摘要:
Techniques for self-diagnosing performance problems in a database are provided. The techniques include classifying one or more performance problems in a database system. One or more values for quantifying an impact of the one or more performance problems on the database system are then determined. The quantified values are determined based on the performance of operations in the database system. A performance problem based on the one or more quantified values is then determined. A solution for the performance problem is generated and may be outputted.
摘要:
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.
摘要:
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.
摘要:
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.
摘要:
A self-managing workload repository (AWR) infrastructure useful for a database server to collect and manage selected sets of important system performance statistics. Based on a schedule, the AWR runs automatically to collect data about the operation of the database system, and stores the data that it captures into the database. The AWR is advantageously designed to be lightweight and to self manage its use of storage space so as to avoid ending up with a repository of performance data that is larger than the database that it is capturing data about. 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. Both the frequency of the statistics data capture and length of time for which data is kept is adjustable. Manual snapshots and purging may also be performed. The AWR captured data allows for both system level and user level analysis to be automatically performed without unduly impacting system performance, e.g., by eliminating or reducing the requirement to repeat the workload in order to diagnose problems.
摘要:
The methods and systems for database statement execution plan optimization exploit bind variable data available on the network to build and optimize an execution plan for the statement. A system for database statement execution plan optimization comprises a bind variable analyzer, a frame allocator, and an optimizer, in addition to a parser for parsing and analyzing the statement, a type checker for type checking the statement, and a tree builder for building an expression tree.
摘要:
The methods and systems for database statement execution plan optimization exploit bind variable data available on the network to build and optimize an execution plan for the statement. A system for database statement execution plan optimization comprises a bind variable analyzer, a frame allocator, and an optimizer, in addition to a parser for parsing and analyzing the statement, a type checker for type checking the statement, and a tree builder for building an expression tree.