WO2019144552A1

WO2019144552A1 - Data task processing method, application server and computer-readable storage medium

Info

Publication number: WO2019144552A1
Application number: PCT/CN2018/089192
Authority: WO
Inventors: 陈龙
Original assignee: 平安科技（深圳）有限公司
Priority date: 2018-01-24
Filing date: 2018-05-31
Publication date: 2019-08-01
Also published as: CN108427600B; CN108427600A

Abstract

Disclosed is a data task processing method, the method comprising: acquiring a task list from a terminal device; configuring a task relier so as to analyze a reliance relationship between data and a task; recording an execution process of data synchronization; judging whether data is synchronized according to the execution process of data synchronization, and the reliance relationship between the data and the task; if the data synchronization has been completed, executing the task for which the data synchronization has been completed; and if the data synchronization has not been completed, sending out pre-warning information. Also provided in the present application is an application server and a computer-readable storage medium. By means of the data task processing method, application server and computer-readable storage medium provided in the present application, whether data is synchronized can be judged according to the execution process of data synchronization and the reliance relationship between data and a task, so that the task can be executed only if the data synchronization is completed.

Description

Data task processing method, application server, and computer readable storage medium

Priority claim

This application claims priority to Chinese Patent Application No. 201810066359.7, filed on January 24, 2018, entitled "Data Task Processing Method, Application Server, and Computer Readable Storage Media", the contents of which are all passed. The citations are incorporated herein by reference.

Technical field

The present application relates to the field of data analysis, and in particular, to a data task processing method, an application server, and a computer readable storage medium.

Background technique

Hadoop is an open source distributed infrastructure that allows users to develop distributed programs without knowing the underlying details of the distribution. Hadoop implements a distributed file system that provides high transfer rates to access application data for applications with very large data sets. Usually, ozzie is used to implement task scheduling, but task scheduling based on individual ozzie cannot analyze the dependency relationship between data and tasks. For example, the task of the model can be executed after the data synchronization is completed for a period of time, but the data and task dependencies are controlled. Confusion, it is hard to find after a problem.

Summary of the invention

In view of this, the present application provides a data task processing method, an application server, and a computer readable storage medium, which can obtain a help document corresponding to a current page operation by analyzing the request help information, thereby improving a user experience.

First, in order to achieve the above object, the present application provides a data task processing method, which is applied to an application server, and the method includes:

Obtaining a task list from the terminal device;

Configuring the task relyer to analyze data and task dependencies;

Record the execution process of data synchronization;

Determining whether the data is synchronized according to the execution process of the data synchronization and the dependency relationship between the data and the task;

If the data has been synchronized, perform the task of completing the data synchronization;

If the data is not synchronized, an alert message is issued.

In addition, in order to achieve the above object, the present application further provides an application server, where the application server includes a memory, a processor, and a data task processing system executable on the processor, where the data task is stored. The processing system implements the following steps when executed by the processor:

Obtaining a task list from the terminal device;

Configuring the task relyer to analyze data and task dependencies;

Record the execution process of data synchronization;

If the data is not synchronized, an alert message is issued.

Further, to achieve the above object, the present application further provides a computer readable storage medium storing a data task processing system, the data task processing system being executable by at least one processor, such that The at least one processor performs the steps of the data task processing method as described above.

Compared with the prior art, the application server, the data task processing method, and the computer readable storage medium proposed by the present application firstly acquire a task list from a terminal device; and then configure the task relyer to analyze data and tasks. Dependency; then, recording the execution process of the data synchronization; further, determining whether the data is synchronized according to the execution process of the data synchronization and the dependency relationship between the data and the task; finally, if the data has been synchronized, performing the task of completing the data synchronization If the data is not synchronized, an alert message is issued. In this way, the defect of the dependency control of the data and the task in the prior art can be avoided, and the execution process of the data synchronization and the dependency relationship between the data and the task can be used to judge whether the data is synchronized, and the task can be executed only when the data is synchronized. .

