Abstract: Systems, methods, and non-transitory computer-readable media are provided for data analysis. A user interface comprising boards corresponding to one or more objects and one or more operations on the input and/or output objects of the boards can be generated for high-scale top-down data analysis.

Abstract: Errors encountered by executing applications can be recorded in one or more logs. A search engine can be configured to retrieve error data from the one or more logs using pre-specified rules. A portion of the error data can be included in a small portable message (e.g., SMS text message) and sent to the developers or administrators of the applications. An administrative console can generate different visualizations based upon what errors the search engine retrieved.

Abstract: One or more software products/services may be installed on a cloud deployment. Product versions of such services can be upgraded (or rolled back) based on a deployment plan comprising tasks adapted to reach a target deployment state. A central upgrade server can forward tasks to an upgrade agent for execution, the tasks being based on a current operational state of the cloud deployment (obtained by the upgrade agent) and one or more constraints. In multiple node deployments, some nodes may be upgraded to a new product version, while other nodes are kept at a current product version until stability of the new product version is determined. Traffic across nodes can be shaped to ensure a deployment is healthy before upgrading other nodes/deployments. If the health of a node/deployment does not meet specified criteria, an upgrade can be stopped, an alert can be triggered, and the node/deployment can be rolled back.

Abstract: In some embodiments, systems and methods for visualizing one or more datasets include importing a plurality of root objects, each root object including linked data attributes and obtaining a joined dataset based on the plurality of root objects, that includes for each or the plurality of root objects, a plurality of rows of related attribute data linked to each root object as a result of a join operation. The systems and methods perform an aggregation computation on the plurality of rows of related attribute data corresponding to each of the plurality of root objects to produce a corresponding single aggregation row of consolidated data for each root object and present a user interface that shows each of the plurality of root objects with their corresponding single aggregation row of consolidated data resulting from the aggregation computation, in a one-to-one manner.

Abstract: A computer-implemented method comprises obtaining a first build task for building first source code in a first programming language of a plurality of programming languages; retrieving, by the processor, the first source code based on the first build task; building the first source code into one or more artifacts and one or more job specifications; storing the one or more artifacts in a cache shared across a cluster; and initializing an application module on the cluster based on the first programming language, the application module configured to receive a job specification of the one or more job specifications and execute a data transformation job using a reference to a location in the cache.

Abstract: Systems, methods, and non-transitory computer-readable media are provided for data analysis. A user interface comprising boards corresponding to one or more objects and one or more operations on the input and/or output objects of the boards can be generated for high-scale top-down data analysis.

Abstract: One or more software products/services may be installed on a cloud deployment. Product versions of such services can be upgraded (or rolled back) based on a deployment plan comprising tasks adapted to reach a target deployment state. A central upgrade server can forward tasks to an upgrade agent for execution, the tasks being based on a current operational state of the cloud deployment (obtained by the upgrade agent) and one or more constraints. In multiple node deployments, some nodes may be upgraded to a new product version, while other nodes are kept at a current product version until stability of the new product version is determined. Traffic across nodes can be shaped to ensure a deployment is healthy before upgrading other nodes/deployments. If the health of a node/deployment does not meet specified criteria, an upgrade can be stopped, an alert can be triggered, and the node/deployment can be rolled back.

Abstract: Data transformation in a distributed system of applications and data repositories is described. The subsystems for the overall framework are distributed, thereby allowing for customization to require only isolated changes to one or more subsystems. In one embodiment, a source code repository is used to receive and store source code. A build subsystem can retrieve source code from the source code repository and build it, using one or more criteria. By building the source code, the build subsystem can generate an artifact, which is executable code, such as a JAR or SQL file. Likewise, by building the source code, the build subsystem can generate one or more job specifications for executing the executable code. In one embodiment, the artifact and job specification may be used to launch an application server in a cluster. The application server can then receive data transformation instructions and execute the data transformation instructions.

Abstract: In some embodiments, systems and methods for visualizing one or more datasets include importing a plurality of root objects, each root object including linked data attributes and obtaining a joined dataset based on the plurality of root objects, that includes for each or the plurality of root objects, a plurality of rows of related attribute data linked to each root object as a result of a join operation. The systems and methods perform an aggregation computation on the plurality of rows of related attribute data corresponding to each of the plurality of root objects to produce a corresponding single aggregation row of consolidated data for each root object and present a user interface that shows each of the plurality of root objects with their corresponding single aggregation row of consolidated data resulting from the aggregation computation, in a one-to-one manner.

