CN107204868A - A kind of task run monitoring information acquisition methods and device - Google Patents

Abstract

The invention discloses a method for obtaining task operation monitoring information. According to the operation information of each task node where the task is located, task identifiers are respectively set; The task monitoring information, and/or platform monitoring information, and/or device monitoring information of the task node corresponding to the task identification content of the failure point determines the failure information. The invention also discloses a task operation monitoring information acquisition device.

Description

Method and device for acquiring task operation monitoring information

technical field

The invention relates to big data operation management technology, in particular to a method and device for acquiring task operation monitoring information.

Background technique

At present, big data applications are developing rapidly and are widely used in various fields; each technology platform has its own unique advantages in task operation, but it is self-contained and independent; the big data platform needs to integrate the advantages of different technology systems to meet the needs of different levels. Therefore, building a heterogeneous, technology-mashup, integrated deployment, and multi-service linkage operating model has become a distinctive feature of a big data platform that is different from traditional platforms. In this case, when a failure occurs, the troubleshooting steps are basically as follows:

1. Fault location: Since the task operation of the big data platform is scattered in each platform, the monitoring information management systems of each platform are independent of each other, and they work according to their own standards and rules. When a fault occurs, the operation and maintenance personnel need to manually check each platform. Cross-comparison on the management platform, check the fault information found on each platform, manually eliminate minor and related alarms, and confirm the fault alarm and the cause of the fault;

2. Fault analysis: Since the data of each system is independent, most of the current fault analysis is carried out in the system, and the data of each system is summarized and correlated manually. When there are many tasks on the platform, the logical relationship between operations When it is complicated, it is basically impossible to judge the mutual cross-relationship, and the analysis can only be gradually refined from the whole system. This process takes a long time, and it is impossible to confirm the impact degree and scope of the fault at the first time;

3. Troubleshooting: After summarizing the information of each manufacturer and manually determining the fault point, it is necessary to coordinate with each manufacturer to solve it together. Each manufacturer is only responsible for the fault resolution of the system, regardless of the impact of the fault resolution of this system on other systems. At the system architecture level, we can grasp the fault as a whole; after the solution is completed, we need to confirm the solution on the management and control platform of each system, and manually judge whether the fault has been solved or whether new problems have arisen, etc.

Under the existing conditions, the business impact assessment of faults, fault analysis efficiency, and alarm accuracy of the big data platform have the following shortcomings: the current fault location is analyzed by different manufacturers, especially under the mixed technology of the big data platform, as the platform More and more tasks are launched online, it is impossible to truly understand the logical relationship between platform tasks, and it is difficult to clarify the operational dependencies between tasks, resulting in a lack of comprehensive fault analysis capabilities, making it difficult to accurately assess the impact of faults on business; In some fault analysis, under the background of uneven big data technology operation and management levels of various manufacturers, especially in the mixed use of Spark, Storm, Sqoop, HIVE, HBASE and many other technical components, it is impossible to clarify the system faults between components Correlation impact, in the process of fault location, each component can only be inspected and located from the beginning, so that the time for solving the entire fault can be extended; the existing fault monitoring is independent, and each task fault, platform fault, and equipment fault has its own interface and information, lack of correlation and fusion of information, when a fault occurs, a large number of alarm information appears at different levels, and the above alarm information cannot be effectively correlated and filtered, forming an alarm storm, which makes the operation and maintenance personnel at a loss. It is necessary to manually summarize and analyze the alarm information of each platform, eliminate minor alarms and related alarms, and find the cause of the fault. The dependence on expert personnel is high, and the fault handling efficiency is low.

It can be seen that improving the rapid location of faults on the big data platform, realizing automatic analysis of fault impacts, and improving the timeliness of fault resolution are urgent problems to be solved.

Contents of the invention

In view of this, the embodiments of the present invention expect to provide a method and device for obtaining task operation monitoring information, which can improve the rapid location of faults on the big data platform, realize automatic analysis of fault impacts, and improve the timeliness of fault resolution.

