WO2022188509A1

WO2022188509A1 - Method and apparatus for task processing in distributed environment, and electronic device and medium

Info

Publication number: WO2022188509A1
Application number: PCT/CN2021/140522
Authority: WO
Inventors: 李大鹏; 白雪; 郑晓静; 张洪钏; 刘宝矿; 邢晓东
Original assignee: 天翼云科技有限公司
Priority date: 2021-03-12
Filing date: 2021-12-22
Publication date: 2022-09-15
Also published as: CN115080193A

Abstract

The present disclosure provides a method and apparatus for task processing in a distributed environment, and an electronic device and a medium, which relate to the technical field of data processing. The method for task processing in a distributed environment comprises: acquiring request information for requesting a server to execute a task; determining, according to the request information, whether to send the task to a designated server or a non-designated server; if it is determined that the task will be sent to a non-designated server, acquiring a non-designated server that can execute the task, and an execution weight of the non-designated server; and allocating the task to the non-designated server according to the execution weight. By means of the technical solution of the present disclosure, the efficiency of task processing, and the balance and reliability of service resources are improved.

Description

Task processing method, apparatus, electronic device and medium in distributed environment

This disclosure claims the priority of the Chinese patent application with the application number 202110270111.4 and titled "Task Processing Method, Apparatus, Electronic Device and Medium in Distributed Environment", filed on March 12, 2021, and all of the Chinese patent application The contents are incorporated herein by reference in their entirety.

technical field

The present disclosure relates to the technical field of data processing, and in particular, to a task processing method, apparatus, electronic device and medium in a distributed environment.

Background technique

Under the distributed cluster architecture, multiple application tasks are usually executed collaboratively by multiple servers in the architecture. The processing stage within the task system includes task reception (stored in the library), task assignment, and task result presentation. Among them, The assignment of tasks includes the implementation of the following scenarios:

(1) The function of task allocation is directly lowered to the user terminal, and the user terminal has obtained which server to send the task to for execution.

However, the user terminal is not under the control of the server cluster, and security problems may occur during the task assignment process.

In addition, if the service address list is not updated in time, the address of the server accessed by the user terminal may be invalid, which affects the user's product experience.

(2) The specific execution server of the task is determined by the task distribution system, which can be understood as the existence of a central control node that distributes tasks uniformly.

However, the task allocation system relies on too many open source components, which affects the stability of the system and is not conducive to upgrades and later functional iterations. In most software companies, this type of system must universally serve various business lines. , that is, it needs to be compatible with various scenarios, which makes the whole system more complex and also leads to an increase in maintenance costs in the later period.

(3) The above two task allocation schemes also have the problem of uneven task allocation, which may cause some server resources to be unused, while another part of the server is in an overloaded state, which will reduce the efficiency of distributed cluster processing tasks. It also seriously affects the reliability, throughput and resource balance of the server.

It should be noted that the information disclosed in the above Background section is only for enhancement of understanding of the background of the present disclosure, and therefore may contain information that does not form the prior art that is already known to a person of ordinary skill in the art.

SUMMARY OF THE INVENTION

The purpose of the present disclosure is to provide a task processing method, apparatus, electronic device and medium in a distributed environment, which at least to a certain extent overcomes the problem of low task processing efficiency in a distributed environment in the related art.

Other features and advantages of the present disclosure will become apparent from the ensuing detailed description, or be learned in part by practice of the present disclosure.

According to one aspect of the present disclosure, there is provided a task processing method in a distributed environment, comprising: obtaining request information requesting a server to execute a task; determining to send the task to a designated server or a non-designated server according to the request information; If it is determined to send to the non-designated server, the non-designated server capable of executing the task and the execution weight of the non-designated server are obtained; the task is allocated to the non-designated server according to the execution weight.

In an embodiment of the present disclosure, the method further includes: acquiring the execution time of the non-designated server processing the task within a specified time; and updating the execution weight according to the execution time.

In an embodiment of the present disclosure, updating the execution weight according to the execution time includes: setting the initial execution weights of the non-designated servers to be equal; determining the sum of execution times of all the non-designated servers; determining the execution time The proportion of time to the sum of the execution time; the execution weight is updated according to the proportion.

