Abstract: According to some embodiments, methods and systems may be associated with a cloud computing environment. A unified provisioning service may include a plan configuration data store that contains information associated with a combined service representing a plurality of multi-tenant cloud applications. A cloud platform provisioning framework may receive an indication of a subscription request for the combined service from a consumer via a Software as a Service (“SaaS”) marketplace and access, responsive to the received indication, a dependent service framework of the unified provisioning service. The cloud platform provisioning framework may then receive dependency subscription data from the unified provisioning service, and, based on the dependency subscription data, arrange for the consumer to be subscribed to each of the plurality of multi-tenant cloud applications.

Abstract: In one general aspect, a method can include receiving, in a user interface of a first page of an application executing on a computing device, a selection of an animation option, receiving, in a user interface of a second page of the application executing on the computing device, a selection of an icon. In response to receiving the selection of the icon, the method can further include launching a third page of the application, and performing an animation of a visual presentation of the launching of the third page of the application from the second page of the application. The animation can be based on the received animation option selection.

Abstract: Provided are systems and methods for linking source data fields to target inputs having a different data structure. In one example, the method may include receiving a request to load a data file from a source data structure to a target data structure, identifying a plurality of target inputs of the target data structure, wherein the plurality of target inputs include a format of the target data structure, and at least one of the target inputs has a format that is different from a format of a source data structure, dynamically linking the plurality of source data fields to the plurality of target inputs based on metadata of the plurality of source data fields, and loading the data file from the source data structure to the target data structure.

Abstract: A computer-implemented method can receive a new plan deviation alert having a deviation level that quantifies a mismatch between expected supply chain parameters specified by a supply chain plan and observed supply chain parameters. Responsive to the new plan deviation alert, the method can perform a rule-based search to find a plurality of potential remediation solutions to correct the mismatch. The method can simulate implementation of the potential remediation solutions and evaluate expended resources associated with them. Based on the evaluated expended resources, the method can generate a ranked list of candidate remediation solutions and display the ranked list of candidate remediation solutions in a user interface. The method can receive a selected remediation solution from the ranked list of candidate remediation solutions for initiation. Machine learning can be used on an expert user's selection to adapt to the expert's preferences and provide more relevant remediation solutions.

Abstract: Various examples are directed to systems and methods for providing software services to one or more consumer systems. A cloud service provider system may receive a first outage message from a second cloud service provider system. The first outage message may describe a first outage of a first software service consumed by the first cloud service provider system and provided by the second cloud service provider system. The cloud service provider system may apply a set of outage inheritance rules to the first outage message and determine that the first outage is to be auto-reported. The cloud service provider system may render a revised first outage message and send the revised first outage message to a consumer system that receives a second software service provided by the cloud service provider system.

Abstract: There is provided a method for compressing a first tree data structure. The method includes determining, by a processor, to compress a first tree data structure associated with a dictionary of a database management system. The method further includes compressing the first tree data structure to generate a compressed tree data structure. The compressing includes traversing, by the processor and in response to the determining, the first tree data structure on a lowest level. The compressing further includes identifying, by the processor and in response to traversing, empty nodes on the lowest level. The compressing further includes removing the identified empty nodes to compress the lowest level. The compressing further includes constructing, in response to the removing, a second level of the compressed tree data structure based on the compressed lowest level, the second level higher in the compressed tree data structure than the compressed lowest level.

Abstract: A method may include generating, based a context-free grammar, a sample forming a corpus. The context-free grammar may include production rules for replacing a first nonterminal symbol with a second nonterminal symbol and/or a terminal symbol. The sample may be generated by rewriting recursively a first text string to form a second text string associated with the sample. The first text string may be rewritten by applying the production rules to replace nonterminal symbols included in the first text string until no nonterminal symbols remain in the first text string. A machine learning model may be trained, based on the corpus, to process a natural language. Related methods and articles of manufacture are also disclosed.

Abstract: The present disclosure relates to computer-implemented methods, software, and systems for database persistency. A first data request is received at a first instance of an application. The application is associated with multiple instances that share the database layer. In response to determining that the database is available for accessing after receiving the first request, the database is identified as a primary storage for the application, the data is written in the database and at an in-memory persistence storage of the first instance of the application. In response to determining that the database has become unavailable after identifying the database layer as the primary storage, the in-memory persistence storage is configured as the primary storage for the first instance of the application. A second request received at the first instance of the application is routed to the in-memory persistence storage while the in-memory persistence storage is configured as the primary storage.

Abstract: The present disclosure involves systems, software, and computer implemented methods for defining and using a system metamodel for an event-driven cluster of microservices. A deployment package that includes metadata definitions is received for a microservice. The metadata definitions include: a reference to a service; a reference to a resource entity served by the service; a reference to an event subscribed to by the service; a reference to a micro frontend that provides a user interface for the service; and a reference to an API for performing operations on the resource entity. The microservice is deployed, which includes including the metadata definitions in a system metamodel graph. The microservice is activated, including generating at least one event corresponding to including the metadata definitions in the system metamodel graph. In response to a request for metadata for the microservice, the system metamodel graph is traversed to retrieve the requested metadata.