In order to achieve the above object, technical solution of the present invention is achieved in that way:

An embodiment of the present invention provides a method for obtaining task operation monitoring information. The method includes: setting task identifiers respectively according to the operation information of each task node where the task is located; the method also includes:

Obtain task monitoring information, platform monitoring information, and/or device monitoring information of the task node corresponding to the failure point task identification content in the monitoring information according to the failure point task identification, and determine the failure information.

In the above solution, the operation information includes: type of operation platform, and/or type of components of operation platform;

The content of the task identification includes: the operating platform type, and/or the operating platform component type, and/or the task sequence number;

The task sequence number includes: a unique identification number preset according to the task, or a unique identification number preset according to the task node.

In the above scheme, the task monitoring information of the task node corresponding to the content of the task identification of the failure point is obtained from the monitoring information according to the task identification of the failure point, and the failure information is determined; including:

Associating the task sequence number with the task monitoring information in advance;

According to the task sequence number in the task identifier of the failure point, determine the task monitoring information of the task node corresponding to the task identifier of the failure point.

In the above scheme, the platform monitoring information of the task node corresponding to the content of the task identification of the failure point is obtained from the monitoring information according to the task identification of the failure point, and the failure information is determined; including:

Determine the platform type and platform component type of the task node corresponding to the fault point task ID according to the operating platform type and operating platform component type in the fault point task ID;

According to the platform type and platform component type of the task node corresponding to the fault point task identifier, determine the platform monitoring information corresponding to the platform type of the task node corresponding to the fault point task identifier and the platform component type.

In the above solution, according to the task identification of the failure point, the equipment monitoring information of the task node corresponding to the content of the task identification of the failure point is obtained from the monitoring information, and the failure information is determined; including:

In the task execution log, retrieve the running platform type and the running device host name of the running platform component type in the fault point task identifier;

According to the host name of the device, determine the device monitoring information of the task node corresponding to the fault point task identifier.

An embodiment of the present invention also provides a task operation monitoring information acquisition device, the device includes: a setting device and a determining device, wherein,

The setting device is used to respectively set task identifiers according to the operation information of each task node where the task is located;

The determining means obtains task monitoring information, and/or platform monitoring information, and/or equipment monitoring information of the task node corresponding to the content of the fault point task ID in the monitoring information according to the fault point task ID, and determines the fault information .

In the above solution, the operation information includes: type of operation platform, and/or type of components of operation platform;

The content of the task identification includes: the operating platform type, and/or the operating platform component type, and/or the task sequence number;

The task sequence number includes: a unique identification number preset according to the task, or a unique identification number preset according to the task node.

In the above solution, the determining device is specifically used for:

Associating the task sequence number with the task monitoring information in advance;

The determining the failure information includes: according to the task sequence number in the task identifier of the failure point, determining the task monitoring information of the task node corresponding to the task identifier of the failure point.

In the above solution, the determining device is specifically used for:

Determine the platform type and platform component type of the task node corresponding to the fault point task ID according to the operating platform type and operating platform component type in the fault point task ID;

According to the platform type and platform component type of the task node corresponding to the fault point task identifier, determine the platform monitoring information corresponding to the platform type of the task node corresponding to the fault point task identifier and the platform component type.

In the above solution, the determining device is specifically used for:

In the task execution log, retrieve the running platform type and the running device host name of the running platform component type in the fault point task identifier;

According to the host name of the device, determine the device monitoring information of the task node corresponding to the fault point task identifier.

The method and device for obtaining task operation monitoring information provided by the embodiments of the present invention set task identifiers respectively according to the operation information of each task node where the task is located; the method further includes: obtaining The task monitoring information of the task node, and/or platform monitoring information, and/or equipment monitoring information corresponding to the task identification content of the failure point determines the failure information. In this way, the task monitoring information, platform monitoring information and equipment monitoring information of the task node at the fault point can be accurately obtained through the task identification of the task node at the fault point; when a fault occurs, the fault monitoring information can be obtained according to the task identification of the fault node, and quickly Locate faults, realize automatic analysis of fault impacts, and improve the timeliness of fault resolution.

