IP Library › Granted Patent US 9,448,873
Granted Patent B2
US 9,448,873 · App. 14/483,699 · Granted Sep 20, 2016

Data processing analysis using dependency metadata associated with error information

Inventors: Gang Huang (Beijing, CN); Tan Jiang (Beijing, CN); Ling Lan (Beijing, CN); Yong Yao (Beijing, CN); Li Yi (Beijing, CN); Liang Wang (Beijing, CN); Yu Zhang (Beijing, CN)
Assignee: International Business Machines Corporation
G06F11/079G06F9/5072G06F11/0709H04L67/10H04W4/003
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Quick Facts
Patent No.
US 9,448,873
App. No.
14/483,699
Granted
Sep 20, 2016
Kind
B2
Abstract

A method, apparatus, and/or computer program product analyzes data processing. Dependency metadata, which is used for representing dependency on data among at least two components of an application, is acquired. Error information, which is used for describing errors that occurred while running the application, and data output, which includes data output by components used to run the application, are acquired. Based on the error information, dependency metadata and data output relevant to the error information are analyzed to provide an analysis result. The analysis result includes at least one of: a reason why an error occurs, a prompt for an error correction method, a relevant dependency metadata leading to an occurrence of an error, and relevant data output leading to an occurrence of an error.

Claims (56)

1. A processor-implemented method for analyzing data processing, the processor-implemented method comprising:

acquiring, by one or more processors, dependency metadata, wherein the dependency metadata is used for representing dependency on data among at least two components of an application, and wherein said acquiring dependency metadata comprises:

acquiring, by one or more processors, a profile of an application instance from a cloud platform; and

searching, by one or more processors, a local environment based on the profile to obtain at least part of the dependency metadata;

acquiring, by one or more processors, error information and data output, wherein the error information is used for describing errors that occur while running the application, and wherein the data output includes data output by said at least two components while running the application;

analyzing, by one or more processors and based on the error information, dependency metadata and data output relevant to the error information; and

providing, by one or more processors, an analysis result, wherein the analysis result includes at least one of: a reason why an error occurs, a prompt for an error correction method, a relevant dependency metadata leading to an occurrence of an error, and relevant data output leading to an occurrence of an error.

2. The processor-implemented method of claim 1 , further comprising:

acquiring, by one or more processors, order constraints, wherein the order constraints are used for representing execution order of the at least two components;

acquiring, by one or more processors, data input, wherein the data input includes data read by components while running the application; and

determining, by one or more processors, redundant order constraints that exist in the order constraints based on the order constraints and the data input.

3. The processor-implemented method of claim 2 , wherein said acquiring order constraints comprises:

acquiring, by one or more processors, order constraints by analyzing the acquired dependency metadata.

4. The processor-implemented method of claim 2 , wherein said acquiring order constraints comprises:

acquiring, by one or more processors, order constraints by parsing a profile of an application instance.

5. The processor-implemented method of claim 2 , further comprising:

prompting, by one or more processors and to a user, existing redundant order constraints and dependency metadata leading to the redundant order constraints.

6. The processor-implemented method of claim 2 , wherein said acquiring data input comprises:

acquiring, by one or more processors, from a cloud platform data input recorded by the cloud platform, wherein the data input recorded by the cloud platform includes data read by components while running the application on the cloud platform; and

running, by one or more processors, the application and recording data read by components while running the application.

7. The processor-implemented method of claim 1 , wherein said acquiring error information and data output comprises:

acquiring, by one or more processors and from a cloud platform, error information and data output recorded by the cloud platform, wherein the error information describes errors that occurred while running the application on the cloud platform, and wherein the data output includes data output by components while running the application on the cloud platform;

re-running, by one or more processors, the application;

recording, by one or more processors, error information that describes errors that occurred while running the application; and

recording, by one or more processors, data output from predetermined components that occur from running the application.

8. The processor-implemented method of claim 1 , wherein said acquiring dependency metadata further comprises:

acquiring, by one or more processors, the dependency metadata from the cloud platform in response to the dependency metadata not being found in the local environment.

9. A computer program product for analyzing data processing, the computer program product comprising a computer readable storage medium having program code embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, and wherein the program code is readable and executable by a processor to perform a method comprising:

acquiring dependency metadata, wherein the dependency metadata is used for representing dependency on data among at least two components of an application, and wherein said acquiring dependency metadata comprises:

acquiring a profile of an application instance from a cloud platform; and

searching a local environment based on the profile to obtain at least part of the dependency metadata;

acquiring error information and data output, wherein the error information is used for describing errors that occur while running the application, and wherein the data output includes data output by components while running the application;

analyzing, based on the error information, dependency metadata and data output relevant to the error information; and

providing an analysis result, wherein the analysis result includes at least one of: a reason why an error occurs, a prompt for an error correction method, a relevant dependency metadata leading to an occurrence of an error, and relevant data output leading to an occurrence of an error.

10. The computer program product of claim 9 , wherein the method further comprises:

acquiring order constraints, wherein the order constraints are used for representing execution order of the at least two components;

acquiring data input, wherein the data input includes data read by components while running the application; and

determining redundant order constraints that exist in the order constraints based on the order constraints and the data input.

11. The computer program product of claim 10 , wherein said acquiring order constraints comprises:

acquiring order constraints by analyzing the acquired dependency metadata.

12. The computer program product of claim 10 , wherein said acquiring order constraints comprises:

acquiring order constraints by parsing a profile of an application instance.

13. The computer program product of claim 10 , wherein the method further comprises:

prompting, to a user, existing redundant order constraints and dependency metadata leading to the redundant order constraints.

14. The computer program product of claim 9 , wherein said acquiring error information and data output comprises:

acquiring, from a cloud platform, error information and data output recorded by the cloud platform, wherein the error information describes errors that occurred while running the application on the cloud platform, and wherein the data output includes data output by components while running the application on the cloud platform;

re-running the application;

recording error information that describes errors that occurred while running the application; and

recording data output from predetermined components that occur from running the application.

15. A data processing apparatus, comprising:

a relationship acquiring hardware module configured to acquire dependency metadata, wherein the dependency metadata is used for representing dependency on data among at least two components of an application, and wherein said relationship acquiring hardware module acquires the dependency metadata by:

acquiring a profile of an application instance from a cloud platform; and

searching a local environment based on the profile to obtain at least part of the dependency metadata;

a first information acquiring hardware module configured to acquire error information and data output, wherein the error information is used for describing errors that occur while running the application, and wherein the data output includes data output by components while running the application;

an analyzing hardware module configured to analyze, based on the error information, dependency metadata and data output relevant to the error information; and

a result hardware module configured to provide an analysis result including at least one of: a reason why an error occurs, a prompt for an error correction method, a relevant dependency metadata leading to an occurrence of an error, and a relevant data output leading to an occurrence of an error.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 11, 2014
From: HUANG, GANG; JIANG, TAN; LAN, LING; YAO, YONG; YI, LI; WANG, LIANG; ZHANG, YU
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 033722/0593 →
Priority Claims (1)
CN 2013 1 0454548 · Sep 29, 2013 · national
Continuity (1)
Related Publication 20150095707A1 · Apr 2, 2015