Task processing method and device, computer equipment and storage medium

Abstract

The invention belongs to the technical field of data processing, and relates to a task processing method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining an SQL statement of an online target task, and preprocessing the SQL statement to obtain a first SQL statement; segmenting the first SQL statement to obtain a second SQL statement; performing grammatical analysis on the second SQL statement to extract a table name and a field name; configuring specified task dependency based on the table name and the field name; task pilot run processing is carried out based on the specified task dependency, and whether abnormity occurs in the task pilot run process or not is judged; if no exception occurs in the task pilot run process, performing data comparison on the specified task dependency and the first task dependency of the target task to obtain a data comparison result; and if the data comparison result is that the data are inconsistent, executing abnormal early warning processing on the target task. In addition, the invention also relates to a block chain technology, and the specified task dependency can be stored in a block chain. The operation stability and reliability of the task can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of data processing, as well as fintech and digital healthcare fields, and particularly relates to a task processing method, apparatus, computer device, and storage medium. Background Art

[0002] In the financial and medical fields, with the continuous expansion and change of business, the demand for data processing tasks is also increasing day by day. These tasks usually involve extracting key information required by the business from a large dataset and going through a series of preprocessing steps to ensure the accuracy and availability of the data. However, with the increase in business complexity, the dependencies between tasks have become more complex and tight.

[0003] In the current task processing flow, each task depends on specific data sources and fields, which usually come from upstream preprocessing tasks. When the business changes, the relevant data processing tasks also need to be adjusted accordingly, including modifying task configurations, updating dependencies, etc. However, due to the intricate dependencies between tasks, once an upstream task changes, its downstream tasks may also be affected, resulting in problems with data extraction or processing.

[0004] More seriously, there is a lack of an effective warning mechanism in the current task processing process. When there are abnormalities in task configurations, such as non-existent dependent tables or fields, data type mismatches, etc., the task often directly reports an error, resulting in incorrect data extraction or processing. This situation not only affects the execution of the current task but may also have a chain reaction on the entire business process, causing the business to not run smoothly. Therefore, due to the lack of a warning mechanism, errors during task execution can often only be discovered and processed after the fact, resulting in low stability of task processing. Summary of the Invention

[0005] The purpose of the embodiments of the present application is to propose a task processing method, apparatus, computer device, and storage medium to solve the technical problem of low stability in existing task processing.

[0006] To solve the above technical problem, the embodiments of the present application provide a task processing method, which adopts the following technical solutions:

[0007] Obtain the SQL statement of the target task that has been launched, and preprocess the SQL statement to obtain the corresponding first SQL statement;

[0008] Perform a splitting process on the first SQL statement to obtain the corresponding second SQL statement;

[0009] Perform a syntax analysis on the second SQL statement to extract the table names and field names in the second SQL statement;

[0010] Configure corresponding specified task dependencies based on the table name and the field name;

[0011] Perform a task trial run process based on the specified task dependencies, and determine whether an exception occurs during the task trial run;

[0012] If no exception occurs during the task trial run, perform a data comparison between the specified task dependencies and the first task dependencies of the target task to obtain a corresponding data comparison result;

[0013] If the data comparison result is inconsistent data, perform an exception warning process corresponding to the relevant personnel on the target task.

[0014] To solve the above technical problems, an embodiment of the present application further provides a task processing device, which adopts the following technical solutions:

[0015] A processing module, configured to obtain the SQL statement of the target task that has been put on the line, and perform preprocessing on the SQL statement to obtain a corresponding first SQL statement;

[0016] A splitting module, configured to perform a splitting process on the first SQL statement to obtain a corresponding second SQL statement;

[0017] An extraction module, configured to perform a syntax analysis on the second SQL statement to extract the table name and the field name in the second SQL statement;

[0018] A configuration module, configured to configure corresponding specified task dependencies based on the table name and the field name;

[0019] A judgment module, configured to perform a task trial run process based on the specified task dependencies, and determine whether an exception occurs during the task trial run;

[0020] A comparison module, configured to, if no exception occurs during the task trial run, perform a data comparison between the specified task dependencies and the first task dependencies of the target task to obtain a corresponding data comparison result;

[0021] A warning module, configured to, if the data comparison result is inconsistent data, perform an exception warning process corresponding to the relevant personnel on the target task.

[0022] To solve the above technical problems, an embodiment of the present application further provides a computer device, which adopts the following technical solutions:

[0023] Obtain the SQL statement of the target task that has been put on the line, and perform preprocessing on the SQL statement to obtain a corresponding first SQL statement;

[0024] Perform segmentation processing on the first SQL statement to obtain the corresponding second SQL statement;

[0025] Perform syntax analysis on the second SQL statement to extract the table name and field name in the second SQL statement;

[0026] Configure the corresponding specified task dependencies based on the table name and the field name;

[0027] Perform task trial operation processing based on the specified task dependencies and determine whether an exception occurs during the task trial operation;

[0028] If no exception occurs during the task trial operation, compare the data of the specified task dependencies with the first task dependencies of the target task to obtain the corresponding data comparison result;

[0029] If the data comparison result is inconsistent data, perform exception warning processing corresponding to the relevant personnel on the target task.

[0030] To solve the above technical problems, an embodiment of the present application further provides a computer-readable storage medium, adopting the following technical solutions:

[0031] Obtain the SQL statement of the target task that has been put on the line, and perform preprocessing on the SQL statement to obtain the corresponding first SQL statement;

[0032] Perform segmentation processing on the first SQL statement to obtain the corresponding second SQL statement;

[0033] Perform syntax analysis on the second SQL statement to extract the table name and field name in the second SQL statement;

[0034] Configure the corresponding specified task dependencies based on the table name and the field name;

[0035] Perform task trial operation processing based on the specified task dependencies and determine whether an exception occurs during the task trial operation;

[0036] If no exception occurs during the task trial operation, compare the data of the specified task dependencies with the first task dependencies of the target task to obtain the corresponding data comparison result;

[0037] If the data comparison result is inconsistent data, perform exception warning processing corresponding to the relevant personnel on the target task.

