CN113608849A - Information flow optimization method based on shader component - Google Patents
Information flow optimization method based on shader component Download PDFInfo
- Publication number
- CN113608849A CN113608849A CN202110861849.8A CN202110861849A CN113608849A CN 113608849 A CN113608849 A CN 113608849A CN 202110861849 A CN202110861849 A CN 202110861849A CN 113608849 A CN113608849 A CN 113608849A
- Authority
- CN
- China
- Prior art keywords
- error
- information
- error information
- sender
- scheduler
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/48—Program initiating; Program switching, e.g. by interrupt
- G06F9/4806—Task transfer initiation or dispatching
- G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
- G06F16/2282—Tablespace storage structures; Management thereof
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/54—Interprogram communication
- G06F9/547—Remote procedure calls [RPC]; Web services
Abstract
The application discloses an information flow optimization method based on a shader component, which comprises the following steps: the client sends a work request; performing parameter detection based on the circular-api; when the parameters are not in compliance, feeding error information back to the client; sending a work request to the finder-scheduler when the parameters are compliant; scheduling processing is carried out based on a circle-scheduler; setting the state of an operation object as error when the scheduling processing fails, writing error information into a log file, analyzing the error information, and recording the analyzed error information into a database table; entering a sender-volume when the scheduling processing is successful; conf, calling a storage back end driver configured in the cider to execute a specific action, if an execution error occurs, setting the state of a processing object as error, writing error information into a corresponding log file, simultaneously analyzing the error information and recording the analyzed error information into a database table; and if the execution is successful, setting the state of the operation object to available. The method and the device can record corresponding information and realize information query when an error occurs in the sender-scheduler/sender-volume service.
Description
Technical Field
The application relates to the technical field of computers, in particular to an information flow optimization method based on a render component.
Background
With the development of cloud computing, the project landing of Openstack is increasingly complicated. To support its huge number of nodes, Openstack adopts a distributed-microservices design architecture. This results in a loose coupling between its various components and the services within a single component. Meanwhile, in order to ensure processing efficiency, asynchronous processing is widely used in Openstack. This results in a one-way circulation of information flow within the individual components. So that it is very unfriendly to acquire some important underlying information. The information can be obtained only by manually inquiring the related logs, so that the operation and maintenance efficiency is very low. Taking the sender component as an example, the inside of the sender component is divided into a sender-api service, a sender-scheduler service and a sender-volume service. The sender-API service provides RESTful API for the user, the sender-scheduler service is responsible for scheduling business, and the sender-volume service is responsible for interfacing specific back-end storage. Message passing is carried out among the three services through rabbitmq, and the RPC call of cast which does not wait for the return value is adopted. Therefore, when the business process has an error in the sender-scheduler or the sender-volume, the error information is written into the log file, and the user cannot obtain the error information through the API.
The invention content is as follows:
the invention aims to provide a sender component-based information flow optimization method, which can record corresponding information and realize information query when an error occurs in a sender-scheduler/sender-volume service.
The technical scheme adopted is as follows:
an information flow optimization method based on a shader component comprises the following steps:
step 2, performing parameter detection based on the circular-api; when the parameters are not in compliance, feeding error information back to the client; when the parameters are in compliance, sending a work request to the finder-scheduler and executing the step 3;
step 3, scheduling processing is carried out based on a sender-scheduler; setting the state of an operation object as error when the scheduling processing fails, writing error information into a log file, analyzing the error information, and recording the analyzed error information into a database table; entering a sender-volume when the scheduling processing is successful;
step 4, calling a storage back end driver configured in the circle to execute a specific action, if an execution error occurs, setting the state of a processing object as error, writing error information into a corresponding log file, simultaneously analyzing the error information and recording the analyzed error information into a database table; and if the execution is successful, setting the state of the operation object to available.
Preferably, in the information flow optimization method based on the shader component, the analysis error information includes:
step 31, capturing abnormal information;
step 32, analyzing and classifying the error information based on an information analysis algorithm to obtain error classification information;
step 33, instantiating an error object of the error information class and writing error classification information into the error object;
and step 34, storing the error classification information into a database.
More preferably, in the information flow optimization method based on the shader component, the step 32 includes: and analyzing and classifying the error information based on an exception _ to _ fact function and a _ get _ fault _ details function.
Further preferably, in the information flow optimization method based on the shader component, the method further includes: the error classification information includes: error information ID, disk ID, error code, error information type, function call stack where the error occurred, host name where the error occurred.
