Oracle International Corporation

Gaylen D Royal

Todd Guay

Gregory P Smith

Ari Wolfe Mozes

Jerry Paul Russell

Harish Akali

Shushuai Zhu

Gregory Scott Smith

Geoffrey Wilson

Haobo He

Cheryl Mrozienski

Wyn Owen

Jonathan Riel

Disclosed is a system, method, and computer program product for implementing a log analytics method and system that can configure, collect, and analyze log records in an efficient manner. In addition, a method and system is provided for implementing collection-wise processing within a log analytics system.

Method and system for implementing collection-wise processing in a log analytics system

A method evaluates a plurality of candidate index sets for a workload of database statements in a database system by first generating baseline statistics for each statement in the workload. An index superset is formed by combining an existing or current index set and a proposed index set. A candidate index set is derived from the index superset, the candidate index being one of the plurality of candidate index sets. Statistics for a statement are generated by first creating an execution plan which represents an efficient series of steps for executing the statement given the candidate index set. The execution plan is evaluated, and statistics based on the evaluation of the execution plan are generated and recorded. The cost of the execution plan is then determined and statistics are generated. Statistics for each candidate index set are rolled up and presented to a user or an index tuning mechanism.

Database index validation mechanism

An approach for automatically determining database tables that are best suited for index tuning involves analyzing query performance data that specifies an average amount of time required to execute a plurality of queries on the database tables. One or more particular queries are selected from the plurality of queries based upon the query performance data. Data tables required to process the one or more particular queries are selected for index tuning.

Automatically determining data that is best suited for index tuning

A method for non-recursive data driven parameter evaluation within an information management system (e.g., a relational database management system, RDBMS). Parameters are attributes within an RDBMS system whose value can be modified to influence the manner in which a database environment responds. Depending on the character of the data within a database environment or the hardware resources allocated to the database, the parameter values have a large influence on the performance efficiency of the database. For instance, a parameter value may influence the memory size of certain data storage areas within a database environment and, if set too small, can cause an inefficiently large amount of input/output accesses to occur as data is moved in and out of disk storage. Also, many parameters are data dependent on other parameters. The novel system presents an automated system for evaluating parameters using a non-recursive evaluation process. By using a non-recursive approach, the evaluation process is streamlined in that only one pass yields an optimum parameter evaluation and the results are reproducible. The novel system identifies a set of parameters within an environment to be tuned, eliminates cyclic dependencies, and orders the parameters based on independence, levels of dependence, impact on system performance and common data usage. The present invention is data driven because rules within a respective parameter are then evaluated based on data availability to arrive at a set of parameter value recommendations. In one embodiment instance, tablespace, system environment, and schema parameters can be evaluated within a RDBMS tuning session.

Non-recursive method for parameter evaluation within an information

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Bedford, NH, United States of America

Gaylen D Royal