DATABASE PERFORMANCE MINING

• US 20090164443A1
• Filed: 12/19/2007
• Published: 06/25/2009
• Est. Priority Date: 12/19/2007
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Ramos, Jo A., Rollins, John B.
• Application Number:
  US11/960,115
• Publication Number:
  US 20090164443A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/21 Design, administration or maintenance of databases

Abstract

A system, method and program product for analyzing performance of a system comprised of a database and its related operating environment. A system is provided that includes: a set of monitoring tools for monitoring event data from a database application and from an operating environment running the database application; a performance data warehouse for storing the event data; a modeling system for generating a performance mining model of the database system based on the event data stored in the performance data warehouse; and a system for comparing a stream of current event data against the performance mining model to identify performance issues in the database system.

Claims

1. A system for analyzing performance of a database system, comprising:

a set of monitoring tools for monitoring event data from a database application and from an operating environment running the database application;

a performance data warehouse for storing the event data;

a modeling system for generating a performance mining model of the database system based on the event data stored in the performance data warehouse; and

a system for comparing a stream of current event data against the performance mining model to identify performance issues in the database system.

2. The system of claim 1, wherein the monitoring tools gather operating environment metrics, database performance metrics, and query workload data.

3. The system of claim 1, wherein the modeling system generates the performance mining model using a modeling technique selected from the group consisting of:

clustering, associations, and sequences.

4. The system of claim 1, wherein the system for comparing the stream of current event data against the performance mining model generates a score for the stream that indicates a type of behavior pattern.

5. The system of claim 4, further comprising an automated performance tuning system that automatically tunes the database system if the score is associated with a performance degradation condition.

6. The system of claim 4, further comprising a system for generating an alert if the score is associated with a performance degradation condition.

7. The system of claim 1, wherein the performance mining model includes a plurality of clusters, wherein each cluster represents a distinct behavioral pattern, wherein each cluster is represented as a plurality of histograms, and wherein each histogram captures historical data of a monitored event.

8. A program product stored on a computer readable medium for analyzing performance of a database system, comprising:

program code for capturing and storing event data from a database application and from an operating environment running the database application;

program code for generating a performance mining model of the database system based on the event data; and

program code for comparing current event data against the performance mining model to identify performance issues in the database system.

9. The program product of claim 8, wherein the event data includes operating environment metrics, database performance metrics, and query workload data.

10. The program product of claim 8, wherein the performance mining model is created using a modeling technique selected from the group consisting of:

clustering, associations, and sequences.

11. The program product of claim 8, wherein the program code for comparing the current event data against the performance mining model generates a score for the stream that reflects a type of behavior pattern for the current event data.

12. The program product of claim 11, further comprising program code that automatically tunes the database system if the score is associated with a performance degradation condition.

13. The program product of claim 11, further comprising program code for generating an alert if the score is associated with a performance degradation condition.

14. The program product of claim 8, wherein the performance mining model includes a plurality of clusters, wherein each cluster represents a distinct behavioral pattern, wherein each cluster is represented as a plurality of histograms, and wherein each histogram captures historical data of a monitored event.

15. A method for analyzing performance of a database system, comprising:

capturing and storing event data from a database application and from an operating environment running the database application;

generating a performance mining model of the database system based on the event data; and

comparing current event data against the performance mining model to identify performance issues in the database system.

16. The method of claim 15, wherein the event data includes operating environment metrics, database performance metrics, and query workload data.

17. The method of claim 15, wherein the performance mining model is created using a modeling technique selected from the group consisting of:

clustering, associations, and sequences.

18. The method of claim 15, wherein comparing the current event data against the performance mining model generates a score for the stream that reflects a type of behavioral pattern for the current event data.

19. The method of claim 18, further comprising automatically tuning the database system if the score is associated with a performance degradation condition.

20. The method of claim 18, further comprising generating an alert if the score is associated with a performance degradation condition.

21. The method of claim 15, wherein the performance mining model includes a plurality of clusters, wherein each cluster represents a distinct behavioral pattern, wherein each cluster is represented as a plurality of histograms, and wherein each histogram captures historical data of a monitored event.

22. A method for deploying a system for analyzing performance of a database system, comprising:

providing a computer infrastructure being operable to;

capture and store event data from a database application and from an operating environment running the database application;

generate a performance mining model of the database system based on the event data; and

compare current event data against the performance mining model to identify performance issues in the database system.