CN109359094B - Distributed system log full-link tracking method and device - Google Patents
Distributed system log full-link tracking method and device Download PDFInfo
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Abstract
The invention relates to a distributed system log full-link tracking method and a distributed system log full-link tracking device. The method comprises the following steps: s1, creating a configuration file configuration system, and executing according to the following procedures: configuring a cluster server; configuring a cluster dependency relationship; configuring a data logic relation; s2, reading and analyzing the configuration file through the application program to obtain key information; and S3, acquiring the life history of the system data according to the key information. The device comprises a system configuration unit, an information acquisition unit and a cluster traversing unit. The data log full link tracking is abstracted into three configuration files, the configuration files are read and analyzed by corresponding application programs, the key information, such as server information, the upstream and downstream sequences of a system and the logic relation among system data, corresponding to each cluster can be obtained, the life history of the system data can be obtained in a code-free embedded mode in a one-key mode, and problems encountered in an online or testing process can be located.
Description
Technical Field
The invention relates to the field of log tracking systems, in particular to a distributed system log full-link tracking method and device.
Background
Today's internet companies have a large number of distributed servers, each routing request through multiple business systems and leaving footprints and generating many DB accesses, but these distributed data are located on different servers, managed by different development teams, and have limited help for problem troubleshooting, or process optimization. Once a problem occurs on the line, all involved development groups are added to the queue for problem troubleshooting, wasting valuable development resources. If a set of system can accurately position the time and place of the problem, the problem solving efficiency is greatly improved, and the influence time of the on-line problem is shortened. Tracking the complete call link of each request, collecting the service data of each service on the call link, and locating the reason of the abnormal position data also become the urgent needs of each company.
Currently, many companies build log management platforms by using ELKs, which include ElasticSearch (data storage, fast query), logstack (log collection), and kibana (graphical interface for displaying ElasticSearch data). kibana is a graphical interface on which data stored in the Elastic Search (ES) can be retrieved, corresponding to the visualization operations manager that provides the ES.
Currently, there is a log tracking system built based on an Elasticsearch, in which a log transmission tool is needed, and currently available transmission tools include: logstash, Filebeat, Fluentd, rsyslog, syslog-ng, and Lotagent. Log analysis system based on logstack + Elasticisearch + kibana combination. For logstash, the configuration is needed to include: 1. data source 2, define data format 3, output configuration (output to the elasticsearch). Cons f, then operating logstash, and seeing that logstash can automatically inquire the attribution of IP, and analyzing the device field in the request. For the Elasticsearch and kibana, the required configuration is: 1. yml, elstic search uses default configuration with configuration name config/elstic search. Wherein the Elasticsearch default listening is at 9200 port, and can inquire and manage the Elasticsearch default listening. 2. Kibana also does not need special configuration, and listens on 5601 port by default.
The main advantage of Logstash is its flexible configuration, with a variety of customizable plug-ins, such as: input, filter, output, so that rich data can be retrieved and sent to the target for storage. But at the same time, the disadvantage of logstash is very obvious, which is mainly reflected in that one can not correlate the cross-system data, the other can not customize one-key query, and the third is the problem of performance and resource consumption, and the speed is slower when the data volume is large. Therefore, when logstack is selected, the performance of the server needs to be considered. If the performance of the server is poor, a lightweight log transmission tool is needed to replace logstack.
Through the analysis, the log management system can realize the query and record of different service logs, but cannot quickly and conveniently acquire, process and transfer data in each system.
The method is characterized in that a unique id scheme is created for data flowing into a next system at a code buried point, and full-link log query can also be realized, but the scheme needs to invest more manpower and material resources, modifies the original code, influences the performance of the system and possibly introduces new problems to the system.
Disclosure of Invention
In order to solve the above problems, an object of the present invention is to provide a method and an apparatus for full link tracking of distributed system logs. The data log full link tracking is abstracted into three configuration files, namely cluster server configuration, cluster dependency relationship configuration and data logic relationship configuration, the configuration files are read and analyzed through corresponding application programs, and key information, namely server information, upstream and downstream sequences of a system and logic relationships among system data, corresponding to each cluster can be obtained.