DRAWINGS

1 is a schematic diagram of an optional application environment of each embodiment of the present application;

2 is a schematic diagram of an optional hardware architecture of the application server of FIG. 1;

3 is a schematic diagram of a program module of a first embodiment of a data task processing system of the present application;

4 is a schematic diagram of a program module of a second embodiment of the data task processing system of the present application;

FIG. 5 is a schematic flowchart diagram of a first embodiment of a data task processing method according to the present application;

6 is a schematic flowchart of a second embodiment of a data task processing method according to the present application;

The implementation, functional features and advantages of the present application will be further described with reference to the accompanying drawings.

Detailed ways

In order to make the objects, technical solutions, and advantages of the present application more comprehensible, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It is understood that the specific embodiments described herein are merely illustrative of the application and are not intended to be limiting. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present application without departing from the inventive scope are the scope of the present application.

It should be noted that the descriptions of "first", "second" and the like in the present application are for the purpose of description only, and are not to be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. . Thus, features defining "first" or "second" may include at least one of the features, either explicitly or implicitly. In addition, the technical solutions between the various embodiments may be combined with each other, but must be based on the realization of those skilled in the art, and when the combination of the technical solutions is contradictory or impossible to implement, it should be considered that the combination of the technical solutions does not exist. Nor is it within the scope of protection required by this application.

Referring to FIG. 1 , it is a schematic diagram of an optional application environment of each embodiment of the present application.

In this embodiment, the present application is applicable to an application environment including, but not limited to, the terminal device 1, the application server 2, and the network 3. The terminal device 1 may be a mobile phone, a smart phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a navigation device, an in-vehicle device, etc. Mobile devices such as, and fixed terminals such as digital TVs, desktop computers, notebooks, servers, and the like. The application server 2 may be a computing device such as a rack server, a blade server, a tower server, or a rack server. The application server 2 may be a stand-alone server or a server cluster composed of multiple servers. The network 3 may be an intranet, an Internet, a Global System of Mobile communication (GSM), a Wideband Code Division Multiple Access (WCDMA), a 4G network, Wireless or wired networks such as 5G networks, Bluetooth, Wi-Fi, and call networks.

The application server 2 is respectively connected to one or more of the terminal devices 1 through the network 3 for data transmission and interaction.

Referring to FIG. 2, it is a schematic diagram of an optional hardware architecture of the application server 2 in FIG.

In this embodiment, the application server 2 may include, but is not limited to, the memory 11, the processor 12, and the network interface 13 being communicably connected to each other through a system bus. It is pointed out that Figure 1 only shows the application server 2 with components 11-13, but it should be understood that not all illustrated components may be implemented, and more or fewer components may be implemented instead.

The memory 11 includes at least one type of readable storage medium including a flash memory, a hard disk, a multimedia card, a card type memory (eg, SD or DX memory, etc.), and a 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 disk, and the like. In some embodiments, the memory 11 may be an internal storage unit of the application server 2, such as a hard disk or memory of the application server 2. In other embodiments, the memory 11 may also be an external storage device of the application server 2, such as a plug-in hard disk equipped on the application server 2, a smart memory card (SMC), and a secure digital number. (Secure Digital, SD) card, flash card, etc. Of course, the memory 11 can also include both the internal storage unit of the application server 2 and its external storage device. In this embodiment, the memory 11 is generally used to store an operating system installed in the application server 2 and various types of application software, such as program code of the data task processing system 200. Further, the memory 11 can also be used to temporarily store various types of data that have been output or are to be output.

The processor 12 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data processing chip in some embodiments. The processor 12 is typically used to control the overall operation of the application server 2. In this embodiment, the processor 12 is configured to run program code or process data stored in the memory 11, such as running the data task processing system 200 and the like.

The network interface 13 may comprise a wireless network interface or a wired network interface, which is typically used to establish a communication connection between the application server 2 and other electronic devices. In this embodiment, the network interface 13 is mainly used to connect the application server 2 to one or more of the terminal devices 1 through the network 3, and the application server 2 and the one or more terminals. A data transmission channel and a communication connection are established between the devices 1.