In an embodiment of the present disclosure, determining to send the task to a designated server or a non-designated server according to the request information includes: parsing the request information to determine whether address information of the designated server is included; If the information includes the address information, the task is sent to the designated server according to the address information.

In an embodiment of the present disclosure, determining to send the task to a designated server or a non-designated server according to the request information further includes: parsing the request information to determine whether address information of the designated server is included; If the request information does not include the address information, it is determined to send the task to the non-designated server.

In an embodiment of the present disclosure, the method further includes: receiving result information of the non-designated server executing the task; determining triple data information and execution time field information contained in the result information; The group data information updates the triplet data in the preset library table; and the execution time of the redis cache is updated according to the execution time field information.

In an embodiment of the present disclosure, acquiring request information requesting a server to perform a task includes: acquiring the request information; parsing the request information to include invocation services and invocation parameters; determining the request according to the invocation services and the invocation parameters The server scope includes the designated server and the non-designated server.

According to another aspect of the present disclosure, there is provided a task processing apparatus in a distributed environment, comprising: an acquisition module for acquiring request information requesting a server to perform a task; a determination module for determining according to the request information The task is sent to a designated server or a non-designated server; the obtaining module is further configured to, if it is determined to be sent to the non-designated server, obtain the non-designated server capable of executing the task and the execution weight of the non-designated server; assign a module for allocating the task to the non-designated server according to the execution weight.

According to yet another aspect of the present disclosure, there is provided an electronic device, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute any one of the foregoing by executing the executable instructions Task processing methods in a distributed environment.

According to yet another aspect of the present disclosure, there is provided a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, implements any one of the above-mentioned task processing methods in a distributed environment.

In the task processing solution in a distributed environment provided by the embodiments of the present disclosure, the task is determined to be sent to a designated server or a non-designated server according to the request information, and the task is allocated to all the tasks according to the execution weight. The non-designated server described above improves the security and reliability of task processing, optimizes the resource balance of servers in the distributed cluster, and improves the overall throughput and task processing efficiency of the distributed cluster.

It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure.

Description of drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description serve to explain the principles of the disclosure. Obviously, the drawings in the following description are only some embodiments of the present disclosure, and for those of ordinary skill in the art, other drawings can also be obtained from these drawings without creative effort.

1 shows a schematic diagram of a task processing method in a distributed environment in an embodiment of the present disclosure;

FIG. 2 shows a flowchart of another task processing method in a distributed environment in an embodiment of the present disclosure;

3 shows a flowchart of yet another task processing method in a distributed environment in an embodiment of the present disclosure;

4 shows a flowchart of yet another task processing method in a distributed environment in an embodiment of the present disclosure;

5 shows a flowchart of yet another task processing method in a distributed environment in an embodiment of the present disclosure;

6 shows a flowchart of yet another task processing method in a distributed environment in an embodiment of the present disclosure;

7 shows a flowchart of yet another task processing method in a distributed environment in an embodiment of the present disclosure;

8 shows a flowchart of yet another task processing method in a distributed environment in an embodiment of the present disclosure;

9 shows a flowchart of yet another task processing method in a distributed environment in an embodiment of the present disclosure;

10 shows a schematic diagram of a task processing apparatus in a distributed environment in an embodiment of the present disclosure;

FIG. 11 shows a schematic diagram of an electronic device in an embodiment of the present disclosure.

Detailed ways

Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments, however, can be embodied in various forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repeated descriptions will be omitted. Some of the block diagrams shown in the figures are functional entities that do not necessarily necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.

The solution provided by the present disclosure improves the security of task processing by determining to send the task to a designated server or a non-designated server according to the request information, and assigning the task to the non-designated server according to the execution weight It optimizes the resource balance of the servers in the distributed cluster and improves the overall throughput and task processing efficiency of the distributed cluster.

The above task processing solution in a distributed environment can be implemented through the interaction of multiple terminals and server clusters.

The terminal can be a mobile phone, game console, tablet computer, e-book reader, smart glasses, MP4 (Moving Picture Experts Group Audio Layer IV, moving image expert compression standard audio layer 4) player, smart home equipment, AR (Augmented Reality, Augmented reality) equipment, VR (Virtual Reality, virtual reality) equipment and other mobile terminals, or, the terminal can also be a personal computer (Personal Computer, PC), such as a laptop portable computer and a desktop computer and so on.