In order to achieve the above purpose, the embodiments of the present application are implemented as follows:
the embodiment of the application provides a distributed system log full link tracking method, which comprises the following steps:
s1, creating a configuration file configuration system, and executing according to the following procedures:
configuring a cluster server;
configuring a cluster dependency relationship;
configuring a data logic relation;
s2, reading and analyzing the configuration file through the application program to obtain key information;
and S3, acquiring the life history of the system data according to the key information.
As a preferred technical solution, the configuring the cluster server includes:
defining unique identification of each group of cluster servers;
and increasing or decreasing servers under each group of cluster servers.
As a preferred technical solution, the configuring the cluster dependency relationship includes:
defining an upstream cluster server and a downstream cluster server;
and establishing a corresponding relation between the upstream cluster server and the downstream cluster server.
As a preferred technical solution, one upstream cluster server may correspond to one or more downstream cluster servers.
As a preferred technical solution, the configuring the data logical relationship includes:
defining a data line mark;
configuring a rule that a server with data change under each data line acquires data from an upstream cluster server and/or a downstream cluster server;
wherein the rules include transfer rules of data and processing rules of data.
As a preferred technical solution, the key information in S2 includes: server information corresponding to each cluster, the upstream and downstream sequence of each group of cluster servers and the logical relationship among system data.
As a preferred embodiment, the S3 includes:
s31, providing a system data;
s32, traversing the corresponding cluster server in the cluster server configuration file by taking the key information as a query condition;
and S33, outputting the data line where the system data is located.
As a preferred technical solution, the S32 is executed according to the following procedure:
writing a function method by taking the key data obtained in the S2 and the system data given in the S31 as function parameters, traversing all servers, and inquiring the affairs related to the system data in the S1;
inquiring upstream and downstream cluster servers according to the cluster dependency configuration file, traversing the rest cluster servers in the system by two branches, wherein one branch is searched one by one upstream, and the other branch is searched one by one downstream; when searching for an upstream or downstream cluster server, the data logical relationship configuration file needs to be read to obtain the data conversion relationship between the current and upstream or downstream cluster servers.
As a preferred embodiment, in S2, after traversing to the warning information or the error information, the user jumps out of the traversal.
The embodiment of the application provides a full link tracer of distributed system log, includes:
the system configuration unit is used for creating a configuration file configuration system, and the configuration file comprises cluster server configuration, cluster dependency relationship configuration and data logic relationship configuration;
the information acquisition unit is used for reading and analyzing the configuration file through the application program to acquire key information;
and the cluster traversing unit is used for inputting system data and acquiring the life history of the system data according to the key information.
The invention has the advantages that:
1. the scheme is a complete scheme for inquiring the key data log full link, and can provide information, warning, errors and the like of data left by each cluster server.
2. The scheme is simple to apply, points do not need to be buried in original system codes, and developers do not need to invest in a large amount of manpower and material resources.
3. The method is simple to operate, can locate the problems on the line or in the test process by one key, and the time saved by the locating problem is also in direct proportion to the number of clusters. If there are five systems, 4/5 log query time would be saved.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
FIG. 2 is a flow chart of S3 in the method of the present invention.
Fig. 3 is a system architecture diagram of an embodiment of the present invention.
Fig. 4 is a schematic diagram of performing S3 according to the present invention.
FIG. 5 is a block diagram of functional blocks of the apparatus of the present invention.
Detailed Description
Preferred embodiments of this patent are described in further detail below with reference to the accompanying drawings.
Fig. 1 shows an implementation manner of a distributed system log full-link tracking method, where the method includes:
s1, creating a configuration file configuration system, and executing according to the following procedures:
configuring a cluster server;
configuring a cluster dependency relationship;
and configuring the data logical relation.
