Abstract: A computer implemented method can receive a write request to store sensor data generated by a sensor group including a plurality of sensors. The sensor data includes at least a structure identifier and one or more pairs of sensor parameters and sensor values. The method can identify a metadata structure based on the structure identifier. The metadata structure includes a plurality of tuples corresponding to the plurality of sensors in the sensor group. The tuples define pairs of field names and data types of the corresponding sensors. The method can pack the one or more pairs of sensor parameters and sensor values into one or more data containers, and store the one or more data containers respectively into one or more columns of a sensor data table.

Abstract: Techniques and solutions are provided for determining changes to networks formed from network objects. Changes to network objects, such as addition or deletion operations are received and associated with timestamps. Last data changes for respective network objects are determined, including a last data change for a particular type associated with a respective networked object, where a networked object may be concurrently associated with a plurality of types. A first network object is removed from a first network, and contributions of the first network object to edges in the first network are removed. A second network object is associated with an addition operation and at least one edge is determined that connects the second network object and a third network object. Sets of disconnected network objects are determined. Network objects are associated with an identifier identifying a network that includes a respective network object.

Abstract: Technologies are described for migrating deployment infrastructure containers. Deployment infrastructure containers are used for isolating and deploying related database objects together. Deployment infrastructure containers can store design-time artifacts and run-time artifacts. Deployment infrastructure containers can be migrated using a first migration technique in which catalog objects are migrated from a source database system to a target database system and updated to work in the target database system (e.g., by updating metadata). Deployment infrastructure containers can also be migrated using a second migration technique that migrates design-time artifacts and builds the design-time artifacts at the target database system to re-create the run-time artifacts. Migrated deployment infrastructure containers can be integrated into the target environment, which can include creating new service instances and associating them with the migrated deployment infrastructure containers.

Abstract: Data sources provide access to data. The data stored by the data source may be transformed before use by an application. Different data sources support different transformations. A data agent sidecar for the application accepts work orders from the application and submits work orders to data sources. A work order identifies a data source from which data is requested. The work order optionally includes one or more transformations to be applied to the data from the data source. The data agent sidecar determines, for the data source from which data is requested, which transformations can be performed by the data source and which transformations are not supported by the data source. The data transformations that can be performed by the data source are included in the work order to the data source. The remaining data transformations are performed by the data agent sidecar.

Abstract: Various examples described herein are directed to systems and methods for managing a cloud-implemented database management application. A frontend service executing at a cloud environment may receive a plugin request from a first user associated with a first user group and determine a version of a database management application executing at the cloud environment for the first user group. The frontend service may access a plugin catalog to determine at least one plugin compatible with the database management application and provide an indication of the at least one plugin to the first user. The frontend service may receive from the first user a selection of a first plugin from the at least one plugin and call a plugin installer service executing at the cloud environment to install the first plugin to the database management application.

Abstract: Provided are a computer-implemented method, a computer program and a system for determining a knowledge graph query having a response conforming to a plurality of training samples. The method may comprise receiving a knowledge graph; receiving the training samples, wherein each of the training samples is a relation, wherein each value in the training samples corresponds to one of the nodes of the knowledge graph, wherein the training samples include one or more positive training samples and one or more negative training samples; identifying one or more variables from the training samples.

Abstract: In some implementations, there is provided a method including receiving, by a centralized controller, data from a plurality of database tables at a plurality of database instances at a cloud service, wherein the data is received via a plurality of database views on the plurality of database tables; in response to receiving the data, performing, by the centralized controller, a union view of the data obtained from the plurality of database views; storing, by the centralized controller, the union view of the data as configuration metadata; and performing, by the centralized controller, at least one calculation view to update a value of the configuration metadata and to provide the updated value to at least one of the plurality of database tables at the cloud service. Related systems and articles of manufacture are also disclosed.

Abstract: Implementations include receiving, by a semantic translation service of a ML platform, an output data set from a ML model, the output data set including a predicted value and a set of metrics, determining, by the semantic translation service, a numerical value based on at least two or more metrics in the set of metrics, selecting, by the semantic translation service, a semantic result by mapping the numerical value to a projection including two or more semantic values, and transmitting, by the ML platform, a prediction result at least partially including the semantic result for selective display to a user using one or more user interfaces (UIs).

Abstract: According to some embodiments, systems and methods are provided, comprising receiving a code fragment exhibiting a static code issue; determining, via a trained exemption neural network, whether the received code fragment is exempt or not exempt from resolution; in a case it is not exempt, inputting the code fragment to a trained classification neural network; determining whether the static code issue is a syntactical static code issue or a non-syntactical static code issue; in a case it is a syntactical static code issue, inputting the code fragment to a first trained network to generate a first resolution; and in a case the static code issue is a non-syntactical static code issue, inputting the code fragment to a second trained network to generate a second resolution of the non-syntactical static code issue. Numerous other aspects are provided.

Abstract: Techniques and solutions are provided for grouping of applications, including application content, or other content useable by a computer-implemented process. In particular, a consolidation space is provided as a lightweight mechanism for this purpose. Identifiers are received for multiple landscape elements, where a landscape element can be an application, application content, or other content. A given landscape element has a type and has one or more artifacts. A consolidation space is generated for at least first and second landscape elements having a first type. A consolidation artifact is generated in the consolidation space, where the consolidation artifact references respective first and second instances of a first artifact in the first and second landscape elements.

Abstract: Technologies are described for determining a loading arrangement for hollow circular pipes. Determining the loading arrangement can comprise determining an optimal telescopic arrangement for a plurality of hollow circular pipes. Determining the optimal telescopic arrangement can comprise determining a concentric telescopic arrangement and determining a radial telescopic arrangement. Groups of hollow circular pipes can be generated based on the concentric telescopic arrangement and the radial telescopic arrangement that specifies which of the hollow circular pipes will be arranged within each other concentrically and which of the hollow circular pipes will be arranged within each other radially. The loading arrangement can be determined that includes the optimal telescopic arrangement. The loading arrangement can also indicate how the groups of hollow circular pipes will be loaded into a container for shipment.

Abstract: To perform 3-dimensional interpolation, a 3-dimensional model of an input text character is generated. For example, a 2-dimensional character may be given depth using an extrusion transformation. The 3-dimensional model of the input text character is compared to 3-dimensional models of candidate characters and the results of the 3-dimensional comparisons are used to select the optical character recognition (OCR) output for the input text character. The 3-dimensional comparison may be performed directly on the 3-dimensional models. Alternatively, a set of 2-dimensional images may be generated for each 3-dimensional model and 2-dimensional comparisons performed. By use of the additional information gathered from the comparisons of the 3-dimensional models, the correct OCR output character can be identified with greater confidence.

Abstract: Disclosed herein are various embodiments for performing a delta merge with location data. An embodiment operates by receiving a command to merge a delta storage with an original main storage. A coordinate system corresponding to a plurality of data entries of location-based data in the delta storage is identified. A coordinate system specification, corresponding to one of the identified coordinate system, is added to a metadata of a new version of the main storage. A merge operation is performed between the delta storage and the original main storage, in which the plurality of data entries of the delta storage are copied to a container portion of the new version of the main storage, separate from the metadata. The plurality of data entries of the delta storage are deleted and the original main storage is replaced with the new version of the main storage.

Abstract: The present disclosure relates to computer-implemented methods, software, and systems for detecting outages in a cloud environment. Internal web agents installed at corresponding network segments of a first cloud platform and external web agents installed at an external second cloud platform are configured to perform network calls between themselves and the other web agents. Data from the internal web agents is automatically collected to generate structured data defining network connectivity status corresponding to the network segments of the first cloud platform based on the performed network calls between the internal and external web agents. In response to evaluating the structured data, a health status of network connectivity of the first cloud platform is determined. The health status can be provided to platform services provided by the first cloud platform and/or applications running on the first cloud platform to support managing of lifecycles of entities running on the first cloud platform.

Abstract: Disclosed herein are system, method, and computer program product embodiments for classifying data objects using machine learning. In an embodiment, an artificial neural network may be trained to identify explained variable values corresponding to data object attributes. For example, the explained variables may be a category and a subcategory with the subcategory having a hierarchical relationship to the category. The artificial neural network may then receive a data record having one or more attribute values. The neural network may then identify a first and second explained variable value corresponding to the one or more attribute values based on the trained neural network model. The first and second explained variable values may then be associated with the data record. For example, if the data record is stored in a database, the record may be updated to include the first and second explained variable values.

Abstract: Provided is a method and system for building a compliance software service using reusable and configurable components. In one example, the method may include receiving a request to build a software in association with an identified jurisdiction from among a plurality of jurisdictions, retrieving a plurality of configurable software components which comprise built-in functionality that is generic across the plurality of jurisdictions, dynamically configuring non-generic functionality for the identified jurisdiction within the plurality of configurable software components based on inputs received from a user, and creating a software program for the identified jurisdiction based on the dynamically configured software components and storing a file including the created software program in a storage device.

Abstract: A log sampling and storage system reduces volumes of stored log information. A log storage engine receives a series of log messages responsive to a request. The engine compares that series to various patterns previously generated from historical log data. This comparison can reference •a name of the request; •a total time to process the request; •an item count; •a message length; and/or •a message hash code. Comparing incoming log series with the predefined patterns, results in generation of a similarity score. If the score falls outside a tolerance, the existence of an outlier log message series is indicated, and that outlier log message series is stored in its entirety. However, if the similarity score falls within a tolerance, similarity to an existing predefined pattern is indicated. Rather than storing the (non-outlier) log message series, the engine directs storing a link to a sample log message series reflecting the pattern.

Abstract: A computer implemented method can receive a request for a fallback query execution plan of a query in a database system. The query involves an object of the database system. The object is associated with a captured object. The method can evaluate whether the object and the captured object have the same logical structure. Responsive to an indication that the object and the captured object have the same logical structure, the method can reuse the fallback query execution plan to execute the query. The evaluating includes identifying a logical structure of the captured object stored in an object definition table, obtaining a current logical structure of the object, and comparing the logical structure of the captured object with the current logical structure of the object.

Abstract: Systems and processes for managing access to personal data based on a purpose for storing the personal data are provided. In a method for managing personal data access, personal data for a data subject corresponding to a first data category is received, and an operation is executed in a purpose agent to associate one or more purposes to the personal data, where the one or more purposes are assigned to the first data category and include at least a first purpose. The personal data may be stored in a data storage system, and the stored personal data may be designated as being associated with the one or more purposes. Access to the personal data may be controlled based on the one or more purposes.

Abstract: Methods, systems, and computer-readable storage media for executing a first application on a source system during production use of the source system, providing a second application on a target system, during the production use of the source system: migrating data from the source system to the target system based on a catalog delta, and a data delta, each of the catalog delta, and the data delta being periodically determined, and determining whether a completion time exceeds a threshold time, the completion time being determined based on a last-determined data delta, and, in response to determining that the completion time does not exceed the threshold time: halting production use of the source system, and completing migration to the target system based on the last-determined data delta.