Description of drawings

1 is a schematic flow diagram of a method for obtaining task operation monitoring information according to an embodiment of the present invention;

Fig. 2 is a schematic diagram of the composition of the task identification of the embodiment of the present invention;

Fig. 3 is a schematic diagram of the fault location process sequence diagram of the task identification implementation of the embodiment of the present invention;

Fig. 4 is a schematic diagram of the principle of task identification association according to the embodiment of the present invention;

Fig. 5 is a schematic diagram of the business process of the application example of the embodiment of the present invention;

FIG. 6 is a schematic diagram of a business process operation record of an application example in an embodiment of the present invention;

Fig. 7 is a schematic diagram of the operation result of the business task identification of the application instance of the embodiment of the present invention;

FIG. 8 is a schematic diagram of the composition and structure of an apparatus for acquiring task operation monitoring information according to an embodiment of the present invention.

detailed description

In the embodiment of the present invention, task identifiers are respectively set according to the operation information of each task node where the task is located; the method further includes: according to the task identifier of the fault point, obtaining the information corresponding to the content of the task identifier of the fault point from the monitoring information The task monitoring information of the task node, and/or the platform monitoring information, and/or the equipment monitoring information determine the fault information.

The present invention will be described in further detail below in conjunction with the examples.

A method for obtaining task operation monitoring information provided by an embodiment of the present invention, as shown in FIG. 1 , the method includes:

Step 101: according to the operation information of each task node where the task is located, respectively set the task identifier;

Usually, a big data application contains multiple tasks. The relationship between big data applications and tasks is one-to-many, and the relationship between big data applications and tasks is maintained by the system; a single task is also called a job process, and a single job process is determined by Composed of multiple task nodes; the method adopted in the prior art is to assign each task a task identification or task sequence number that has nothing to do with task operation information, and is used to track the execution status of the task. The disadvantage is that it is impossible to accurately obtain each task node execution status, and running information cannot be obtained directly from it;

In the technical solution of the present invention, different task identifiers are set for each task node in the task running process, and the task identifier includes the operation information of the task at the task node, and the operation information includes: the type of operating platform, the type of operating platform components, and/or task sequence number; wherein, the running platform type refers to the type of running platform of the node where the task runs, such as Java, Storm, Hadoop, Spark and other platforms; the running platform component type refers to the running platform of the task node where the task runs The type of the component of the platform, such as the Java-Node component in the Java platform; the task sequence number is the unique sequence number assigned to the task before the task runs.

In practical applications, the form of the task identification can be shown in Figure 2. Here, the task identification can also include: task type and task name for faster and more convenient identification of tasks; according to different specific task component types, according to Figure 2 In the form of , the task ID can be set as follows:

For the synchronous task component, it runs directly on the oozie server, only success or failure information, no particularly obvious information, therefore, the task ID can be set to: oozie: none;

For the single-map (map)/regression (Reduce) task component, a single-map (only map) mapreduce task will be submitted to trigger the operation. In this task, the user-defined action component is encapsulated in the map, and the task ID of the task can be defined as :oozie:lancher:T={0}:W={1}:A={2}:ID={3}; where 0 means component type, 1 means platform type, 2 means task name, 3 means task sequence No. In this way, the task representation reflects the relationship between the task and the platform;

For a dual map/reduce task component, based on the operation of a single map/reduce task, the user-defined action encapsulated in the map is a mapreduce job, and the task ID of a mapreduce job of this nature can be defined as: oozie: action: T={0}:W={1}:A={2}:ID={3}, where 0 represents the component type, 1 represents the platform type, 2 represents the task name, 3 represents the task sequence number, and so on , the task representation reflects the relationship between the task and the platform;

Here, the single map/reduce task component and the dual map/reduce task component are called asynchronous task components.

