CN115174366A - Data processing method and device - Google Patents
Data processing method and device Download PDFInfo
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- CN115174366A CN115174366A CN202210602611.8A CN202210602611A CN115174366A CN 115174366 A CN115174366 A CN 115174366A CN 202210602611 A CN202210602611 A CN 202210602611A CN 115174366 A CN115174366 A CN 115174366A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/0677—Localisation of faults
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/069—Management of faults, events, alarms or notifications using logs of notifications; Post-processing of notifications
Abstract
The embodiment of the specification provides a data processing method and a device, wherein the data processing method is applied to a client, the client comprises at least two distributed application nodes, a log acquisition module and a data processing module, and the method comprises the following steps: determining at least two distributed application nodes related to a target project, calling the target distributed application nodes to execute data processing logics corresponding to the target distributed application nodes, and calling a log acquisition module to acquire data processing logs generated by executing the data processing logics, wherein the target distributed application nodes are any one of the at least two distributed application nodes, calling the data processing module to analyze the data processing logs, and determining a data processing link formed by the at least two distributed application nodes and processing flow information corresponding to the data processing link according to an analysis result.
Description
Technical Field
The embodiment of the specification relates to the technical field of computers, in particular to a data processing method.
Background
With the increasing expansion of the service types and service scales of the sales operation service providers, the architecture of the service system is more and more complex, and for the service system with the distributed architecture, the operation service of the user is cooperatively completed through the mutual call among a plurality of service nodes of each service system.
However, at present, in the operation process of the whole service system, each node for cooperatively processing the operation service may be in a different service system, that is, may be deployed on a different server, so when providing the operation service to the user, only the final operation result data is often provided to the user. When the service system is abnormal, for the reason of the abnormality, the user still needs to analyze data corresponding to the operation service in each node in the entire service system to determine whether each node has a problem, so as to determine the reason of the abnormality of the service system.
Disclosure of Invention
In view of this, the embodiments of the present specification provide a data processing method. One or more embodiments of the present specification also relate to a data processing apparatus, a computing device, a computer-readable storage medium, and a computer program, so as to solve the technical deficiencies of the prior art.
According to a first aspect of embodiments of the present specification, there is provided a data processing method applied to a client, where the client includes at least two distributed application nodes, a log collection module, and a data processing module, and the method includes:
determining at least two distributed application nodes related to the target project;
calling a target distributed application node to execute data processing logic corresponding to the target distributed application node, and calling a log acquisition module to acquire and execute a data processing log generated by the data processing logic, wherein the target distributed application node is any one of the at least two distributed application nodes;
and calling the data processing module to analyze the data processing log, and determining a data processing link formed by the at least two distributed application nodes and processing flow information corresponding to the data processing link according to an analysis result.
According to a second aspect of the embodiments of the present specification, there is provided a data processing apparatus applied to a client, where the client includes at least two distributed application nodes, a log collection module, and a data processing module, and the apparatus includes:
a determination module configured to determine at least two distributed application nodes related to a target project;
the system comprises a calling module and a log acquisition module, wherein the calling module is configured to call a target distributed application node to execute data processing logic corresponding to the target distributed application node, and call the log acquisition module to acquire and execute a data processing log generated by the data processing logic, and the target distributed application node is any one of the at least two distributed application nodes;
and the analysis module is configured to call the data processing module to analyze the data processing log, and determine a data processing link formed by the at least two distributed application nodes and processing flow information corresponding to the data processing link according to an analysis result.
According to a third aspect of embodiments herein, there is provided a computing device comprising:
a memory and a processor;
the memory is configured to store computer-executable instructions, and the processor is configured to execute the computer-executable instructions to implement the steps of any of the data processing methods.
According to a fourth aspect of embodiments herein, there is provided a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of any one of the data processing methods.
According to a fifth aspect of embodiments herein, there is provided a computer program, wherein the computer program, when executed in a computer, causes the computer to perform the steps of the above-mentioned data processing method.
In an embodiment of the present description, at least two distributed application nodes related to a target project are determined, a target distributed application node is called to execute a data processing logic corresponding to the target distributed application node, and a log collection module is called to collect a data processing log generated by executing the data processing logic, where the target distributed application node is any one of the at least two distributed application nodes, the data processing log is called to be analyzed by the data processing module, and a data processing link formed by the at least two distributed application nodes and processing flow information corresponding to the data processing link are determined according to an analysis result.
In the embodiment of the specification, after the data processing log generated by the execution data processing logic is acquired by the call log acquisition module, the data processing log can be analyzed by the call data processing module, so that the context tracing of the data processing link of the target project is performed according to the analysis result, and the processing flow information of the data processing link is determined, so that the data processing process of the target project has interpretability; in addition, in the process of executing the data processing logic, the data processing link and the processing flow information of the target item are determined by analyzing the acquired data processing log, so that a user can quickly locate an abnormality reason according to the data processing link and the processing flow information under the condition that the data processing process of the target item is abnormal, thereby being beneficial to reducing the difficulty in locating the abnormality and improving the efficiency of processing the abnormality.
