CN115687406A - Sampling method, device and equipment of call chain data and storage medium - Google Patents
Sampling method, device and equipment of call chain data and storage medium Download PDFInfo
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Abstract
The invention discloses a sampling method, a device, equipment and a storage medium of call chain data, wherein the sampling method comprises the following steps: acquiring link data corresponding to all call chains in a service system and initial span information included in the link data; determining target abnormal span information in the link data according to the abnormal field characteristics recorded in the initial span information; according to the target abnormal span information, determining associated span information corresponding to the target abnormal span information in the link data, and aggregating abnormal features corresponding to the target abnormal span information into the associated span information; and sampling to obtain abnormal call chain data according to the characteristics corresponding to all span information in the link data. The technical scheme of the embodiment of the invention can improve the sampling efficiency of the abnormal call chain data and ensure the accuracy of the sampling result.
Description
Technical Field
The embodiment of the invention relates to the technical field of computers, in particular to a sampling method, a sampling device, sampling equipment and a storage medium of call chain data.
Background
The call chain refers to a process of completing a service call by a system, dotting call information (time, interface, hierarchy, result and the like) among services into a log, and then connecting all dotting data into a tree chain, namely generating a call chain.
In order to analyze the service data, it is generally required to sample call chain data, and complete an analysis process of the service data according to a call chain sampling result. The current call chain sampling strategy is roughly divided into sampling based on link characteristics, sampling based on service characteristics, sampling based on operation and maintenance characteristics, sampling based on time characteristics and the like.
However, for practical application analysis and monitoring, the abnormal data is information that needs to be focused, the abnormal service data cannot be accurately filtered out by the existing call chain sampling method, and a corresponding sampling mode needs to be manually selected and a sampling rule needs to be set, so that the sampling process is time-consuming and low in efficiency.
Disclosure of Invention
The embodiment of the invention provides a method, a device, equipment and a storage medium for sampling call chain data, which can improve the sampling efficiency of abnormal call chain data and ensure the accuracy of a sampling result.
In a first aspect, an embodiment of the present invention provides a method for sampling call chain data, where the method includes:
acquiring link data corresponding to all call chains in a service system and initial span information included in the link data;
determining target abnormal span information in the link data according to the abnormal field characteristics recorded in the initial span information;
determining associated span information corresponding to the target abnormal span information in the link data according to the target abnormal span information, and aggregating abnormal features corresponding to the target abnormal span information into the associated span information;
and sampling to obtain abnormal call chain data according to the characteristics corresponding to all span information in the link data.
Optionally, the obtaining of link data corresponding to all call chains in the service system includes:
acquiring a processing operator matched with each storage position according to the storage position corresponding to each calling chain in the service system;
and acquiring link data corresponding to the call chain from the corresponding storage position through each processing operator.
Optionally, determining target abnormal span information in the link data according to the abnormal field feature recorded in the initial span information, including:
extracting a failed link from the link data according to a link execution result field recorded in the initial span information;
and determining target abnormal span information in the link data according to the characteristics corresponding to the failed link.
Optionally, determining target abnormal span information in the link data according to the corresponding characteristic of the failed link, including:
and determining target abnormal span information in the link data according to the abnormal field and the tracking identifier corresponding to the failed link.
Optionally, determining, according to the target abnormal span information, associated span information corresponding to the target abnormal span information in the link data, including:
and determining the associated span information corresponding to the target abnormal span information according to the tracking identification corresponding to the target abnormal span information and the tracking identification corresponding to each remaining span information in the link data.
Optionally, aggregating the abnormal features corresponding to the target abnormal span information into associated span information includes:
and adding the abnormal field corresponding to the target abnormal span information into the characteristics of the associated span information.
Optionally, after obtaining link data corresponding to all call chains in the service system, the method further includes:
analyzing the link data through a preset analysis operator, and storing the analysis result according to a preset format;
acquiring initial span information included in the link data, wherein the initial span information includes:
and acquiring initial span information included in the link data according to the analysis result corresponding to the link data.