So far, the application environment of the various embodiments of the present application and the hardware structure and functions of related devices have been described in detail. Hereinafter, various embodiments of the present application will be proposed based on the above-described application environment and related devices.

First, the present application proposes a data task processing system 200.

Referring to FIG. 3, it is a program module diagram of the first embodiment of the data task processing system 200 of the present application.

In this embodiment, the data task processing system 200 includes a series of computer program instructions stored in the memory 11, and when the computer program instructions are executed by the processor 12, the data task processing operations of the embodiments of the present application may be implemented. . In some embodiments, data task processing system 200 can be divided into one or more modules based on the particular operations implemented by the various portions of the computer program instructions. For example, in FIG. 3, the data task processing system 200 can be divided into an acquisition module 201, a configuration module 202, a recording module 203, a determination module 204, an execution module 205, and an early warning module 206. among them:

The obtaining module 201 is configured to acquire a task list from the terminal device 1.

Specifically, the application server 2 has a Hadoop data platform center built therein, and the Hadoop data platform center acquires data from the external terminal device 1, and when the application server 2 performs data processing according to the data acquired by the Hadoop data platform center, Data acquisition, data cleaning, data analysis and other operations are required. Each process may involve multiple tasks, some need to be executed sequentially, and some may be executed in parallel.

In this embodiment, the application server 2 acquires a task list from the terminal device 1 through the acquisition module 201. The application server 2 manages the execution and order of these tasks through oozie. Oozie is a Hadoop-based scheduler that writes the scheduling process in the form of xml. It can schedule mr, pig, hive, shell, jar, and so on. The application server 2 executes the task flow node in the order of oozie, supports fork (multiple branches), and join (combines multiple nodes into one).

The configuration module 202 is configured to configure a relying party of the task in the task list to configure a dependency relationship between the data and the task.

Specifically, the task dependant is configured to configure the dependency relationship between the data and the task, and only the task with complete data can be executed. In this embodiment, the application server 2 obtains a valid reer (dependency) configuration of the task flow node fork (branching multiple nodes), and executes a resume state query statement to output the original result, thereby merging the plurality of task nodes, and supplementing Fully dependent on the state, and the result of the dependency is de-duplicated. Finally, the de-duplicated dependency result is labeled with the configuration slice tag, and the scheduling dependency of all tasks is completed.

Please refer to Table 1, which is the dependency configuration format requirement in this embodiment.

Table 1

In this embodiment, the application server 2 loads the configuration file by using the hive load, overwrites the configuration table, and collects the latest configuration file from the production environment, and then deploys the configuration and deploys the command to implement the configuration dependent:

Step1: Upload the script and authorize, format (allow private users to operate), upload to /tmp directory

Chmod 777/tmp/relier_config_all.txt

Step2: Switch users (if your private user allows you to execute the hive command, you can not switch)

Sudo su-hduser0006

Step3: Execute the command

Hive-e"use aml_awbs;set mapred.job.queue.name=queue_0006_02;

Truncate table fm_relier_check_script;

Load data local inpath'/tmp/relier_config_all.txt'into table aml_awbs.fm_relier_check_script;"

In another embodiment of the invention, the implementation configuration dependency can be modified by modifying the configuration deployment command:

Step1: Switch users (if your private user allows you to execute the hive command, you can not switch)

Sudo su-hduser0006

Step2: Execute the command

Hive-e"set mapred.job.queue.name=queue_0006_02;

Insert overwrite table aml_awbs.fm_relier_check_script

Select relier_name,

Src_job_name,

If(relier_name='i_jt-aml-999-cd',

'select concat(y,m,d)datestr,\'Y\'state from aml_awbs.JOB_STATE where JOB_NAME=\'jt-aml-999-cd\",

Relier_name)script_string,

Fork

From aml_awbs.fm_relier_check_script"

The recording module 203 is configured to record an execution process of data synchronization of the task.

