CN107204868B - Task operation monitoring information acquisition method and device - Google Patents

Abstract

The invention discloses a method for acquiring task operation monitoring information, which respectively sets task identifiers according to the operation information of each task node where a task is located; the method further comprises the following steps: according to the fault point task identification, task monitoring information, platform monitoring information and/or equipment monitoring information of the task node corresponding to the fault point task identification content are obtained from the monitoring information, and fault information is determined. The invention also discloses a device for acquiring the task operation monitoring information.

Description

Method and device for obtaining task operation monitoring information

technical field

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

Background technique

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

1. Fault location: Since the tasks of the big data platform are scattered in each platform, the monitoring information management systems of each platform are independent of each other, and they work in accordance with their own standards and rules. Cross-comparison on the management platform, check the fault information found on each platform, manually remove minor and related alarms, and confirm fault alarms and fault causes;

2. Failure analysis: Since the data of each system is independent, most of the failure analysis is carried out in this system at present, and the data of each system is aggregated and correlated manually. When there are many tasks on the platform, the logical relationship When it is complex, 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 collecting the information of each manufacturer and manually determining the fault point, it is necessary to coordinate with each manufacturer to solve the fault together. Each manufacturer is only responsible for the fault solving of this system, regardless of the impact of the fault solving of this system on other systems. At the system architecture level, the overall grasp of the fault should be carried out; after the solution is completed, the solution should be confirmed on the management and control platform of each system, and the fault should be manually judged whether it has been solved, whether new problems have occurred, and so on.

Under the existing conditions, the evaluation of fault business impact, the efficiency of fault analysis, and the accuracy of alarms on the big data platform have the following shortcomings: the current fault location is analyzed by different manufacturers, especially under the multi-technology mix and match of the big data platform, with the platform As more and more tasks are launched, 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 operation and management of big data technology of various manufacturers, especially in the case of mixed use of many technical components such as Spark, Storm, Sqoop, HIVE, HBASE, etc., it is impossible to sort out the system faults between components. In the process of fault location, only each component can be checked and located from the beginning, so that the time limit for solving the entire fault can be prolonged; the existing fault monitoring is independent, and each task fault, platform fault, and equipment fault has its own There is a lack of correlation and fusion of information. When a fault occurs, a large amount of alarm information appears at different levels, and the above alarm information cannot be effectively correlated and filtered, forming an alarm storm, which makes operation and maintenance personnel at a loss. It is necessary to manually summarize and analyze the alarm information of each platform, eliminate secondary alarms and related alarms, and find the cause of the failure.

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

SUMMARY OF THE INVENTION

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

In order to achieve the above object, the technical scheme of the present invention is achieved in this 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 further includes:

According to the task identification of the fault point, the task monitoring information, and/or the platform monitoring information, and/or the equipment monitoring information of the task node corresponding to the content of the task identification of the fault point are obtained from the monitoring information, and the fault information is determined.

In the above solution, the operating information includes: operating platform type and/or operating platform component type;

The content of the task identification includes: the running platform type, and/or the running 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 task monitoring information of the task node corresponding to the content of the task identification of the failure point is obtained in 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;

The task monitoring information of the task node corresponding to the task identification of the failure point is determined according to the task sequence number in the task identification of the failure point.

In the above solution, according to the task identifier of the fault point, the platform monitoring information of the task node corresponding to the content of the task identifier of the fault point is obtained in the monitoring information, and the fault information is determined; including:

According to the operating platform type and operating platform component type in the fault point task identifier, determine the platform type and platform component type of the task node corresponding to the fault point task identifier;

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

In the above solution, according to the task identifier of the fault point, the device monitoring information of the task node corresponding to the content of the task identifier of the fault point is obtained in the monitoring information, and the fault information is determined; including:

Retrieve the operating platform type and the device host name of the operating platform component type in the fault point task identifier from the task execution log;

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

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

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

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

In the above solution, the operating information includes: operating platform type and/or operating platform component type;

The content of the task identification includes: the running platform type, and/or the running 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 determining device is specifically used for:

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

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

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

According to the operating platform type and operating platform component type in the fault point task identifier, determine the platform type and platform component type of the task node corresponding to the fault point task identifier;

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

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

Retrieve the operating platform type and the device host name of the operating platform component type in the fault point task identifier from the task execution log;

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

In the method and device for obtaining task operation monitoring information provided by the embodiments 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: obtaining the task identifier from the monitoring information according to the task identifier of the fault point The fault information is determined according to the task monitoring information, and/or the platform monitoring information, and/or the equipment monitoring information of the task node corresponding to the task identification content of the fault point. In this way, the task monitoring information, platform monitoring information and equipment monitoring information of the task node at the failure point can be accurately obtained through the task identification of the task node at the failure point; when a failure occurs, the failure monitoring information can be obtained according to the task identification of the failure node, and the failure monitoring information can be quickly obtained. Locate faults, realize automatic analysis of fault impact, and improve the timeliness of fault resolution.

