Abstract: A self-managing workload repository infrastructure (or “AWR” for Automatic workload repository) which is useful for a database server to collect and manage useful system performance statistics. The AWR runs automatically to collect performance data about the operation of the database system, and stores the data that it captures into the database. The collection process is done inside the database, and the collection process is highly efficient as data is retrieved directly from the shared memory of the database kernel. The data captured allows both system level and user level analysis to be performed without unduly impacting system performance, e.g., by eliminating or reducing the requirement to repeat the workload in order to diagnose problems. The AWR is configured to automatically capture snapshots of statistics data on a periodic basis as well as purge stale data on a periodic basis. The captured performance data includes one or more of the top N (e.g.

Abstract: An intelligent database infrastructure wherein the management of all database components is performed by and within the database itself by integrating management of various components with a central management control. Each individual database component, as well as the central management control, is self-managing. A central management control module integrates and interacts with the various database components. The database is configured to automatically tune to varying workloads and configurations, correct or alert about bad conditions, and advise on ways to improve overall system performance.

Abstract: Techniques for controlling collection of diagnostic data in a monitored system. A set of flood control rules are configured for the monitored system for controlling the gathering of diagnostic data in the monitored system. The set of flood control rules may include one or more default flood control rules. The set of flood control rules are user-configurable enabling the user of the monitored system to set policies for dynamically controlling gathering of diagnostic data for the monitored system. In one embodiment, diagnostic data gathering is controlled based upon a number of previous occurrences of a condition in some predefined or user-configured time frame that triggers diagnostic data gathering and/or a number of previous executions of an action performed in some predefined or user-configured time frame responsive to the condition in the monitored system.

Abstract: A diagnosability system for automatically collecting, storing, communicating, and analyzing diagnostic data for one or more monitored systems. The diagnosability system comprises several components configured for the collection, storage, communication, and analysis of diagnostic data for a condition detected in monitored system. The diagnosability system enables targeted dumping of diagnostic data so that only diagnostic data that is relevant for diagnosing the condition detected in the monitored system is collected and stored. This in turn enables first failure analysis thereby reducing the time needed to resolve the condition detected in the monitored system.

Abstract: An infrastructure is provided for gathering diagnostic data that is relevant to an error or other conditions detected in a monitored system. A diagnosability framework is provided that automates the gathering of relevant diagnostic data upon occurrence of the condition in the monitored system. In one embodiment, context data is determined for the condition detected in the monitored system. A rule-based engine is provided that is configured to automatically determine one or more actions to be performed for the condition detected in the monitored system based on the determined context data. The actions may include performing tasks that gather diagnostic data that is relevant to the detected condition, store the gathered diagnostic data in a repository, recommend one or more diagnostic actions to a user, and other diagnostic related actions.

Abstract: Techniques for indicating the status or health of a software system in a simple and summarized manner. In one embodiment, a health meter is displayed that displays a status value indicating the status or health of the software system. The status or health of the system as indicated by the health meter may be based upon one or more characteristics or perspectives (or components) of the system, such as performance, resource utilization, reliability, availability, scalability, and status values computed for the components.

Abstract: Techniques for non-intrusive performance of diagnostic actions including actions that result in gathering of diagnostic data in response to a condition detected in a monitored system. In one embodiment, the diagnostic actions are performed asynchronously by processes or threads that are different from the failing process or thread that receives or detects the condition that triggers the diagnostic actions such that the failing process or thread can continue processing without being affected by the executions of the diagnostic actions. Multiple asynchronous processes or threads that are different from the failing process or thread may be spawned to perform multiple diagnostic actions in parallel. The asynchronous processes or threads may be monitored to ensure that they do not adversely impact the monitored system.

Abstract: Techniques for proactively and reactively running diagnostic functions. These diagnostic functions help to improve diagnostics of conditions detected in a monitored system and to limit/quarantine the damages caused by the detected conditions. In one embodiment, a health monitor infrastructure is provided that is configured to perform one or more health checks in a monitored system for diagnosing and/or gathering information related to the system. The one or more health checks may be invoked pro-actively on a scheduled basis, reactively in response to a condition detected in the system, or may even be invoked manually by a user such as a system administrator.

Abstract: An infrastructure is provided for gathering diagnostic data that is relevant to an error or other conditions detected in a monitored system. A diagnosability framework is provided that automates the gathering of relevant diagnostic data upon occurrence of the condition in the monitored system. In one embodiment, context data is determined for the condition detected in the monitored system. A rule-based engine is provided that is configured to automatically determine one or more actions to be performed for the condition detected in the monitored system based on the determined context data. The actions may include performing tasks that gather diagnostic data that is relevant to the detected condition, store the gathered diagnostic data in a repository, recommend one or more diagnostic actions to a user, and other diagnostic related actions.