[0038] Compared with the prior art, the embodiments of the present application mainly have the following beneficial effects:

[0039] This application first obtains the SQL statement of the target task that has been launched, and preprocesses the SQL statement to obtain the corresponding first SQL statement; then performs a splitting process on the first SQL statement to obtain the corresponding second SQL statement; then performs a syntax analysis on the second SQL statement to extract the table name and field name in the second SQL statement; subsequently configures the corresponding specified task dependencies based on the table name and the field name; further performs a task trial run process based on the specified task dependencies, and determines whether an exception occurs during the task trial run; if no exception occurs during the task trial run, then performs a data comparison between the specified task dependencies and the first task dependencies of the target task to obtain the corresponding data comparison result; if the data comparison result is inconsistent data, then performs an exception warning process corresponding to the relevant personnel on the target task. This application preprocesses the SQL statement of the target task that has been launched to obtain the first SQL statement, then performs a splitting process on the first SQL statement to obtain the second SQL statement, and performs a syntax analysis on the second SQL statement to extract the table name and field name, and then configures the corresponding specified task dependencies based on the table name and the field name, and then performs a task trial run process based on the specified task dependencies. When it is detected that no exception occurs during the task trial run, it will further perform a data comparison between the specified task dependencies and the first task dependencies of the target task. If it is detected that the data comparison result is inconsistent data, it will automatically perform the corresponding exception warning process on the target task, so that the relevant personnel can repair it in advance according to the exception warning, and then ensure that no exception occurs when the target task is officially running, which helps to improve the running stability and reliability of the target task. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the solutions in this application, the following will briefly introduce the drawings required for the description of the embodiments of this application. Obviously, the following drawings are some embodiments of this application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0041] Figure 1 is an exemplary system architecture diagram to which this application can be applied;

[0042] Figure 2 Flowchart of an embodiment of the task processing method according to this application;

[0043] Figure 3 is a schematic structural diagram of an embodiment of the task processing device according to this application;

[0044] Figure 4 is a schematic structural diagram of an embodiment of the computer device according to this application. Detailed implementation manners

[0045] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this application belongs; the terms used in the description of this application in the specification are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above drawings are intended to cover non-exclusive inclusion. The terms "first", "second", etc. in the specification and claims of this application or the above drawings are used to distinguish different objects and not to describe a specific order.

[0046] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in connection with the embodiments can be included in at least one embodiment of this application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0047] In order to enable those skilled in the technical field to better understand the solutions of this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0048] As Figure 1 shown, the system architecture 100 may include a terminal device 101, a network 102, and a server 103. The terminal device 101 may be a laptop computer 1011, a tablet computer 1012, or a mobile phone 1013. The network 102 is a medium for providing a communication link between the terminal device 101 and the server 103. The network 102 may include various connection types, such as wired, wireless communication links, or fiber optic cables, etc.

[0049] A user may use the terminal device 101 to interact with the server 103 via the network 102 to receive or send messages, etc. Various communication client applications may be installed on the terminal device 101, such as a web browser application, a shopping application, a search application, an instant messaging tool, an email client, a social platform software, etc.

[0050] The terminal device 101 can be various electronic devices with a display screen and supporting web browsing. In addition to the laptop 1011, tablet computer 1012, or mobile phone 1013, the terminal device 101 can also be an e-book reader, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 (Moving Picture Experts Group Audio Layer IV) player, a laptop computer, a desktop computer, and so on.

[0051] The server 103 can be a server that provides various services, such as a background server that supports the pages displayed on the terminal device 101.

[0052] It should be noted that the task processing method provided by the embodiments of the present application is generally executed by the server / terminal device. Correspondingly, the task processing device is generally set in the server / terminal device.

[0053] It should be understood that Figure 1 the numbers of the terminal devices, networks, and servers in

[0054] Continue to refer to Figure 2 , which shows a flowchart of an embodiment of the task processing method according to the present application. According to different requirements, the order of the steps in this flowchart can be changed, and some steps can be omitted. The task processing method provided by the embodiments of the present application can be applied to any scenario that requires product recommendation. Then, this task processing method can be applied to the products in these scenarios. For example, product recommendation in the financial insurance field. The described task processing method includes the following steps:

[0055] Step S201, obtain the SQL statement of the target task that has been launched, and preprocess the SQL statement to obtain the corresponding first SQL statement.

[0056] In this embodiment, the electronic device on which the task processing method runs (such as Figure 1The server / terminal device shown can obtain the SQL statement of the target task that has gone online through a wired connection method or a wireless connection method. It should be noted that the above wireless connection method can include, but is not limited to, 3G / 4G / 5G connection, WiFi connection, Bluetooth connection, WiMAX connection, Zigbee connection, UWB (ultra wideband) connection, and other wireless connection methods known now or developed in the future. The execution subject of this application is specifically a task processing system, which can be abbreviated as the system. The above target task that has gone online can refer to a newly launched business task, and this target task has not been formally operated yet. This application can be applied to the business scenario of task anomaly warning analysis in the financial field or the medical field. Exemplarily, in the business scenario of the financial field, the above newly launched target tasks can include intelligent investment advisor service tasks, blockchain financial service tasks, green financial project tasks, and so on. Among them, the above intelligent investment advisor service task refers to a task of providing personalized investment advice and asset allocation solutions for customers by using big data and artificial intelligence technologies. The above blockchain financial service task refers to a task of providing more secure, transparent, and efficient financial services, such as digital asset transactions, supply chain finance, etc. based on blockchain technology. The above green financial project task refers to a task of supporting the development of green industries, providing financial products such as green credit and green bonds, and tracking the environmental benefits of green projects. In the business scenario of the medical field, the above newly launched target tasks can include remote medical service tasks, intelligent medical image analysis tasks, and so on. Among them, the above remote medical service task refers to a task of providing medical services such as remote consultation and remote diagnosis by using Internet and mobile communication technologies. The above intelligent medical image analysis task refers to a task of automatically analyzing and diagnosing medical images by using artificial intelligence technologies to improve the diagnosis efficiency and accuracy. In addition, the specific implementation process of preprocessing the SQL statement to obtain the corresponding first SQL statement will be further described in detail in the subsequent specific embodiments of this application, and will not be elaborated here too much.

