Abstract: Embodiments are directed to predicting the health of a computer node using health report data and to proactively handling failures in computer network nodes. In an embodiment, a computer system monitors various health indicators for multiple nodes in a computer network. The computer system accesses stored health indicators that provide a health history for the computer network nodes. The computer system then generates a health status based on the monitored health indicators and the health history. The generated health status indicates the likelihood that the node will be healthy within a specified future time period. The computer system then leverages the generated health status to handle current or predicted failures. The computer system also presents the generated health status to a user or other entity.

Abstract: Embodiments are directed to predicting the health of a computer node using health report data and to proactively handling failures in computer network nodes. In an embodiment, a computer system monitors various health indicators for multiple nodes in a computer network. The computer system accesses stored health indicators that provide a health history for the computer network nodes. The computer system then generates a health status based on the monitored health indicators and the health history. The generated health status indicates the likelihood that the node will be healthy within a specified future time period. The computer system then leverages the generated health status to handle current or predicted failures. The computer system also presents the generated health status to a user or other entity.

Abstract: Embodiments are directed to predicting the health of a computer node using health report data and to proactively handling failures in computer network nodes. In an embodiment, a computer system monitors various health indicators for multiple nodes in a computer network. The computer system accesses stored health indicators that provide a health history for the computer network nodes. The computer system then generates a health status based on the monitored health indicators and the health history. The generated health status indicates the likelihood that the node will be healthy within a specified future time period. The computer system then leverages the generated health status to handle current or predicted failures. The computer system also presents the generated health status to a user or other entity.

Abstract: Examples of the disclosure provide for monitoring upgrades using health information. An upgrade domain includes a set of one or more nodes from a cluster of nodes. As the upgrade domain is upgraded, the health of the upgrade domain and applications hosted by nodes of the upgrade domain is monitored. Health information is received from the applications and the nodes of the upgrade domain, and is evaluated against health policies at a health check to determine if the upgrade is successful.

Abstract: Embodiments are directed to predicting the health of a computer node using health report data and to proactively handling failures in computer network nodes. In an embodiment, a computer system monitors various health indicators for multiple nodes in a computer network. The computer system accesses stored health indicators that provide a health history for the computer network nodes. The computer system then generates a health status based on the monitored health indicators and the health history. The generated health status indicates the likelihood that the node will be healthy within a specified future time period. The computer system then leverages the generated health status to handle current or predicted failures. The computer system also presents the generated health status to a user or other entity.

Abstract: Embodiments are directed to predicting the health of a computer node using health report data and to proactively handling failures in computer network nodes. In an embodiment, a computer system monitors various health indicators for multiple nodes in a computer network. The computer system accesses stored health indicators that provide a health history for the computer network nodes. The computer system then generates a health status based on the monitored health factors and the health history. The generated health status indicates the likelihood that the node will be healthy within a specified future time period. The computer system then leverages the generated health status to handle current or predicted failures. The computer system also presents the generated health status to a user or other entity.

Abstract: Embodiments are directed to predicting the health of a computer node using health report data and to proactively handling failures in computer network nodes. In an embodiment, a computer system monitors various health indicators for multiple nodes in a computer network. The computer system accesses stored health indicators that provide a health history for the computer network nodes. The computer system then generates a health status based on the monitored health factors and the health history. The generated health status indicates the likelihood that the node will be healthy within a specified future time period. The computer system then leverages the generated health status to handle current or predicted failures. The computer system also presents the generated health status to a user or other entity.

Abstract: Embodiments are directed to predicting the health of a computer node using health report data and to proactively handling failures in computer network nodes. In an embodiment, a computer system monitors various health indicators for multiple nodes in a computer network. The computer system accesses stored health indicators that provide a health history for the computer network nodes. The computer system then generates a health status based on the monitored health factors and the health history. The generated health status indicates the likelihood that the node will be healthy within a specified future time period. The computer system then leverages the generated health status to handle current or predicted failures. The computer system also presents the generated health status to a user or other entity.

Abstract: Embodiments are directed to predicting the health of a computer node using health report data and to proactively handling failures in computer network nodes. In an embodiment, a computer system monitors various health indicators for multiple nodes in a computer network. The computer system accesses stored health indicators that provide a health history for the computer network nodes. The computer system then generates a health status based on the monitored health factors and the health history. The generated health status indicates the likelihood that the node will be healthy within a specified future time period. The computer system then leverages the generated health status to handle current or predicted failures. The computer system also presents the generated health status to a user or other entity.

Abstract: Embodiments are directed to predicting the health of a computer node using health report data and to proactively handling failures in database services. In an embodiment, a computer system monitors various health indicators for multiple nodes in a database cluster. The computer system accesses stored health indicators that provide a health history for the database cluster nodes. The computer system then generates a health status based on the monitored health factors and the health history. The generated health status indicates the likelihood that the node will be healthy within a specified future time period. The computer system then leverages the generated health status to handle current or predicted failures. The computer system also presents the generated health status to a user or other entity.

