Abstract: Methods and systems are disclosed for automated semantic tagging that include detecting a particular thread executed by a processor and identifying a root process of the particular thread. An object-process link may be by linking an object that executed code that called the particular thread to the root process. A thread list of thread definitions of the object may be identified. A particular thread definition that corresponds to the particular thread can be mapped. Resource types to be consumed upon executing an instance of the thread instantiated from the particular thread definition can be identified and the corresponding values of the resource types can be determined. A process specification can be generated that encapsulates the thread definition, resource types and values so as to reproduce a state of the root process at a point in which the particular thread executed.

Abstract: Methods and systems are disclosed for automated semantic tagging that include detecting a particular thread executed by a processor and identifying a root process of the particular thread. An object-process link may be by linking an object that executed code that called the particular thread to the root process. A thread list of thread definitions of the object may be identified. A particular thread definition that corresponds to the particular thread can be mapped. Resource types to be consumed upon executing an instance of the thread instantiated from the particular thread definition can be identified and the corresponding values of the resource types can be determined. A process specification can be generated that encapsulates the thread definition, resource types and values so as to reproduce a state of the root process at a point in which the particular thread executed.

Abstract: Methods and systems are disclosed for automated semantic tagging that include detecting a particular thread executed by a processor and identifying a root process of the particular thread. An object-process link may be by linking an object that executed code that called the particular thread to the root process. A thread list of thread definitions of the object may be identified. A particular thread definition that corresponds to the particular thread can be mapped. Resource types to be consumed upon executing an instance of the thread instantiated from the particular thread definition can be identified and the corresponding values of the resource types can be determined. A process specification can be generated that encapsulates the thread definition, resource types and values so as to reproduce a state of the root process at a point in which the particular thread executed.

Abstract: Methods and systems are disclosed for automated semantic tagging that include detecting a particular thread executed by a processor and identifying a root process of the particular thread. An object-process link may be by linking an object that executed code that called the particular thread to the root process. A thread list of thread definitions of the object may be identified. A particular thread definition that corresponds to the particular thread can be mapped. Resource types to be consumed upon executing an instance of the thread instantiated from the particular thread definition can be identified and the corresponding values of the resource types can be determined. A process specification can be generated that encapsulates the thread definition, resource types and values so as to reproduce a state of the root process at a point in which the particular thread executed.

Abstract: Methods and system are presented for monitoring database processes to generate machine learning predictions. A plurality of database processes executed on database implementations can be monitored, wherein the monitoring includes determining a start time, an end time, and a number of rows impacted by portions of the database processes, and the monitored database processes generate instances of machine learning data including at least the number of rows impacted and an associated duration of time. Using a machine learning component and the machine learning data, a duration of time can be predicted for a candidate database process for execution on a database implementation.

Abstract: Methods and systems are disclosed for automated semantic tagging that include detecting a particular thread executed by a processor and identifying a root process of the particular thread. An object-process link may be by linking an object that executed code that called the particular thread to the root process. A thread list of thread definitions of the object may be identified. A particular thread definition that corresponds to the particular thread can be mapped. Resource types to be consumed upon executing an instance of the thread instantiated from the particular thread definition can be identified and the corresponding values of the resource types can be determined. A process specification can be generated that encapsulates the thread definition, resource types and values so as to reproduce a state of the root process at a point in which the particular thread executed.

Abstract: Methods and systems are disclosed for automated semantic tagging that include detecting a particular thread executed by a processor and identifying a root process of the particular thread. An object-process link may be by linking an object that executed code that called the particular thread to the root process. A thread list of thread definitions of the object may be identified. A particular thread definition that corresponds to the particular thread can be mapped. Resource types to be consumed upon executing an instance of the thread instantiated from the particular thread definition can be identified and the corresponding values of the resource types can be determined. A process specification can be generated that encapsulates the thread definition, resource types and values so as to reproduce a state of the root process at a point in which the particular thread executed.

Abstract: Methods and systems are disclosed for automated semantic tagging that include detecting a particular thread executed by a processor and identifying a root process of the particular thread. An object-process link may be by linking an object that executed code that called the particular thread to the root process. A thread list of thread definitions of the object may be identified. A particular thread definition that corresponds to the particular thread can be mapped. Resource types to be consumed upon executing an instance of the thread instantiated from the particular thread definition can be identified and the corresponding values of the resource types can be determined. A process specification can be generated that encapsulates the thread definition, resource types and values so as to reproduce a state of the root process at a point in which the particular thread executed.

Abstract: Methods and system are presented for monitoring database processes to generate machine learning predictions. A plurality of database processes executed on database implementations can be monitored, wherein the monitoring includes determining a start time, an end time, and a number of rows impacted by portions of the database processes, and the monitored database processes generate instances of machine learning data including at least the number of rows impacted and an associated duration of time. Using a machine learning component and the machine learning data, a duration of time can be predicted for a candidate database process for execution on a database implementation.

Abstract: Methods and systems are disclosed for automated semantic tagging that include detecting a particular thread executed by a processor and identifying a root process of the particular thread. An object-process link may be by linking an object that executed code that called the particular thread to the root process. A thread list of thread definitions of the object may be identified. A particular thread definition that corresponds to the particular thread can be mapped. Resource types to be consumed upon executing an instance of the thread instantiated from the particular thread definition can be identified and the corresponding values of the resource types can be determined. A process specification can be generated that encapsulates the thread definition, resource types and values so as to reproduce a state of the root process at a point in which the particular thread executed.