[0057] Step S202: Perform a splitting process on the first SQL statement to obtain the corresponding second SQL statement.

[0058] In this embodiment, the specific implementation process of performing a splitting process on the first SQL statement to obtain the corresponding second SQL statement will be further described in detail in the subsequent specific embodiments of this application, and will not be elaborated here too much.

[0059] Step S203: Perform a syntax analysis on the second SQL statement to extract the table name and field name in the second SQL statement.

[0060] In this embodiment, the specific implementation process of performing syntax analysis on the second SQL statement to extract the table name and field name in the second SQL statement will be further described in detail in subsequent specific embodiments of this application, and will not be elaborated here too much.

[0061] Step S204, configure the corresponding specified task dependencies based on the table name and the field name.

[0062] In this embodiment, by analyzing the SQL statement in the target task before the officially launched target task runs, the table name and field name required by the target task are extracted, so that it is possible to locate whether the actual dependencies of the target task are correct and whether the dependent tasks have been modified. Among them, the specific implementation process of configuring the corresponding specified task dependencies based on the table name and the field name will be further described in detail in subsequent specific embodiments of this application, and will not be elaborated here too much.

[0063] Step S205, perform a task trial run process based on the specified task dependencies, and determine whether an exception occurs during the task trial run process.

[0064] In this embodiment, after the configuration of the above-mentioned specified task dependencies is completed, the current task corresponding to the specified task dependencies can be subjected to a trial run process, and a regular expression or a log analysis tool can be used to quickly find any possible exceptions in the current task, such as exceptions like "table does not exist" and "field does not exist". Among them, if an exception occurs, it means that both the upstream dependent task table and fields have been updated, and some fields included in the dependent table may have been deleted or renamed. In such a case, relevant personnel need to be notified in a timely manner to repair the occurred exception to prevent the target task from reporting an error during the official operation, thereby ensuring the smooth operation of the target task.

[0065] Step S206, if no exception occurs during the task trial run process, compare the data between the specified task dependencies and the first task dependencies of the target task to obtain the corresponding data comparison result.

[0066] In this embodiment, the specific implementation process of comparing the data between the specified task dependencies and the first task dependencies of the target task to obtain the corresponding data comparison result will be further described in detail in subsequent specific embodiments of this application, and will not be elaborated here too much.

[0067] Step S207, if the data comparison result is data inconsistency, perform an exception warning process corresponding to the relevant personnel on the target task.

[0068] In this embodiment, if it is detected that the data comparison result is inconsistent, it indicates that problems such as errors will definitely occur in the operation of the above-mentioned target task that has been launched. Furthermore, corresponding abnormal warning processing will be automatically and intelligently performed on the target task. Specifically, relevant personnel can be notified in a timely manner to check the dependencies of the target task and repair relevant problems in advance to prevent errors from occurring during the formal operation of the target task, thereby ensuring the stable operation of the target task.

[0069] Among them, when there are changes in the task dependencies of the launched target task, it may cause errors in the current task operation. Discovering such problems in advance can timely remind relevant personnel to check and update the task dependencies of the target task in a timely manner, so as to ensure that no abnormalities occur during the formal operation of the launched target task.

[0070] In addition, the task processing logic can be updated in a timely manner. Since the subsequent SQL statements may be complex and changeable, the table field extraction logic also needs to be updated to adapt to more complex scenarios and prevent inaccurate extraction.

[0071] This application first obtains the SQL statement of the launched target task, preprocesses the SQL statement to obtain the corresponding first SQL statement; then performs a segmentation process on the first SQL statement to obtain the corresponding second SQL statement; then performs a syntax analysis on the second SQL statement to extract the table name and field name in the second SQL statement; subsequently, configures the corresponding specified task dependencies based on the table name and the field name; further performs a task trial run process based on the specified task dependencies and determines whether an abnormality occurs during the task trial run process; if no abnormality occurs during the task trial run process, then compares the specified task dependencies with the first task dependencies of the target task to obtain the corresponding data comparison result; if the data comparison result is inconsistent, then performs corresponding abnormal warning processing on the target task corresponding to the relevant personnel. This application preprocesses the SQL statement of the launched target task to obtain the first SQL statement, then performs a segmentation process on the first SQL statement to obtain the second SQL statement, and performs a syntax analysis on the second SQL statement to extract the table name and field name. Subsequently, configures the corresponding specified task dependencies based on the table name and the field name, and further performs a task trial run process based on the specified task dependencies. When it is detected that no abnormality occurs during the task trial run process, it will further compare the specified task dependencies with the first task dependencies of the target task. If it is detected that the data comparison result is inconsistent, it will automatically perform corresponding abnormal warning processing on the target task, so that relevant personnel can repair and process in advance according to the abnormal warning, thereby ensuring that no abnormality occurs during the formal operation of the target task, which helps to improve the operation stability and reliability of the target task.

[0072] In some alternative implementations, the preprocessing of the SQL statement in step S201 to obtain the corresponding first SQL statement includes the following steps:

[0073] Perform symbol replacement processing on the SQL statement to obtain a corresponding first statement.

[0074] In this embodiment, the above symbol replacement processing may include: checking whether the SQL statement contains Chinese symbols such as Chinese parentheses (e.g., ()) and commas (e.g.,,) by using regular expressions or string processing functions. Then replace these Chinese symbols with corresponding English symbols and ensure that the syntax of the replaced SQL statement is correct, thereby obtaining the corresponding first statement.

