Database diagnostics interface system

• US 9,842,127 B2
• Filed: 11/17/2016
• Issued: 12/12/2017
• Est. Priority Date: 07/10/2013
• Status: Active Grant

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: Oracle International Corporation (Oracle Corporation)
• Inventors: Bostock, Clive
• Primary Examiner(s): OBERLY, VAN HONG
• Application Number:
  US15/354,752
• Publication Number:
  US 20170068692A1
• Time in Patent Office: 390 Days
• Field of Search: 707764
• CPC Class Codes: G06F 11/0727 in a storage system, e.g. in a DASD or network based storage system drivers for digital recording or reproducing units G06F3/06; circuits for error detection or correction within digital recording or reproducing units G11B20/18; for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS], H04L67/1097
• CPC Class Codes: G06F 11/0748 in a remote unit communicating with a single-box computer node experiencing an error/fault remote testing G06F11/2294
• CPC Class Codes: G06F 11/079 Root cause analysis, i.e. error or fault diagnosis in a hardware test environment G06F11/22; in a software test environment G06F11/36
• CPC Class Codes: G06F 11/3003 Monitoring arrangements specially adapted to the computing system or computing system component being monitored
• CPC Class Codes: G06F 11/3065 Monitoring arrangements determined by the means or processing involved in reporting the monitored data error or fault reporting or logging G06F11/0766
• CPC Class Codes: G06F 11/3089 Monitoring arrangements determined by the means or processing involved in sensing the monitored data, e.g. interfaces, connectors, sensors, probes, agents software debugging using additional hardware using a specific debug interface G06F11/3656; performance evaluation by tracing or monitoring G06F11/3466
• CPC Class Codes: G06F 16/211 Schema design and management
• CPC Class Codes: G06F 16/217 Database tuning G06F16/2282 takes precedence; database performance monitoring G06F11/3409
• CPC Class Codes: G06F 16/2365 Ensuring data consistency and integrity
• CPC Class Codes: G06F 16/24565 Triggers; Constraints
• CPC Class Codes: G06F 16/25 Integrating or interfacing systems involving database management systems
• CPC Class Codes: G06F 2201/80 Database-specific techniques

Abstract

Systems, methods, and machine-readable media are provided for database diagnostics. A specification of a target database system may be processed. A diagnostic tool, corresponding to a plug-in for transmission to the target database system, may be created. A script may be selected to conditionally execute on the target database system when detected values of a monitored parameter satisfy conditional criteria. A plug-in structure that encapsulates modules of the plug-in may be defined. The diagnostic tool may be transmitted via a network to the target database system to cause the diagnostic tool to be executed on the target database system. The execution of the diagnostic tool may include executing a first iteration of the plug-in based on a first threshold specified by conditional criteria, and executing a subsequent iteration of the plug-in based on a subsequent threshold specified by the conditional criteria after the conditional criteria has been adjusted.

Claims

1. A database diagnostics system comprising:

one or more processors; and

a memory communicatively coupled with and readable by the one or more processors and having stored therein instructions which, when executed by the one or more processors, cause the one or more processors to;

process a specification of a target database system that is located remotely from the one or more processors;

create a diagnostic tool, corresponding to a plug-in for transmission to the target database system, at least in part by;

selecting a script from a set of predefined scripts, the script to conditionally execute on the target database system when detected values of a monitored parameter of the target database system satisfy conditional criteria;

defining a plug-in structure that encapsulates modules of the plug-in corresponding at least in part to the script and a configuration;

defining the configuration, the defining the configuration comprising defining;

a mapping of one or more script functions to database system functions of the target database system; and

conditional criteria which triggers execution of the script after the script is transmitted to the target database system, wherein the conditional criteria is dynamically adjusted to specify different thresholds over time based at least in part on the detected values of the monitored parameter of the target database system; and

assembling the script and the configuration into the plug-in to perform a diagnostic task based at least in part on the plug-in structure; and

cause transmission of the diagnostic tool via a network to the target database system to cause the diagnostic tool to be executed on the target database system, wherein the execution of the diagnostic tool comprises;

executing a first iteration of the plug-in based at least in part on a first threshold specified by the conditional criteria; and

executing a subsequent iteration of the plug-in based at least in part on a subsequent threshold specified by the conditional criteria after the conditional criteria has been adjusted.

2. The database diagnostics system of claim 1, wherein:

the execution of the diagnostic tool further causes the diagnostic tool to monitor one or more parameters of the target database system; and

accumulate statistics about the one or more parameters;

wherein the conditional criteria is dynamically adjusted based at least in part on the statistics accumulated.

3. The database diagnostics system of claim 2, wherein the diagnostic tool monitors the one or more parameters continuously.

4. The database diagnostics system of claim 2, wherein the diagnostic tool monitors the one or more parameters periodically.