The method comprises the steps that a cluster server is configured, wherein unique identification of each group of cluster servers is defined; and increasing or decreasing servers under each group of cluster servers.
For example, using xml to generate a cluster server profile, the extension of the cluster server profile is clusters, the cluster server profile xml nodes are as follows: the parent node is clusters, and the child node clusters contains id and servers. The id is the unique identification of the cluster server and is not repeatable, and only one id is provided for one cluster server. And increasing or decreasing servers to operate under servers nodes. For example, two groups of cluster servers are identified by using SystemA and SystemB as ids, two servers with IP of 192.168.1.1 and 192.168.1.2 are associated under SystemA, the above SystemA and SystemB are defined under child node cluseter, and the operation of adding two servers with IP of 192.168.1.1 and 192.168.1.2 is defined under servers.
The configuration cluster server comprises an upstream cluster server and a downstream cluster server which are defined; and establishing a corresponding relation between the upstream cluster server and the downstream cluster server. One upstream cluster server may correspond to one or more downstream cluster servers.
For example, using xml to generate a cluster dependency configuration file, the extension of which is relationships, the cluster dependency configuration file xml nodes are as follows: the father node is relations, and the child node relations comprise upstream and downstream. Upstream cluster servers are defined using the upstream node and downstream cluster servers are defined using the downstream node, the values of upstream and downstream must be the id of the cluster server configuration file already present. For example, if the upstream-downstream relationship between SystemA and SystemB is defined under one relationship node, where SystemA is defined under the upstream node and SystemB is defined under the downstream node, it is known that SystemA is upstream of SystemB. And defining the upstream and downstream relation between SystemB and SystemC under another relation node, wherein SystemB is defined under the upstream node, SystemB is defined under the downstream node, and SystemB is known to be upstream of SystemC. The upstream and downstream relationship between any two cluster servers may be defined in the manner described above. In addition, one upstream cluster server may correspond to a plurality of downstream cluster servers, and for example, if the upstream and downstream relationships of SystemA, SystemB, and SystemC are defined under one relationship node, where SystemA is defined under the upstream node, and SystemB and SystemC are defined under the downstream node, it is known that SystemB and SystemC are upstream of SystemB. Where, SystemA, SystemB, and SystemC are all ids defined in the cluster server configuration file.
Configuring a data logical relationship comprises defining a data line mark; configuring a rule that a server with data change under each data line acquires data from an upstream cluster server and/or a downstream cluster server; as shown in fig. 3, the rules include a transfer rule of data and a processing rule of data.
For example, a data logical relationship configuration file is generated using xml, the extension of which is. By default, all data is not in a conversion relationship, i.e., the shape and value of a piece of data are the same in all cluster servers. After being processed or transferred in a certain cluster server we need to configure the logics files. The data logical relationship configuration file xml nodes are as follows: the parent node of the file is logics, and the child node logic comprises businessId and transfer. One businessId represents one data line, and a plurality of logic is arranged on a plurality of data lines. The change modes of the system data need to be listed under the Transfer node, and the cluster with the changed data needs to give the modes of acquiring data from upstream and downstream, wherein the mode of acquiring data from upstream is defined under the frompstream node, and the mode of acquiring data from upstream is defined under the fromdowstream node, so that the data upstream or downstream of the cluster can be obtained no matter which data in the cluster is given. Some data is not changed in the Transfer process, or the data is located in the initiating cluster and the ending cluster of one data line, so that under one Transfer node, only one of fromuStream and fromDownStream can be present. The Transfer node is a specific implementation of data upstream and downstream logic that defines how data from the current node is queried for data from a parent (frompstream) and a subsystem (fromdowstream). For example, the data of the parent system is stored in the database, and can be queried according to the data of the current system, and we can use the statement SELECT Id _ a FROM SystemA WHERE Id _ B is Value _ B. The Id _ a queried is the data corresponding to our system a, and is also the upstream data of Value _ B. Similarly, we can also query the downstream corresponding Id _ C. Of course, various data forms should be supported here, and if only simple mathematical calculation is carried out, then we list the formula. If the upstream id is divided by 2 to get the downstream id, we can write directly as < fromUpStream > SystemA/2</fromUpStream >. These configurations allow the program to parse what data form is used.