[0075] Exemplarily, the SQL statement submitted by the user may have a mixed use of Chinese and English, such as using Chinese in front of the parentheses and English behind, which may cause anomalies in statement analysis. The Chinese and English symbols can be unified through content replacement.

[0076] Perform comment deletion processing on the first statement to obtain a corresponding second statement.

[0077] In this embodiment, the comment statement only makes it easier for the user to understand the SQL statement, rather than the real processing logic. In SQL analysis, it will make the analysis process and logic more complex. Removing the comment statement in advance can make the SQL statement more concise. Specifically, the comment part in the first statement can be identified, such as single-line comments starting with -- and multi-line comments enclosed by / *...* / . Then use string processing functions or regular expressions to remove these comment parts and retain the core logic of the first statement, thereby obtaining the corresponding second statement.

[0078] Perform statement simplification processing on the second statement based on a preset keyword matching strategy to obtain a corresponding third statement.

[0079] In this embodiment, the content of the above keyword matching strategy may include: identifying and processing complex CASE WHEN statements, simplifying the logic or replacing them with more concise expressions; analyzing complex conditions in the WHERE clause, using logical operators (such as AND, OR) to split and reorganize to improve readability; sorting out multi-layer nested queries, removing unnecessary subqueries or converting them into JOIN operations to simplify the query structure.

[0080] Among them, the second statement can be simplified according to the strategy content of the above keyword matching strategy to obtain the corresponding third statement. Specifically, in order to make the analysis of SQL statements more concise, by matching the keywords in the SQL statement, for example, a long statement for extracting content such as CASE WHEN in a query statement can be directly replaced by a single letter, without affecting the subsequent analysis of the SQL statement, because the SQL dependency only judges whether the dependency is normal based on the table name and field name, so only the required fields need to be obtained in CASE WHEN, without specific judgment logic. Another example is that there may be a long conditional judgment statement after WHERE in the SQL statement, which is unimportant in the SQL analysis process and can also be simplified by matching the content therein to make the SQL statement more concise. In addition, there are multi-layer complex query statements, which can be sorted out layer by layer according to the fields required by the outermost layer, and the useless fields and table names in the middle layer and the innermost layer can be simplified and removed. In addition, the content inside various like quotes and various references are also removed.

[0081] Use the third statement as the first SQL statement.

[0082] In this application, the SQL statement is processed by replacing symbols to obtain the corresponding first statement; then the first statement is processed by deleting comments to obtain the corresponding second statement; then the second statement is simplified based on a preset keyword matching strategy to obtain the corresponding third statement; subsequently, the third statement is used as the first SQL statement. By performing symbol replacement processing, comment deletion processing, and statement simplification processing on the SQL statement, this application can efficiently and accurately complete the preprocessing of the SQL statement, improve the conciseness of the obtained first SQL statement, effectively improve the analysis speed of the SQL statement subsequently, and thus is conducive to improving the processing efficiency of anomaly recognition for the target task.

[0083] In some optional implementation manners of this embodiment, step S202 includes the following steps:

[0084] Call a preset parser.

[0085] In this embodiment, the above parser may specifically adopt an SQL parser.

[0086] Based on the parser, identify the delimiters in the first SQL statement.

[0087] In this embodiment, the above SQL parser can be used to identify the delimiters in the first SQL statement to obtain the delimiters in the first SQL statement.

[0088] Perform splitting processing on the first SQL statement based on the delimiter to obtain a corresponding plurality of independent statements.

[0089] In this embodiment, the above first SQL statement can be split into individual independent SQL statements, that is, the above independent statements, according to the identified delimiter.

[0090] Perform verification processing on all the independent statements.

[0091] In this embodiment, the above verification processing refers to performing syntax verification and running verification on the independent statements to determine whether the independent statements are syntactically correct and can be executed independently. Among them, by performing verification processing on the independent statements, corresponding verification results will be obtained, and the verification results include verification passed or verification failed.

[0092] If all the independent statements pass the verification, then all the independent statements are used as the second SQL statement.

[0093] In this embodiment, only when it is detected that all the independent statements pass the verification, will all the above independent statements be used as the above second SQL statement.

[0094] This application calls a preset parser; and based on the parser, identifies the delimiter in the first SQL statement; then performs splitting processing on the first SQL statement based on the delimiter to obtain a corresponding plurality of independent statements; subsequently performs verification processing on all the independent statements; if all the independent statements pass the verification, then all the independent statements are used as the second SQL statement. This application identifies the delimiter in the first SQL statement based on the use of the parser, and then identifies the delimiter in the first SQL statement based on the parser, and then performs splitting processing on the first SQL statement based on the delimiter to obtain a corresponding plurality of independent statements. Subsequently, by performing verification processing on all the independent statements and detecting that all the independent statements pass the verification, all the independent statements are used as the second SQL statement, so that the splitting processing of the first SQL statement can be efficiently and accurately completed based on the use of the parser, ensuring the accuracy of the obtained second SQL statement. In addition, by splitting the first SQL statement to obtain the second SQL statement, it is beneficial to more conveniently extract the required table names and field names from the second SQL statement subsequently, and thus beneficial to improving the extraction efficiency and extraction intelligence of the table names and field names.

[0095] In some alternative implementation manners, step S203 includes the following steps:

[0096] Obtain the statement type of the second SQL statement.

[0097] In this embodiment, the syntax of the second SQL statement can be analyzed by using an SQL parser to extract each component in the second SQL statement, and the statement type of the second SQL statement can be determined according to the components. Among them, the statement types can include SELECT (query statement type), INSERT (insert statement type), DELETE (delete statement type), and so on.

[0098] Obtain the data extraction strategy corresponding to the statement type.

[0099] In this embodiment, for different statement types, data extraction strategies corresponding to different extraction logics are preset. Specifically, the data extraction strategies can include: Data extraction strategy 1: For a SELECT statement, extract the table name in the FROM clause and the field names in the SELECT clause. Data extraction strategy 2: For an INSERT statement, extract the table name in the INTO clause and the field names in the VALUES clause or the SELECT clause. Data extraction strategy 3: For a DELETE statement, extract the table name in the FROM clause.