Wherein, an application program for providing task processing in a distributed environment may be installed in the terminal.

The terminal and the server cluster are connected through a communication network. Optionally, the communication network is a wired network or a wireless network.

A server cluster is a server, or consists of several servers, or a virtualization platform, or a cloud computing service center. Server clusters are used to provide background services for applications that provide task processing in a distributed environment. Optionally, the server cluster undertakes the main computing work, and the terminal undertakes the secondary computing work; or, the server cluster undertakes the secondary computing work, and the terminal undertakes the main computing work; or, a distributed computing architecture is used between the terminal and the server cluster for collaborative computing. .

Optionally, the clients of the application programs installed in different terminals are the same, or the clients of the application programs installed on the two terminals are clients of the same type of application programs of different control system platforms. Based on different terminal platforms, the specific form of the client of the application program may also be different, for example, the client of the application program may be a mobile phone client, a PC client, or a global wide area network client.

Those skilled in the art may know that the number of the above-mentioned terminals may be more or less. For example, the above-mentioned terminal may be only one, or the above-mentioned terminal may be dozens or hundreds, or more. The embodiments of the present disclosure do not limit the number of terminals and device types.

Optionally, the system may further include a management device, and the management device and the server cluster are connected through a communication network. Optionally, the communication network is a wired network or a wireless network.

Optionally, the above-mentioned wireless network or wired network uses standard communication technologies and/or protocols. The network is usually the Internet, but can be any network, including but not limited to Local Area Network (LAN), Metropolitan Area Network (MAN), Wide Area Network (WAN), mobile, wired or wireless network, private network, or any combination of virtual private networks). In some embodiments, data exchanged over a network is represented using technologies and/or formats including Hyper Text Mark-up Language (HTML), Extensible Markup Language (XML), and the like. In addition, you can also use services such as Secure Socket Layer (SSL), Transport Layer Security (TLS), Virtual Private Network (VPN), Internet Protocol Security (IPsec), etc. Conventional encryption techniques to encrypt all or some of the links. In other embodiments, custom and/or dedicated data communication techniques may also be used in place of or in addition to the data communication techniques described above.

Hereinafter, each step of the task processing method in a distributed environment in this exemplary embodiment will be described in more detail with reference to the accompanying drawings and embodiments.

FIG. 1 shows a flowchart of a task processing method in a distributed environment in an embodiment of the present disclosure. The methods provided by the embodiments of the present disclosure may be executed by any electronic device with computing processing capability.

As shown in FIG. 1 , the method for processing tasks in a distributed environment by an electronic device includes the following steps:

Step S102, acquiring request information requesting the server to perform the task.

Step S104, determining to send the task to a designated server or a non-designated server according to the request information.

Step S106, if it is determined to send to the non-designated server, obtain the non-designated server capable of executing the task and the execution weight of the non-designated server.

Step S108: Allocate the task to the non-designated server according to the execution weight.

In an embodiment of the present disclosure, by determining to send the task to a designated server or a non-designated server according to the request information, and allocating the task to the non-designated server according to the execution weight, the task is improved. The security and reliability of processing optimize the resource balance of servers in the distributed cluster, and improve the overall throughput and task processing efficiency of the distributed cluster.

Further, by concentrating the request information of processing tasks in a distributed environment, rather than handing it over to the user terminal to determine the server that executes the task, the security and reliability of task processing are improved, and the maintenance cost of the distributed architecture is reduced.

As shown in Figure 2, the task processing method in the distributed environment further includes:

Step S202, acquiring the execution time of the non-designated server processing the task within the designated time.

Step S204: Update the execution weight according to the execution time.

In an embodiment of the present disclosure, the execution efficiency of the non-designated server is determined by acquiring the execution time of the non-designated server processing the task within the designated time, and then the computing resources and service resources that the non-designated server can provide are determined, The allocation of subsequent tasks can be optimized based on this updated execution weight to optimize task processing efficiency in a distributed environment.

As shown in Figure 3, updating the execution weight according to the execution time includes:

Step S302, setting the initial execution weights of the non-designated servers to be equal.

Step S304, determining the sum of the execution time of all the non-designated servers.

Step S306, determining the ratio of the execution time to the total execution time.