Description of drawings

1 is a schematic flowchart of a method for acquiring task operation monitoring information according to an embodiment of the present invention;

2 is a schematic diagram of the composition of task identifiers according to an embodiment of the present invention;

3 is a schematic diagram of a sequence diagram of a fault location process for task identification according to an embodiment of the present invention;

4 is a schematic diagram of a task identifier association principle according to an embodiment of the present invention;

5 is a schematic diagram of a business process flow of an application example of an embodiment of the present invention;

6 is a schematic diagram of an application example business process operation record according to an embodiment of the present invention;

FIG. 7 is a schematic diagram of a running result of an application instance business task identifier according to an embodiment of the present invention;

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

Detailed ways

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

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

A method for acquiring 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, set task identifiers respectively;

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 maintained by the system. It is composed of multiple task nodes; the method adopted in the prior art is to assign a task identifier or task sequence number unrelated to the task operation information to each task, which is used to track the execution status of the task. The disadvantage is that each task node cannot be accurately obtained. the execution status, and it is not possible to directly obtain operating information from it;

In the technical solution of the present invention, a different task identifier is set for each task node in the task running process, and the task identifier includes the operation information of the task on the task node, and the operation information includes: the operation platform type, the operation platform component type, and/or task sequence number; wherein, the running platform type refers to the type of the 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 as shown in Figure 2. Here, the task identification may also include: task type and task name, which are used to identify tasks faster and more conveniently; according to different specific task component types, according to Figure 2 In the form of , the task identifier can be set as follows:

For the synchronization task component, which runs directly on the oozie server, there is only success or failure information, and there is no particularly obvious information. Therefore, the task identifier can be set to: oozie: none;

For a single map (map)/regress (Reduce) task component, a mapreduce task with a single map (only map) will be submitted to trigger the operation. In this task, the user-defined action component is encapsulated in the map, and the task identifier of the task can be defined as :oozie:lancher:T={0}:W={1}:A={2}:ID={3}; where 0 is the component type, 1 is the platform type, 2 is the task name, and 3 is the 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, on the basis of running a single map/Reduce task, the user-defined action encapsulated in the map is a job with mapreduce properties, and the task identifier 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, single map/Reduce task components and dual map/Reduce task components are called asynchronous task components.

Step 102: Acquire task monitoring information, and/or platform monitoring information, and/or device monitoring information of task nodes corresponding to the content of the task identification of the fault point in the monitoring information according to the task identifier of the fault point, 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 operation information of the task during the running process; among them, task monitoring information, platform monitoring information Information and device monitoring information are independent and unrelated 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 with task attribution. Task monitoring information, platform monitoring information, and device monitoring information can be associated through the task identifier of the technical solution of the present invention, so as to associate the application monitoring information, task monitoring information, platform monitoring information, and device 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 links, current links, time used in each link, and node transfer information. The device monitoring information includes: device platform, device host information, and device host operating status; the task monitoring information, platform monitoring information and device monitoring information are correlated through the task identification of the technical solution of the present invention, and the The associated information can be incorporated into the application monitoring information, so that the application monitoring information can provide the following information: the tasks included in the application, the execution status of each task, the running status of the task on the platform, and the operating status of the device host where the task is located. ; In this way, each task of the entire application and the information running on each task node can be obtained;

Specifically, before a task runs, a unique task sequence number may be assigned to the task, and the task monitoring information may correspond to the task sequence number. For example, the task monitoring information may be named with the task sequence number. The corresponding task monitoring information can be obtained by the task sequence number in the task identifier; the unique identifier of the task node can also be added after the serial number, and the task monitoring information can be established according to the serial number of each task node. The serial number can obtain the task monitoring information of the corresponding task node; during the operation of the big data task, if a failure occurs, the task monitoring information of the corresponding failed task node can be obtained through the task ID of the failed task node.

Through the running platform type and running platform component type in the task identifier, the platform type and platform component type of the task node on which the current task is running can be determined; 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 with the platform type and the platform component type; during the operation of the big data task, if a fault occurs, the platform type and the platform component type in the task identifier of the faulty task node can be associated. Platform monitoring information of the faulty task node.