In a second aspect, an embodiment of the present invention further provides a device for sampling call chain data, where the device includes:
the system comprises a total data acquisition module, a data processing module and a data processing module, wherein the total data acquisition module is used for acquiring link data corresponding to all call chains in a service system and initial span information included in the link data;
the target span determining module is used for determining target abnormal span information in the link data according to the abnormal field characteristics recorded in the initial span information;
the characteristic aggregation module is used for determining associated span information corresponding to the target abnormal span information in the link data according to the target abnormal span information and aggregating the abnormal characteristics corresponding to the target abnormal span information into the associated span information;
and the data sampling module is used for sampling to obtain abnormal call chain data according to the characteristics corresponding to all span information in the link data.
In a third aspect, an embodiment of the present invention further provides an electronic device, where the electronic device includes:
one or more processors;
storage means for storing one or more programs;
the sampling method of call chain data provided by any embodiment of the present invention is implemented when the one or more programs are executed by the one or more processors, such that the one or more processors execute the programs.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the computer program implements the method for sampling call chain data provided in any embodiment of the present invention.
In a fifth aspect, an embodiment of the present invention further provides a computer program product, where the computer program product includes a computer program, and when the computer program is executed by a processor, the computer program implements the method for sampling call chain data provided in any embodiment of the present invention.
According to the technical scheme of the embodiment of the invention, link data corresponding to all call chains in a service system and initial span information included in the link data are obtained, target abnormal span information is determined in the link data according to abnormal field characteristics recorded in the initial span information, associated span information corresponding to the target abnormal span information is determined in the link data according to the target abnormal span information, abnormal characteristics corresponding to the target abnormal span information are aggregated into the associated span information, and abnormal call chain data are obtained by sampling according to characteristics corresponding to all the span information in the link data.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present invention, nor do they necessarily limit the scope of the invention. Other features of the present invention will become apparent from the following description.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a method for sampling call chain data according to an embodiment of the present invention;
fig. 2 is a flowchart of a method for sampling call chain data according to a second embodiment of the present invention;
fig. 3 is a flowchart of a method for sampling call chain data according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of a sampling apparatus for call chain data according to a fourth embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device implementing the sampling method of call chain data according to the embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not to be construed as limiting the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a flowchart of a method for sampling call chain data according to an embodiment of the present invention, where this embodiment is applicable to sampling call chain data related to an abnormal service, and the method may be executed by a device for sampling call chain data. The sampling device of the call chain data can be implemented by software and/or hardware, and can be generally integrated in an electronic device with a data processing function, and specifically includes the following steps:
In this embodiment, the call chain refers to a tree chain obtained by dotting call information (time, interface, hierarchy, and result) between services into a log and then connecting all the dotting data in the process that a service system completes one service call. Specifically, when sampling call chain data of the service system, link data corresponding to all call chains may be obtained from a preset storage location corresponding to the service system.
In this step, after the full-amount link data is acquired, initial span (i.e., rootspan) information in the full-amount link data may be extracted. The initial span information, as a top event in the link data, may include data characteristics concerned by various operation and maintenance personnel, such as a service type, a data source, a service execution consumption, and a service execution result (e.g., an execution success or failure) corresponding to the link data.
And 120, determining target abnormal span information in the link data according to the abnormal field characteristics recorded in the initial span information.
In this embodiment, optionally, after the initial span information is obtained, according to a service execution result described in the initial span information, an abnormal service that is failed to be executed is searched, an abnormal field characteristic is determined according to the abnormal service, and then the span information with the abnormal field characteristic is used as the target abnormal span information.
And step 130, determining associated span information corresponding to the target abnormal span information in the link data according to the target abnormal span information, and aggregating abnormal features corresponding to the target abnormal span information into the associated span information.
In this embodiment, the associated span information corresponding to the target abnormal span information may be determined according to the associated relationship between the target abnormal span information and other span information. Optionally, the span information in the same link as the target abnormal span information may be used as the associated span information corresponding to the target abnormal span information, and the determination manner of the associated span information is not limited in this embodiment.