Step 102: Obtain task monitoring information, and/or platform monitoring information, and/or equipment monitoring information of the task node corresponding to the content of the fault point task ID in the monitoring information according to the fault point task ID, and determine the fault information;

Existing big data monitoring information includes: application monitoring information, task monitoring information, platform monitoring information, and equipment monitoring information; each monitoring information includes various operating information during the operation of the task; among them, task monitoring information, platform monitoring information Information and equipment monitoring information are independent of each other and not related to each other; the relationship between big data applications and tasks is maintained by the system. Therefore, task monitoring information and application monitoring information can be associated through task affiliation. Task monitoring information, platform monitoring information, and equipment monitoring information can be associated through the task identification of the technical solution of the present invention, thereby associating the application monitoring information, task monitoring information, platform monitoring information, and equipment monitoring information; wherein, The platform monitoring information includes: platform name, platform type, platform status, task execution status and logs on the platform; the task monitoring information includes: task transfer information, transfer link, current link, time spent in each link, node transfer Change, task output log; the equipment monitoring information includes: equipment platform, equipment host information, equipment host operating status; realize the association of task monitoring information, platform monitoring information and equipment monitoring information through the task identification of the technical solution of the present invention, and The associated information can be merged into the application monitoring information. In this way, the application monitoring information can provide the following information: tasks contained in the application, the execution status of each task, the running status of the task on the platform, and the running status of the host device where the task is located. ;In this way, each task of the entire application can be obtained, and the information running on each task node;

Specifically, before the task runs, a unique task sequence number can be assigned to the task, and the task monitoring information can correspond to the task sequence number, such as: the task monitoring information can be named after the task sequence number, so, through The task serial number in the task identification can obtain the corresponding task monitoring information; you can also add the unique identification of the task node after the serial number, and establish the task monitoring information according to the serial number of each task node. In this way, through the task identification in the task identification The serial number can obtain the task monitoring information of the corresponding task node; during the operation of the big data task, if a fault occurs, the task monitoring information of the corresponding faulty task node can be obtained through the task ID of the faulty task node.

Through the running platform type and running platform component type in the task identifier, it can be determined that the task node running the current task is located on the platform type and platform component type; usually, platform monitoring information is classified by platform type and platform component type, so, The platform monitoring information of the task node can be associated through the platform type and platform component type; during the operation of the big data task, if a fault occurs, the platform type and platform component type in the task identifier of the faulty task node can be associated to obtain Platform monitoring information of the faulty task node.

Through the running platform type and running platform component type in the task identification, the host name of the device running the platform type and component type can be retrieved in the task execution log of the platform monitoring information; The device monitoring information of the task node is retrieved from the monitoring information; during the operation of the big data task, if a fault occurs, the platform type and platform component type in the task identifier of the faulty task node can be used to determine the fault in the task execution log. The host name of the device to further obtain the device monitoring information of the task node.

In this way, application monitoring information, task monitoring information, platform monitoring information, and equipment monitoring information complete the association of monitoring information through task identification, and achieve seamless integration of several types of monitoring information; in practical applications, through this fusion relationship, in During daily maintenance and guarantee, a user interface can be established to collect the related information of each monitoring information, so that the related application monitoring information, task monitoring information, platform monitoring information, equipment monitoring information and other information can be provided to the maintenance personnel at the same time, and the application monitoring information can be obtained directly. Contains various monitoring information of tasks at each task node, which is convenient for operation guarantee and fault location; when a fault occurs, the fault point task identification can be used to determine the platform type, platform component type or faulty equipment involved in the fault; greatly improve the efficiency of fault location .

Below in conjunction with embodiment 1, the present invention is described in further detail.

As shown in Figure 3, here a and b respectively show the sequence of the fault location process implemented by the synchronous task component and the asynchronous task component through the task identifier; among them, the principle of associating tasks, platforms, devices, and applications with the task identifier is shown in Figure 4 Shown: An application contains multiple tasks, and the relationship between applications and tasks is a one-to-many relationship, which is maintained by the system; a single task refers to a job process, and a job process consists of multiple task nodes, and each task node is in the Each time the process runs, a unique task identifier is set; through the task identifier, it is associated with the task running on the platform; when the platform job is executing on a specific device, the platform job log or job status can be associated with the corresponding device information association. In this way, the task identification is used to complete tasks, platforms, equipment, application associations and other capabilities; further, when a fault occurs, the task log can be used to complete business processes such as fault location, fault analysis, and fault monitoring.