Step S308, update the execution weight according to the ratio.

In an embodiment of the present disclosure, by determining the ratio of the execution time to the sum of the execution time, and updating the execution weight according to the ratio, the task processing capability of the server in a distributed environment is synthesized, based on In this way, the execution weight of each server is updated, which not only improves the task processing efficiency in a distributed environment, but also balances the load and throughput of each server.

As shown in Figure 4, determining to send the task to a designated server or a non-designated server according to the request information includes:

Step S402: Parse the request information to determine whether the address information of the designated server is included.

Step S404, if it is determined that the request information includes the address information, send the task to the designated server according to the address information.

In an embodiment of the present disclosure, it is determined by parsing the request information whether the address information of the designated server is included, and if it is determined that the request information includes the address information, the task is sent to the address information according to the address information. The designated server improves the processing efficiency of designated tasks.

Further, the priority of the task of the designated server can be set higher than the priority of the task of the non-designated server.

As shown in FIG. 5 , determining to send the task to a designated server or a non-designated server according to the request information further includes:

Step S502: Parse the request information to determine whether the address information of the designated server is included.

Step S504, if it is determined that the request information does not include the address information, it is determined to send the task to the non-designated server.

In an embodiment of the present disclosure, it is determined by parsing the request information whether the address information of the designated server is included, and if it is determined that the request information does not include the address information, it is determined to send the task to the non-designated server The server, that is, the task is sent to the corresponding non-designated server according to the execution weight. Without the need to determine the designated server, the steps to resolve the address of the designated server are reduced, and the load and throughput of the non-designated server are balanced by the execution weight. quantity.

As shown in Figure 6, the task processing method in the distributed environment further includes:

Step S602, receiving result information of the non-designated server executing the task.

Step S604, determining triple data information and execution time field information contained in the result information.

Step S606: Update triple data in the preset library table according to the triple data information.

Step S608, update the execution time of the redis cache according to the execution time field information.

In an embodiment of the present disclosure, by receiving the result information of the non-designated server executing the task, determining the triple data information and the execution time field information contained in the result information, and updating the preset database respectively The triplet data in the table and the execution time of the redis cache are used as an important basis for the feedback of the execution task and the update of the execution weight.

For example, the triple data information includes task parameters, request address, and application identifier to which the task belongs.

For example, the execution time field information may be written into the redis cache in the format of the task ID, the server ID, and the execution time.

As shown in Figure 7, obtaining the request information requesting the server to perform the task also includes:

Step S702, acquiring the request information.

Step S704, parse that the request information contains the calling service and calling parameters.

Step S706: Determine a requested server range according to the invocation service and the invocation parameter, where the server range includes the designated server and the non-designated server.

In an embodiment of the present disclosure, by parsing the request information including the calling service and the calling parameter, and determining the requested server range according to the calling service and the calling parameter, the servers within the server range are based on a distributed architecture. Responding to task processing requests, it can meet the selection requirements of designated servers and non-designated servers, has high flexibility, and does not require cumbersome architecture layout and maintenance.

The task processing scheme in the distributed environment according to this embodiment of the present disclosure will be described below with reference to FIG. 8 and FIG. 9 .

As shown in Figure 8, the task processing scheme in a distributed environment includes:

Take the user terminal User's request to the distributed application A to execute the task T as an example, that is, the system receives the User's request and requests to execute the task T on the application A. The process of the task allocation module is as follows:

(1) Obtain the information of task T, including called services and parameters.

(2) The system obtains the server list of application A from zookeeper (distributed system coordination), and the servers in the list are available.

Among them, ZooKeeper is a distributed, open source distributed application coordination service, an open source implementation of Google's Chubby, and an important component of Hadoop and Hbase. It is a software that provides consistent services for distributed applications. The functions provided include: configuration maintenance, domain name service, distributed synchronization, group service, etc.

The goal of ZooKeeper is to encapsulate complex and error-prone key services, and provide users with an easy-to-use interface and a system with high performance and stable functions.

ZooKeeper includes a simple set of primitives that provide Java and C interfaces. In the ZooKeeper code version, interfaces for distributed exclusive locks, elections, and queues are provided. The code is in zookeeper_home\src\recipes.

There are two versions of distributed locks and queues in Java and C, and only the Java version is available for elections.