In this step, after the relevant span information is obtained, an abnormal feature (for example, the abnormal field feature described above) corresponding to the target abnormal span information may be added to the relevant span information to implement the feature aggregation process.
And 140, sampling to obtain abnormal call chain data according to the characteristics corresponding to all span information in the link data.
In this step, the features corresponding to all span information in the link data can be obtained, and since the associated span information already has the abnormal features, all span information can be filtered by using the abnormal features, and call chain data (i.e., abnormal call chain data) corresponding to the abnormal service is obtained.
In the embodiment, the abnormal features corresponding to the target abnormal span information are aggregated into the associated span information, so that the abnormal call chain data can be accurately filtered, and the corresponding sampling mode and the sampling rule do not need to be manually selected, so that the sampling time consumption of the abnormal call chain data can be reduced, and the sampling efficiency is improved.
According to the technical scheme of the embodiment of the invention, by acquiring the link data corresponding to all call chains in the service system and the initial span information included in the link data, determining the target abnormal span information in the link data according to the abnormal field characteristics recorded in the initial span information, determining the associated span information corresponding to the target abnormal span information in the link data according to the target abnormal span information, aggregating the abnormal characteristics corresponding to the target abnormal span information into the associated span information, and sampling the abnormal call chain data according to the characteristics corresponding to all the span information in the link data, the sampling efficiency of the abnormal call chain data can be improved, and the accuracy of the sampling result can be ensured.
Example two
This embodiment is a further refinement of the above embodiment, and the same or corresponding terms as those of the above embodiment are explained, and this embodiment is not described again. Fig. 2 is a flowchart of a sampling method for call chain data provided in the second embodiment, in this embodiment, the technical solution of this embodiment may be combined with one or more methods in the solutions of the foregoing embodiments, as shown in fig. 2, the method provided in this embodiment may further include:
and step 210, acquiring a processing operator matched with each storage position according to the storage position corresponding to each call chain in the service system.
In this embodiment, the call chain data corresponding to the service system may be stored in different locations according to different storage manners. Before acquiring the link data, processing operators matched with the storage positions, such as kafka source, httplientsource, fileSource and the like, may be acquired in advance.
And step 220, acquiring link data corresponding to the call chain from the corresponding storage position through each processing operator.
In this step, the processing operators may be used to extract link data corresponding to each call chain in the service system from the matched storage location according to a preset processing manner.
The advantage of this setting is that the time consumption of extracting the link data can be saved, and the data sampling efficiency can be improved.
And step 230, acquiring initial span information included in the link data.
And 240, extracting the failed link from the link data according to the link execution result field recorded in the initial span information.
In this embodiment, a preset field may be used in the initial span information to represent the execution result of the link, where the field is a link execution result field. After the link execution result field is obtained, a link (i.e., a failed link) whose execution result is a failure may be extracted according to the field value.
In a specific embodiment, it is assumed that a link execution result field stated in the initial span information is success, and when the field value is true, it may indicate that the link execution is successful, and when the field value is false, it indicates that the link execution is failed. Therefore, a link with a field success value of false may be considered as a failed link.
And step 250, determining target abnormal span information in the link data according to the characteristics corresponding to the failed link.
In this step, optionally, the feature corresponding to the failed link may be used as a target feature, and then the span information having the target feature may be used as target abnormal span information.
In an implementation manner of this embodiment, determining target abnormal span information in the link data according to a feature corresponding to the failed link includes: and determining target abnormal span information in the link data according to the abnormal field and the tracking identification corresponding to the failed link.
In this embodiment, the exception field corresponding to the failed link may be used to indicate an execution result corresponding to the link. Specifically, the exception field corresponding to the failed link may be set to "busineresult: false ", the Trace identifier (TraceId) may be a Trace identifier corresponding to the failed link.
In practical applications, each call chain may generate a Trace, which may be understood as a tree structure composed of a set of other spans sharing a rootspan. Optionally, the Trace may be identified by a 64-bit ID, and all spans in the Trace share the ID of the Trace.