Drawings
FIG. 1 is a flow chart of a data processing method provided by an embodiment of the present description;
FIG. 2a is a schematic diagram of a data processing process provided in one embodiment of the present description;
FIG. 2b is a schematic diagram of another data processing process provided in one embodiment of the present description;
FIG. 2c is a schematic diagram of a data processing link provided in one embodiment of the present description;
FIG. 2d is a schematic diagram of a tree diagram provided in an embodiment of the present disclosure;
FIG. 2e is a schematic diagram of a directed graph provided by an embodiment of the present description;
FIG. 3 is a flowchart illustrating a data processing method according to an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present specification;
fig. 5 is a block diagram of a computing device according to an embodiment of the present disclosure.
Detailed Description
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present specification. This description may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, as those skilled in the art will be able to make and use the present disclosure without departing from the spirit and scope of the present disclosure.
The terminology used in the description of the one or more embodiments is for the purpose of describing the particular embodiments only and is not intended to be limiting of the description of the one or more embodiments. As used in one or more embodiments of the present specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used in one or more embodiments of the present specification refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It will be understood that, although the terms first, second, etc. may be used herein in one or more embodiments to describe various information, these information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, a first can also be referred to as a second and, similarly, a second can also be referred to as a first without departing from the scope of one or more embodiments of the present description. The word "if" as used herein may be interpreted as "at" \8230; "or" when 8230; \8230; "or" in response to a determination ", depending on the context.
In the present specification, a data processing method is provided, and the present specification relates to a data processing apparatus, a computing device, a computer-readable storage medium, and a computer program, which are described in detail one by one in the following embodiments.
Fig. 1 shows a flowchart of a data processing method provided in accordance with an embodiment of the present specification, which specifically includes the following steps.
At step 102, at least two distributed application nodes related to the target project are determined.
Specifically, the data processing method provided in the embodiments of the present specification is applied to a client, where the client includes at least two distributed application nodes, a log collection module, and a data processing module.
The distributed application nodes are used for carrying out data processing on the target project; the log acquisition module is used for acquiring logs generated in the data processing process of the distributed application nodes; the data processing module is used for analyzing the logs collected by the log collection module to determine the data processing flow of the target project; and target items, i.e., including but not limited to operational items, sales items, etc.
With the rapid expansion of internet technology, software architecture becomes increasingly complex, and in order to adapt to high-concurrency requests of a large number of users, more and more components (application nodes) in a system start to be distributed, and the application nodes jointly form a complicated distributed network.
For example, the distributed network may include an order service node, a user service node, an inventory service node, an evaluation service node, and the like, different service nodes may be regarded as one distributed application node, and different distributed application nodes may provide different services, that is, the order service node may provide an order service, the evaluation service node may provide an evaluation service, and the like.
When data processing is performed on different target projects, different distributed application nodes may need to be called, for example, if a target project is an operation project, data indexes of commodity dimensions in the next N days need to be predicted according to a sales plan, good product inventory, reservation purchase amount and the like of upstream commodities, an operator can determine whether current capacity supports activities by referring to the indexes, and if the capacity is insufficient, scheduling or plan changing can be performed in time.
Therefore, when the operation project is processed, it may be necessary to call a replenishment inlet calculation node, an order service node, an in-transit inventory calculation node, and the like to determine whether replenishment is required in the target time period, or in the case of replenishment, the amount of replenishment.
Based on the method, after the target project is determined, at least two distributed application nodes related to the target project can be determined, and the target project is processed in a mode of calling different distributed application nodes.
And 104, calling a target distributed application node to execute a data processing logic corresponding to the target distributed application node, and calling a log acquisition module to acquire a data processing log generated by executing the data processing logic, wherein the target distributed application node is any one of the at least two distributed application nodes.
Specifically, as described above, different distributed application nodes may provide different services, that is, different distributed application nodes may provide different data processing manners (data processing logics) for the target project, and after at least two distributed application nodes related to the target project are determined, each distributed application node (target distributed application node) may be respectively invoked to execute its corresponding data processing logic through the target distributed application node, and then, the log collection module may be invoked to collect a data processing log generated by executing the data processing logic.
Taking the distributed application node as an order service node as an example, the corresponding data processing logic may be order quantity calculation logic, that is, order quantity in a preset time period and commodity quantity corresponding to different orders are determined, so as to determine total quantity of commodities sold in the preset time period, or total commodity quantity in the next time period may be predicted according to the determined total quantity of the commodities. Or, taking the distributed application node as an inventory serving node as an example, the corresponding data processing logic may be an inventory calculation logic, and may specifically determine the inventory reduction amount in a preset time period, or may predict the inventory reduction amount in the next time period according to the determined inventory reduction amount.
In specific implementation, the data processing log comprises a link log, and the client further comprises a link detection module;
correspondingly, before a target distributed application node is called to execute a corresponding data processing logic, the link detection module can be called to execute a first embedded point logic, and a link identifier of a data processing link and an initial calling identifier corresponding to the target project are distributed to the target project;
and adding the link identification and the initial calling identification to the calling context of the target item.
Specifically, the data processing link is specifically a path formed by distributed application nodes called for performing data processing on the target item.
The path detection module may be a tracking module, and may also be referred to as a distributed tracking system.
The link log may be used to trace back the context of the data processing link.
Since the client may initiate multiple node calls in parallel at the same time, in order to identify a data processing link to which a certain node call belongs, before processing a target item, a link detection module may be called to execute its embedded point logic (a first embedded point logic, similar to a Filter mechanism) to assign a globally unique link identifier, i.e., traceId, to the target item, and then the TraceId is added to a call context object, which is stored in thread local variable. In addition, an initial call identifier, namely RPC Id, can be allocated to the target project, the RPC Id is used for distinguishing the call sequence and the nesting hierarchical relationship among a plurality of distributed application nodes in the same data processing link, and the initial call identifier can also be added to the call context of the target project. In practical applications, when the target item is not processed, the initial call identifier may be 0.