From the server list, select a server to execute the task according to our customized allocation strategy.

(3) As shown in Fig. 8, assuming that the distributed application A has 3 servers, denoted as the first service, 802, the second server 804 and the third server 806, and all are available, the system initially considers that each server is With the same execution opportunity, that is, the same execution weight, this data structure is represented by an array. Expand the size of the task array to 9 to leave room for the execution weights of each server. The three arrays are denoted as array M, array N, and array K respectively.

The first round: respectively take the first elements of the three arrays arrayM[0], arrayN[0] and arrayK[0], and put them into the final array array in turn.

The second round: respectively take the first elements of the three arrays arrayM[1], arrayN[1] and arrayK[1], and put them into the final array array in turn.

The third round: respectively take the first elements of the three arrays arrayM[2], arrayN[2] and arrayK[2], and put them into the final array array in turn.

When the user's request is detected, if the user does not specify the hash (hash) field value, then directly execute hash (User's ip address)% 9 to obtain the ip address of the server to perform the task.

If User specifies the hash field value, execute hash (specified field value)%9 to select the server to be executed, so that User can independently decide which server to execute task T on.

(4) When the task T is executed, it will actively update the library table and the execution time field of the task in redis (in milliseconds ms).

As shown in Figure 9, the execution weight of each server in distributed application A will also be updated. The specific update method is as follows:

(1) Take the execution time of the last 5 tasks T from the first server 802, and take the average value

Assuming that the result is 21ms, the average execution time of the second server 804 and the third server 806 is similarly 32ms and 45ms, respectively. Then the proportion of the execution time of the first server 802 is 21ms/(21ms+32ms+45ms)=21%, the proportion of the execution time of the second server 804 is 32ms/(21ms+32ms+45ms)=32%, the third server The proportion of 806 execution time is 45ms/(21ms+32ms+45ms)=45%.

(2) The ratio value shows that the efficiency of the first server 802 is higher, followed by the second server 804 and the third server 806, so the number of tasks allocated to the first server 802 can be increased. For example, the execution weight can be allocated in reverse order, as follows. :

(2.1) The number of arrays is the number of servers ² , that is, 3 ² = 9, and the execution time of the first server 802 accounts for 21%, then the weight of the first server 802 is adjusted to 45%, and 9×45% The calculation result is rounded up to 4. The execution time of the second server 804 accounts for 32%, the weight of the second server 804 is 32%, and the calculation result of 9×32% is rounded to 3. If the execution time of the third server 806 accounts for 45%, the weight of the third server 806 is 21%, and the calculation result of 9×21% is rounded to 2.

(2.2) As shown in Figure 9, the server identifier (that is, the identifier that can uniquely find the server, which can be an ip address) is put into an array by weight, and the three arrays are recorded as array M', array N' and array K' respectively. .

The first round: take the first elements of the three arrays arrayM'[0], arrayN'[0], arrayK'[0], and put them into the final array array in turn.

The second round: respectively take the first elements of the three arrays arrayM'[1], arrayN'[1], arrayK'[1], and put them into the final array array in turn.

Third round: Since arrayK' has only two elements, it will not participate in the third round. Take arrayM'[2] and arrayN'[2] and put them into the final array array in turn.

The fourth round: the first element of the array M', arrayM'[3], is put into the final array array.

In this embodiment, the average execution time of the last Z tasks T may be taken, where Z is a positive integer, and Z may be set to 5, for example, to redefine the execution weight of each server.

For the task execution time, it is affected by many factors, such as: the configuration of the server executing the task, the load status of the server's CPU, etc., so the historical execution time of the task does not have much reference value, only the most recent execution time. The reference value measures the current load of the server through the average execution time of the last Z.

In the embodiment of the present disclosure, the reason for taking the average value of the execution time instead of the variance is because the average value can reflect the load of the server, and the variance can only reflect the fluctuation of the execution time, but cannot reflect the server load, that is, the variance The load of a small server can be very high or very low, so it is impossible to judge the load state of the server, so the average value of the execution time is preferred to evaluate the execution weight of the server.

The task processing apparatus 1000 in a distributed environment according to this embodiment of the present disclosure will be described below with reference to FIG. 10 . The task processing apparatus 1000 in a distributed environment shown in FIG. 10 is only an example, and should not impose any limitations on the functions and scope of use of the embodiments of the present disclosure.

