ANALYZING DATABASE CLUSTER BEHAVIOR BY TRANSFORMING DISCRETE TIME SERIES MEASUREMENTS

• US 20140258254A1
• Filed: 03/08/2013
• Published: 09/11/2014
• Est. Priority Date: 03/08/2013
• Status: Active Grant

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: Oracle International Corporation (Oracle Corporation)
• Inventors: ZOLL, Michael, PRUSCINO, Angelo, SULEIMAN, Yaser Ib
• Granted Patent: US 9,424,288 B2
• Time in Patent Office: Days
• US Class Current: 707/703
• CPC Class Codes: G06F 16/217 Database tuning G06F16/2282 takes precedence; database performance monitoring G06F11/3409
• CPC Class Codes: G06F 16/26 Visual data mining; Browsing structured data
• CPC Class Codes: G06F 16/34 Browsing; Visualisation therefor

Abstract

A method, system, and computer program product for analyzing performance of a database cluster. Disclosed are techniques for analyzing performance of components of a database cluster by transforming many discrete event measurements into a time series to identify dominant signals. The method embodiment commences by sampling the database cluster to produce a set of timestamped events, then pre-processing the timestamped events by tagging at least some of the timestamped events with a semantic tag drawn from a semantic dictionary and formatting the set of timestamped events into a time series where a time series entry comprises a time indication and a plurality of values corresponding to signal state values. Further techniques are disclosed for identifying certain signals from the time series to which is applied various statistical measurement criteria in order to isolate a set of candidate signals which are then used to identify indicative causes of database cluster behavior.

Claims

1. A computer implemented method for analyzing performance of components of a database cluster by transforming discrete events into a time series to identify dominant signals, the method comprising:

sampling, using a measurement instrument, a plurality of discrete event measurements of the database cluster to produce a set of timestamped events, at least some of the timestamped events sampled by one or more hardware components or one or more software components of the database cluster;

formatting the set of timestamped events into a time series wherein a time series entry comprises a time indication and a plurality of values, the values corresponding to a state value of the database cluster; and

processing the time series to identify at least one state signal.

2. The method of claim 1, wherein the components of the database cluster comprise at least one of, a shared resource, a channel, or a process.

3. The method of claim 1, wherein the time series comprises a series of vectors of state values.

4. The method of claim 1, wherein the one or more hardware components is taken from a resource list and the one or more software components is taken from a process list.

5. The method of claim 1, further comprising smoothing the set of timestamped events to remove events exhibiting highest-frequency fluctuations.

6. The method of claim 1, further comprising extracting the dominant signals from the time series.

7. The method of claim 1, further comprising displaying, using a display screen, at least one of the dominant signals.

8. A computer system for analyzing performance of components of a database cluster by transforming discrete events into a time series to identify dominant signals, the computer system comprising:

a computer processor to execute a set of program code instructions; and

a memory to hold the program code instructions, in which the program code instructions comprises program code to perform,

sampling a plurality of discrete event measurements of the database cluster to produce a set of timestamped events, at least some of the timestamped events sampled by one or more hardware components or one or more software components of the database cluster;

formatting the set of timestamped events into a time series wherein a time series entry comprises a time indication and a plurality of values, the values corresponding to a state value of the database cluster; and

processing the time series to identify at least one state signal.

9. The computer system of claim 8, wherein the components of the database cluster comprise at least one of, a shared resource, a channel, or a process.

10. The computer system of claim 8, wherein the time series comprises a series of vectors of state values.

11. The computer system of claim 8, wherein the one or more hardware components is taken from a resource list and the one or more software components is taken from a process list.

12. The computer system of claim 8, further comprising program code for smoothing the set of timestamped events to remove events exhibiting highest-frequency fluctuations.

13. The computer system of claim 8, further comprising program code for extracting the dominant signals from the time series.

14. The computer system of claim 8, further comprising program code for displaying, using a display screen, at least one of the dominant signals.

15. A computer program product embodied in a non-transitory computer readable medium, the computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a process to analyze performance of components of a database cluster by transforming discrete events into a time series to identify dominant signals, the process comprising:

sampling a plurality of discrete event measurements of the database cluster to produce a set of timestamped events, at least some of the timestamped events sampled by one or more hardware components or one or more software components of the database cluster;

formatting the set of timestamped events into a time series wherein a time series entry comprises a time indication and a plurality of values, the values corresponding to a state value of the database cluster; and

processing the time series to identify at least one state signal.

16. The computer program product of claim 15, wherein the components of the database cluster comprise at least one of, a shared resource, a channel, or a process.

17. The computer program product of claim 15, wherein the time series comprises a series of vectors of state values.

18. The computer program product of claim 15, wherein the one or more hardware components is taken from a resource list and the one or more software components is taken from a process list.

19. The computer program product of claim 15, further comprising instructions for smoothing the set of timestamped events to remove events exhibiting highest-frequency fluctuations.

20. The computer program product of claim 15, further comprising instructions for extracting the dominant signals from the time series.