[0100] Extract the table name and field names in the second SQL statement based on the data extraction strategy.

[0101] In this embodiment, the data extraction process can be performed on the second SQL statement according to the strategy content of the data extraction strategy to obtain the table name and field names in the second SQL statement.

[0102] This application obtains the statement type of the second SQL statement; then obtains the data extraction strategy corresponding to the statement type; subsequently, extracts the table name and field names in the second SQL statement based on the data extraction strategy. By obtaining the statement type of the second SQL statement, then obtaining the data extraction strategy corresponding to the statement type, and then based on the use of the data extraction strategy, it can be realized to efficiently and accurately extract the table name and field names in the second SQL statement, improve the data extraction efficiency of the table name and field names, and ensure the data accuracy of the obtained table name and field names.

[0103] In some alternative implementation manners, step S204 includes the following steps:

[0104] Determine the specified task corresponding to the table name and the field names.

[0105] In this embodiment, all involved tasks, that is, the above-mentioned specified tasks, can be identified according to the table name and field names extracted from the second SQL statement.

[0106] Create a dependency graph corresponding to the specified task.

[0107] In this embodiment, a dependency graph is created for each specified task, where the nodes in the graph represent tasks and the edges represent the dependencies between tasks.

[0108] Call a preset task scheduler.

[0109] In this embodiment, the above-mentioned task scheduler can specifically adopt Apache Airflow or Cron.

[0110] Based on the dependency graph, use the task scheduler to configure the second task dependency corresponding to the specified task.

[0111] In this embodiment, the configuration of the second task dependency corresponding to the specified task can be completed by opening the configuration interface of the above-mentioned task scheduler, and then, according to the above-mentioned dependency graph, configuring the execution order and dependencies of the above-mentioned specified tasks one by one in the above-mentioned configuration interface, and specifying the input and output of the above-mentioned specified tasks in the configuration page to ensure that they match the table names and field names extracted from the second SQL statement. Among them, a simple verification step can also be run in the above-mentioned task scheduler to check whether the configuration of the above-mentioned second task dependency is correct, so as to ensure that all specified tasks can be correctly identified and the dependencies are correctly established.

[0112] Take the second task dependency as the specified task dependency.

[0113] This application determines the specified tasks corresponding to the table names and the field names; then creates a dependency graph corresponding to the specified tasks; then calls a preset task scheduler; and based on the dependency graph, uses the task scheduler to configure the second task dependency corresponding to the specified task; subsequently, takes the second task dependency as the specified task dependency. This application determines the specified tasks corresponding to the table names and field names, creates a dependency graph corresponding to the specified tasks, then calls a preset task scheduler, and further, based on the dependency graph, uses the task scheduler to configure the second task dependency corresponding to the specified task and takes it as the required specified task dependency, thereby realizing the intelligent and accurate configuration process of the specified task dependencies corresponding to the table names and field names, and ensuring the accuracy of the obtained specified task dependencies.

[0114] In some alternative implementation manners of this embodiment, step S206 includes the following steps:

[0115] Obtain the first task dependency of the target task.

[0116] In this embodiment, the first task dependency of the target task can be obtained by performing a task dependency query on the above-mentioned target task.

[0117] Invoke a preset data comparison tool.

[0118] In this embodiment, the above data comparison tool may specifically adopt a comparison script with data comparison function. Specifically, the above comparison script can be written using the pandas library of Python or other database operation libraries.

[0119] Based on the data comparison tool, perform data comparison between the specified task dependency and the first task dependency.

[0120] In this embodiment, by using the above data comparison tool, the first key dependency information such as table names, field names, and data types included in the specified task dependency can be automatically compared one by one with the second key dependency information such as table names, field names, and data types included in the first task dependency, and the corresponding data comparison results can be recorded.

[0121] If the specified task dependency is consistent with the first task dependency, generate a first data comparison result indicating data consistency.

[0122] In this embodiment, if it is detected that the first key dependency information such as table names, field names, and data types included in the specified task dependency is all consistent with the second key dependency information such as table names, field names, and data types included in the first task dependency, it is determined that the specified task dependency is consistent with the first task dependency, and a first data comparison result indicating data consistency is generated.

[0123] If the specified task dependency is inconsistent with the first task dependency, generate a second data comparison result indicating data inconsistency.

[0124] In this embodiment, if it is detected that the first key dependency information such as table names, field names, and data types included in the specified task dependency is not all consistent with the second key dependency information such as table names, field names, and data types included in the first task dependency, it is determined that the specified task dependency is inconsistent with the first task dependency, and then a second data comparison result indicating data inconsistency is generated.

[0125] This application obtains the first task dependency of the target task; then calls a preset data comparison tool; subsequently, based on the data comparison tool, it compares the specified task dependency with the first task dependency; if the specified task dependency is consistent with the first task dependency, it generates a first data comparison result indicating consistent data; if the specified task dependency is inconsistent with the first task dependency, it generates a second data comparison result indicating inconsistent data. By obtaining the first task dependency of the target task and then performing a data comparison between the specified task dependency and the first task dependency based on the use of the data comparison tool, this application can automatically and accurately generate corresponding data comparison results, effectively improving the data comparison efficiency and ensuring the accuracy of the generated data comparison results.

[0126] In some alternative implementation manners of this embodiment, after step S205, the above-mentioned electronic device may further perform the following steps:

[0127] If an exception occurs during the task trial run, obtain the exception information found during the task trial run.

[0128] In this embodiment, by analyzing the logs during the task trial run and using regular expressions or log analysis tools, any possible exceptions can be quickly found. If exceptions such as "table does not exist" or "field does not exist" are found, the discovered exception information, which may include information such as the error type, occurrence time, and task name, can be recorded.

[0129] Determine the preset task-related personnel.