Based on this, invoking the target distributed application node to execute the data processing logic corresponding to the target distributed application node, including:
acquiring the calling context;
and calling a target distributed application node to execute data processing logic corresponding to the target distributed application node, and updating the initial calling identifier contained in the calling context based on the calling information of the target distributed application node.
Specifically, in the process of executing data processing of a target project by a client, when an RPC call needs to be initiated, a call context of a target application may be obtained from a Thread Local variable Thread Local, and when any one of at least two distributed application nodes (target distributed application node) is called to execute a corresponding data processing logic thereof, an initial call identifier in the call context may be incremented by one sequence number.
Since a multi-level sequence number can be used in the link detection module to represent the RPC Id, for example, if the initial call identification RPC Id set for the target item before it is not processed is 0, the call identification RPC Id of the target distributed application node a is updated to 0.1 when the target distributed application node a is called for the first time.
If the target distributed application node A needs to call the target distributed application node B when processing the target project, the call identifier corresponding to the target distributed application node B can be changed to 0.1.1 to represent the call sequence between the target distributed application node A and the target distributed application node B, and the link identifier of the call link between the target distributed application node A and the target distributed application node B is consistent with the link identifier of the target project to represent the data processing link of the target distributed application node A and the target distributed application node B belonging to the target project.
In addition, after the target distributed application node is called to execute the data processing logic corresponding to the target distributed application node, the method further includes:
and generating the link log according to the calling information of the target distributed application node, the link identification contained in the calling context and the updating result of the initial calling information, and deleting the updating result.
Specifically, each distributed application node in the at least two distributed application nodes is called to execute the corresponding data processing logic, and after the execution is completed, the calling condition of each distributed application node, the calling identifier corresponding to each distributed application node, and the link identifier can be printed in the corresponding access log, that is, the link log is generated, and meanwhile, the calling context of the target application can be cleared from the thread local variable ThreadLocal.
In the embodiment of the specification, the first embedded point logic is executed to embed points, so that the link logs are collected based on the embedded point result, and the full link tracking of the data processing process of the target item based on the analysis result of the link logs is realized.
Or, in specific implementation, the data processing log includes an index log, and the client further includes an application detection module;
correspondingly, before the target distributed application node is called to execute the data processing logic corresponding to the target distributed application node, the method further includes:
calling the application detection module to execute a second embedded point logic, and acquiring a data processing logic corresponding to the target distributed application node;
and analyzing the index calculation information contained in the data processing logic, and performing point burying operation on at least two indexes to be calculated according to the analysis result.
Specifically, a detection module, i.e., a measurement index detection module, is used to collect key indexes used in the data processing logic execution process in a point-burying manner.
The index log is used for determining index data of key indexes used in the data processing logic process executed by each distributed application node.
In practical application, the application detection module can realize link index collection based on an SDK (software development kit) embedded point, and a data processing link of a target project may include two or more distributed application nodes, each distributed application node corresponds to different data processing logics, so that the SDK can be started before the SDK embedded point is carried out, each distributed application node is scanned through an interceptor, and annotation is added in each distributed application node, namely index calculation information is added, and the index calculation information is used for representing calculation methods among different indexes to be calculated, such as addition, subtraction, multiplication, division and the like; static proxies can then be generated for the index computation information through the SDK.
In the process of embedding the SDK, the corresponding embedded point logic (second embedded point logic) can be executed by calling the application detection module to acquire the data processing logic corresponding to each distributed application node, index calculation information contained in each data processing logic is analyzed to acquire a calculation method among indexes to be calculated, and then code enhancement logic can be executed, namely, the embedded point operation is carried out on each index to be calculated in a static agent compiling mode.
In the embodiment of the specification, the interpretability of the data processing process is enhanced by acquiring the index logs and determining the processing flow information of the target item in a manner of analyzing the index logs, so that at least two indexes to be calculated can be determined in a manner of analyzing the index calculation information contained in the data processing logic corresponding to the target distributed application node in the process of embedding the points, and the point embedding operation is performed on the indexes to be calculated, so that the embedded data of the indexes to be calculated can be obtained based on the embedded point information in the process of executing the data processing logic.
Based on this, after the target distributed application node is called to execute the data processing logic corresponding to the target distributed application node, the index log can be generated according to the buried data of the at least two indexes to be calculated, which is collected in the process of executing the data processing logic.
Specifically, each distributed application node in the at least two distributed application nodes is called to respectively execute the corresponding data processing logic, and after the execution is completed, the embedded data of each index to be calculated, which is collected in the process of executing the data processing logic, can be printed in the corresponding access log, so as to generate the index log.
In the embodiment of the specification, the second point burying logic is executed to bury the points, so that the index logs are collected based on the point burying result, and the processing flow information of the target item is tracked based on the analysis result of the index logs, so that the interpretability of the data processing result is ensured.