Below in conjunction with embodiment 2 the present invention is described in further detail.

In this embodiment, task identifiers are set on the task nodes of each task in the specific business application, which has a good monitoring effect on the task operation in the specific business application;

Here, the functions realized by the specific business application are: calculate and analyze the behavior of the user's social circle, use the user's voice detailed list to discover and analyze the user's social circle, and judge the call behavior between the user and other users, such as call frequency, call duration, call time To analyze the user's communication behavior by segment and other indicators, and judge whether it is the user with the highest influence in the communication circle; the specific business process is shown in Figure 5, including:

Step 501: collect the detailed list file from the interface machine in the distributed file system (HDFS, Hadoop Distributed File System) of Hadoop;

Step 502: Use the Map/Reduce program to clean, filter and sort the detailed list;

Step 503: The result of step 502 is entered into the Hive library, and is summarized according to the calling number and the called number, and indicators such as the number of calls, the duration of the call, and the time period of the call are calculated;

Step 504: Export the analysis results to the relational database through the sqoop script.

In the business process, the technical solution of the present invention is adopted, task identification is set at each node, the business process operation record is shown in Figure 6, the business process node status is shown in Figure 7(a), and the business process operation log is shown in Figure 7(a). 7(b); the corresponding status of the task IDs in the business process nodes by name in the platform is shown in Figure 7(c); the corresponding job running status of the task IDs in the business process nodes in the platform is shown in Figure 7(d) ) as shown in FIG. 7(e);

It can be seen from Figure 7 that in the entire business process, the task monitoring information, platform monitoring information, and equipment monitoring information in the task node have been associated through the task identification; in this way, maintenance personnel can easily obtain the required information; You can easily determine the platform where the fault occurred, platform components or equipment and other information.

An embodiment of the present invention provides a task operation monitoring information acquisition device, as shown in FIG. 8 , the device includes: a setting module 81, a determination module 82, wherein,

The setting module 81 is configured to set task identifiers respectively according to the operation information of each task node where the task is located;

Usually, a big data application contains multiple tasks. The relationship between big data applications and tasks is one-to-many, and the relationship between big data applications and tasks is maintained by the system; a single task is also called a job process, and a single job process is determined by Composed of multiple task nodes; the method adopted in the prior art is to assign each task a task identification or task sequence number that has nothing to do with task operation information, and is used to track the execution status of the task. The disadvantage is that it is impossible to accurately obtain each task node execution status, and running information cannot be obtained directly from it;

In the technical solution of the present invention, different task identifiers are set for each task node in the task running process, and the task identifier includes the operation information of the task at the task node, and the operation information includes: the type of operating platform, the type of operating platform components, and/or task sequence number; where, the running platform type refers to the type of running platform of the task node where the task runs, such as Java, Storm, Hadoop, Spark and other platforms; the running platform component type refers to the type of the task node where the task runs The component type of the running platform, such as the Java-Node component in the Java platform; the task sequence number is the unique sequence number assigned to the task before the task runs.

In practical applications, the form of the task identification can be shown in Figure 2. Here, the task identification can also include: task type and task name for faster and more convenient identification of tasks; according to different specific task component types, according to Figure 2 In the form of , the task ID can be set as follows:

For the synchronous task component, it runs directly on the oozie server, only success or failure information, no particularly obvious information, therefore, the task ID can be set to: oozie: none;

For the single-map (map)/regression (Reduce) task component, a single-map (only map) mapreduce task will be submitted to trigger the operation. In this task, the user-defined action component is encapsulated in the map, and the task ID of the task can be defined as :oozie:lancher:T={0}:W={1}:A={2}:ID={3}; where 0 means component type, 1 means platform type, 2 means task name, 3 means task sequence No. In this way, the task representation reflects the relationship between the task and the platform;