Specifically, it can be seen from the above that only the task with complete data can be executed, so in order to ensure that the data of the Hadoop data platform center from the external terminal device 1 is complete, when the data is updated or modified, the application server 2 The execution process of data synchronization is recorded by the recording module 203. In this embodiment, the recording module 203 uses a shell to create a log and a status table, and records the execution process of the data synchronization and the execution time of the data synchronization.

The determining module 204 is configured to determine, according to the execution process of the data synchronization and the dependency relationship between the data and the task, whether the data is synchronized.

Specifically, before executing the task, the application server 2 first determines whether the data has been synchronized by the determining module 204. The application server 2 determines whether the data is synchronized according to the execution process of the data synchronization recorded in the log and the status table, the execution time of the data synchronization, and the dependency relationship between the data and the task.

The executing module 205 is configured to perform a task of completing data synchronization when data has been synchronized.

The warning module 206 is configured to issue an early warning message if the data is not synchronized.

Specifically, the execution module 205 performs the task only when the data is synchronized, that is, the data is complete. The warning module 206 sends the warning information when the data is not synchronized. In this embodiment, the warning information includes, but is not limited to, data information that has not been synchronized, time of the last synchronization, and the like, to notify the staff. Manual intervention.

Through the above program modules 201-206, the data task processing system 200 proposed by the present application firstly acquires a task list from the terminal device 1; then, configures the task relyer to analyze the dependency relationship between the data and the task; and then, records The execution process of the data synchronization; further, determining whether the data is synchronized according to the execution process of the data synchronization and the dependency relationship between the data and the task; finally, if the data has been synchronized, performing the task of completing the data synchronization; if the data is not completed , issued an early warning message. In this way, the defect of the dependency control of the data and the task in the prior art can be avoided, and the execution process of the data synchronization and the dependency relationship between the data and the task can be used to judge whether the data is synchronized, and the task can be executed only when the data is synchronized. .

Further, based on the above-described first embodiment of the data task processing system 200 of the present application, a second embodiment of the present application (shown in FIG. 4) is proposed. In this embodiment, the data task processing system 200 further includes a sorting module 207, where

The obtaining module 201 is further configured to acquire a waiting running task;

As apparent from the above, in the first embodiment, the task of completing the data synchronization is performed only when the data synchronization is completed. In this embodiment, the tasks include, but are not limited to, a round running task and a heavy running task. A round-robin task refers to a task that is executed cyclically within an effective date. A re-run task refers to a task that needs to be re-executed after a failed execution.

Specifically, the application server 2 obtains the waiting round running task through the obtaining module 201, and determines whether the dependent configuration is satisfied, and analyzes the valid round running date series of the task, in the case that the dependent configuration is satisfied. In the embodiment, the round running task sequence is based on the working day or the natural day series, and the default setting round running sequence length is up to 730 days in the past.

Please refer to Table 2 for the configuration requirements for the round-trip task:

Table 2

In this embodiment, the code for implementing the round running task is:

Insert the configuration table:

Sudo su-hduser0006

Step2: Execute the command

The obtaining module 201 is further configured to acquire a re-running task that is waiting;

Specifically, please refer to Table 3, which is a configuration requirement of the re-run task in an implementation of the present application:

table 3

In this embodiment, the code for implementing the re-run task is:

Insert the configuration table:

Sudo su-hduser0006

Step2: Execute the command

Hive-e"set mapred.job.queue.name=queue_0006_02;

Insert into table aml_awbs.fm_model_task_rerun_set

Select'ky', 'zq', '1214-25', '20141202', 'y', 'y', '1.0' from default.dual"

The sorting module 207 is further configured to sort the round running task and the heavy running task according to a priority level.

The execution module 205 is further configured to preferentially execute a task with a high level.

Specifically, in this embodiment, the sorting module 207 prioritizes the round running task and the heavy running task according to the chronological order of the obtaining tasks. It can be understood that in other embodiments of the present application, the priority level requirement can be set according to actual needs.

The warning module 206 is further configured to monitor a currently executed task, and issue an early warning when an abnormality occurs during the execution of the task.