As shown in FIG. 10 , the task processing apparatus 1000 in a distributed environment is represented in the form of hardware modules. The components of the task processing apparatus 1000 in a distributed environment may include, but are not limited to: an acquisition module 1002 , a determination module 1004 and an allocation module 1006 .

The obtaining module 1002 is configured to obtain request information for requesting the server to perform a task.

The determining module 1004 is configured to determine, according to the request information, to send the task to a designated server or a non-designated server.

The acquiring module 1002 is further configured to acquire the non-designated server capable of executing the task and the execution weight of the non-designated server if it is determined to be sent to the non-designated server.

An allocation module 1006, configured to allocate the task to the non-designated server according to the execution weight.

The electronic device 1100 according to this embodiment of the present disclosure is described below with reference to FIG. 11 . The electronic device 1100 shown in FIG. 11 is only an example, and should not impose any limitation on the function and scope of use of the embodiments of the present disclosure.

As shown in FIG. 11, electronic device 1100 takes the form of a general-purpose computing device. Components of the electronic device 1100 may include, but are not limited to: the above-mentioned at least one processing unit 1110 , the above-mentioned at least one storage unit 1120 , and a bus 1130 connecting different system components (including the storage unit 1120 and the processing unit 1110 ).

The storage unit stores program codes, which can be executed by the processing unit 1110, so that the processing unit 1110 performs the steps according to various exemplary embodiments of the present disclosure described in the above-mentioned "Exemplary Methods" section of this specification. For example, the processing unit 1110 may execute the steps defined in the task processing method in a distributed environment of the present disclosure.

The storage unit 1120 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 11201 and/or a cache storage unit 11202 , and may further include a read only storage unit (ROM) 11203 .

The storage unit 1120 may also include a program/utility 11204 having a set (at least one) of program modules 11205 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, An implementation of a network environment may be included in each or some combination of these examples.

The bus 1130 may be representative of one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local area using any of a variety of bus structures bus.

The electronic device 1100 may also communicate with one or more external devices 1140 (eg, keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device, and/or The electronic device 1100 can communicate with any device (eg, router, modem, etc.) that communicates with one or more other computing devices. Such communication may occur through input/output (I/O) interface 1150 . Also, the electronic device 1100 can communicate with one or more networks (eg, a local area network (LAN), a wide area network (WAN), and/or a public network such as the Internet) through a network adapter 1110 , which communicates with the electronic device 1100 through a bus 1130 . communication with other modules. It should be understood that, although not shown in the figures, other hardware and/or software modules may be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RA identification systems, tape drives and data backup storage systems.

From the description of the above embodiments, those skilled in the art can easily understand that the exemplary embodiments described herein may be implemented by software, or may be implemented by software combined with necessary hardware. Therefore, the technical solutions according to the embodiments of the present disclosure may be embodied in the form of software products, and the software products may be stored in a non-volatile storage medium (which may be CD-ROM, U disk, mobile hard disk, etc.) or on the network , including several instructions to cause a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to an embodiment of the present disclosure.

In an exemplary embodiment of the present disclosure, there is also provided a computer-readable storage medium on which a program product capable of implementing the above-described method of the present specification is stored. In some possible implementations, various aspects of the present disclosure can also be implemented in the form of a program product, which includes program code, when the program product runs on a terminal device, the program code is used to cause the terminal device to execute the above-mentioned procedures in this specification. Steps according to various exemplary embodiments of the present disclosure are described in the "Example Methods" section.

A program product for implementing the above method according to an embodiment of the present disclosure may adopt a portable compact disc read only memory (CD-ROM) and include program codes, and may run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto, and in this document, a readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

A computer readable signal medium may include a propagated data signal in baseband or as part of a carrier wave with readable program code embodied thereon. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing. A readable signal medium can also be any readable medium, other than a readable storage medium, that can transmit, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.

Program code embodied on a readable medium may be transmitted using any suitable medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Program code for performing the operations of the present disclosure may be written in any combination of one or more programming languages, including object-oriented programming languages—such as Java, C++, etc., as well as conventional procedural programming Language - such as the "C" language or similar programming language. The program code may execute entirely on the user computing device, partly on the user device, as a stand-alone software package, partly on the user computing device and partly on a remote computing device, or entirely on the remote computing device or server execute on. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (eg, using an Internet service provider business via an Internet connection).