Compared with the prior art, the application has the following technical effects:
send create disk request through standard RESTful API interface: recording corresponding information when an error occurs in a circle-scheduler/circle-volume service; and the client sends a request for acquiring the disk details through a standard RESTful API (application program interface), and if the disk state is Error, information containing a specific reason that the disk state is Error is added in the acquired disk details. Only the sender-api interface is used, and other interfaces are not influenced; the method and the device can be used for capturing error information, monitoring information, metadata information customized by a client and other information which the user wants to transmit.
Drawings
The present application will now be described in further detail with reference to the following detailed description and accompanying drawings:
FIG. 1 is a first work flow diagram of the present invention;
FIG. 2 is a second workflow diagram of the present invention;
FIG. 3 is a screenshot of an interface for a human destruction environment of example 1;
fig. 4 is an interface screenshot for calling an interface to perform information analysis and recording in embodiment 1;
FIG. 5 is a screenshot of an interface for creating a disk in example 1;
fig. 6 is a screenshot of short information of a disk when the disk information is viewed in embodiment 1;
fig. 7 is a screenshot of detailed information of a disk when disk information is viewed in embodiment 1;
FIG. 8 is an error message screenshot of the Cinder-scheduler log file in example 1.
Detailed Description
In order to more clearly illustrate the technical solutions of the present application, the following will be further described with reference to various embodiments.
An information flow optimization method based on a shader component comprises the following steps:
step 2, performing parameter detection based on the circular-api; when the parameters are not in compliance, feeding error information back to the client; when the parameters are in compliance, sending a work request to the finder-scheduler and executing the step 3;
step 3, scheduling processing is carried out based on a sender-scheduler; setting the state of an operation object as error when the scheduling processing fails, writing error information into a log file, analyzing the error information, and recording the analyzed error information into a database table; entering a sender-volume when the scheduling processing is successful;
step 4, calling a storage back end driver configured in the circle to execute a specific action, setting the state of a processing object as error when an error occurs, writing error information into a corresponding log file, analyzing the error information and recording the analyzed error information into a database table; when the execution is successful, the state of the operation object is set to available.
If the Error information is required to be acquired, whether the disk state is Error or not can be judged in a circle, api, v2, volumes, volume controller, show, an Error information object is instantiated, a method for acquiring the latest Error information of the disk is called, the latest Error information is acquired, and the Error information is added into the disk attribute through a setar method. Error information is then added to the return value of the disk details in the circle, api, v2, volumes, views.
Example 1:
take the process of creating a disk as an example
The first step is as follows: as shown in FIG. 3, the environment is artificially destroyed, at which point the creation of the disk fails, and there is no circle-volume service available for circle-scheduler scheduling, which must fail in circle-scheduler.
The second step is that: as shown in FIG. 4, in the circular-scheduler, add _ volume _ fault _ from _ exc is called. The adding position is/usr/lib/python 2.7/site-packages/circle/schedule/flows/create _ volume
The third step: creating a magnetic disk; as shown in fig. 5: at this point the disk is now under creation, with the disk ID ef1a128b-b6d4-4a31-b984-b8822f7c2ab8
The fourth step: checking disk information;
FIG. 6 is a short message for a disk, and it can be seen that the disk is now in an error state;
FIG. 7 is a portion of disk detail, where it can be seen that detailed error information is contained in the Fault entry;
the fifth step: comparing the log files;
FIG. 8 is a comparison of the error report part of the Cinder-scheduler log file with FIG. 7, which demonstrates that the method described herein can correctly record error information
The above description is only for the specific embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application are intended to be covered by the scope of the present application. The protection scope of the present application shall be subject to the protection scope of the claims.
Claims (4)
1. An information flow optimization method based on a shader component is characterized by comprising the following steps:
step 1, a client sends a work request;
step 2, performing parameter detection based on the circular-api; when the parameters are not in compliance, feeding error information back to the client; when the parameters are in compliance, sending a work request to the finder-scheduler and executing the step 3;
step 3, scheduling processing is carried out based on a sender-scheduler; setting the state of an operation object as error when the scheduling processing fails, writing error information into a log file, analyzing the error information, and recording the analyzed error information into a database table; entering a sender-volume when the scheduling processing is successful;
step 4, calling a storage back end driver configured in the circle to execute a specific action, if an execution error occurs, setting the state of a processing object as error, writing error information into a corresponding log file, simultaneously analyzing the error information and recording the analyzed error information into a database table; and if the execution is successful, setting the state of the operation object to available.
