Abstract: In an example embodiment, a first version of a cloud-based application is deployed. The first version of the cloud-based application contains references, based on a first schema, to a first database. Then a second version of the cloud-based application, different than the first version, is deployed. The second version of the cloud-based application contains references, based on a second schema, to the first database. Then access to the second version of the cloud-based application to one or more user devices is prevented while permitting testing devices to have access to the second version of the cloud-based application, while migrating data from the first schema of the first database to the second schema of the first database. Then access to the second version of the cloud-based application to the one or more user devices is permitted once the migrating of the data is complete.

Abstract: The present disclosure relates to computer-implemented methods, software, and systems for utilizing tools and techniques for identifying process rules for automated execution of instances of a process workflow. One example method includes extracting rules from a machine learning model for prediction of execution results of process workflow instances. Metrics defining coverage and accuracy of the rules are calculated. The rules are evaluated according to the metrics and are reduced to a first set of rules that are provided for further evaluation. A rule from the first set of rules is determined to be incorporated into process rules defined for the process workflow at a process execution engine. The process rules associated with execution of the process workflow are updated to include the first rule and to generate a process result automatically according to the first rule when the instance complies with prerequisites defined at the first rule.

Abstract: Various examples are directed to systems and methods optimizing database queries. A database management system may receive a first query comprising a plurality of query expressions. The database management system may determine that a first expression of the first query is nullable and that the first expression is null preserving. The database management system may generate optimized query code for the first query. The optimized query code may comprise a first code segment and a conditional jump instruction. The first code segment that, when executed by a processor, may cause the processor to perform operations comprising determining a value of the first expression. The conditional jump instruction may, when executed by the processor, cause the processor to perform operations comprising: skipping execution of at least a portion of the first code segment and returning null for the first expression.

Abstract: A system includes reception of a first request for a lock on a lock object, storage of a first entry associated with the first request and the lock object in a queue, determination of a first queue position associated with the first entry based on a first priority level of the first request and on a priority level of each of a plurality of entries in the queue associated with the lock object, determination of whether a predetermined expiration time associated with the first request has expired, and, if it is determined that the predetermined expiration time has expired, deletion of the first entry from the queue.

Abstract: Provided is a system and method for transferring data attributes of an embedded software program on a device into a PLM instance of the device. Data attributes may be mapped to a predefined data structure of the PLM instance thereby ensuring that the software data is compatible with the process of a PLM environment. In one example, the method may include receiving a request that identifies a software program of an embedded system, identifying data attributes of the software program within a software development application, where the data attributes comprise a description of the software program and a build version of the software program, and translating the identified data attributes of the software program into a predefined data structure of a lifecycle management instance of the embedded system.

Abstract: Systems, methods, and computer media are described for user risk assessment using similarity analysis. Records of transactions performed by a user while in previous enhanced application access sessions can be evaluated against records of transactions performed by other users in previous sessions. The more similar a user is to other users, the more likely it is the user was acting in a typical manner, and the less likely the user poses a security risk. A similarity analysis can be performed using a bipartite graph linking a group of users and a group of application transactions. By examining an edge between a user and a performed transaction, other edges (and corresponding other users) can be identified that also performed the transaction. A similarity score can be calculated based on the bipartite graph and can be used to determine a risk classification and allow or deny an enhanced application access session request.

Abstract: Disclosed herein are system, method, and computer program product embodiments for determining a constraint data statistics object is consistent. An embodiment operates by receiving a query for a database table. The embodiment determines a constraint data statistic object associated with a partition of the database table. The embodiment determines the constraint data statistics object is consistent with a data state of the partition of the database table based on consistency metadata of the constraint data statistics object. The embodiment processes the query for the database table based on the determining the constraint data statistics object is consistent with the data state of the partition of the database table.

Abstract: Implementations of the present disclosure include methods, systems, and computer-readable storage mediums for receiving first and second data sets, both the first and second data sets including structured data in a plurality of columns, for each of the first data set and the second data set, inputting each column into an encoder specific to a column type of a respective column, the encoder providing encoded data for the first data set, and the second data set, respectively, providing a first multi-dimensional vector based on encoded data of the first data set, providing a second multi-dimensional vector based on encoded data of the second data set, and outputting the first multi-dimensional vector and the second multi-dimensional vector to a loss-function, the loss-function processing the first multi-dimensional vector and the second multi-dimensional vector to provide an output, the output representing matched data points between the first and second data sets.

Abstract: A database receives pages that are piped from backup media with each of the pages having a corresponding savepoint version. At least a portion of the pages are then flagged as being from recovery. The savepoint versions for the pages are maintained if they have a flag. A single checksum is then calculated for each page to confirm integrity. Each page is then loaded into memory of the database after it is confirming the corresponding calculated single checksum. Related apparatus, systems, techniques and articles are also described.

Abstract: Provided are systems and methods for generating an agnostic data structure that stores debriefing information for a predictive model. In one example, the method may include receiving training data of a predictive program having a model type from among a plurality of different model types, identifying values of generic debriefing information from the training data which is generic among the different model types and values of semantic debriefing information from the training data which is unique to the model type of the received predictive program from among the plurality of different model types, extracting the values of the generic debriefing information and the values of the semantic debriefing information, and storing the values of the generic debriefing information and the semantic debriefing information within an agnostic debriefing data structure.