Abstract: Systems, methods, and non-transitory computer-readable media are provided for data analysis. A user interface comprising boards corresponding to one or more objects and one or more operations on the input and/or output objects of the boards can be generated for high-scale top-down data analysis.

Abstract: Errors encountered by executing applications can be recorded in one or more logs. A search engine can be configured to retrieve error data from the one or more logs using pre-specified rules. A portion of the error data can be included in a small portable message (e.g., SMS text message) and sent to the developers or administrators of the applications. An administrative console can generate different visualizations based upon what errors the search engine retrieved.

Abstract: Errors encountered by executing applications can be recorded in one or more logs. A search engine can be configured to retrieve error data from the one or more logs using pre-specified rules. A portion of the error data can be included in a small portable message (e.g., SMS text message) and sent to the developers or administrators of the applications. An administrative console can generate different visualizations based upon what errors the search engine retrieved.

Abstract: Systems, methods, and non-transitory computer-readable media are provided for data analysis. A user interface comprising boards corresponding to one or more objects and one or more operations on the input and/or output objects of the boards can be generated for high-scale top-down data analysis.

Abstract: Systems, methods, and non-transitory computer-readable media are provided for data analysis. A user interface comprising boards corresponding to one or more objects and one or more operations on the input and/or output objects of the boards can be generated for high-scale top-down data analysis.

Abstract: Systems and methods for aggregating and storing different types of data, and generating interactive user interfaces for analyzing the stored data. In some embodiments, entity data is received for a plurality of entities from one or more data sources, and used to determine attribute values for the entities for one or more given time periods. The plurality of entities may be categorized into one or more entity groups, and aggregate attribute values may be generated based upon the entity groups. A first interactive user interface is generated displaying the one or more entity groups in association with the aggregated attribute values associated with the entity group. In response to a received indication of a user selection of an entity group, a second interactive user interface is generated displaying the one or more entities associated with the selected entity group, each entity displayed in association with the attribute values associated with the entity.

Abstract: Methods, systems and computer programs are disclosed for managing data bugs in a data processing system comprising one or more data resources. The method may comprise receiving an indication of one or more bugs relating to one or more data resources, and contextual information for the one or more bugs and determining, from the received indication, one or more bug types and grouping the bugs by bug type for the same data resource to produce a aggregated list of open issues requiring fixing. Further operations may comprise presenting the aggregated list of one or more open issues on a user interface for selection, the one or more open issues being selectable, and, responsive to receiving selection of a particular open issue, presenting contextual information for the one or more bugs within the group on the user interface.

Abstract: Data transformation in a distributed system of applications and data repositories is described. The subsystems for the overall framework are distributed, thereby allowing for customization to require only isolated changes to one or more subsystems. In one embodiment, a source code repository is used to receive and store source code. A build subsystem can retrieve source code from the source code repository and build it, using one or more criteria. By building the source code, the build subsystem can generate an artifact, which is executable code, such as a JAR or SQL file. Likewise, by building the source code, the build subsystem can generate one or more job specifications for executing the executable code. In one embodiment, the artifact and job specification may be used to launch an application server in a cluster. The application server can then receive data transformation instructions and execute the data transformation instructions.

Abstract: Errors encountered by executing applications can be recorded in one or more logs. A search engine can be configured to retrieve error data from the one or more logs using pre-specified rules. A portion of the error data can be included in a small portable message (e.g., SMS text message) and sent to the developers or administrators of the applications. An administrative console can generate different visualizations based upon what errors the search engine retrieved.

Abstract: Errors encountered by executing applications can be recorded in one or more logs. A search engine can be configured to retrieve error data from the one or more logs using pre-specified rules. A portion of the error data can be included in a small portable message (e.g., SMS text message) and sent to the developers or administrators of the applications. An administrative console can generate different visualizations based upon what errors the search engine retrieved.

Abstract: One or more software products/services may be installed on a cloud deployment. Product versions of such services can be upgraded (or rolled back) based on a deployment plan comprising tasks adapted to reach a target deployment state. A central upgrade server can forward tasks to an upgrade agent for execution, the tasks being based on a current operational state of the cloud deployment (obtained by the upgrade agent) and one or more constraints. In multiple node deployments, some nodes may be upgraded to a new product version, while other nodes are kept at a current product version until stability of the new product version is determined. Traffic across nodes can be shaped to ensure a deployment is healthy before upgrading other nodes/deployments. If the health of a node/deployment does not meet specified criteria, an upgrade can be stopped, an alert can be triggered, and the node/deployment can be rolled back.