Abstract: Embodiments are directed to predicting the health of a computer node using health report data and to proactively handling failures in database services. In an embodiment, a computer system monitors various health indicators for multiple nodes in a database cluster. The computer system accesses stored health indicators that provide a health history for the database cluster nodes. The computer system then generates a health status based on the monitored health factors and the health history. The generated health status indicates the likelihood that the node will be healthy within a specified future time period. The computer system then leverages the generated health status to handle current or predicted failures. The computer system also presents the generated health status to a user or other entity.

Abstract: The subject disclosure pertains to computer programming languages and translation or conversion thereof. Rather than a complicated semantics preserving translation or conversion from a first source language to a second target language, the conversion can be one of syntax. The conversion can be accomplished, for example, via employment of a map that defines the relation between the syntax of the first language and the second language. The semantics of at least a part of the first language can be defined by the second target language. Thus, the first language can be open-ended and/or semantically extensible based on the second language.

Abstract: A data mapping architecture for mapping between two or more data sources without modifying the metadata or structure of the data sources themselves. Data mapping also supports updates. The architecture also supports at least the case where data sources that are being mapped, are given, their schemas predefined, and cannot be changed. The architecture includes a mapping component that receives respective metadata from at least two arbitrary data models, and maps expressions between the data models.

Abstract: A system and/or methodology that employs a non-relational (e.g., XML (extensible markup language)) query language to access stored procedures employed in connection with relational (e.g., SQL (structured query language)) database management systems is provided. Stored procedures in SQL enable the predetermination of queries that can be executed against the relational database. The invention bridges the gap between non-relational query languages and relational data stores. In other words, the invention enables the integration of non-relational query languages with relational data stores. The invention can define a view of the relational data in the current data model, convert data from relational to non-relational format and provide a mechanism in which a stored procedure can be referenced from the non-relational query language, using, for example, a function.

Abstract: A distributed query engine pipeline architecture comprises cascaded analysis engines that accept an input query and each identifies a portion of the input query that it can pass on to an execution engine. Each stage rewrites the input query to remove the portion identified and replaces it with a placeholder. The rewritten query is forwarded to the next analysis engine in the cascade. Each engine compiles the portion it identified so that an execution engine may process that portion. Execution preferably proceeds from the portion of the query compiled by the last analysis engine. The execution engine corresponding to the last analysis engine executes the query and makes a call to the next higher execution engine in the cascade for data from the preceding portion. The process continues until the results from the input query are fully assembled.

Abstract: A query runtime architecture and an exemplary application programming interface suitable for the architecture are presented. The architecture inputs one or more XML queries and views and enables the queries to be translated wherein the queries and views may be run over multiple data sources of different data models. The architecture incorporates front-end compilers which convert input queries and views into an intermediate language representation which represents the meaning of the respective query or view. The architecture may then allow the back-end compiling of the intermediate language representation to target languages compatible with the data sources desired to be queried. The architecture also allows the execution of those target compilations to extract the data requested of the queries. The invention also discloses an example application programming interface for the query runtime system.

Abstract: The present invention relates to a system and methodology to facilitate data communications and data management between network entities operating in accordance with various data structures and operating environments. A managed class of application programming interfaces (API) are provided that support data communications between remote/local locations employing a first data structure and a second location supporting a second data structure (e.g., API for NET languages to access SQL Server via XML views). The managed class and associated APIs provide data transformations between such structures to facilitate communications and data management among various locations and architectures. In addition, the managed class and APIs facilitate operations between disparate object systems such as between managed and unmanaged object systems via interface support of a wrapper and associated marshalling technologies to bridge communications between such systems.

Abstract: A distributed query engine pipeline architecture comprises cascaded analysis engines that accept an input query and each identifies a portion of the input query that it can pass on to an execution engine. Each stage rewrites the input query to remove the portion identified and replaces it with a placeholder. The rewritten query is forwarded to the next analysis engine in the cascade. Each engine compiles the portion it identified so that an execution engine may process that portion. Execution preferably proceeds from the portion of the query compiled by the last analysis engine. The execution engine corresponding to the last analysis engine executes the query and makes a call to the next higher execution engine in the cascade for data from the preceding portion. The process continues until the results from the input query are fully assembled.

Abstract: A query runtime architecture and an exemplary application programming interface suitable for the architecture are presented. The architecture inputs one or more XML queries and views and enables the queries to be translated wherein the queries and views may be run over multiple data sources of different data models. The architecture incorporates front-end compilers which convert input queries and views into an intermediate language representation which represents the meaning of the respective query or view. The architecture may then allow the back-end compiling of the intermediate language representation to target languages compatible with the data sources desired to be queried. The architecture also allows the execution of those target compilations to extract the data requested of the queries. The invention also discloses an example application programming interface for the query runtime system.

Abstract: The present invention relates to a system and methodology to facilitate data communications and data management between network entities operating in accordance with various data structures and operating environments. A managed class of application programming interfaces (API) are provided that support data communications between remote/local locations employing a first data structure and a second location supporting a second data structure (e.g., API for NET languages to access SQL Server via XML views). The managed class and associated APIs provide data transformations between such structures to facilitate communications and data management among various locations and architectures. In addition, the managed class and APIs facilitate operations between disparate object systems such as between managed and unmanaged object systems via interface support of a wrapper and associated marshalling technologies to bridge communications between such systems.