Abstract: Disclosed herein are system, method, and computer program product embodiments for using a data statistic as a dynamic data integrity constraint. An embodiment operates by defining a data statistic for a column or a set of columns of a partition of a plurality of partitions of a database table. The embodiment creates a constraint data statistics object based on the data statistic. The embodiment receives a query for the database table. The embodiment determines the constraint data statistics object is consistent with a data state of the partition. The embodiment derives an implied constraint based on the constraint data statistics object. The embodiment processes the query for the partition based on the implied constraint.

Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. Upon receiving an email from a client device, the program determines a datamap from a plurality of datamaps that corresponds to the email. The program further uses the determined datamap to parse the email and extract data from the email. Based on the extracted data from the email, the program also determines that the email is a cancelation for a first event. The program further determines that the cancelation for the first event matches a second event of a collection of events. The program also associates the cancelation for the first event with the second event of the collection of events.

Abstract: A system for an in-memory row storage architecture can be provided. In some implementations, the system performs operations comprising monitoring access to a plurality of rows in a database partition, a first portion of the plurality of rows stored in a persistent page store and a second portion of the plurality of rows stored in an in-memory row store. The operations can further comprise determining workload parameters based on the monitoring, selecting a location for performing a database operation on the database partition based on the workload parameters, and performing the database operation on the database partition within the selected location (e.g., the persistent page store or the in-memory row store). Related systems, methods, and articles of manufacture are also described.

Abstract: A content replication connector receives control data associated with replication of content data from a source system. Based on the control data, the content replication connector fetches the content data from the source system, converts the content data from a first data format to a second data format, and sends the content data to a content replication server. The content replication server replicates the content data, and a target system fetches the content data from the content replication server.

Abstract: Example systems and methods of developing a learning model are presented. In one example, a sample data set to train a first learning algorithm is accessed. A number of states for each input of the sample data set is determined. A subset of the inputs is selected, and the sample data set is partitioned into a number of partitions equal to a combined number of states of the selected inputs. A second learning algorithm is created for each of the partitions, wherein each second learning algorithm receives the unselected inputs. Each of the second learning algorithms is assigned to a processor and trained using the samples of the partition corresponding to that algorithm. Decision logic is generated to direct each of a plurality of operational data units as input to one of the second learning algorithms based on states of the selected inputs of the operational data unit.

Abstract: A process is provided for independently hashing and filtering a data set, such as during preprocessing. For the data set, one or more records, separately having one or more fields, may be identified. A record hash value set, containing one or more record hash values for the respective one or more records, may be generated. Generating a given record hash value may be accomplished as follows. For a given record, a hash value set may be generated, having one or more field hash values for the respective one or more fields of the given record. The record hash value for the given record may be generated based on the hash value set. A total hash value for the data set may be generated based on the record hash value set. The records of the data set may be filtered based on classification of the query that generated the records.

Abstract: Systems, methods, and computer media are described for process-oriented application configuring using semantic mapping. Desired application processes can be identified by a user, and a semantic map can be generated linking the application processes, and components of processes, to corresponding configuration objects that are used to implement the processes in the application. Configuration objects can be settings, objects, functions, user interface features, executables, etc. The semantic map thus bridges between the process-oriented view of an application and the functional, implementation-oriented view of the application. The applications can then be configured using the configuration objects identified and linked by the semantic map.

Abstract: Technologies are described for routing structured query language (SQL) statements to elastic compute nodes (ECNs) using workload classes within a distributed database environment. The elastic compute nodes do not store persistent database tables. For example, a SQL statement can be received for execution within the distributed database environment. A workload class can be identified that matches properties of the SQL statement. Based on the workload class, a routing location hint can be obtained that identifies a set of elastic compute nodes. The SQL statement can then be routed to one of the identified elastic compute nodes for execution. Execution of the SQL statement at the elastic compute node can involve retrieving database data from other nodes which store persistent database tables.

Abstract: In some embodiments, a method receives a query to retrieve data from a source table and insert the data into a target table and allocates a size of memory. A portion of the data from the source table is retrieved based on the size of memory and stored in the memory. Then, the method stores the retrieved portion of the data stored in the memory into the target table and continues to retrieve portions of data from the source table in increments based on the size of memory, store the retrieved portions of data in the memory, and store the retrieved portions of data from the memory in the target table until the data from the source table has been inserted into the target table.

Abstract: Embodiments offer early assessment of upgrade compliance checking upon software landscape production data, prior to actually executing a full impact analysis. In a pre-transport phase, discrete upgrade compliance checks are run and corresponding reports returned to individual developers. In a transport phase, batches of combined compliance checks (bundled into released transports) are run and corresponding reports returned to higher level users. According to certain embodiments, pre-transport and/or transport compliance checking is performed upon landscape production data condensed to a bi-value states. Such condensing can desirably reduce stored data volumes and impart security. According to some embodiments, pre-transport and/or transport compliance checking is performed upon production data merged across multiple landscapes. This avoids storing redundant upgrade check data.