[0130] In this embodiment, the above-mentioned task-related personnel may be the relevant personnel responsible for task processing matters, such as data engineers, project managers, etc.

[0131] Obtain the preset target notification method.

[0132] In this embodiment, there is no specific limitation on the selection of the above-mentioned target notification method, which can be determined according to actual business requirements. For example, it may include methods such as email, text message, or internal system notification.

[0133] Based on the target notification method, send the exception information to the task-related personnel.

[0134] In this embodiment, by adopting the above-mentioned target notification method, the exception warning process of sending the above-mentioned exception information to the task-related personnel can be executed in a standardized manner, so that the task-related personnel can timely check and update the task dependency configuration of the target task according to the received exception information, thereby ensuring that no exceptions occur when the target task is officially running.

[0135] If an exception occurs during the task trial run in this application, obtain the exception information found during the task trial run; then determine the preset task-related personnel; then obtain the preset target notification method; subsequently, based on the target notification method, send the exception information to the task-related personnel. When this application detects an exception during the task trial run, it will intelligently obtain the exception information found during the task trial run, determine the preset task-related personnel, and then send the exception information to the task-related personnel according to the obtained target notification method, so that the task-related personnel can timely check and update the task dependency configuration of the target task based on the received exception information, thereby ensuring that no exception will occur when the target task is officially run, and further ensuring the stable operation of the target task.

[0136] In some alternative implementation manners, the obtained user information has obtained the consent of the user and complies with the provisions of relevant laws and relevant policies.

[0137] In addition, the non-company software tools or components that appear in the embodiments of this application are only for illustrative introduction and do not represent actual use.

[0138] In addition, the task processing method proposed in this application is mainly to solve the problem that the task officially goes into production and runs with errors due to changes in the task dependencies during the online process or the task dependency configuration not being updated. Because the configured dependency tests before the task goes online may be okay, or some may not have been tested at all, resulting in abnormal dependencies, or the dependency tasks have changed after passing the pre-online tests, which may also cause abnormal production runs. Based on all these situations, this matter mainly uses the function of task SQL statement analysis to analyze it before the task runs, timely discover the problems therein, and notify the relevant personnel for processing, thereby reducing the impact on production tasks and reducing the risk of affecting business progress.

[0139] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0140] It should be emphasized that to further ensure the privacy and security of the above-specified task dependencies, the above-specified task dependencies can also be stored in a node of a blockchain.

[0141] The blockchain referred to in this application is a new application mode of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, and encryption algorithms. Blockchain, in essence, is a decentralized database, a series of data blocks generated by using cryptographic methods. Each data block contains information about a batch of network transactions, which is used to verify the validity of the information (anti-counterfeiting) and generate the next block. The blockchain can include the blockchain underlying platform, the platform product service layer, and the application service layer, etc.

[0142] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Among them, Artificial Intelligence (AI) is to use a digital computer or a machine controlled by a digital computer to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to obtain the best results of theory, methods, technologies, and application systems.

[0143] Artificial intelligence basic technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation / interaction systems, and mechatronics. Artificial intelligence software technologies mainly include several major directions such as computer vision technology, robotics, biometric technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0144] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through computer-readable instructions. The computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, the aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, an optical disc, a Read-Only Memory (ROM), etc., or a Random Access Memory (RAM), etc.

[0145] It should be understood that although each step in the flowchart of the accompanying drawings is displayed sequentially according to the indication of the arrow, these steps do not necessarily execute sequentially according to the order indicated by the arrow. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings can include multiple sub-steps or multiple stages. These sub-steps or stages do not necessarily need to be completed at the same moment, but can be executed at different moments. Their execution order does not necessarily need to be sequential, but can be executed alternately or alternately with at least a part of other steps or sub-steps or stages of other steps.

[0146] For further referenceFigure 3 , as an implementation of the method described above Figure 2 , this application provides an embodiment of a task processing device. This device embodiment corresponds to Figure 2 the method embodiment shown, and this device can be specifically applied to various electronic devices.

[0147] As Figure 3 shown, the task processing device 300 described in this embodiment includes: a processing module 301, a splitting module 302, an extraction module 303, a configuration module 304, a judgment module 305, a comparison module 306, and a warning module 307. Among them:

[0148] The processing module 301 is used to obtain the SQL statement of the target task that has been launched, and preprocess the SQL statement to obtain the corresponding first SQL statement;

[0149] The splitting module 302 is used to perform splitting processing on the first SQL statement to obtain the corresponding second SQL statement;

[0150] The extraction module 303 is used to perform syntax analysis on the second SQL statement to extract the table name and field name in the second SQL statement;

[0151] The configuration module 304 is used to configure the corresponding specified task dependencies based on the table name and the field name;

[0152] The judgment module 305 is used to perform task trial operation processing based on the specified task dependencies, and judge whether an exception occurs during the task trial operation;

[0153] The comparison module 306 is used to, if no exception occurs during the task trial operation, compare the specified task dependencies with the first task dependencies of the target task to obtain the corresponding data comparison result;

[0154] The warning module 307 is used to, if the data comparison result is data inconsistency, perform exception warning processing on the target task corresponding to the relevant personnel.

[0155] In this embodiment, the operations respectively performed by the above modules or units correspond one by one to the steps of the task processing method in the foregoing embodiment, and will not be elaborated here.

[0156] In some optional implementation manners of this embodiment, the processing module 301 includes:

[0157] The first processing sub-module is used to perform replacement symbol processing on the SQL statement to obtain the corresponding first statement;

[0158] The second processing sub-module is used to perform comment deletion processing on the first statement to obtain a corresponding second statement;

[0159] The third processing sub-module is used to perform statement simplification processing on the second statement based on a preset keyword matching strategy to obtain a corresponding third statement;

[0160] The first determination sub-module is used to use the third statement as the first SQL statement.

[0161] In this embodiment, the operations respectively performed by the above modules or units correspond one by one to the steps of the task processing method in the foregoing embodiment, and will not be elaborated herein.