Specifically, the application server 2 monitors the currently executed task through the early warning module 206. When an abnormality occurs during the execution of the task, an early warning is issued to notify the staff to process in time.

Through the above-mentioned program module 207, the data task processing system 200 proposed by the present application may further sort the acquired round running task and the heavy running task according to the priority level, preferentially execute the high level task, and monitor the current execution. The task, when an abnormality occurs during the execution of the task, issues an early warning to achieve the supervisory task.

In addition, the present application also proposes a data task processing method.

Referring to FIG. 5, it is a schematic flowchart of the first embodiment of the data task processing method of the present application. In this embodiment, the order of execution of the steps in the flowchart shown in FIG. 5 may be changed according to different requirements, and some steps may be omitted.

Step S301, the task list is acquired from the terminal device 1.

In this embodiment, the application server 2 acquires a task list from the terminal device 1. The application server 2 manages the execution and order of these tasks through oozie. Oozie is a Hadoop-based scheduler that writes the scheduling process in the form of xml. It can schedule mr, pig, hive, shell, jar, and so on. The application server 2 executes the task flow node in the order of oozie, supports fork (multiple branches), and join (combines multiple nodes into one).

Step S302, configuring a relying party of the task in the task list to configure a dependency relationship between the data and the task.

Table 1

Chmod 777/tmp/relier_config_all.txt

Sudo su-hduser0006

Step3: Execute the command

Hive-e"use aml_awbs;set mapred.job.queue.name=queue_0006_02;

Truncate table fm_relier_check_script;

Sudo su-hduser0006

Step2: Execute the command

Hive-e"set mapred.job.queue.name=queue_0006_02;

Insert overwrite table aml_awbs.fm_relier_check_script

Select relier_name,

Src_job_name,

If(relier_name='i_jt-aml-999-cd',

Relier_name)script_string,

Fork

From aml_awbs.fm_relier_check_script"

Step S303, recording an execution process of data synchronization of the task.

Specifically, it can be seen from the above that only the task with complete data can be executed, so in order to ensure that the data of the Hadoop data platform center from the external terminal device 1 is complete, when the data is updated or modified, the application server 2 Record the execution process of data synchronization. In this embodiment, the application server 2 uses a shell to create a log and a status table, and records the execution process of the data synchronization and the execution time of the data synchronization.

Step S304, determining whether the data is synchronized according to the execution process of the data synchronization and the dependency relationship between the data and the task.

Specifically, before executing the task, the application server 2 first determines whether the data has been synchronized. The application server 2 determines whether the broken data is completed according to the execution process of the data synchronization recorded in the log and the status table, the execution time of the data synchronization, and the dependency relationship between the data and the task.

Step S305, when the data has been synchronized, the task of completing the data synchronization is performed.

Step S306, if the data is not synchronized, an early warning message is issued.

Specifically, the application server 2 performs the task only when the data is synchronized, that is, when the data is complete. When the data is not synchronized, the application server 2 sends an alert message. In this embodiment, the alert information includes, but is not limited to, data information that has not been synchronized, time of the last synchronization, and the like, to notify the staff. Manual intervention.

Through the above steps S301-306, the data task processing method proposed by the present application firstly acquires a task list from the terminal device 1; then, configures the task relyer to analyze the dependency relationship between the data and the task; and then, records the data synchronization. Execution process; further, determining whether the data is synchronized according to the execution process of the data synchronization and the dependency relationship between the data and the task; finally, if the data has been synchronized, performing the task of completing the data synchronization; if the data is not synchronized, issuing Early warning information. In this way, the defect of the dependency control of the data and the task in the prior art can be avoided, and the execution process of the data synchronization and the dependency relationship between the data and the task can be used to judge whether the data is synchronized, and the task can be executed only when the data is synchronized. .

Further, based on the above first embodiment of the data task processing method of the present application, a second embodiment of the data task processing method of the present application is proposed.