And S2, reading and analyzing the configuration file through the application program to acquire key information.
With the configuration files created above, java or other types of applications can be newly created, and the configuration files can be read and analyzed. We will get the following information: server information corresponding to each group of clusters, the upstream and downstream sequence of each group of cluster servers and the logical relationship among system data.
And S3, acquiring the life history of the system data according to the key information.
The life history of the data refers to the flow of data throughout the life cycle: from creation and initial storage to its obsolescence is deleted.
As shown in fig. 2 and 4, S3 includes:
s31, a system data, such as data C in SystemC, is given. For example, a system name, a business key name (e.g., buisinsessid), and a value (e.g., P123456) are selected via the webUI.
And S32, traversing the corresponding cluster server in the cluster server configuration file by taking the key information as a query condition. The S32 is executed according to the following procedure:
compiling a function method by taking the key data obtained in the S2 and the system data given in the S31 as function parameters, traversing all servers, inquiring affairs, warning information or error information related to the system data in the S1, and jumping out of traversal; once the warning or error information is detected, the current system name, machine name and a specific warning or error log are printed out.
Inquiring upstream and downstream cluster servers according to the cluster dependency configuration file, traversing the rest cluster servers in the system by two branches, wherein one branch is searched one by one upstream, and the other branch is searched one by one downstream; when searching for an upstream or downstream cluster server, the data logical relationship configuration file needs to be read to obtain the data conversion relationship between the current and upstream or downstream cluster servers.
And S33, outputting the data line where the system data is located.
The specific implementation of S3 will be described by taking a java application as an example:
a method with three parameters is designed, such as sequential DataFlow (String System Id, String businessId, String value).
And obtaining a corresponding server in the clusters file according to the systemId, writing a function method to traverse into all servers, inquiring info associated with the data, and jumping out of the traversal after warning and errors. The businessId may be conditioned on querying upstream and downstream system relationships.
According to the relations, the upstream and downstream systems are inquired, and the rest clusters are traversed by dividing two branches. One branch is looked up one by one upstream and the other branch is looked up one by one downstream.
The configuration file of the logics is read when searching the upstream (or downstream) cluster, the data conversion relation between the current and the upstream (or downstream) clusters is obtained, if the relation can be embodied in the database, the converted data can be inquired by using the database, and then the info, the warning and the error which are associated with the converted data are inquired in the upstream (or downstream) cluster; if the relation is calculated by a specific algorithm, only a method corresponding to the algorithm needs to be added to the program code of the user, and then the method is called to acquire the converted data.
A distributed system log full link trace as shown in fig. 5, the apparatus comprising:
a system configuration unit 51, configured to create a configuration file configuration system, where the configuration file includes a cluster server configuration, a cluster dependency configuration, and a data logic relationship configuration;
an information obtaining unit 52, configured to read and parse the configuration file through the application program to obtain key information;
and the cluster traversing unit 53 is used for inputting system data and acquiring the life history of the system data according to the key information.
Claims (5)
1. A distributed system log full link tracking method is characterized by comprising the following steps:
s1, creating a configuration file configuration system, and executing according to the following procedures:
configuring a cluster server; defining unique identification of each group of cluster servers; increasing or decreasing servers under each group of cluster servers;
configuring a cluster dependency relationship; the method comprises the steps of defining an upstream cluster server and a downstream cluster server; establishing a corresponding relation between an upstream cluster server and a downstream cluster server, wherein one upstream cluster server corresponds to one or more downstream cluster servers;
configuring a data logic relation; including defining a data line flag; configuring a rule that a server with data change under each data line acquires data from an upstream cluster server and/or a downstream cluster server; the rules comprise data transfer rules and data processing rules;
s2, reading and analyzing the configuration file through the application program to obtain key information; the key information comprises server information corresponding to each group of clusters, the upstream and downstream sequence of each group of cluster servers and the logical relationship among system data;
and S3, acquiring the life history of the system data according to the key information.