[0162] In some optional implementation manners of this embodiment, the splitting module 302 includes:

[0163] The first calling sub-module is used to call a preset parser;

[0164] The recognition sub-module is used to recognize the delimiters in the first SQL statement based on the parser;

[0165] The splitting sub-module is used to perform splitting processing on the first SQL statement based on the delimiters to obtain corresponding multiple independent statements;

[0166] The verification sub-module is used to perform verification processing on all the independent statements;

[0167] The second determination sub-module is used to use all the independent statements as the second SQL statement if all the independent statements pass the verification.

[0168] In this embodiment, the operations respectively performed by the above modules or units correspond one by one to the steps of the task processing method in the foregoing embodiment, and will not be elaborated herein.

[0169] In some optional implementation manners of this embodiment, the extraction module 303 includes:

[0170] The first obtaining sub-module is used to obtain the statement type of the second SQL statement;

[0171] The second obtaining sub-module is used to obtain a data extraction strategy corresponding to the statement type;

[0172] The extraction sub-module is used to extract the table name and field name in the second SQL statement based on the data extraction strategy.

[0173] In this embodiment, the operations respectively performed by the above modules or units correspond one by one to the steps of the task processing method in the foregoing embodiment, and will not be elaborated herein.

[0174] In some alternative implementation manners of this embodiment, the configuration module 304 includes:

[0175] A third determination sub-module, configured to determine a specified task corresponding to the table name and the field name;

[0176] A creation sub-module, configured to create a dependency graph corresponding to the specified task;

[0177] A second invocation sub-module, configured to invoke a preset task scheduler;

[0178] A configuration sub-module, configured to configure a second task dependency corresponding to the specified task based on the dependency graph by using the task scheduler;

[0179] A fourth determination sub-module, configured to use the second task dependency as the specified task dependency.

[0180] In this embodiment, the operations respectively performed by the foregoing modules or units correspond one by one to the steps of the task processing method in the foregoing embodiment, and will not be elaborated herein.

[0181] In some alternative implementation manners of this embodiment, the comparison module 306 includes:

[0182] A third acquisition sub-module, configured to acquire a first task dependency of the target task;

[0183] A third invocation sub-module, configured to invoke a preset data comparison tool;

[0184] A comparison sub-module, configured to perform data comparison on the specified task dependency and the first task dependency based on the data comparison tool;

[0185] A first generation sub-module, configured to generate a first data comparison result indicating consistent data if the specified task dependency is consistent with the first task dependency;

[0186] A second generation sub-module, configured to generate a second data comparison result indicating inconsistent data if the specified task dependency is inconsistent with the first task dependency.

[0187] In this embodiment, the operations respectively performed by the foregoing modules or units correspond one by one to the steps of the task processing method in the foregoing embodiment, and will not be elaborated herein.

[0188] In some alternative implementation manners of this embodiment, the task processing apparatus further includes:

[0189] A first acquisition module, configured to acquire exception information found during the task trial run if an exception occurs during the task trial run;

[0190] A determination module, configured to determine preset task-related personnel;

[0191] A second acquisition module, configured to acquire a preset target notification method;

[0192] A sending module, configured to send the exception information to the task-related personnel based on the target notification method.

[0193] In this embodiment, the operations respectively performed by the foregoing modules or units correspond one by one to the steps of the task processing method in the foregoing embodiment, and will not be elaborated herein.

[0194] To solve the above technical problems, an embodiment of the present application further provides a computer device. For details, please refer to Figure 4 , Figure 4 which is a basic structural block diagram of the computer device in this embodiment.

[0195] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are communicatively connected to each other through a system bus. It should be noted that only the computer device 4 with components 41-43 is shown in the figure, but it should be understood that it is not required to implement all the shown components, and more or fewer components can be alternatively implemented. Among them, those skilled in the art of the present technology can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to a microprocessor, an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a digital signal processor (DSP), an embedded device, etc.

[0196] The computer device may be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The computer device can perform human-computer interaction with a user through means such as a keyboard, a mouse, a remote control, a touchpad, or a voice control device.

[0197] The memory 41 includes at least one type of readable storage medium, which includes flash memory, hard disk, multimedia card, card-type memory (such as SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disc, etc. In some embodiments, the memory 41 may be an internal storage unit of the computer device 4, such as the hard disk or memory of the computer device 4. In other embodiments, the memory 41 may also be an external storage device of the computer device 4, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, FlashCard, etc. equipped on the computer device 4. Of course, the memory 41 may also include both the internal storage unit and the external storage device of the computer device 4. In this embodiment, the memory 41 is generally used to store the operating system and various application software installed in the computer device 4, such as computer-readable instructions of the task processing method. In addition, the memory 41 may also be used to temporarily store various data that have been output or will be output.

[0198] In some embodiments, the processor 42 may be a central processing unit (CPU), controller, microcontroller, microprocessor, or other data processing chip. The processor 42 is generally used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to run the computer-readable instructions stored in the memory 41 or process data, such as running the computer-readable instructions of the task processing method.

[0199] The network interface 43 may include a wireless network interface or a wired network interface, and the network interface 43 is generally used to establish a communication connection between the computer device 4 and other electronic devices.

[0200] Compared with the prior art, the embodiments of the present application mainly have the following beneficial effects:

[0201] In the embodiments of the present application, the SQL statement of the target task that has been launched is preprocessed to obtain a first SQL statement, then the first SQL statement is split to obtain a second SQL statement, and the second SQL statement is syntactically analyzed to extract the table name and field name. After that, the corresponding specified task dependencies are configured based on the table name and field name, and then the task is run for testing based on the specified task dependencies. When it is detected that no exception occurs during the task running test, the data of the specified task dependencies and the first task dependencies of the target task are further compared. If it is detected that the data comparison result is inconsistent, the corresponding exception warning process will be automatically executed on the target task, so that relevant personnel can perform repair processing in advance according to the exception warning, and then ensure that no exception occurs when the target task is officially running, thereby helping to improve the running stability and reliability of the target task.