FIG. 6 is a schematic flowchart diagram of a second embodiment of a data task processing method of the present application. In this embodiment, the method further includes the following steps:

Step S401, acquiring a waiting running task;

As apparent from the above, in the first embodiment, the task is executed only when the data synchronization is completed. In this embodiment, the tasks include, but are not limited to, a round running task and a heavy running task. A round-robin task refers to a task that is executed cyclically within an effective date. A re-run task refers to a task that needs to be re-executed after a failed execution.

Specifically, the application server 2 acquires the waiting round running task, and determines whether the relying party configuration is satisfied, and analyzes the effective round running date series of the task on the premise that the relying party configuration is satisfied. In this embodiment, the round running The task sequence is based on the weekday or natural day series. The default setting of the round run sequence length is up to 730 days.

Table 2

In this embodiment, the code for implementing the round running task is:

Insert the configuration table:

Sudo su-hduser0006

Step2: Execute the command

Step S402, acquiring a re-running task that is waiting;

table 3

In this embodiment, the code for implementing the re-run task is:

Insert the configuration table:

Sudo su-hduser0006

Step2: Execute the command

Hive-e"set mapred.job.queue.name=queue_0006_02;

Insert into table aml_awbs.fm_model_task_rerun_set

Select'ky', 'zq', '1214-25', '20141202', 'y', 'y', '1.0' from default.dual"

Step S403, sorting the round running task and the running running task according to a priority level.

In step S404, the task with a high level is preferentially executed.

Specifically, in the embodiment, the application server 2 prioritizes the round running task and the heavy running task according to the chronological order of the obtaining tasks. It can be understood that in other embodiments of the present application, the priority level requirement can be set according to actual needs.

Step S405, monitoring the currently executed task, and issuing an early warning when an abnormality occurs during the execution of the task.

Specifically, the application server 2 monitors the currently executed task, and when an abnormality occurs during the execution of the task, an early warning is issued to notify the staff to process in time.

Through the above steps S401-S405, the data task processing method proposed by the present application may further sort the acquired round running task and the heavy running task according to the priority level, preferentially execute the high level task, and monitor the current execution. The task, when an abnormality occurs during the execution of the task, issues an early warning to achieve the supervisory task.

The serial numbers of the embodiments of the present application are merely for the description, and do not represent the advantages and disadvantages of the embodiments.

Through the description of the above embodiments, those skilled in the art can clearly understand that the foregoing embodiment method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be through hardware, but in many cases, the former is better. Implementation. Based on such understanding, the technical solution of the present application, which is essential or contributes to the prior art, may be embodied in the form of a software product stored in a storage medium (such as ROM/RAM, disk, The optical disc includes a number of instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the methods described in various embodiments of the present application.

The above is only a preferred embodiment of the present application, and is not intended to limit the scope of the patent application, and the equivalent structure or equivalent process transformations made by the specification and the drawings of the present application, or directly or indirectly applied to other related technical fields. The same is included in the scope of patent protection of this application.

Claims

A data task processing method is applied to an application server, and the method includes:

Obtaining a task list from the terminal device;

Configuring a relying party of tasks in the task list to analyze data and task dependencies;

Recording an execution process of data synchronization of the task;

Determining whether the data is synchronized according to the execution process of the data synchronization and the dependency relationship between the data and the task;

If the data has been synchronized, perform the task of completing the data synchronization;

If the data is not synchronized, an alert message is issued.
The data task processing method according to claim 1, wherein the step of configuring a relying party of the task in the task list to analyze a dependency relationship between the data and the task comprises the following steps:

Obtaining an effective dependency configuration of the process node of the task;

Execute a dependency state query statement and output the original dependency result;

Merging multiple task nodes, completing the dependency state, and deduplicating the dependency result;

Labeling the de-duplicated dependency results with the dependency configuration slice tag completes the analysis of the dependencies of all tasks.
The data task processing method according to claim 1, wherein the step of performing a task of completing data synchronization, if the data has been synchronized, comprises the following steps:

Obtain the waiting for running and re-running tasks;