Through the running platform type and running platform component type in the task identifier, the host name of the device running the platform type and component type can be retrieved from 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 determined in the task execution log. Device host name, and 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 monitoring information; in practical applications, through this fusion relationship, in During daily maintenance, 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 directly obtained. It contains various monitoring information of tasks in each task node, which is convenient for operation guarantee and fault location; in the event of a fault, the fault point task identification can be used to determine the type of platform involved in the fault, the type of platform components or the faulty equipment; greatly improve the efficiency of fault location. .

The present invention will be described in further detail below in conjunction with Example 1.

As shown in Figure 3, here a and b respectively show that the synchronous task component and the asynchronous task component implement the fault location process sequence through the task identification; among them, the principle of the task identification associating tasks, platforms, devices, and applications is shown in Figure 4 Show: an application contains multiple tasks, the relationship between the application and the task is a one-to-many relationship, and this relationship is maintained by the system; a single task also refers to a job process, and the job process consists of multiple task nodes, each task node in 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 executed 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 identifier can be used to complete the task, platform, device, application association and other capabilities; further, when a fault occurs, fault location, fault analysis, fault monitoring and other business processing can be completed through the task log.

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 of the specific business application, which has a good effect of monitoring the task operation in the specific business application;

Here, the functions implemented by the specific business application are: calculating and analyzing the behavior of the user's contact circle, using the user's voice detailed list to discover and analyze the user's contact circle, and judging the call behavior of the user and other users, such as call frequency, call duration, call time Segment and other indicators to analyze the user's communication behavior, and determine 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 into the Hadoop Distributed File System (HDFS, Hadoop Distributed File System);

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 database, and the calling number and the called number are aggregated to calculate indicators such as the number of calls, the duration of the call, and the duration of the call;

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

The technical solution of the present invention is adopted in the business process, and task identifiers are 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 6 As shown in Figure 7(b); the corresponding situation of the task ID in the business process node in the platform by name is shown in Figure 7(c); the corresponding job running status of the task ID in the business process node in the platform is shown in Figure 7(d) ); the operation situation of the task identifier in the business process node in the platform and the corresponding equipment situation are shown in Figure 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, the maintenance personnel can easily obtain the required information; in the event of a failure When the fault occurs, it can easily determine the platform, platform components or equipment and other information.

An apparatus for obtaining task operation monitoring information provided by an embodiment of the present invention, as shown in FIG. 8 , the apparatus includes: a setting module 81 and a determination module 82 , wherein,

The setting module 81 is used to respectively set the task identifier 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 maintained by the system. It is composed of multiple task nodes; the method adopted in the prior art is to assign a task identifier or task sequence number unrelated to the task operation information to each task, which is used to track the execution status of the task. The disadvantage is that each task node cannot be accurately obtained. the execution status, and it is not possible to directly obtain operating information from it;

In the technical solution of the present invention, a different task identifier is set for each task node in the task running process, and the task identifier includes the operation information of the task on the task node, and the operation information includes: the operation platform type, the operation platform component type, and/or the task sequence number; wherein, the running platform type refers to the type of the 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 type of the component 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 as shown in Figure 2. Here, the task identification may also include: task type and task name, which are used to identify tasks faster and more conveniently; according to different specific task component types, according to Figure 2 In the form of , the task identifier can be set as follows:

For the synchronization task component, which runs directly on the oozie server, there is only success or failure information, and there is no particularly obvious information. Therefore, the task identifier can be set to: oozie: none;

For a single map (map)/regress (Reduce) task component, a mapreduce task with a single map (only map) will be submitted to trigger the operation. In this task, the user-defined action component is encapsulated in the map, and the task identifier of the task can be defined as :oozie:lancher:T={0}:W={1}:A={2}:ID={3}; where 0 is the component type, 1 is the platform type, 2 is the task name, and 3 is the 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, on the basis of running a single map/Reduce task, the user-defined action encapsulated in the map is a job with mapreduce properties, and the task identifier 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, single map/Reduce task components and dual map/Reduce task components are called asynchronous task components.

The determining module 82, according to each task identifier, obtains the monitoring information of the task operation of each task node corresponding to the content of the task identifier in the monitoring 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 operation information of the task during the running process; among them, task monitoring information, platform monitoring information Information and device monitoring information are independent and unrelated 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 with task attribution. Task monitoring information, platform monitoring information, and device monitoring information can be associated through the task identifier of the technical solution of the present invention, so as to associate the application monitoring information, task monitoring information, platform monitoring information, and device 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 links, current links, time used in each link, and node transfer information. The device monitoring information includes: device platform, device host information, and device host operating status; the task monitoring information, platform monitoring information and device monitoring information are correlated through the task identification of the technical solution of the present invention, and the The associated information can be incorporated into the application monitoring information, so that the application monitoring information can provide the following information: the tasks included in the application, the execution status of each task, the running status of the task on the platform, and the operating status of the device host where the task is located. ; In this way, each task of the entire application and the information running on each task node can be obtained;