Or, in specific implementation, the data processing log includes a link log, an index log and/or an abnormal information log;
correspondingly, after the invoking of the log collection module collects and executes the data processing log generated by the data processing logic, the method further includes:
storing the link log, the index log and/or the abnormal information log to a memory module;
and under the condition that the execution of the data processing logic is detected to be finished, writing the link log, the index log and/or the abnormal information log stored in the memory module into a disk file.
Specifically, the data processing logs collected by the log collection module may include link logs, index logs and/or abnormal information logs; the link log is used for tracing the context of the data processing link; the index log is used for collecting key indexes used in the data processing logic process of each distributed application node; and the abnormal information log is used for determining abnormal alarm information generated in the data processing logic process executed by each distributed application node.
A schematic diagram of a data processing process provided in an embodiment of the present specification is shown in fig. 2 a. In fig. 2a, when the distributed application node a starts to execute the corresponding data processing logic, the link log generated by executing the data processing logic may be collected by the SDK, and the link log is stored in the memory module (virtual machine memory); then, the annotation can be intercepted through the SDK, namely, the index calculation information contained in the data processing logic is intercepted and analyzed to determine the index to be calculated, and then the index log of the index to be calculated is collected and stored to a memory module (a virtual machine memory) by calling a buried point interface (a buried point API) in the data processing logic; in addition, under the condition that the execution of the data processing logic is detected to be abnormal, an abnormal information log can be collected and stored in a memory module (a virtual machine memory); and executing a disk brushing operation until the execution of the data processing logic is detected to be finished, and writing the link log, the index log and/or the abnormal information log stored in the memory module into a disk file.
In the embodiment of the specification, the SDK collects link logs, index logs and abnormal information logs generated in the data processing logic execution process to form calculation scene data of a full link, and the SDK stores the logs in the memory module in the data processing logic execution process, writes the logs stored in the memory module into a disk file once after the data processing logic execution is completed, and then clears the memory module.
And 106, calling the data processing module to analyze the data processing log, and determining a data processing link formed by the at least two distributed application nodes and processing flow information corresponding to the data processing link according to an analysis result.
Specifically, the data processing module may include a real-Time data transmission component (Time-Tunnel) and a real-Time data calculation component.
After the data processing log generated by the execution data processing logic is acquired by the call log acquisition module, the data processing log can be analyzed by the call data processing module, so that the context tracing of the data processing link of the target project is performed according to the analysis result, and the processing flow information of the data processing link is determined, so that the data processing process of the target project has interpretability.
In practical application, after the link logs, the index logs and/or the abnormal information logs stored in the memory module are written into a disk file, the real-time data transmission assembly asynchronously collects the logs written into the disk file, then writes the collected logs into the real-time data calculation assembly in real time for processing, and generates corresponding log analysis results.
Another schematic diagram of a data processing process provided in this specification is shown in fig. 2 b. In fig. 2b, when the distributed application node a starts to execute the corresponding data processing logic, the data processing log generated by executing the data processing logic may be collected by the SDK, and the data processing log is stored in the memory module (virtual machine memory), until the end of executing the data processing logic is detected, the disk-flushing operation is executed, and the data processing log stored in the memory module is written into the disk file. After the real-time data transmission assembly writes the logs collected from the disk files into the real-time data calculation assembly in real time, the real-time data calculation assembly serves as a converter and can be connected with different data sources in an abutting mode to store the data, wherein the first database mainly keeps pull-down list data screened by the front end and is used for storing small data quantity and fixed data, and the second database is used for storing mass data and keeping index logs and link logs.
After different types of logs are written into different databases, the logs can be continuously analyzed, and a data processing link formed by at least two distributed application nodes and processing flow information corresponding to the data processing link are determined according to an analysis result.
The embodiment of the specification completes the synchronous operation from the log to different databases through the real-time data computing component, supports the user-defined database, and is beneficial to improving the user experience.
In specific implementation, when the data processing log includes a link log, invoking the data processing module to analyze the data processing log, and determining a data processing link formed by the at least two distributed service nodes according to an analysis result, including:
calling the data processing module to analyze the link log to obtain the link identifier contained in the link log and an updating result of the initial calling identifier;
determining at least two distributed application nodes contained in the data processing link according to the link identification, and determining the calling sequence of the at least two distributed application nodes according to the updating result of the initial calling identification;
and determining a data processing link formed by the at least two distributed service nodes according to the calling sequence.
Specifically, the collected link logs include call information of each distributed application node, link identifiers included in call contexts of each distributed application node, and update results of initial call information of each distributed application node, that is, call identifiers (RPC ids) corresponding to each distributed application node, and if a call relationship exists between two distributed application nodes, a corresponding link identifier exists between the two distributed application nodes, and the link identifier uniquely represents a certain data processing link.
In the embodiment of the present specification, the link log includes a link identifier traceId, a calculation scene name sceneName, a calculation method name nodeName, a project identifier bizCode, a creation time createDate, and the like.
The project identification facilitates target project retrieval, and the creation time is used for sequencing all distributed application nodes and facilitating display.
A schematic diagram of a data processing link provided in an embodiment of the present specification is shown in fig. 2 c. In fig. 2C, the data processing link includes a node a, a node B, and a node C, and there is a call relationship between the node a and the node B, and there is a call relationship between the node B and the node C, so that, in the data processing process of the target item, after the data processing link for performing data processing starts, the node a is called first, the computing method 1 (data processing logic) corresponding to the node a is executed, and a corresponding data processing log is generated, in the execution process of the node a, the node B is called to execute the computing method 2 corresponding to the node a by means of RPC call, and a corresponding data processing log is generated, in the execution process of the node B, the node C is called by means of RPC call, and a corresponding computing method 3 is generated, and thus, the data processing process result of the target item, that is, the data processing link ends, based on the data processing logs generated by the nodes a, B, and C, a full link log corresponding to the data processing link can be obtained, and the data processing link formed by each node for performing data processing on the target item can be restored according to the full link log.