It should be noted that although several modules or units of the apparatus for action performance are mentioned in the above detailed description, this division is not mandatory. Indeed, according to embodiments of the present disclosure, the features and functions of two or more modules or units described above may be embodied in one module or unit. Conversely, the features and functions of one module or unit described above may be further divided into multiple modules or units to be embodied.

Additionally, although the various steps of the methods of the present disclosure are depicted in the figures in a particular order, this does not require or imply that the steps must be performed in the particular order or that all illustrated steps must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step for execution, and/or one step may be decomposed into multiple steps for execution, and the like.

From the description of the above embodiments, those skilled in the art can easily understand that the exemplary embodiments described herein may be implemented by software, or may be implemented by software combined with necessary hardware. Therefore, the technical solutions according to the embodiments of the present disclosure may be embodied in the form of software products, and the software products may be stored in a non-volatile storage medium (which may be CD-ROM, U disk, mobile hard disk, etc.) or on the network , which includes several instructions to cause a computing device (which may be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute a method according to an embodiment of the present disclosure.

Other embodiments of the present disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common general knowledge or techniques in the technical field not disclosed by this disclosure . The specification and examples are to be regarded as exemplary only, with the true scope and spirit of the disclosure being indicated by the appended claims.

Industrial Applicability

Claims

A task processing method in a distributed environment, comprising:

Get the request information that requests the server to perform the task;

Determine to send the task to a designated server or a non-designated server according to the request information;

If it is determined to send to the non-designated server, obtain the non-designated server capable of executing the task and the execution weight of the non-designated server;

The tasks are allocated to the non-designated servers according to the execution weights.
The task processing method in a distributed environment according to claim 1, further comprising:

Obtain the execution time of the non-designated server processing the task within the specified time;

The execution weight is updated according to the execution time.
The task processing method in a distributed environment according to claim 2, wherein updating the execution weight according to the execution time comprises:

Set the initial execution weights of the non-designated servers to be equal;

determining the sum of the execution times of all said non-designated servers;

determining the proportion of the execution time to the sum of the execution times;

The execution weights are updated according to the scale.
The task processing method in a distributed environment according to claim 1, wherein determining to send the task to a designated server or a non-designated server according to the request information comprises:

Parse the request information to determine whether it contains the address information of the specified server;

If it is determined that the request information includes the address information, the task is sent to the designated server according to the address information.
The task processing method in a distributed environment according to claim 1, wherein determining to send the task to a designated server or a non-designated server according to the request information further comprises:

Parse the request information to determine whether it contains the address information of the specified server;

If it is determined that the request information does not include the address information, it is determined to send the task to the non-designated server.
The task processing method in a distributed environment according to any one of claims 1-5, further comprising:

receiving result information of the non-designated server performing the task;

Determine the triple data information and execution time field information contained in the result information;

Update the triple data in the preset library table according to the triple data information;

Update the execution time of the redis cache according to the execution time field information.
The task processing method in a distributed environment according to any one of claims 1-5, wherein obtaining request information requesting a server to perform a task comprises:

obtain the request information;

Parse the request information including the calling service and calling parameters;

The server scope of the request is determined according to the invocation service and the invocation parameter, and the server scope includes the designated server and the non-designated server.
A task processing device in a distributed environment, comprising:

The obtaining module is used to obtain the request information for requesting the server to perform the task;

a determining module, configured to determine to send the task to a designated server or a non-designated server according to the request information;

The obtaining module is further configured to, if it is determined to be sent to the non-designated server, obtain the non-designated server capable of executing the task and the execution weight of the non-designated server;

an allocation module, configured to allocate the task to the non-designated server according to the execution weight.
An electronic device, comprising:

processor; and

a memory for storing executable instructions for the processor;

Wherein, the processor is configured to execute the task processing method in a distributed environment according to any one of claims 1-7 by executing the executable instructions.
A computer-readable storage medium on which a computer program is stored, characterized in that:

When the computer program is executed by the processor, the task processing method in a distributed environment according to any one of claims 1-7 is implemented.