For a dual map/reduce task component, based on the operation of a single map/reduce task, the user-defined action encapsulated in the map is a mapreduce job, and the task ID of a mapreduce job of this nature can be defined as: oozie: action: T={0}:W={1}:A={2}:ID={3}, where 0 represents the component type, 1 represents the platform type, 2 represents the task name, 3 represents the task sequence number, and so on , the task representation reflects the relationship between the task and the platform;

Here, the single map/reduce task component and the dual map/reduce task component are called asynchronous task components.

The determination module 82 obtains, from the monitoring information, monitoring information on the task operation of each task node corresponding to the content of the task identification according to each task identification;

Existing big data monitoring information includes: application monitoring information, task monitoring information, platform monitoring information, and equipment monitoring information; each monitoring information includes various operating information during the operation of the task; among them, task monitoring information, platform monitoring information Information and equipment monitoring information are independent of each other and not related to each other; the relationship between big data applications and tasks is maintained by the system. Therefore, task monitoring information and application monitoring information can be associated through task affiliation. Task monitoring information, platform monitoring information, and equipment monitoring information can be associated through the task identification of the technical solution of the present invention, thereby associating the application monitoring information, task monitoring information, platform monitoring information, and equipment monitoring information; wherein, The platform monitoring information includes: platform name, platform type, platform status, task execution status and logs on the platform; the task monitoring information includes: task transfer information, transfer link, current link, time spent in each link, node transfer Change, task output log; the equipment monitoring information includes: equipment platform, equipment host information, equipment host operating status; realize the association of task monitoring information, platform monitoring information and equipment monitoring information through the task identification of the technical solution of the present invention, and The related information can be merged into the application monitoring information. In this way, the application monitoring information can provide the following information: tasks contained in the application, the execution status of each task, the running status of the task on the platform, and the running status of the host device where the task is located. ;In this way, each task of the entire application can be obtained, and the information running on each task node;

Specifically, before the task runs, a unique task sequence number can be assigned to the task, and the task monitoring information can correspond to the task sequence number, such as: the task monitoring information can be named after the task sequence number, so, through The task serial number in the task identification can obtain the corresponding task monitoring information; you can also add the unique identification of the task node after the serial number, and establish the task monitoring information according to the serial number of each task node. In this way, through the task identification in the task identification The serial number can obtain the task monitoring information of the corresponding task node; during the operation of the big data task, if a fault occurs, the task monitoring information of the corresponding faulty task node can be obtained through the task ID of the faulty task node.

Through the running platform type and running platform component type in the task identifier, it can be determined that the task node running the current task is located on the platform type and platform component type; usually, platform monitoring information is classified by platform type and platform component type, so, The platform monitoring information of the task node can be associated through the platform type and platform component type; during the operation of the big data task, if a fault occurs, the platform type and platform component type in the task identifier of the faulty task node can be associated to obtain Platform monitoring information of the faulty task node.

Through the running platform type and running platform component type in the task identification, the host name of the device running the platform type and component type can be retrieved in the task execution log of the platform monitoring information; The device monitoring information of the task node is retrieved from the monitoring information; during the operation of the big data task, if a fault occurs, the platform type and platform component type in the task identification of the faulty task node can be used to determine the fault in the task execution log. The host name of the device to further obtain the device monitoring information of the task node.

In this way, application monitoring information, task monitoring information, platform monitoring information, and equipment monitoring information complete the association of monitoring information through task identification and achieve seamless integration of several types of monitoring information; in practical applications, through this fusion relationship, in During daily maintenance and guarantee, a user interface can be established to collect the related information of each monitoring information, so that the related application monitoring information, task monitoring information, platform monitoring information, equipment monitoring information and other information can be provided to the maintenance personnel at the same time, and the application monitoring information can be obtained directly. Contains various monitoring information of tasks at each task node, which is convenient for operation guarantee and fault location; when a fault occurs, the fault point task identification can be used to determine the platform type, platform component type or faulty equipment involved in the fault; greatly improve the efficiency of fault location .