In the embodiment of the specification, a distributed request for a target project is restored to a node call link, that is, a data processing link, by using a distributed link tracking technology, and the call situations of distributed application nodes of the target project are collectively displayed, for example, time consumption on each distributed application node, request states of each distributed application node, and the like, abnormal information can be quickly located by using the data processing link and combining logs, and the data processing process of the target project can be displayed by displaying the node call process, so that the data processing process of the target project has interpretability.
Or, when the data processing log includes the index log, invoking the data processing module to analyze the data processing log, and determining a data processing link formed by the at least two distributed application nodes and processing flow information corresponding to the data processing link according to an analysis result, including:
calling the data processing module to analyze the index log to obtain a calculation relation between the at least two indexes to be calculated;
and determining a data processing link formed by the at least two distributed application nodes and the dendrograms corresponding to the at least two indexes to be calculated according to the calculation relationship, and taking the dendrograms as processing flow information corresponding to the data processing link.
Specifically, the index log may include a metricName index name, a metricValue index value, a metricdescr index description, a faulmetric parent index, a createDate creation time, and the like.
The index description is used for displaying the calculation formula among the indexes to be calculated, the father index is used for binding the father-son relationship among the indexes to be calculated, the display is convenient, and the creation time is used for sequencing the indexes to be calculated, so that the display is convenient.
Specifically, after the index log is acquired, the index log can be analyzed by using a data processing module to obtain a calculation relationship between at least two indexes to be calculated, a data processing link formed by at least two distributed application nodes and a dendrogram corresponding to the at least two indexes to be calculated are determined according to the calculation relationship, and the dendrogram is used as processing flow information corresponding to the data processing link.
A schematic diagram of a tree diagram provided in the embodiments of the present specification is shown in fig. 2 d. In fig. 2d, the indexes to be calculated are aggregated by formula and parent-child relationship between the indexes to form a tree diagram. For example, if index 0= index 1+ index 2+ index 3, and index 2= index 4+ index 5, as shown in fig. 2d, the parent index of index 0 is null, and serves as the parent node of all indexes, and the other indexes are shown recursively downward.
The embodiment of the specification displays the indexes to be calculated with the parent-child relationship and the calculation formulas of the indexes to be calculated through the dendrogram, and is beneficial to reducing the workload of checking the calculation accuracy.
In addition, when the data processing log includes an index log, invoking the data processing module to analyze the data processing log, and determining a data processing link formed by the at least two distributed application nodes and processing flow information corresponding to the data processing link according to an analysis result, including:
calling the data processing module to analyze the index log to obtain a calculation relation between the at least two indexes to be calculated;
and determining a data processing link formed by the at least two distributed application nodes and the directed graph corresponding to the at least two indexes to be calculated according to the calculation relationship, and taking the directed graph as processing flow information corresponding to the data processing link.
Specifically, in the foregoing embodiment, the tree graph is constructed by using the parent-child relationship between the indexes to be calculated and the calculation formula, and in the embodiment of the present specification, a directed graph (Dag directed acyclic graph) may also be constructed by using the parent-child relationship between the indexes to be calculated and the calculation formula, and a specific schematic diagram is shown in fig. 2e, so that the dependency relationship and the calculation relationship between the indexes to be calculated are represented by using the directional relationship between the nodes in the directed graph. For example, if index 0= index 1+ index 2+ index 3 and index 2= index 4+ index 5, then as shown in fig. 2d, index 2 is the parent of index 4 and index 5 and index 0 is the parent of index 2 and index 3.
The embodiment of the specification displays the calculation relation of each index to be calculated through the directed graph, and is beneficial to reducing the workload of checking the calculation accuracy.
In addition, after determining a data processing link formed by each distributed application node and processing flow information corresponding to the data processing link, a data processing result generated by executing the data processing logic can be acquired, and the data processing link, the processing flow information and the data processing result are displayed.
The embodiment of the specification simultaneously displays the data processing result, the data processing link and the processing flow information of the target project to the user, realizes a visual page, enables the user to clearly see the complete processing process of the target project, and is beneficial to enabling the data processing result of the target project to have interpretability.
In an embodiment of the present specification, at least two distributed application nodes related to a target project are determined, a target distributed application node is called to execute a data processing logic corresponding to the target distributed application node, and a log acquisition module is called to acquire a data processing log generated by executing the data processing logic, where the target distributed application node is any one of the at least two distributed application nodes, the data processing log is called to analyze by the data processing module, and a data processing link formed by the at least two distributed application nodes and processing flow information corresponding to the data processing link are determined according to an analysis result.
In the embodiment of the specification, after the data processing log generated by the execution data processing logic is acquired by the call log acquisition module, the data processing log can be analyzed by the call data processing module, so that the context tracing of the data processing link of the target project is performed according to the analysis result, and the processing flow information of the data processing link is determined, so that the data processing process of the target project has interpretability; in addition, in the process of executing the data processing logic, the data processing link and the processing flow information of the target item are determined by analyzing the acquired data processing log, so that a user can quickly locate an abnormality reason according to the data processing link and the processing flow information under the condition that the data processing process of the target item is abnormal, thereby being beneficial to reducing the difficulty in locating the abnormality and improving the efficiency of processing the abnormality.