In this step, optionally, a Filter operator may be used, and according to the exception field "busineresult" of the failed link: false "and TraceId, filtering to obtain target abnormal span information.
And step 260, according to the target abnormal span information, determining associated span information corresponding to the target abnormal span information in the link data, and aggregating abnormal features corresponding to the target abnormal span information into the associated span information.
And 270, sampling to obtain abnormal call chain data according to the characteristics corresponding to all span information in the link data.
According to the technical scheme, the processing operators matched with the storage positions are obtained according to the storage positions corresponding to the call chains in the service system, the link data corresponding to the call chains are obtained from the corresponding storage positions through the processing operators, the initial span information included in the link data is obtained, the failed links are extracted from the link data according to the link execution result fields recorded in the initial span information, the target abnormal span information is determined in the link data according to the characteristics corresponding to the failed links, the associated span information is determined in the link data according to the target abnormal span information, the abnormal characteristics corresponding to the target abnormal span information are aggregated into the associated span information, and the abnormal call chain data are obtained through sampling according to the characteristics corresponding to all the span information in the link data.
EXAMPLE III
This embodiment is a further refinement of the above embodiment, and the same or corresponding terms as those of the above embodiment are explained, and this embodiment is not described again. Fig. 3 is a flowchart of a sampling method for call chain data provided in a third embodiment, in this embodiment, the technical solution of this embodiment may be combined with one or more methods in the solutions of the foregoing embodiments, as shown in fig. 3, the method provided in this embodiment may further include:
and 310, acquiring link data corresponding to all call chains in the service system.
And 320, analyzing the link data through a preset analysis operator, and storing the analysis result according to a preset format.
In this embodiment, optionally, the data of each link may be analyzed by using a Json parser operator to obtain an analysis result in a Json format, and the analysis result is stored. Specifically, deserialization processing may be performed on data of the Json character String in the link data by using the open source library Jackson to obtain a Map < String, object > Object, and then the Object is converted into a preset data structure.
The advantage of setting up like this is through resolving link data, is convenient for carry out the sampling of unusual call chain data according to the analysis result, can guarantee the accuracy of sampling result from this.
And step 330, acquiring initial span information included in the link data according to the analysis result corresponding to the link data.
And step 340, extracting the failed link from the link data according to the link execution result field recorded in the initial span information.
And step 350, determining target abnormal span information in the link data according to the abnormal field and the tracking identification corresponding to the failed link.
And step 360, determining associated span information corresponding to the target abnormal span information according to the tracking identification corresponding to the target abnormal span information and the tracking identification corresponding to each remaining span information in the link data.
And 370, adding the abnormal field corresponding to the target abnormal span information into the characteristics of the associated span information.
In this step, the exception field "busineresult" corresponding to the target exception span information may be: false ", added to the feature of the associated span information.
In a specific embodiment, when feature aggregation is performed, the key state (KeyedState) of the span information can be maintained through the feature aggregation operator module at the same time, including the generation state (BuildState) corresponding to the target abnormal span information and the probe state (ProbeState) corresponding to the associated span information. Among them, probe records (Probe Record) corresponding to the associated span information are stored in the ProbeState.
And after the characteristic aggregation operator module detects that a new generation Record (Build Record) is stored in the Build State, judging whether data is stored in the Probe Record, and if not, adding an abnormal field in the Build Record to the Probe Record. Otherwise, if the fact that the Probe State stores the new Probe Record is detected, whether the Build Record has data or not is judged, and if the Build Record has data, the Build State is cleared.
The method has the advantages that the characteristics of the target abnormal span information and the characteristics corresponding to the associated span information are detected in real time, and the characteristics of the target abnormal span information are aggregated into the associated span information in time, so that omission of characteristic aggregation results can be avoided, and the accuracy of data sampling results of the abnormal call chain is guaranteed.
