attributes can be defined for the solutions category. In some cases, a first machine learning model is trained using input values for the requirements attributes and the configuration attributes, and is used to recommend a particular solution in response to a set of input requirement attribute values.

Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program receives, from a client device, a request for information associated with a category. In response to the request, the program further accesses a storage to retrieve a first value associated with the category. The program also determines a set of values associated with the category based on a plurality of transactions. The program further determines an optimization level value associated with the category. The program also determines a second value associated with the category based on the first value, the set of values, and the optimization level value. The program further provides, by an application operating on the device, a graphical user interface (GUI) to the client device, the GUI comprising the second value.