[0202] The present application also provides another implementation manner, that is, a computer-readable storage medium is provided. The computer-readable storage medium stores computer-readable instructions, and the computer-readable instructions can be executed by at least one processor to enable the at least one processor to execute the steps of the task processing method as described above.

[0203] Compared with the prior art, the embodiments of the present application mainly have the following beneficial effects:

[0204] In the embodiments of the present application, the SQL statement of the target task that has been launched is preprocessed to obtain a first SQL statement, then the first SQL statement is split to obtain a second SQL statement, and the second SQL statement is syntactically analyzed to extract the table name and field name. After that, the corresponding specified task dependencies are configured based on the table name and field name, and then the task is run for testing based on the specified task dependencies. When it is detected that no exception occurs during the task running test, the data of the specified task dependencies and the first task dependencies of the target task are further compared. If it is detected that the data comparison result is inconsistent, the corresponding exception warning process will be automatically executed on the target task, so that relevant personnel can perform repair processing in advance according to the exception warning, and then ensure that no exception occurs when the target task is officially running, thereby helping to improve the running stability and reliability of the target task.

[0205] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-described example methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation. Based on such an understanding, the technical solution of the present application, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions for causing a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present application.

[0206] Obviously, the above-described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The accompanying drawings show the preferred embodiments of the present application, but do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosed content of the present application more thorough and comprehensive. Although the present application has been described in detail with reference to the foregoing embodiments, for those skilled in the art, they can still modify the technical solutions described in the foregoing specific embodiments or equivalently replace some of the technical features. Any equivalent structure directly or indirectly using the content of the specification and drawings of the present application in other related technical fields is similarly within the scope of the patent protection of the present application.

Claims

1. A task processing method, characterized in that: The steps include: Obtaining the SQL statement of the online target task, and preprocessing the SQL statement to obtain the corresponding first SQL statement; Splitting the first SQL statement to obtain a corresponding second SQL statement; Performing syntax analysis on the second SQL statement to extract table names and field names in the second SQL statement; Configure the corresponding specified task dependency based on the table name and the field name; Performing a task trial run based on the specified task dependency, and determining whether an abnormality occurs during the task trial run; If no abnormality occurs during the task trial run, data comparison is performed on the designated task dependency and the first task dependency of the target task to obtain a corresponding data comparison result; If the data comparison result is that the data is inconsistent, an abnormal warning process corresponding to the relevant personnel is executed for the target task.

2. The task processing method according to claim 1, characterized in that: The step of preprocessing the SQL statement to obtain the corresponding first SQL statement specifically includes: Perform symbol replacement processing on the SQL statement to obtain a corresponding first statement; Deleting comments from the first statement to obtain a corresponding second statement; Simplifying the second sentence based on a preset keyword matching strategy to obtain a corresponding third sentence; The third statement is used as the first SQL statement.

3. The task processing method according to claim 1, characterized in that: The step of segmenting the first SQL statement to obtain a corresponding second SQL statement specifically includes: Call the preset parser; Identify a delimiter in the first SQL statement based on the parser; Splitting the first SQL statement based on the separator to obtain corresponding multiple independent statements; Performing verification processing on all the independent statements; If all the independent statements pass the verification, all the independent statements are used as the second SQL statements.

4. The task processing method according to claim 1, characterized in that: The step of configuring the corresponding specified task dependency based on the table name and the field name specifically includes: Obtaining the statement type of the second SQL statement; Obtaining a data extraction strategy corresponding to the statement type; The table name and field name in the second SQL statement are extracted based on the data extraction strategy.

5. The task processing method according to claim 1, characterized in that: The step of configuring the corresponding specified task dependency based on the table name and the field name specifically includes: Determine a designated task corresponding to the table name and the field name; Creating a dependency graph corresponding to the specified task; Call the preset task scheduler; Based on the dependency graph, using the task scheduler to configure a second task dependency corresponding to the specified task; The second task dependency is used as the designated task dependency.

6. The task processing method according to claim 1, characterized in that: The step of performing data comparison on the designated task dependency and the first task dependency of the target task to obtain a corresponding data comparison result specifically includes: Obtaining a first task dependency of the target task; Call the preset data comparison tool; Performing data comparison between the designated task dependency and the first task dependency based on the data comparison tool; If the specified task dependency is consistent with the first task dependency, generating a first data comparison result with consistent data; If the designated task dependency is inconsistent with the first task dependency, a second data comparison result indicating data inconsistency is generated.

7. The task processing method according to claim 1, characterized in that: After the step of performing a task trial run based on the specified task dependency and determining whether an abnormality occurs during the task trial run, the method further includes: If an abnormality occurs during the task trial run, obtain the abnormality information found during the task trial run; Determine the personnel involved in the preset tasks; Get the preset target notification method; Based on the target notification method, the abnormal information is sent to the task-related personnel.

8. A task processing device, characterized in that: include: A processing module, used to obtain the SQL statement of the online target task, and pre-process the SQL statement to obtain the corresponding first SQL statement; A segmentation module, used to segment the first SQL statement to obtain a corresponding second SQL statement; An extraction module, used for performing syntax analysis on the second SQL statement to extract table names and field names in the second SQL statement; A configuration module, used to configure the corresponding specified task dependency based on the table name and the field name; A judgment module, used to perform task trial operation processing based on the specified task dependency, and to judge whether an abnormality occurs during the task trial operation; A comparison module, configured to compare data of the specified task dependency with the first task dependency of the target task if no abnormality occurs during the task trial operation, to obtain a corresponding data comparison result; The early warning module is used to execute abnormal early warning processing corresponding to relevant personnel for the target task if the data comparison result is data inconsistency.

9. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the task processing method according to any one of claims 1 to 7 when executing the computer-readable instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by a processor, the steps of the task processing method according to any one of claims 1 to 7 are implemented.

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