In a specific embodiment, the feature aggregation operator module may use a preset timer to detect the feature corresponding to the abnormal span information and the associated span information.
And 380, sampling to obtain abnormal call chain data according to the characteristics corresponding to all span information in the link data.
In this embodiment, after the abnormal call chain data is obtained through sampling, the data may be stored in a preset storage location (e.g., the weaver) by using the weavesink operator, so as to perform the next processing and analysis on the abnormal call chain data.
According to the technical scheme, link data corresponding to all call chains in a service system are obtained, each link data is analyzed through a preset analysis operator, an analysis result is stored according to a preset format, initial span information included in the link data is obtained according to the analysis result corresponding to the link data, a failed link is extracted from the link data according to a link execution result field recorded in the initial span information, target abnormal span information is determined in the link data according to an abnormal field corresponding to the failed link and a tracking identifier, associated span information corresponding to the target abnormal span information is determined according to the tracking identifier corresponding to the target abnormal span information and the tracking identifier corresponding to each remaining span information in the link data, the abnormal field corresponding to the target abnormal span information is added into the characteristics of the associated span information, and the abnormal call chain data is obtained through sampling according to the characteristics corresponding to all the span information in the link data.
Example four
Fig. 4 is a schematic structural diagram of a sampling apparatus for call chain data according to a fourth embodiment of the present invention, as shown in fig. 4, the apparatus includes: a full data acquisition module 410, a target span determination module 420, a feature aggregation module 430, and a data sampling module 440.
The full data acquiring module 410 is configured to acquire link data corresponding to all call chains in a service system and initial span information included in the link data;
a target span determining module 420, configured to determine target abnormal span information in the link data according to the abnormal field feature described in the initial span information;
a feature aggregation module 430, configured to determine, according to the target abnormal span information, associated span information corresponding to the target abnormal span information in the link data, and aggregate abnormal features corresponding to the target abnormal span information into the associated span information;
and the data sampling module 440 is configured to sample to obtain abnormal call chain data according to features corresponding to all span information in the link data.
According to the technical scheme provided by the embodiment of the invention, by acquiring the link data corresponding to all call chains in the service system and the initial span information included in the link data, determining the target abnormal span information in the link data according to the abnormal field characteristics recorded in the initial span information, determining the associated span information corresponding to the target abnormal span information in the link data according to the target abnormal span information, aggregating the abnormal characteristics corresponding to the target abnormal span information into the associated span information, and sampling to obtain the abnormal call chain data according to the characteristics corresponding to all the span information in the link data, the sampling efficiency of the abnormal call chain data can be improved, and the accuracy of the sampling result is ensured.
On the basis of the above embodiment, the full data obtaining module 410 includes:
the operator acquisition unit is used for acquiring processing operators matched with the storage positions according to the storage positions corresponding to the calling chains in the service system;
the data acquisition unit is used for acquiring link data corresponding to the call chain from the corresponding storage position through each processing operator;
the analysis unit is used for analyzing the link data through a preset analysis operator and storing an analysis result according to a preset format;
and the initial span acquisition unit is used for acquiring initial span information included in the link data according to the analysis result corresponding to the link data.
The target span determination module 420 comprises:
a failed link extraction unit, configured to extract a failed link from the link data according to a link execution result field recorded in the initial span information;
the failed link processing unit is used for determining target abnormal span information in the link data according to the characteristics corresponding to the failed link;
and the characteristic processing unit is used for determining target abnormal span information in the link data according to the abnormal field corresponding to the failed link and the tracking identifier.
The feature aggregation module 430 includes:
the tracking identifier processing unit is used for determining associated span information corresponding to the target abnormal span information according to the tracking identifier corresponding to the target abnormal span information and the tracking identifiers corresponding to the remaining span information in the link data;
and the abnormal field adding unit is used for adding the abnormal field corresponding to the target abnormal span information into the characteristics of the associated span information.
The device can execute the methods provided by all the embodiments of the invention, and has corresponding functional modules and beneficial effects for executing the methods. For technical details which are not described in detail in the embodiments of the present invention, reference may be made to the methods provided in all the aforementioned embodiments of the present invention.