In practical applications, the setting module 81 and the determining module 82 can be composed of a central processing unit (CPU), a microprocessor (MPU), a digital signal processor (DSP), or a field programmable gate array (FPGA) of the big data server system. accomplish.

The above is only a preferred embodiment of the present invention, and is not used to limit the scope of protection of the present invention. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present invention should be included in this document. within the scope of protection of the invention.

Claims (10)

1. A task operation monitoring information acquisition method is characterized in that, the method includes: according to the operation information of each task node where the task is located, the task identification is respectively set; the method also includes: Obtain task monitoring information, and/or platform monitoring information, and/or equipment monitoring information of the task node corresponding to the content of the fault point task identification in the monitoring information according to the fault point task identification, and determine the fault information; The content of the task identification includes: the operating platform type, and/or the operating platform component type, and/or the task sequence number. 2. The method of claim 1, wherein, The running information includes: running platform type, and/or running platform component type; The task sequence number includes: a unique identification number preset according to the task, or a unique identification number preset according to the task node. 3. The method according to claim 2, wherein, according to the fault point task identification, the task monitoring information of the task node corresponding to the fault point task identification content is obtained in the monitoring information, and the fault information is determined; comprising : Associating the task sequence number with the task monitoring information in advance; According to the task sequence number in the task identifier of the failure point, determine the task monitoring information of the task node corresponding to the task identifier of the failure point. 4. The method according to claim 2, wherein, according to the fault point task identification, the platform monitoring information of the task node corresponding to the fault point task identification content is obtained in the monitoring information, and the fault information is determined; comprising : Determine the platform type and platform component type of the task node corresponding to the fault point task ID according to the operating platform type and operating platform component type in the fault point task ID; According to the platform type and platform component type of the task node corresponding to the fault point task identifier, determine the platform monitoring information corresponding to the platform type of the task node corresponding to the fault point task identifier and the platform component type. 5. The method according to claim 2, wherein, according to the task identification of the failure point, the device monitoring information of the task node corresponding to the content of the task identification of the failure point is obtained in the monitoring information, and the failure information is determined; : In the task execution log, retrieve the running platform type and the running device host name of the running platform component type in the fault point task identifier; According to the host name of the device, determine the device monitoring information of the task node corresponding to the fault point task identifier. 6. A task operation monitoring information acquisition device, characterized in that the device comprises: a setting device and a determining device, wherein, The setting device is used to respectively set task identifiers according to the operation information of each task node where the task is located; The determining means obtains task monitoring information, and/or platform monitoring information, and/or equipment monitoring information of the task node corresponding to the content of the fault point task ID in the monitoring information according to the fault point task ID, and determines the fault information ; The content of the task identification includes: the operating platform type, and/or the operating platform component type, and/or the task sequence number. 7. The device of claim 6, wherein: The running information includes: running platform type, and/or running platform component type; The task sequence number includes: a unique identification number preset according to the task, or a unique identification number preset according to the task node. 8. The device according to claim 7, wherein the determining device is specifically used for: Associating the task sequence number with the task monitoring information in advance; The determining the failure information includes: according to the task sequence number in the task identifier of the failure point, determining the task monitoring information of the task node corresponding to the task identifier of the failure point. 9. The device according to claim 7, wherein the determining device is specifically used for: Determine the platform type and platform component type of the task node corresponding to the fault point task ID according to the operating platform type and operating platform component type in the fault point task ID; According to the platform type and platform component type of the task node corresponding to the fault point task identifier, determine the platform monitoring information corresponding to the platform type of the task node corresponding to the fault point task identifier and the platform component type. 10. The device according to claim 7, wherein the determining device is specifically used for: In the task execution log, retrieve the running platform type and the running device host name of the running platform component type in the fault point task identifier; According to the host name of the device, determine the device monitoring information of the task node corresponding to the fault point task identifier.