The following describes the data processing method further by taking an application of the data processing method provided in this specification to an operation project as an example, with reference to fig. 3. Fig. 3 shows a processing procedure flowchart of a data processing method provided in an embodiment of the present specification, which specifically includes the following steps.
At step 302, at least two distributed application nodes related to an operation project are determined.
And step 306, calling the target distributed application node to execute the corresponding data processing logic, and updating the initial calling identifier contained in the calling context based on the calling information of the target distributed application node, wherein the target distributed application node is any one of at least two distributed application nodes.
And 308, acquiring a link log generated by the execution data processing logic by using a call log acquisition module, wherein the link log is generated according to the call information of the target distributed application node, the link identifier contained in the call context and the update result of the initial call information.
And step 310, calling the data processing module to analyze the link log, and determining at least two distributed application nodes contained in the data processing link and the calling sequence of the at least two distributed application nodes according to the analysis result.
Step 312, determining a data processing link formed by at least two distributed service nodes according to the calling sequence.
And step 314, calling the application detection module to execute a second point burying logic, acquiring a data processing logic corresponding to the target distributed application node, analyzing index calculation information contained in the data processing logic, and performing point burying operation on at least two indexes to be calculated according to an analysis result.
And step 316, calling the target distributed application node to execute the data processing logic corresponding to the target distributed application node, and calling a log acquisition module to acquire an index log generated by executing the data processing logic, wherein the index log is generated according to the buried data of at least two indexes to be calculated, which are acquired in the process of executing the data processing logic.
Step 318, a data processing module is called to analyze the index log to obtain a calculation relationship between at least two indexes to be calculated, a dendrogram corresponding to the at least two indexes to be calculated is determined according to the calculation relationship, and the dendrogram is used as processing flow information corresponding to the data processing link.
In the embodiment of the specification, after the data processing log generated by the execution data processing logic is acquired by the call log acquisition module, the data processing log can be analyzed by the call data processing module, so that the context tracing of the data processing link of the operation project is performed according to the analysis result, and the processing flow information of the data processing link is determined, so that the data processing process of the operation project has interpretability; in addition, in the process of executing the data processing logic, the embodiment of the present specification determines the data processing link and the processing flow information of the operation project by analyzing the acquired data processing log, so that when an abnormality occurs in the data processing process of the operation project, a user can quickly locate the cause of the abnormality according to the data processing link and the processing flow information, which is beneficial to reducing the difficulty of locating the abnormality, and thus, the efficiency of processing the abnormality is improved.
Corresponding to the above method embodiment, this specification further provides a data processing apparatus embodiment, and fig. 4 shows a schematic structural diagram of a data processing apparatus provided in an embodiment of this specification. As shown in fig. 4, the apparatus is applied to a client, where the client includes at least two distributed application nodes, a log collection module, and a data processing module, and the apparatus includes:
a determining module 402 configured to determine at least two distributed application nodes related to the target project;
a calling module 404 configured to call a target distributed application node to execute a data processing logic corresponding to the target distributed application node, and call the log acquisition module to acquire a data processing log generated by executing the data processing logic, where the target distributed application node is any one of the at least two distributed application nodes;
the analysis module 406 is configured to invoke the data processing module to analyze the data processing log, and determine, according to an analysis result, a data processing link formed by the at least two distributed application nodes and processing flow information corresponding to the data processing link.
Optionally, the data processing log includes a link log, and the client further includes a link detection module;
accordingly, the apparatus further comprises an assignment module configured to:
calling the link detection module to execute a first embedded point logic, and distributing a link identifier of a data processing link and an initial calling identifier corresponding to the target project;
and adding the link identification and the initial calling identification to the calling context of the target item.
Optionally, the invoking module 404 is further configured to:
acquiring the calling context;
and calling a target distributed application node to execute the data processing logic corresponding to the target distributed application node, and updating the initial calling identifier contained in the calling context based on the calling information of the target distributed application node.
Optionally, the data processing apparatus further includes a first log generation module configured to:
and generating the link log according to the calling information of the target distributed application node, the link identification contained in the calling context and the updating result of the initial calling information, and deleting the updating result.
Optionally, the analysis module 406 is further configured to:
calling the data processing module to analyze the link log to obtain the link identifier contained in the link log and an updating result of the initial calling identifier;
determining at least two distributed application nodes contained in the data processing link according to the link identification, and determining the calling sequence of the at least two distributed application nodes according to the updating result of the initial calling identification;
and determining a data processing link formed by the at least two distributed service nodes according to the calling sequence.
Optionally, the data processing log includes an index log, and the client further includes an application detection module;
accordingly, the apparatus further comprises a parsing module configured to:
calling the application detection module to execute a second embedded point logic, and acquiring a data processing logic corresponding to the target distributed application node;
and analyzing the index calculation information contained in the data processing logic, and performing point burying operation on at least two indexes to be calculated according to the analysis result.
Optionally, the data processing apparatus further includes a second log generation module configured to:
and generating the index log according to the embedded data of the at least two indexes to be calculated, which is collected in the process of executing the data processing logic.