Performing the round running task and the running back task.
The data task processing method according to claim 1, wherein said warning information includes data information that has not been synchronized and a time of the last synchronization.
The data task processing method according to claim 3, wherein before the step of executing the round running task and the running task, the method further comprises the following steps:

Sorting the round running task and the running task according to a priority level;

Priority is given to performing high-level tasks.
The data task processing method according to claim 5, wherein the round running task and the heavy running task are prioritized according to a chronological order of the obtaining tasks.
The data task processing method according to claim 5, wherein the method further comprises the following steps:

Monitor the currently executing tasks;

An alert is issued when an exception occurs during the execution of the task.
An application server, comprising: a memory, a processor, on the memory, a data task processing system operable on the processor, wherein the data task processing system is used by the processor The following steps are implemented during execution:

Obtaining a task list from the terminal device;

Configuring the task relyer to analyze data and task dependencies;

Record the execution process of data synchronization;

Determining whether the data is synchronized according to the execution process of the data synchronization and the dependency relationship between the data and the task;

If the data has been synchronized, perform the task of completing the data synchronization;

If the data is not synchronized, an alert message is issued.
The application server according to claim 8, wherein the step of configuring a relying party of the task in the task list to analyze the dependency relationship between the data and the task comprises the following steps:

Obtaining an effective dependency configuration of the process node of the task;

Execute a dependency state query statement and output the original dependency result;

Merging multiple task nodes, completing the dependency state, and deduplicating the dependency result;

Labeling the de-duplicated dependency results with the dependency configuration slice tag completes the analysis of the dependencies of all tasks.
The application server according to claim 8, wherein the step of performing the task of completing the data synchronization, if the data has been synchronized, comprises the following steps:

Obtain the waiting for running and re-running tasks;

Performing the round running task and the running back task.
The application server according to claim 8, wherein said warning information includes data information that has not been synchronized and a time of the last synchronization.
The application server according to claim 10, wherein before the step of executing the round running task and the running task, the method further comprises the following steps:

Sorting the round running task and the running task according to a priority level;

Priority is given to performing high-level tasks.
The application server according to claim 12, wherein the round running task and the heavy running task are prioritized according to a chronological order of obtaining tasks.
The application server according to claim 12, wherein when the data task processing system is executed by the processor of the application server, the following steps are further implemented:

Monitor the currently executing tasks;

An alert is issued when an exception occurs during the execution of the task.
A computer readable storage medium storing a data task processing system, the data task processing system being executable by at least one processor to cause the at least one processor to perform the following steps:

Obtaining a task list from the terminal device;

Configuring the task relyer to analyze data and task dependencies;

Record the execution process of data synchronization;

Determining whether the data is synchronized according to the execution process of the data synchronization and the dependency relationship between the data and the task;

If the data has been synchronized, perform the task of completing the data synchronization;

If the data is not synchronized, an alert message is issued.
The computer readable storage medium according to claim 15, wherein the step of configuring a relying party of the task in the task list to analyze a dependency relationship between the data and the task comprises the following steps:

Obtaining an effective dependency configuration of the process node of the task;

Execute a dependency state query statement and output the original dependency result;

Merging multiple task nodes, completing the dependency state, and deduplicating the dependency result;

Labeling the de-duplicated dependency results with the dependency configuration slice tag completes the analysis of the dependencies of all tasks.
The computer readable storage medium according to claim 15, wherein the step of performing a task of completing data synchronization if the data has been synchronized is completed, and specifically includes the following steps:

Obtain the waiting for running and re-running tasks;

Performing the round running task and the running back task.
The computer readable storage medium according to claim 17, wherein said step of performing said round running task and said rerunning task further comprises the steps of:

Sorting the round running task and the running task according to a priority level;

Priority is given to performing high-level tasks.
The computer readable storage medium according to claim 18, wherein the round running task and the heavy running task are prioritized according to a chronological order of obtaining tasks.
The computer readable storage medium of claim 18, wherein when the data task processing system is executed by the processor, the following steps are further implemented:

Monitor the currently executing tasks;

An alert is issued when an exception occurs during the execution of the task.