2. The information flow optimization method based on a shader component as claimed in claim 1, wherein said parsing error information includes:
step 31, capturing abnormal information;
step 32, analyzing and classifying the error information based on an information analysis algorithm to obtain error classification information;
step 33, instantiating an error object of the error information class and writing error classification information into the error object;
and step 34, storing the error classification information into a database.
3. The information flow optimization method based on the shader component as set forth in claim 2, wherein said step 32 includes: and analyzing and classifying the error information based on an exception _ to _ fact function and a _ get _ fault _ details function.
4. The information flow optimization method based on the shader component as recited in claim 2, wherein: the error classification information includes: error information ID, disk ID, error code, error information type, function call stack where the error occurred, host name where the error occurred.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110861849.8A CN113608849A (en) | 2021-07-29 | 2021-07-29 | Information flow optimization method based on shader component |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110861849.8A CN113608849A (en) | 2021-07-29 | 2021-07-29 | Information flow optimization method based on shader component |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113608849A true CN113608849A (en) | 2021-11-05 |
Family
ID=78305890
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110861849.8A Pending CN113608849A (en) | 2021-07-29 | 2021-07-29 | Information flow optimization method based on shader component |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113608849A (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20040051927A (en) * | 2002-12-13 | 2004-06-19 | 삼성전자주식회사 | The method for log processing of application error information |
| CN107741874A (en) * | 2017-10-12 | 2018-02-27 | 武汉中地数码科技有限公司 | A kind of GIS clouds virtual machine automatically creates method and system |
| CN111106965A (en) * | 2019-12-25 | 2020-05-05 | 浪潮商用机器有限公司 | Intelligent log analysis method, tool, equipment and medium for complex system |
-
2021
- 2021-07-29 CN CN202110861849.8A patent/CN113608849A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20040051927A (en) * | 2002-12-13 | 2004-06-19 | 삼성전자주식회사 | The method for log processing of application error information |
| CN107741874A (en) * | 2017-10-12 | 2018-02-27 | 武汉中地数码科技有限公司 | A kind of GIS clouds virtual machine automatically creates method and system |
| CN111106965A (en) * | 2019-12-25 | 2020-05-05 | 浪潮商用机器有限公司 | Intelligent log analysis method, tool, equipment and medium for complex system |
Non-Patent Citations (1)
| Title |
|---|
| LUOHAIXIAN: ""Cinder组件解析"", 《HTTPS://WWW.CNBLOGS.COM/LUOHAIXIAN/P/8134967.HTML》, pages 2 - 12 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109284269B (en) | Abnormal log analysis method and device, storage medium and server | |
| US7886281B2 (en) | System and methods for cross-tier transaction tracing | |
| US5933639A (en) | System and method for debugging distributed programs | |
| CN107105009B (en) | Job scheduling method and device for butting workflow engine based on Kubernetes system | |
| US7941789B2 (en) | Common performance trace mechanism | |
| US20050223365A1 (en) | System and methods for tracing transactions | |
| US20050223366A1 (en) | System and methods for transaction tracing | |
| US20050223367A1 (en) | System and methods for instrumenting applications | |
| US8667333B2 (en) | Extensible testing system | |
| US11119843B2 (en) | Verifying application behavior based on distributed tracing | |
| US20160274997A1 (en) | End user monitoring to automate issue tracking | |
| US20050222689A1 (en) | Method of determining performance of an application server environment relating to a transaction | |
| EP3362900B1 (en) | Telemetry system extension | |
| CN111930489B (en) | Task scheduling method, device, equipment and storage medium | |
| CN110717130A (en) | Dotting method, dotting device, dotting terminal and storage medium | |
| CN113608849A (en) | Information flow optimization method based on shader component | |
| CN116795712A (en) | Reverse debugging method, computing device and storage medium | |
| CN114553663B (en) | Abnormality detection method, abnormality detection device, abnormality detection equipment and storage medium | |
| CN112241362A (en) | Test method, test device, server and storage medium | |
| CN112650613B (en) | Error information processing method and device, electronic equipment and storage medium | |
| CN111045891B (en) | Monitoring method, device, equipment and storage medium based on java multithreading | |
| CN112162954B (en) | User operation log generation and path positioning method, device, equipment and medium | |
| CN113342769A (en) | Unified log recording tool, method, storage medium and equipment | |
| CN113760696A (en) | Program problem positioning method and device, electronic equipment and storage medium | |
| CN111428260A (en) | File security access control method and system based on chip protection device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |