CN111400017A - Distributed complex task scheduling method - Google Patents
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- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
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Abstract
A distributed complex task scheduling method defines complex tasks by using a task tree, the hierarchical relationship of each node in the task tree represents the dependency relationship of the tasks, and the task tree is divided into a common task tree and a hierarchical task tree; generating a construction template of the task tree according to a rule engine, and constructing the task tree layer by layer from top to bottom through the construction template, wherein each node in the task tree has a unique ID; storing the task tree into a relational database; the method comprises the steps that a distributed architecture is adopted to divide nodes in a scheduling cluster into main nodes and common nodes, and the main nodes distribute task information in a scheduling queue and send the task information to the common nodes through a message queue; the common node executes the task information and sends an execution result to the main node through a message queue; when a certain task node fails to execute in the scheduling process, the scheduling of the whole task tree is stopped, and manual operation can be executed for the task which fails to be scheduled. The method makes the development process of the complex business into a template, and can greatly improve the development efficiency.
Description
Technical Field
The invention belongs to the technical field of distributed scheduling, and particularly relates to a distributed complex task scheduling method.
Background
Products that are relatively well known in the task scheduling art are: quartz, xxl-joba, and the like. However, the application scenarios of these task scheduling products are mainly: the timed scheduling of the tasks, i.e. the execution time of the arriving tasks, automatically triggers the execution of the tasks or the periodic automatic execution of the configuration tasks. xxl-jobs carries out distributed scheduling by dividing the nodes of the cluster into a scheduling center and an execution node, but does not solve the problems that logical precedence relationship exists among subtasks in scheduling, the logical relationship is required to be scheduled in advance for previous tasks, and how to combine a plurality of subtasks to generate a complex task and provide an integral interface service for the outside.
Disclosure of Invention
The technical problem to be solved by the invention is to overcome the defects of the prior art, provide a distributed complex task scheduling method, template the development process of complex services and greatly improve the development efficiency.
The invention provides a distributed complex task scheduling method, which comprises the following steps,
step S1, defining a complex task by using a task tree, wherein the hierarchical relationship of each node in the task tree represents the dependency relationship of the task, and the task tree is divided into a common task tree and a hierarchical task tree;
step S2, generating a construction template of the task tree according to the rule engine, and constructing the task tree layer by layer from top to bottom through the construction template, wherein each node in the task tree has a unique ID; and persistently storing the task tree into a relational database;
step S3, dividing the nodes in the dispatching cluster into main nodes and common nodes by adopting a distributed architecture, distributing task information in a dispatching queue by the main nodes, and sending the task information to the common nodes through a message queue; the common node is responsible for executing the task information and sending the task execution result to the main node through the message queue;
step S4, when a task node fails to execute in the scheduling process, the scheduling of the whole task tree may be terminated, and for the task that fails to be scheduled, manual operation may be performed.
As a further technical scheme of the invention, the nodes of the common task tree are divided into a root task, an intermediate task and an atomic task, wherein the root task is the root node of the task tree and is the task to be executed finally in all the task trees; the atomic task is a leaf node of the task tree and is the task executed firstly in the task tree; the intermediate tasks are non-atomic and non-root tasks in the task tree, and execution of the intermediate tasks depends on atoms and other intermediate tasks.
Furthermore, only one task node may be in a layer of the hierarchical task tree, which means that the task node at the upper layer of the layer must wait for the completion of the execution of the node before being executed.
Furthermore, the construction process of the task tree is decoupled from the execution process of each task, so that multiplexing of a single task and multiplexing of part of task branches in the task tree are realized, the construction of the task tree defines the execution sequence and the dependency relationship of each task, and simultaneously entry parameters for task execution are saved.
Further, the nodes in the scheduling cluster dynamically select the master node through the ZooKeeper.
Further, the specific process of step S3 is,
step S31, after the task tree is built, the main node or the common node puts the atomic task into a scheduling queue, the main node of the scheduling cluster polls the scheduling queue to take out the task from the scheduling queue, and sends the task reaching the execution condition to a message queue, and the task not reaching the execution condition is not processed to wait for the next scheduling;
step S32, after receiving the message of the master node, the common node queries complete task information and executes specific task scheduling logic; after the task is executed, the execution result of the task is sent to a message queue;
and step S33, after receiving the message of the common node, the main node determines whether to continue to execute the scheduling of the parent task according to the execution result of the task. If the task is successfully executed and the brother tasks of the task are successfully executed, executing parent task scheduling; if the task execution fails, the scheduling of the whole task tree is terminated;
step S34, executing task tree scheduling strategies, wherein the task tree scheduling strategies comprise two scheduling strategies of concurrent scheduling and sequential scheduling;
and step S35, the task execution completes triggering callback, and the content of the callback is defined by the user for each task.
Furthermore, the tasks which are scheduled to reach the execution condition concurrently can be scheduled to be executed, the sequence scheduling means that all the tasks must be executed in series, and the tasks which reach the execution condition comprise an atomic task and an intermediate task which is triggered to be executed.
Further, the manual operation comprises manual redo, manual successful placement, manual failed placement and task tree check;
the manual redo is to trigger the re-execution of the task for the task which fails to be scheduled, and trigger the task tree to continue to execute if the task is successfully executed; the task can be redone again if the task fails to be executed;
the manual successful placement is that for the task which fails in scheduling, the execution state of the task is modified into the manual successful placement, and the task tree is triggered to continue execution; each failed task can only execute one manual successful setting operation;
the manual setting failure is to modify the execution state of the task into the manual setting failure and modify the state of the root task into the manual setting failure for the task with failed scheduling. The manual setting failure means that the whole task tree fails to be executed, and each task tree can be manually set to fail only once;
the task tree checking means that access participation, execution state and abnormal information in the task execution process are recorded in the task scheduling process, and the execution information of the task tree can be checked according to the task Id.
The invention can organize the complex service logic into a unified external interface, and can decouple the service logic from the specific service realization so as to realize the multiplexing of the service logic and the service realization; the user only needs to pay attention to the writing of the business logic layer and the specific implementation of a single task, the system can automatically complete the scheduling of the task and can output the specific execution details of each subtask in the complex task, and the method is suitable for the business scene with the complex business process.
By the method, the development process of the complex business can be templated, and the development efficiency is greatly improved. Meanwhile, a series of manual operation functions are provided, the execution flow of the complex service can be controlled and the failure retry can be carried out, and the robustness of the service system is improved.
Drawings
FIG. 1 is a block diagram of a generic task tree structure of the present invention;
FIG. 2 is a block diagram of a hierarchical task tree structure of the present invention;
FIG. 3 is a block diagram of the overall architecture of the present invention.
Detailed Description
Referring to fig. 3, the present embodiment provides a distributed complex task scheduling method, including the following steps,
step S1, defining a complex task by using a task tree, wherein the hierarchical relationship of each node in the task tree represents the dependency relationship of the task, and the task tree is divided into a common task tree and a hierarchical task tree;
step S2, generating a construction template of the task tree according to the rule engine, and constructing the task tree layer by layer from top to bottom through the construction template, wherein each node in the task tree has a unique ID; and persistently storing the task tree into a relational database;
step S3, dividing the nodes in the dispatching cluster into main nodes and common nodes by adopting a distributed architecture, distributing task information in a dispatching queue by the main nodes, and sending the task information to the common nodes through a message queue; the common node is responsible for executing the task information and sending the task execution result to the main node through the message queue;
step S4, when a task node fails to execute in the scheduling process, the scheduling of the whole task tree may be terminated, and for the task that fails to be scheduled, manual operation may be performed.
As shown in FIG. 1, 4 nodes are arranged in the task tree, R represents a root node, M1 represents an intermediate node, L1 and L2 represent atomic nodes, wherein L1 and L2 do not depend on other nodes and can be executed concurrently, M1 depends on L2, R depends on L1 and M1, and the dependent nodes can be executed after the dependent nodes are required to be executed.
As shown in FIG. 2, the hierarchical task tree is defined as follows, wherein R represents a root node, M1 and M2 represent middle nodes, L1 represents an atomic node, L1 is executed independently of other nodes, M1 and M2 depend on L1, and R depends on M1 and M2.
The key information of the task tree record in step S3 is shown in table 1 below,
| field(s) | Means of |
| taskId | Task ID |
| fatherTaskId | Parent task ID |
| rootTaskId | Root task ID |
| taskType | Node type (virtual node, real node with virtual node) |
| taskStatus | Task execution state |
| inParam | Task participation |
| outParam | Task participation |
TABLE 1 mission Tree Key information Table
The construction process of the task tree is decoupled from the execution process of each task so as to realize multiplexing of a single task and multiplexing of part of task branches in the task tree, the construction of the task tree defines the execution sequence and the dependency relationship of each task, and simultaneously, the entry parameters of task execution are saved.
And the nodes in the dispatching cluster dynamically select the main nodes through the ZooKeeper.
The task node can configure execution time (such as transaction day, 9:00-11:30,13: 00-15: 00 in the morning), the master node judges the execution time of the task when distributing the task, the task is not distributed to the slave node when the execution time of the task is reached, and the task is not distributed until the execution time of the task is reached.
The specific process of step S3 is,
step S31, after the task tree is built, the main node or the common node puts the atomic task into a scheduling queue, the main node of the scheduling cluster polls the scheduling queue to take out the task from the scheduling queue, and sends the task reaching the execution condition to a message queue, and the task not reaching the execution condition is not processed to wait for the next scheduling;
step S32, after receiving the message of the master node, the common node queries complete task information and executes specific task scheduling logic; after the task is executed, the execution result of the task is sent to a message queue;
and step S33, after receiving the message of the common node, the main node determines whether to continue to execute the scheduling of the parent task according to the execution result of the task. If the task is successfully executed and the brother tasks of the task are successfully executed, executing parent task scheduling; if the task execution fails, the scheduling of the whole task tree is terminated;
step S34, executing task tree scheduling strategies, wherein the task tree scheduling strategies comprise two scheduling strategies of concurrent scheduling and sequential scheduling;
and step S35, the task execution completes triggering callback, and the content of the callback is defined by the user for each task.
The tasks which are dispatched in a concurrent mode and reach the execution condition can be dispatched in a concurrent mode, the tasks which reach the execution condition are dispatched in a sequential mode, all the tasks are dispatched in a serial mode, the tasks which reach the execution condition comprise atomic tasks and intermediate tasks which are triggered to execute, and taking the task tree shown in the figure 1 as an example, the tasks are dispatched in a concurrent mode, the execution sequence of the tasks under the dispatching strategy is L1, L2- > M1- > R, it can be seen that L1 and L2 can be executed in a concurrent mode.
And (2) sequentially scheduling, wherein the execution sequence of tasks under the scheduling strategy is L1- > L2- > M1- > R, and it can be seen that L1 and L2 are sequentially executed, the sequential scheduling mainly aims at some service scenes, and the simultaneous execution of write operations brings about service problems, and the service problems are solved through the sequential scheduling in such a scene.
The manual operation comprises manual redo, manual successful placement, manual failed placement and task tree check;
the manual redo is to trigger the re-execution of the task for the task which fails to be scheduled, and trigger the task tree to continue to execute if the task is successfully executed; the task can be redone again if the task fails to be executed;
the manual successful placement is that for the task which fails in scheduling, the execution state of the task is modified into the manual successful placement, and the task tree is triggered to continue execution; each failed task can only execute one manual successful setting operation;
the manual setting failure is to modify the execution state of the task into the manual setting failure and modify the state of the root task into the manual setting failure for the task with failed scheduling. The manual setting failure means that the whole task tree fails to be executed, and each task tree can be manually set to fail only once;
the task tree checking means that access participation, execution state and abnormal information in the task execution process are recorded in the task scheduling process, and the execution information of the task tree can be checked according to the task Id.
The embodiment is applied to a distributed complex task scheduling system DATD. The system uses easy rules as a rule engine to perform task orchestration; using mysql as a relational database for storing a task tree and task scheduling parameters; using redis as a task scheduling queue to store tasks to be scheduled; and sending task scheduling notifications among various scheduling nodes by using kafka as a message queue. And selecting a scheduling node from the cluster nodes by using a ZooKeeper selection master.
The DATD framework developed by the embodiment is applied to a security industry comprehensive service processing system, bears a plurality of important services such as real-time account opening, client combination account cancellation, scientific creation board opening and the like, greatly improves the service development efficiency, reduces the operation and maintenance cost, and achieves better effect.
The foregoing illustrates and describes the principles, general features, and advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are intended to further illustrate the principles of the invention, and that various changes and modifications may be made without departing from the spirit and scope of the invention, which is intended to be protected by the appended claims. The scope of the invention is defined by the claims and their equivalents.
Claims (8)
1. A distributed complex task scheduling method is characterized by comprising the following steps,
step S1, defining a complex task by using a task tree, wherein the hierarchical relationship of each node in the task tree represents the dependency relationship of the task, and the task tree is divided into a common task tree and a hierarchical task tree;
step S2, generating a construction template of the task tree according to the rule engine, and constructing the task tree layer by layer from top to bottom through the construction template, wherein each node in the task tree has a unique ID; and persistently storing the task tree into a relational database;
step S3, dividing the nodes in the dispatching cluster into main nodes and common nodes by adopting a distributed architecture, distributing task information in a dispatching queue by the main nodes, and sending the task information to the common nodes through a message queue; the common node is responsible for executing the task information and sending the task execution result to the main node through the message queue;
step S4, when a task node fails to execute in the scheduling process, the scheduling of the whole task tree may be terminated, and for the task that fails to be scheduled, manual operation may be performed.
2. The distributed complex task scheduling method according to claim 1, wherein the nodes of the common task tree are divided into a root task, an intermediate task and an atomic task, and the root task is a root node of the task tree and is a task to be executed last in all task trees; the atomic task is a leaf node of the task tree and is the task executed firstly in the task tree; the intermediate tasks are non-atomic and non-root tasks in the task tree, and execution of the intermediate tasks depends on atoms and other intermediate tasks.
3. The distributed complex task scheduling method according to claim 1, wherein only one task node in a layer of the hierarchical task tree indicates that a task node at an upper layer of the layer must wait for the completion of the execution of the task node before being executed.
4. The distributed complex task scheduling method according to claim 1, wherein a construction process of the task tree is decoupled from an execution process of each task to realize multiplexing of a single task and multiplexing of part of task branches in the task tree, the construction of the task tree defines an execution sequence and a dependency relationship of each task, and meanwhile entry parameters for task execution are saved.
5. The distributed complex task scheduling method of claim 1, wherein the nodes in the scheduling cluster dynamically select the master node through ZooKeeper.
6. The distributed complex task scheduling method according to claim 1, wherein the specific process of step S3 is,
step S31, after the task tree is built, the main node or the common node puts the atomic task into a scheduling queue, the main node of the scheduling cluster polls the scheduling queue to take out the task from the scheduling queue, and sends the task reaching the execution condition to a message queue, and the task not reaching the execution condition is not processed to wait for the next scheduling;
step S32, after receiving the message of the master node, the common node queries complete task information and executes specific task scheduling logic; after the task is executed, the execution result of the task is sent to a message queue;
step S33, after receiving the message of the common node, the main node determines whether to continue to execute the scheduling of the father task according to the execution result of the task;
if the task is successfully executed and the brother tasks of the task are successfully executed, executing parent task scheduling; if the task execution fails, the scheduling of the whole task tree is terminated;
step S34, executing task tree scheduling strategies, wherein the task tree scheduling strategies comprise two scheduling strategies of concurrent scheduling and sequential scheduling;
and step S35, the task execution completes triggering callback, and the content of the callback is defined by the user for each task.
7. The distributed complex task scheduling method according to claim 6, wherein the tasks that arrive at the execution condition by the concurrent scheduling can be executed by the concurrent scheduling, the sequential scheduling is that all the tasks must be executed serially, and the tasks that arrive at the execution condition include an atomic task and an intermediate task that is triggered to be executed.
8. The distributed complex task scheduling method according to claim 1, wherein the manual operations include manual redo, manual successful placement, manual failed placement, and task tree check;
the manual redoing is to trigger the re-execution of the tasks for the tasks with failed scheduling, and trigger the task tree to continue executing if the tasks are successfully executed; the task can be redone again if the task fails to be executed;
the manual successful placement is that for the task which is failed in scheduling, the execution state of the task is modified to be the manual successful placement, and a task tree is triggered to continue execution; each failed task can only execute one manual successful setting operation;
the manual setting failure is to modify the execution state of the task into manual setting failure and modify the state of the root task into manual setting failure for the task with scheduling failure; the manual setting failure means that the whole task tree fails to be executed, and each task tree can be manually set to fail only once;
the task tree checking means that access participation, execution state and abnormal information in the task execution process are recorded in the task scheduling process, and the execution information of the task tree can be checked according to the task Id.
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