Abstract: A predictive model pipeline data store may contain electronic records defining a predictive model pipeline composed of operation nodes. Based on the information in the data store, an execution framework platform may calculate a hash value for each operation node by including all recursive dependencies using ancestor node hash values and current node parameters. The platform may then compare each computed hash value with a previously computed hash value associated with a prior execution of a prior version of the pipeline. Operation nodes that have an unchanged hash value may be tagged “idle.” Operation nodes that have a changed hash value may be tagged “train and apply” or “apply” based on current node parameters (and an “apply” tag may propagate backwards through the pipeline to ancestor nodes). The platform may then ignore the operation nodes tagged “idle” when creating a physical execution plan to be provided to a target platform.

Abstract: Systems, methods, and computer media are described for index-based join size estimation. For a join operation between two tables, a filter is applied to the first table, resulting in a filter output. The filter output is then sampled. For each sample, an index for a second table is accessed and counts of records in the second table that match the sample are retrieved. Using the sample size and the retrieved counts from the index of the second table, a data size for the join operation can be efficiently and accurately estimated. Statistical confidence in the estimate can also be assessed using variance-based calculations.

Abstract: A client device sends a connection request to a virtual system in a Kubernetes cluster. The connection request identifies the client device and the application to which the request pertains. Based on a tenant associated with the client device, the virtual system connects the client device to an instance of the application. The instance of the application has access to data for the tenant but not for other tenants. Another client device of the tenant sends another connection request to the virtual system for a connection to another application. Because the tenant is the same, the instance of the other application may access the same data as the instance of the first application. In this way, applications for a single tenant may share data while maintaining the security of the data from other tenants.

Abstract: Technologies are described for managing multiple cache specifications for a single view in a database environment. For example, a plurality of caches can be crated for the single view. Each of the plurality of caches can have a different cache specification. A query can then be received that operates on the single view. One of the plurality of caches can be selected for processing the query based at least in part on the cache specifications. The query can be processed using the selected cache. Results of processing the query can be output.

Abstract: A global dictionary is described that corresponds to a database or table stored across multiple partitions. The global dictionary can be used to identify which partitions of the database contain records that are relevant to a user's query on the database. The global dictionary is made up of variable tables. Each variable table corresponds to a column of the database. A given variable table includes value tables where each value table corresponds to a defined value that has been assigned to a record in the database. A value table can include a list of partitions that contain a record having the related defined value.

Abstract: A method for integrated database user privilege management can be implemented. The method presents a computer interface for managing access privileges of one or more users to a database comprising independent data and dependent data, and retrieves one or more role objects, record filter objects, and attribute filter objects assigned to a user. A role object defines access privileges to selected values of the independent data and dependent data. A record filter object can modify the access privileges defined in the one or more role objects. An attribute filter object defines access privileges to selected attributes of the independent data. The method can calculate, and present on the computer interface, a list of attributes of the independent data and a list of dependent data that the user has access privileges based on the one or more role objects, record filter objects, and attribute filter objects assigned to the user.

Abstract: Disclosed herein are various embodiments for targeted document information extraction. An embodiment operates by receiving a document associated with a particular customer of a plurality of customers. It is determined whether to use a global processor or template processor to analyze the document based on whether one or more customer templates are associated with the particular customer. Which of the one or more templates associated with the particular customer correspond to the document is identified. The document is compared to the identified template associated with the customer. Information is extracted from the document based on the identified template and the identified plurality of variations. The extracted information for the document is output.

Abstract: The present disclosure involves systems, software, and computer implemented methods for resolving data location for queries in a multi-system instance landscape. One example method includes receiving a request for data for at least one entity that includes a qualified identifier that includes a system tenant qualifier and a local identifier. The system tenant qualifier identifies a system tenant in a multi-system tenant landscape and the local identifier identifies an entity instance of an entity in the system tenant. A routing policy table configured for the multi-system tenant landscape is identified and a cell is located in the routing policy table that corresponds to the entity and the system tenant. A routing policy is determined for routing the request based on the cell. The routing policy is used to determine a target system tenant to which to route the request and the request is provided to the target system tenant.

Abstract: An information retrieval system is provided.

Abstract: Computer-readable media, methods, and systems are disclosed for storing and analyzing dynamic data within a semantic data store. The dynamic data comprises one or more types of data having a normalized data schema. A dynamic data manager interfaces with the semantic data store to instruct storage of the data. The data may be received through an event service from either of an external data source or an internal data source.

Abstract: A method for managing the configuration of an in-memory database running in a cluster of computing nodes may include receiving a configuration request to configure an instance of the in-memory database. The configuration request may include an identifier of a configuration profile specifying a value for each of one or more parameters of the in-memory database. The presence of the instance of the in-memory database and the configuration profile specified in the configuration request may be verified. Upon verifying the presence of the in-memory database and the configuration profile, the instance of the in-memory database may be configured based the configuration profile. The configuring may include setting, to the value specified in the configuration profile, the one or more parameters of the in-memory database. Related systems and articles of manufacture, including computer program products, are also provided.