Abstract: A method for executing a dynamically generated operation in a parallel processing framework may include executing the dynamically generated operation sequentially for a threshold quantity of times before initiating a compilation operation to generate precompiled code for the dynamically generated operation. Upon generating the precompiled code, execution of the precompiled code may be parallelized by determining, based on a quantity of time required to execute the precompiled code on a portion of a dataset, a task size. The execution of the precompiled code may be divided, based on the task size, into one or more tasks. Moreover, a corresponding quantity of worker threads may be allocated to perform the one or more tasks in parallel. Related methods and computer program products are also provided.

Abstract: Methods, systems, and computer-readable storage media for authorizing execution of processes that access cached data of an application running in a virtualized cloud environment. A first composite encrypted value comprising a first encrypted secret and a first secure hash value of a first secret is retrieved at a first virtual machine. The first encrypted secret is decrypted using a cryptographic key to determine a second secret to be used for initiating a first process (p?) on the first virtual machine. A second secure hash value of the second secret is generated. The second secure hash value is compared with the first secure hash value to determine whether to authorize execution of the first process on the first virtual machine using the first secret. In response to determining that the second secure hash value and the first secure hash value match, the first process is initiated at the first virtual machine.

Abstract: Various embodiments for a data management system for managing inferences are described herein. An embodiment operates by identifying a set of core data stored in a named graph and inferences generated based on the core data. A plurality of logged updates to the core data are detected. A query to execute against the named graph is received, and a signal to update the named graph is detected. At least a subset of the inferences are deleted, and the core data is modified based on the plurality of logged updates. A new plurality of inferences are generated based on the updated data. The query is executed against the named graph with the updated data and the new plurality of inferences, and a result from executing the query is returned.

Abstract: In some implementations, generating enriched data includes actions of receiving a user input comprising object data. A communication with an analytics library is triggered to determine, by using an identification algorithm, a derivation scenario corresponding to the object data, the derivation scenario being stored in a relational database and comprising derivation rules. Modeled information is determined based on the derivation rules. Enriched data is generated based on the object data and by using the modeled information and provided for display.

Abstract: Disclosed herein are system, method, and computer program product embodiments for utilizing non-RAM memory to implement a cloud storage system. An embodiment operates by receiving a request from an on-premises computer system to securely access a cloud drive by receiving an object specific template for an object. Based on the object specific template, an object specific plugin is selected, wherein the object specific plugin is configured to provide a connection to a cloud-based repository to obtain real time data for the object. An instance of the object is generated and communicated to a cloud plugin, wherein the cloud plugin is configured to communicate to a specific cloud drive through an HTTP client and further upload the instance of the object to the specific cloud drive.

Abstract: A method for instrumenting an update to a software application may include determining, based on a source code file affected by the update to the software application, a first method affected by the update to the software application. A second method called by the first method and a third method called by the second method may also be identified as being affected by the update to the software application. A user interface file that includes a call to the first method, the second method, and/or the third method may be identified. The functional impact of the update may be determined by identifying one or more functional flows that match the user interface file. A recommendation identifying the one or more matching functional flows as candidates for testing may be generated. Related systems and computer program products are also provided.

Abstract: Embodiments are described for a user device comprising a transceiver configured to communicate with a server and a processor communicatively coupled to the transceiver. The processor is configured to receive a uniform resource locator (URL) from the server and determine that the URL is a universal link. The processor is further configured to authenticate the universal link and parse the universal link to obtain a domain link. The processor is further configured to connect to the domain link.

Abstract: A method for processing a query may include receiving a query associated with one or more predicate columns and one or more aggregate columns. To respond to the query, one or more partial data pages including the one or more predicate columns but not the one or more aggregate columns may be loaded from disk to memory. For each partial data page, a first value occupying the one or more predicate columns may be evaluated to identify one or more rows satisfying a predicate associated with the query. A portion of a data page containing the aggregate columns may be loaded from disk into memory. A result of the query corresponding to a second value occupying the aggregate columns may be generated based on the portion of the data page loaded in the memory. Related systems and articles of manufacture are also provided.

Abstract: Embodiments of the present disclosure include techniques for cooperative memory management. In one embodiment, a database management system includes a memory manager for managing a memory buffer. The memory buffer is configured to allocate memory to table data and temporary data dynamically. In some embodiments, table data memory allocations are reduced and temporary data memory allocations are increased to process queries. Temporary data memory allocations may be increased to store temporary data associated with one or more portions of a query. The memory buffer reallocates table data memory allocations and temporary data memory allocations as needed to more efficiently use available memory.

Abstract: Some embodiments are directed to a data center selection device for cloud-based application deployment. The device may send a request for test data from multiple test applications at multiple data centers and determine separate network statistics for the multiple data centers. A data center may be selected based at least in part on the measured network statistics, where an application may be deployed.

Abstract: Techniques and solutions are provided for a table schema that facilitates data denormalization, and which can allow for improved database system performance. Rather than accessing multiple tables, database operations can access a single table, which can reduce the number and complexity of database operations. The table schema includes an attribute subset indicator field. Different values of the attribute subset indicator field can be associated with different contexts, such as different tables or views, which in turn can represent different entity types. A given value of the attribute subset indicator field allows data to be accessed at a coarse granularity, while more-fine grained results can be obtained by providing a value for one or more attribute fields of the table. Different subsets of attributes are retrievable for a given value of the attribute subset indicator field.

