Iterative performance analysis with interval expansion

Patent metadata

Field	Value
Publication number	US-11630818-B2
Application number	US-202117304015-A
Country	US
Kind code	B2
Filing date	Jun 11, 2021
Priority date	Jun 11, 2021
Publication date	Apr 18, 2023
Grant date	Apr 18, 2023

Abstract

Performance data characterizing operations of an application may be collected by time interval, and a plurality of keys may be associated with each element of the performance data. A first time interval may be received. An iterative group-and-filter search may be executed against the keyed elements within the first time interval, each iteration including an iteration key used to perform a key-based grouping operation followed by a group-based filter operation, wherein each iteration key is added to a composite key at each iteration. A selection of at least one keyed element within the first time interval and obtained from the iterative group-and-filter search may be received. A second time interval that precedes the first time interval may be received, and the keyed elements may be filtered using the composite key and within the second time interval to return the at least one keyed element within the second time interval.

First claim

What is claimed is:

1. A computer program product, the computer program product being tangibly embodied on a non-transitory computer-readable storage medium and comprising instructions that, when executed by at least one computing device, are configured to cause the at least one computing device to:
collect, over a time period, performance data including performance elements characterizing operations of an application of an operating system environment;
associate a plurality of keys with each performance element, to obtain keyed performance elements;
receive a first time interval within the time period;
execute an iterative group-and-filter search against the keyed performance elements within the first time interval, including:
(a) performing a key-based grouping operation using an iteration key of the plurality of keys,
(b) adding the iteration key to a composite key,
(c) performing a group-based filter operation to identify a narrowed set of keyed performance elements associated with a problem in the performance data of the application, and
(d) repeating operations (a)-(c) until a final iteration is reached, the final iteration including at least one keyed performance element of the narrowed set of keyed elements of the final iteration;

receive a second time interval that precedes the first time interval within the time period;
filter the keyed performance elements using the composite key and within the second time interval to return the at least one keyed performance element within the second time interval; and
identify the problem within the second time interval, based on the at least one keyed performance element within the second time interval.

2. The computer program product of claim 1 , wherein the group-based filter operation is conducted using an iteration key value of the iteration key, and the iteration key value is added to the composite key.

3. The computer program product of claim 2 , wherein the instructions, when executed by the at least one computing device, are further configured to cause the at least one computing device to:
display the composite key at each iteration of the iterative group-and-filter search, including each iteration key and iteration key value determined in preceding iterations.

4. The computer program product of claim 1 , wherein the instructions, when executed by the at least one computing device, are further configured to cause the at least one computing device to execute an iteration of the iterative group-and-filter search including causing the at least one computing device to:
execute the key-based grouping operation, wherein the key-based grouping operation is defined with respect to a current iteration key of the plurality of keys and the key-based grouping operation produces key-based groups;
display the key-based groups within the first time interval and sorted by performance data included in each of the key-based groups;
receive a selected group of the key-based groups, the selected group representing a current iteration key value for the current iteration key;
execute the group-based filter operation to filter non-selected ones of the key-based groups, using the current iteration key value; and
add the current iteration key and the current iteration key value to the composite key.

5. The computer program product of claim 1 , wherein the performance data is stored by interval and aggregated over each interval within log files.

6. The computer program product of claim 5 , wherein the log files are stored in an archive as sequential files after archive criteria are met.

7. The computer program product of claim 6 , wherein the instructions, when executed by the at least one computing device, are further configured to cause the at least one computing device to:
determine that the second time interval requires performance data from the archive; and
apply the composite key and the second time interval to the archive to return the at least one keyed element.

8. The computer program product of claim 1 , wherein the instructions, when executed by the at least one computing device, are further configured to cause the at least one computing device to:
store the composite key using a data structure with a defined mapping that includes slots corresponding to the plurality of keys, in which an iteration key value is added into a corresponding slot for a corresponding iteration key at each iteration.

9. The computer program product of claim 1 , wherein the instructions, when executed by the at least one computing device, are further configured to cause the at least one computing device to:
receive a selection of at least a second keyed element within the first time interval, obtained from the iterative group-and-filter search;
receive a third time interval that precedes the first time interval; and
filter the keyed elements using the composite key and within the third time interval to return the at least the second keyed element within the third time interval.

10. A computer-implemented method, the method comprising:
collecting, over a time period, performance data including performance elements characterizing operations of an application of an operating system environment;
associating a plurality of keys with each performance element to obtain keyed performance elements;
receiving a first time interval within the time period;
executing an iterative group-and-filter search against the keyed performance elements within the first time interval, including:
(a) performing a key-based grouping operation using an iteration key of the plurality of keys,
(b) adding the iteration key to a composite key,
(c) performing a group-based filter operation to identify a narrowed set of keyed performance elements associated with a problem in the performance data of the application, and
(d) repeating operations (a)-(c) until a final iteration is reached, the final iteration including at least one keyed performance element of the narrowed set of keyed elements of the final iteration;

receiving a second time interval that precedes the first time interval within the time period;
filtering the keyed performance elements using the composite key and within the second time interval to return the at least one keyed performance element within the second time interval; and
identifying the problem within the second time interval, based on the at least one keyed performance element within the second time interval.

11. The method of claim 10 , wherein the group-based filter operation is conducted using an iteration key value of the iteration key, and the iteration key value is added to the composite key.

12. The method of claim 11 , further comprising:
displaying the composite key at each iteration of the iterative group-and-filter search, including each iteration key and iteration key value determined in preceding iterations.

13. The method of claim 10 , wherein an iteration of the iterative group-and-filter search includes:
executing the key-based grouping operation, wherein the key-based grouping operation is defined with respect to a current iteration key of the plurality of keys and the key-based grouping operation produces key-based groups;
displaying the key-based groups within the first time interval and sorted by performance data included in each of the key-based groups;
receiving a selected group of the key-based groups, the selected group representing a current iteration key value for the current iteration key;
executing the group-based filter operation to filter non-selected ones of the key-based groups, using the current iteration key value; and
adding the current iteration key and the

Assignees

• Bmc Software Inc

Inventors

• Behne Michael D

Classifications

• G06F11/079

  Root cause analysis, i.e. error or fault diagnosis (in a hardware test environment G06F11/22; in a software test environment G06F11/36) · CPC title

• G06F11/3409

  for performance assessment · CPC title

• G06F11/3476

  Data logging (G06F11/14, G06F11/2205 take precedence) · CPC title

• G06F11/3006 Primary

  where the computing system is distributed, e.g. networked systems, clusters, multiprocessor systems (multiprogramming arrangements G06F9/46; allocation of resources G06F9/50) · CPC title

• G06F16/2358 Primary

  Change logging, detection, and notification (replication G06F16/27) · CPC title