EXAMPLE five
FIG. 5 illustrates a schematic diagram of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 5, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, and the like, wherein the memory stores a computer program executable by the at least one processor, and the processor 11 can perform various suitable actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from a storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data necessary for the operation of the electronic apparatus 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.
A number of components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, or the like; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The processor 11 performs the various methods and processes described above, such as invoking sampling methods of chain data.
In some embodiments, the sampling method of call chain data may be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the sampling method of call chain data described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured by any other suitable means (e.g., by means of firmware) to perform the sampling method of the call chain data.
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Computer programs for implementing the methods of the present invention can be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be performed. A computer program can execute entirely on a machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service are overcome.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present invention may be executed in parallel, sequentially, or in different orders, and are not limited herein as long as the desired result of the technical solution of the present invention can be achieved.
The above-described embodiments should not be construed as limiting the scope of the invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method for sampling call chain data, the method comprising:
acquiring link data corresponding to all call chains in a service system and initial span information included in the link data;
determining target abnormal span information in the link data according to the abnormal field characteristics recorded in the initial span information;
determining associated span information corresponding to the target abnormal span information in the link data according to the target abnormal span information, and aggregating abnormal features corresponding to the target abnormal span information into the associated span information;
and sampling to obtain abnormal call chain data according to the characteristics corresponding to all span information in the link data.
2. The method of claim 1, wherein obtaining link data corresponding to all call chains in a service system comprises:
acquiring a processing operator matched with each storage position according to the storage position corresponding to each calling chain in the service system;
and acquiring link data corresponding to the call chain from the corresponding storage position through each processing operator.
3. The method of claim 1, wherein determining target abnormal span information in the link data according to the abnormal field characteristics recorded in the initial span information comprises:
extracting a failed link from the link data according to a link execution result field recorded in the initial span information;
and determining target abnormal span information in the link data according to the characteristics corresponding to the failed link.
4. The method according to claim 3, wherein determining target abnormal span information in the link data according to the characteristics corresponding to the failed link comprises:
and determining target abnormal span information in the link data according to the abnormal field and the tracking identification corresponding to the failed link.
5. The method according to claim 4, wherein determining associated span information corresponding to the target abnormal span information in the link data according to the target abnormal span information comprises:
and determining associated span information corresponding to the target abnormal span information according to the tracking identification corresponding to the target abnormal span information and the tracking identification corresponding to each remaining span information in the link data.
6. The method according to claim 4, wherein aggregating the abnormal features corresponding to the target abnormal span information into associated span information comprises:
and adding the abnormal field corresponding to the target abnormal span information into the characteristics of the associated span information.
7. The method according to claim 6, further comprising, after obtaining link data corresponding to all call chains in the service system:
analyzing the link data through a preset analysis operator, and storing the analysis result according to a preset format;
acquiring initial span information included in the link data, wherein the acquisition comprises the following steps:
and acquiring initial span information included in the link data according to the analysis result corresponding to the link data.
8. An apparatus for sampling call chain data, the apparatus comprising:
the system comprises a total data acquisition module, a service system and a processing module, wherein the total data acquisition module is used for acquiring link data corresponding to all call chains in a service system and initial span information included in the link data;
the target span determining module is used for determining target abnormal span information in the link data according to the abnormal field characteristics recorded in the initial span information;
the characteristic aggregation module is used for determining associated span information corresponding to the target abnormal span information in the link data according to the target abnormal span information and aggregating the abnormal characteristics corresponding to the target abnormal span information into the associated span information;
and the data sampling module is used for sampling to obtain abnormal call chain data according to the characteristics corresponding to all span information in the link data.
9. An electronic device, the electronic device comprising:
one or more processors;
storage means for storing one or more programs;
the one or more programs when executed by the one or more processors cause the one or more processors to implement the method of sampling call chain data as recited in any of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out a method for sampling call chain data according to any one of claims 1 to 7.
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