Abstract: Techniques are provided for analyzing performance differences for a set of database query language statements on two different database systems. The performance analysis is based on quantitative measurements and estimates of the execution of the set of database query language statements on the two different database systems. This performance analysis process may be used by database administrators to predict impacts to performance due to a change in a database system.

Abstract: Techniques are provided for a fully-automated process for tuning database query language statements that selects database query language statements for tuning, tunes the database query language statements and generates tuning recommendations, tests the tuning recommendations, and determines whether to implement the tuning recommendations based on the test results. The fully-automated tuning process may also automatically implement certain tuning recommendations and monitor the performance of the database query language statements for which tuning recommendations have been implemented.

Abstract: Quantifying the impact of wasteful operations on a database system is provided. One or more operations that are determined to be wasteful are received. The impact of the wasteful operations on performance in a database may then be quantified. The database is monitored to determine when a wasteful operation is being performed. When a wasteful operation is detected, a time value is recorded of the time spent on processing the wasteful operation. The time value is stored and used to quantify an impact of a performance problem in a database. The time value may be stored and associated with other time values that are recorded for the same wasteful operation. Thus, the impact of wasteful operations that are performed and processed in a database may be determined.

Abstract: A method and apparatus for capturing database system workload and replaying that workload in a database system is provided. According to one aspect, in order to subject a test database system to the same workload to which the production database system actually would be subjected, a database server in the production system captures and records workload that the database server receives from external entities. This captured workload is processed. Processes external to a database server in the test database system send the processed workload to that database server. As a result, the test database system is subjected to the same workload to which the production database system originally was subjected. The foregoing technique permits a database administrator to determine how the production database system will fare if the difference that is present in the test database system is introduced into the production database system.

Abstract: A method and apparatus for capturing database system workload and replaying that workload in a database system is provided. According to one aspect, in order to subject a test database system to the same workload to which the production database system actually would be subjected, a database server in the production system captures and records workload that the database server receives from external entities. This captured workload is processed. Processes external to a database server in the test database system send the processed workload to that database server. As a result, the test database system is subjected to the same workload to which the production database system originally was subjected. The foregoing technique permits a database administrator to determine how the production database system will fare if the difference that is present in the test database system is introduced into the production database system.

Abstract: A method and apparatus for capturing database system workload and replaying that workload in a database system is provided. According to one aspect, in order to subject a test database system to the same workload to which the production database system actually would be subjected, a database server in the production system captures and records workload that the database server receives from external entities. This captured workload is processed. Processes external to a database server in the test database system send the processed workload to that database server. As a result, the test database system is subjected to the same workload to which the production database system originally was subjected. The foregoing technique permits a database administrator to determine how the production database system will fare if the difference that is present in the test database system is introduced into the production database system.

Abstract: A method and apparatus for capturing database system workload and replaying that workload in a database system is provided. According to one aspect, in order to subject a test database system to the same workload to which the production database system actually would be subjected, a database server in the production system captures and records workload that the database server receives from external entities. This captured workload is processed. Processes external to a database server in the test database system send the processed workload to that database server. As a result, the test database system is subjected to the same workload to which the production database system originally was subjected. The foregoing technique permits a database administrator to determine how the production database system will fare if the difference that is present in the test database system is introduced into the production database system.

Abstract: A method and apparatus for capturing database system workload and replaying that workload in a database system is provided. According to one aspect, in order to subject a test database system to the same workload to which the production database system actually would be subjected, a database server in the production system captures and records workload that the database server receives from external entities. This captured workload is processed. Processes external to a database server in the test database system send the processed workload to that database server. As a result, the test database system is subjected to the same workload to which the production database system originally was subjected. The foregoing technique permits a database administrator to determine how the production database system will fare if the difference that is present in the test database system is introduced into the production database system.

Abstract: Techniques for capturing samples of session activity in a database are provided. Session activity for active sessions is recorded at certain times over a time period. Accordingly, a sample of session activity is taken for sessions in a database.

Abstract: Various embodiments of the invention provide solutions that can offer a consistent framework for tools that assist in the configuration, tuning, and/or troubleshooting of a database and/or an RDBMS. Merely by way of example, one set of embodiments provides a software framework for an advisor component of a database and/or RDBMS. In accordance with some embodiments, the framework might specify a common data model for such advisor components. The data model can include, merely by way of example, a set of one or more findings (which might, in some cases, describe the result of an analysis of a circumstance in the database, RDBMS, and/or a mid-tier application used with the database) and/or a set of one or more recommendations (which might provide suggestions for addressing the circumstance). In particular embodiments. In particular embodiments, the data model might include a set of on or more rationales, which can explain the recommendations.

Abstract: One or more usage models are provided for a database. Each usage model includes a set of rules that are used to analyze database performance. A usage model in one or more usage models is determined. Database information is determined based on the usage model. The database information is then analyzed based on rules associated with the usage model. One or more performance problems are determined based on the analysis.