Specifically, before a task runs, a unique task sequence number may be assigned to the task, and the task monitoring information may correspond to the task sequence number. For example, the task monitoring information may be named with the task sequence number. The corresponding task monitoring information can be obtained by the task sequence number in the task identifier; the unique identifier of the task node can also be added after the serial number, and the task monitoring information can be established according to the serial number of each task node. The serial number can obtain the task monitoring information of the corresponding task node; during the operation of the big data task, if a failure occurs, the task monitoring information of the corresponding failed task node can be obtained through the task ID of the failed task node.

Through the running platform type and running platform component type in the task identifier, the platform type and platform component type of the task node on which the current task is running can be determined; 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 with the platform type and the platform component type; during the operation of the big data task, if a fault occurs, the platform type and the platform component type in the task identifier of the faulty task node can be associated. Platform monitoring information of the faulty task node.

Through the running platform type and running platform component type in the task identifier, the host name of the device running the platform type and component type can be retrieved from 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 determined in the task execution log. Device host name, and 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 monitoring information; in practical applications, through this fusion relationship, in During daily maintenance, 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 directly obtained. It contains various monitoring information of tasks in each task node, which is convenient for operation guarantee and fault location; in the event of a fault, the fault point task identification can be used to determine the type of platform involved in the fault, the type of platform components or the faulty equipment; greatly improve the efficiency of fault location. .

In practical applications, the setting module 81 and the determination module 82 can be 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, etc. accomplish.

The above are only preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present invention shall be included in the present invention. within the scope of protection of the invention.

Claims (4)

1. A method for obtaining task operation monitoring information, characterized in that the method comprises: setting task identifiers respectively according to the operation information of each task node where the task is located; the method further comprises: According to the task identification of the fault point, obtain the task monitoring information and/or platform monitoring information and/or equipment monitoring information of the task node corresponding to the content of the task identification of the fault point in the monitoring information, and determine the fault information; The content of the task identification includes: operating platform type, and/or operating platform component type, and/or task sequence number; Wherein, obtaining the task monitoring information of the task node corresponding to the content of the task identification of the failure point in the monitoring information according to the task identification of the failure point, and determining the failure information; including: pre-associating the task sequence number with the task monitoring information; according to the task sequence number in the task identifier of the fault point, determine the task monitoring information of the task node corresponding to the task identifier of the fault point; The step of obtaining the platform monitoring information of the task node corresponding to the content of the task identification of the failure point in the monitoring information according to the task identification of the failure point, and determining the failure information; including: according to the operation platform type and operation platform type in the task identification of the failure point Platform component type, determine the platform type and platform component type of the task node corresponding to the fault point task identifier; according to the platform type and platform component type of the task node corresponding to the fault point task identifier, determine the fault point task identifier corresponding to The platform monitoring information corresponding to the platform type and platform component type of the task node; According to the task identifier of the fault point, obtaining the device monitoring information of the task node corresponding to the content of the task identifier of the fault point in the monitoring information, and determining the fault information; including: retrieving the fault point task identifier in the task execution log. The operating platform type and the operating device host name of the operating platform component type; according to the device host name, the device monitoring information of the task node corresponding to the fault point task identifier is determined. 2. The method according to claim 1, wherein The operating information includes: operating platform type, and/or operating 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. 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 the task identifier according to the operation information of each task node where the task is located; The determining device, according to the task identification of the fault point, obtains the task monitoring information, and/or the platform monitoring information, and/or the equipment monitoring information of the task node corresponding to the content of the task identification of the fault point in the monitoring information, and determines the fault information ; The content of the task identification includes: operating platform type, and/or operating platform component type, and/or task sequence number; The determining device is specifically used for: Determine the task monitoring information of the task node corresponding to the task identification of the failure point according to the task sequence number in the task identification of the failure point; According to the operating platform type and operating platform component type in the fault point task identifier, determine the platform type and platform component type of the task node corresponding to the fault point task identifier; according to the fault point task identifier corresponding to the task node platform Type and platform component type, determine the platform type of the task node corresponding to the fault point task identifier and the platform monitoring information corresponding to the platform component type; Retrieve the operating platform type in the fault point task identifier and the device host name of the operating platform component type in the task execution log; determine the device monitoring information of the task node corresponding to the fault point task identifier according to the device host name. 4. The device of claim 3, wherein The operating information includes: operating platform type, and/or operating 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.

Images