2. The distributed system log full link tracing method of claim 1, wherein said S3 comprises: s31, providing a system data;
s32, traversing the corresponding cluster server in the cluster server configuration file by taking the key information as a query condition;
and S33, outputting the data line where the system data is located.
3. The distributed system log full link tracing method according to claim 2, wherein said S32 is executed according to the following process:
writing a function method by taking the key data obtained in the S2 and the system data given in the S31 as function parameters, traversing all servers, and inquiring the affairs related to the system data in the S1;
inquiring upstream and downstream cluster servers according to the cluster dependency configuration file, traversing the rest cluster servers in the system by two branches, wherein one branch is searched one by one upstream, and the other branch is searched one by one downstream; when searching for an upstream or downstream cluster server, the data logical relationship configuration file needs to be read to obtain the data conversion relationship between the current and upstream or downstream cluster servers.
4. The method for full-link tracing of distributed system logs according to claim 2, wherein in S3, the traversal is skipped after traversing to the warning message or the error message.
5. A distributed system log full link tracking apparatus, comprising:
the system configuration unit is used for creating a configuration file configuration system, and the configuration file comprises cluster server configuration, cluster dependency relationship configuration and data logic relationship configuration; configuring a cluster server; defining unique identification of each group of cluster servers; increasing or decreasing servers under each group of cluster servers; configuring a cluster dependency relationship; the method comprises the steps of defining an upstream cluster server and a downstream cluster server; establishing a corresponding relation between an upstream cluster server and a downstream cluster server, wherein one upstream cluster server corresponds to one or more downstream cluster servers; configuring a data logic relation; including defining a data line flag; configuring a rule that a server with data change under each data line acquires data from an upstream cluster server and/or a downstream cluster server; the rules comprise data transfer rules and data processing rules;
the information acquisition unit is used for reading and analyzing the configuration file through the application program to acquire key information; the key information comprises server information corresponding to each group of clusters, the upstream and downstream sequence of each group of cluster servers and the logical relationship among system data;
and the cluster traversing unit is used for inputting system data and acquiring the life history of the system data according to the key information.
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| CN110636112A (en) * | 2019-08-22 | 2019-12-31 | 达疆网络科技(上海)有限公司 | ES double-cluster solution and method for realizing final data consistency |
| CN110716842B (en) * | 2019-10-09 | 2023-11-21 | 北京小米移动软件有限公司 | Cluster fault detection method and device |
| CN111158995B (en) * | 2019-11-29 | 2020-12-29 | 武汉物易云通网络科技有限公司 | Method and system for realizing cross-system log tracking query based on skywalk and ELK platform |
| CN111638973A (en) * | 2020-05-11 | 2020-09-08 | 紫光云技术有限公司 | Method for tracing execution sequence of calculation by link |
| CN112486786B (en) * | 2020-11-12 | 2022-08-09 | 贝壳技术有限公司 | Calling link tracking method and device |
| CN112363855B (en) * | 2020-11-13 | 2021-06-18 | 北京基调网络股份有限公司 | Call chain data generation method, topology generation method and system and computer equipment |
| CN112737856B (en) * | 2020-12-31 | 2023-02-03 | 青岛海尔科技有限公司 | Link tracking method and device, storage medium and electronic device |
| CN112835988A (en) * | 2021-03-31 | 2021-05-25 | 中国工商银行股份有限公司 | Integrated switching method and switching device for application programs and databases |
| CN114691707B (en) * | 2022-05-27 | 2022-10-28 | 云账户技术(天津)有限公司 | Online cluster service configuration method, system, network equipment and storage medium |
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