5. The database diagnostics system of claim 2, wherein the conditional criteria is dynamically adjusted according to one or more temporal bases.

6. The database diagnostics system of claim 5, wherein the statistics about the one or more parameters comprise statistics on average service times of queries for different periods of time.

7. The database diagnostics system of claim 6, wherein:

the first threshold specified by the conditional criteria corresponds to a first time period; and

the subsequent threshold specified by the conditional criteria corresponds to a second time period and is specified based at least in part on the statistics on the average service times.

8. A method of database diagnostics, the method comprising:

processing a specification of a target database system;

creating a diagnostic tool, corresponding to a plug-in for transmission to the target database system, at least in part by;

selecting a script from a set of predefined scripts, the script to conditionally execute on the target database system when detected values of a monitored parameter of the target database system satisfy conditional criteria;

defining a plug-in structure that encapsulates modules of the plug-in corresponding at least in part to the script and a configuration;

defining the configuration, the defining the configuration comprising defining;

a mapping of one or more script functions to database system functions of the target database system; and

conditional criteria which triggers execution of the script after the script is transmitted to the target database system, wherein the conditional criteria is dynamically adjusted to specify different thresholds over time based at least in part on the detected values of the monitored parameter of the target database system; and

assembling the script and the configuration into the plug-in to perform a diagnostic task based at least in part on the plug-in structure; and

causing transmission of the diagnostic tool via a network to the target database system to cause the diagnostic tool to be executed on the target database system, wherein the execution of the diagnostic tool comprises;

executing a first iteration of the plug-in based at least in part on a first threshold specified by the conditional criteria; and

executing a subsequent iteration of the plug-in based at least in part on a subsequent threshold specified by the conditional criteria after the conditional criteria has been adjusted.

9. The method of claim 8, wherein:

the execution of the diagnostic tool further causes the diagnostic tool to monitor one or more parameters of the target database system; and

accumulate statistics about the one or more parameters;

wherein the conditional criteria is dynamically adjusted based at least in part on the statistics accumulated.

10. The method of claim 9, wherein the diagnostic tool monitors the one or more parameters continuously.

11. The method of claim 9, wherein the diagnostic tool monitors the one or more parameters periodically.

12. The method of claim 9, wherein the conditional criteria is dynamically adjusted according to one or more temporal bases.

13. The method of claim 12, wherein the statistics about the one or more parameters comprise statistics on average service times of queries for different periods of time.

14. The method of claim 13, wherein:

the first threshold specified by the conditional criteria corresponds to a first time period; and

the subsequent threshold specified by the conditional criteria corresponds to a second time period and is specified based at least in part on the statistics on the average service times.

15. One or more non-transitory, machine-readable media having machine-readable instructions thereon, which, when executed by one or more processing devices, cause the one or more processing devices to:

process a specification of a target database system that is located remotely from the one or more processing devices;

create a diagnostic tool, corresponding to a plug-in for transmission to the target database system, at least in part by;

selecting a script from a set of predefined scripts, the script to conditionally execute on the target database system when detected values of a monitored parameter of the target database system satisfy conditional criteria;

defining a plug-in structure that encapsulates modules of the plug-in corresponding at least in part to the script and a configuration;

defining the configuration, the defining the configuration comprising defining;

a mapping of one or more script functions to database system functions of the target database system; and

conditional criteria which triggers execution of the script after the script is transmitted to the target database system, wherein the conditional criteria is dynamically adjusted to specify different thresholds over time based at least in part on the detected values of the monitored parameter of the target database system; and

assembling the script and the configuration into the plug-in to perform a diagnostic task based at least in part on the plug-in structure; and

cause transmission of the diagnostic tool via a network to the target database system to cause the diagnostic tool to be executed on the target database system, wherein the execution of the diagnostic tool comprises;

executing a first iteration of the plug-in based at least in part on a first threshold specified by the conditional criteria; and

executing a subsequent iteration of the plug-in based at least in part on a subsequent threshold specified by the conditional criteria after the conditional criteria has been adjusted.

16. The one or more non-transitory, machine-readable media of claim 15, wherein:

the execution of the diagnostic tool further causes the diagnostic tool to monitor one or more parameters of the target database system; and

accumulate statistics about the one or more parameters;

wherein the conditional criteria is dynamically adjusted based at least in part on the statistics accumulated.

17. The one or more non-transitory, machine-readable media of claim 16, wherein the diagnostic tool monitors the one or more parameters continuously.

18. The one or more non-transitory, machine-readable media of claim 16, wherein the diagnostic tool monitors the one or more parameters periodically.

19. The one or more non-transitory, machine-readable media of claim 16, wherein the conditional criteria is dynamically adjusted according to one or more temporal bases.

20. The one or more non-transitory, machine-readable media of claim 16, wherein the statistics about the one or more parameters comprise statistics on average service times of queries for different periods of time.