Optionally, the analysis module 406 is further configured to:
calling the data processing module to analyze the index log to obtain a calculation relation between the at least two indexes to be calculated;
and determining a data processing link formed by the at least two distributed application nodes and the dendrograms corresponding to the at least two indexes to be calculated according to the calculation relationship, and taking the dendrograms as processing flow information corresponding to the data processing link.
Optionally, the analysis module 406 is further configured to:
calling the data processing module to analyze the index log to obtain a calculation relation between the at least two indexes to be calculated;
and determining a data processing link formed by the at least two distributed application nodes and the directed graph corresponding to the at least two indexes to be calculated according to the calculation relationship, and taking the directed graph as processing flow information corresponding to the data processing link.
Optionally, the data processing log includes a link log, an index log and/or an abnormal information log;
accordingly, the apparatus further comprises a storage module configured to:
storing the link log, the index log and/or the abnormal information log to a memory module;
and under the condition that the execution of the data processing logic is detected to be finished, writing the link log, the index log and/or the abnormal information log stored in the memory module into a disk file.
Optionally, the data processing apparatus further includes a presentation module configured to:
acquiring a data processing result generated by executing the data processing logic;
and displaying the data processing link, the processing flow information and the data processing result.
The above is a schematic configuration of a data processing apparatus of the present embodiment. It should be noted that the technical solution of the data processing apparatus and the technical solution of the data processing method belong to the same concept, and details that are not described in detail in the technical solution of the data processing apparatus can be referred to the description of the technical solution of the data processing method.
FIG. 5 illustrates a block diagram of a computing device 500 provided in accordance with one embodiment of the present description. The components of the computing device 500 include, but are not limited to, a memory 510 and a processor 520. Processor 520 is coupled to memory 510 via bus 530, and database 550 is used to store data.
Computing device 500 also includes access device 540, access device 540 enabling computing device 500 to communicate via one or more networks 560. Examples of such networks include the Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a Personal Area Network (PAN), or a combination of communication networks such as the internet. The access device 540 may include one or more of any type of network interface, e.g., a Network Interface Card (NIC), wired or wireless, such as an IEEE802.11 Wireless Local Area Network (WLAN) wireless interface, a worldwide interoperability for microwave access (Wi-MAX) interface, an ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a bluetooth interface, a Near Field Communication (NFC) interface, and so forth.
In one embodiment of the present description, the above-described components of computing device 500, as well as other components not shown in FIG. 5, may also be connected to each other, such as by a bus. It should be understood that the block diagram of the computing device structure shown in FIG. 5 is for illustration purposes only and is not intended to limit the scope of the present description. Other components may be added or replaced as desired by those skilled in the art.
Computing device 500 may be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., tablet, personal digital assistant, laptop, notebook, netbook, etc.), mobile phone (e.g., smartphone), wearable computing device (e.g., smartwatch, smartglasses, etc.), or other type of mobile device, or a stationary computing device such as a desktop computer or PC. Computing device 500 may also be a mobile or stationary server.
The processor 520 is configured to execute computer-executable instructions, which, when executed by the processor, implement the steps of the data processing method described above.
The above is an illustrative scheme of a computing device of the present embodiment. It should be noted that the technical solution of the computing device belongs to the same concept as the technical solution of the data processing method, and for details that are not described in detail in the technical solution of the computing device, reference may be made to the description of the technical solution of the data processing method.
An embodiment of the present specification further provides a computer-readable storage medium storing computer-executable instructions, which when executed by a processor implement the steps of the data processing method described above.
The above is an illustrative scheme of a computer-readable storage medium of the present embodiment. It should be noted that the technical solution of the storage medium belongs to the same concept as the technical solution of the data processing method, and details that are not described in detail in the technical solution of the storage medium can be referred to the description of the technical solution of the data processing method.
An embodiment of the present specification further provides a computer program, wherein when the computer program is executed in a computer, the computer is caused to execute the steps of the data processing method.
The above is an illustrative scheme of a computer program of the present embodiment. It should be noted that the technical solution of the computer program and the technical solution of the data processing method belong to the same concept, and details that are not described in detail in the technical solution of the computer program can be referred to the description of the technical solution of the data processing method.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The computer instructions comprise computer program code which may be in source code form, object code form, an executable file or some intermediate form, or the like. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U.S. disk, removable hard disk, magnetic diskette, optical disk, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), electrical carrier wave signal, telecommunications signal, and software distribution medium, etc. It should be noted that the computer-readable medium may contain suitable additions or subtractions depending on the requirements of legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer-readable media may not include electrical carrier signals or telecommunication signals in accordance with legislation and patent practice.
It should be noted that, for the sake of simplicity, the foregoing method embodiments are described as a series of acts, but those skilled in the art should understand that the present embodiment is not limited by the described acts, because some steps may be performed in other sequences or simultaneously according to the present embodiment. Further, those skilled in the art should also appreciate that the embodiments described in this specification are preferred embodiments and that acts and modules referred to are not necessarily required for an embodiment of the specification.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
The preferred embodiments of the present specification disclosed above are intended only to aid in the description of the specification. Alternative embodiments are not exhaustive and do not limit the invention to the precise embodiments described. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the embodiments and the practical application, and to thereby enable others skilled in the art to best understand the specification and utilize the specification. The specification is limited only by the claims and their full scope and equivalents.