Abstract: Methods, systems, and computer-readable storage media for receiving, by a service stack recovery engine, an error message indicating a failed service in a plurality of services executed in a cloud platform, determining, by the service stack recovery engine, a set of services for recovery in response to the error message, and, for each service in the set of services, identifying, by the service stack recovery engine, an error handler that is associated with a service recovery type in a set of service recovery types, the error handler including a set of error handling operations to be executed to recover the failed service, and transmitting, by the service stack recovery engine, the error handler to a service recovery agent associated with the respective service, the service recovery agent executing error handling operations of the error handler to recover the service.

Abstract: The present disclosure involves systems, software, and computer implemented methods for bundling line item based events in an event-driven architecture. One example method includes receiving, at a message outbox of a first microservice, a new line-item based event. A determination is made as to whether a compatible open event bundle can be located. In response to locating the compatible open event bundle, the compatible open event bundle is updated to include the new line-item based event. In response to determining that the compatible open event bundle cannot be located, the compatible open event bundle is created as a new open event bundle and the new open event bundle is updated to include the new line-item based event. The compatible open event bundle is closed in response to a closing condition. A bundled event message is generated and sent to a second microservice.

Abstract: In one embodiment, the present disclosure pertains to dynamically generating normalized master data. In one embodiment, input records comprising string representations of entities are received from multiple sources. The input records may be used as queries to a similarity search data store of master data records. One or more most likely matching master records are returned with corresponding similarity scores. The input record, master record, and a training set are processed using a machine learning algorithm. In one embodiment, one or more similarity scores are incorporated into the machine learning algorithm. The machine learning algorithm produces a final score. Data from input records may be merged into the master records if the final score is greater than a threshold.

Abstract: Translation capability for language processing determines an existence of an abbreviation, followed by non-exact matching to map the abbreviation to the original full term. A received string in a source language is provided as input to a translation service. Translation proposals in a different target language are received back. A ruleset (considering factors, e.g., camel case format, the presence of a concluding period, and/or consecutive consonants) is applied to generate abbreviation candidates from the translation proposals. Non-exact matching (referencing e.g., a comparison metric) may then be used to map the abbreviation candidates to text strings of their original full terms. A mapping of the abbreviation to the text string of the original full term is stored in a translation database comprising linguistic data. Embodiments leverage existing resources (e.g.

Abstract: A system and method including receiving a request to update a timestamp associated with database pages of a database instance logically organized into at least one page set, each of the at least one page set including a plurality of the database pages; updating the timestamp associated with each database page in each respective at least one page set; issuing, in response to updating the timestamp associated with a last database page in each of the at least one page set, a write request to write the plurality of database pages in each of the respective at least one page set to a persistent data store; and writing the plurality of database pages in each of the respective at least one page set to a persistent data store, the plurality of database pages written to the persistent data store having an updated timestamp associated therewith.

Abstract: Provided is a software process that can dynamically identify and display a plurality of category values of an electronic file based on a file name assigned to the electronic file. Thus, the software can automatically populate a user interface with details about content within the electronic file based on the file name. In one example, the method may include receiving an electronic computer file having a file name, identifying a subset of characters within the file name which correspond to a data category, mapping a value of the identified subset of characters to a category value in the data category, displaying an identifier of the electronic file on a user interface, and dynamically populating a predefined field within the user interface corresponding to the data category with the mapped category value.

Abstract: The present disclosure involves systems, software, and computer implemented methods for integrated data privacy services. An example method includes determining to initiate an integrated end of purpose protocol for an object. An end-of-purpose query is provided to multiple applications that requests each application to determine whether the application is able to block the object. End-of-purpose statuses are received, in response to the end-of-purpose query, that each indicate whether a respective application is able to block the object. The end-of-purpose statuses are evaluated to determine whether an aligned end of purpose has been reached for the object. In response to determining that the aligned end of purpose has been reached for the object, a block command is provided to each application that instructs the application to locally block the object in the application.

Abstract: A non-interactive protocol is provided for evaluating machine learning models such as decision trees. A client can delegate the evaluation of a machine learning model such as a decision tree to a server by sending an encrypted input and receiving only the encryption of the result. The inputs can be encoded as vector of integers using their binary representation. The server can then evaluate the machine learning model using a homomorphic arithmetic circuit. The homomorphic arithmetic circuit provides an implementation that requires fewer multiplication than a Boolean comparison circuit. Efficient data representations are then combined with different algorithmic optimizations to keep the computational overhead and the communication cost low. Related apparatus, systems, techniques and articles are also described.

Abstract: Systems, methods, and computer media for securing software applications are provided herein. Through an enhanced authentication token, an application session request can be deceptively authenticated. When a malicious session request is detected, an enhanced authentication token can be generated that appears to successfully authenticate the session but contains information indicating that the session is malicious. The attacker believes that the session has been authenticated, but the information in the token indicating that the session is malicious causes an application clone session to be established instead of an actual application session. The clone session appears to be an actual application session but protects the valid user's account by including fake data instead of the user's actual data.