Claims (14)
1. A data processing method is applied to a client, the client comprises at least two distributed application nodes, a log acquisition module and a data processing module, and the method comprises the following steps:
determining at least two distributed application nodes related to the target project;
calling a target distributed application node to execute data processing logic corresponding to the target distributed application node, and calling a log acquisition module to acquire and execute a data processing log generated by the data processing logic, wherein the target distributed application node is any one of the at least two distributed application nodes;
and calling the data processing module to analyze the data processing log, and determining a data processing link formed by the at least two distributed application nodes and processing flow information corresponding to the data processing link according to an analysis result.
2. The data processing method of claim 1, the data processing log comprising a link log, the client further comprising a link detection module;
accordingly, the method further comprises:
calling the link detection module to execute a first embedded point logic, and distributing a link identifier of a data processing link and an initial calling identifier corresponding to the target project;
and adding the link identification and the initial calling identification to the calling context of the target item.
3. The data processing method according to claim 2, wherein the invoking of the target distributed application node executes data processing logic corresponding to the target distributed application node, and comprises:
acquiring the calling context;
and calling a target distributed application node to execute data processing logic corresponding to the target distributed application node, and updating the initial calling identifier contained in the calling context based on the calling information of the target distributed application node.
4. The data processing method according to claim 3, after the invoking the target distributed application node executes the data processing logic corresponding to the target distributed application node, further comprising:
and generating the link log according to the calling information of the target distributed application node, the link identification contained in the calling context and the updating result of the initial calling information, and deleting the updating result.
5. The data processing method of claim 4, wherein the invoking the data processing module to analyze the data processing log and determine the data processing link formed by the at least two distributed service nodes according to the analysis result comprises:
calling the data processing module to analyze the link log to obtain the link identifier contained in the link log and an updating result of the initial calling identifier;
determining at least two distributed application nodes contained in the data processing link according to the link identification, and determining the calling sequence of the at least two distributed application nodes according to the updating result of the initial calling identification;
and determining a data processing link formed by the at least two distributed service nodes according to the calling sequence.
6. The data processing method of claim 1 or 2, the data processing log comprising an metrics log, the client further comprising an application detection module;
accordingly, the method further comprises:
calling the application detection module to execute a second embedded point logic, and acquiring a data processing logic corresponding to the target distributed application node;
and analyzing the index calculation information contained in the data processing logic, and performing point burying operation on at least two indexes to be calculated according to the analysis result.
7. The data processing method according to claim 6, after the invoking the target distributed application node executes the data processing logic corresponding to the target distributed application node, further comprising:
and generating the index log according to the embedded data of the at least two indexes to be calculated, which is collected in the process of executing the data processing logic.
8. The data processing method according to claim 7, wherein the invoking the data processing module to analyze the data processing log and determine, according to an analysis result, a data processing link formed by the at least two distributed application nodes and processing flow information corresponding to the data processing link includes:
calling the data processing module to analyze the index log to obtain a calculation relation between the at least two indexes to be calculated;
and determining a data processing link formed by the at least two distributed application nodes and the dendrograms corresponding to the at least two indexes to be calculated according to the calculation relationship, and taking the dendrograms as processing flow information corresponding to the data processing link.
9. The data processing method according to claim 7, wherein the invoking the data processing module to analyze the data processing log and determine, according to an analysis result, a data processing link formed by the at least two distributed application nodes and processing flow information corresponding to the data processing link includes:
calling the data processing module to analyze the index log to obtain a calculation relation between the at least two indexes to be calculated;
and determining a data processing link formed by the at least two distributed application nodes and the directed graph corresponding to the at least two indexes to be calculated according to the calculation relationship, and taking the directed graph as processing flow information corresponding to the data processing link.
10. The data processing method of claim 1, the data processing log comprising a link log, an index log, and/or an anomaly information log;
correspondingly, after the invoking of the log collection module collects and executes the data processing log generated by the data processing logic, the method further includes:
storing the link log, the index log and/or the abnormal information log to a memory module;
and under the condition that the execution of the data processing logic is detected to be finished, writing the link log, the index log and/or the abnormal information log stored in the memory module into a disk file.
11. The data processing method of claim 1, further comprising:
acquiring a data processing result generated by executing the data processing logic;
and displaying the data processing link, the processing flow information and the data processing result.
12. A data processing device is applied to a client, the client comprises at least two distributed application nodes, a log acquisition module and a data processing module, and the device comprises:
a determination module configured to determine at least two distributed application nodes related to a target project;
the system comprises a calling module and a log acquisition module, wherein the calling module is configured to call a target distributed application node to execute data processing logic corresponding to the target distributed application node and call the log acquisition module to acquire and execute a data processing log generated by the data processing logic, and the target distributed application node is any one of the at least two distributed application nodes;
and the analysis module is configured to call the data processing module to analyze the data processing log, and determine a data processing link formed by the at least two distributed application nodes and processing flow information corresponding to the data processing link according to an analysis result.
13. A computing device, comprising:
a memory and a processor;
the memory is for storing computer-executable instructions, and the processor is for executing the computer-executable instructions, which when executed by the processor, implement the steps of the data processing method of any one of claims 1 to 11.
14. A computer-readable storage medium storing computer-executable instructions which, when executed by a processor, implement the steps of the data processing method of any one of claims 1 to 11.
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