CN107968810B - Resource scheduling method, device and system for server cluster - Google Patents
Resource scheduling method, device and system for server cluster Download PDFInfo
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- CN107968810B CN107968810B CN201610917683.6A CN201610917683A CN107968810B CN 107968810 B CN107968810 B CN 107968810B CN 201610917683 A CN201610917683 A CN 201610917683A CN 107968810 B CN107968810 B CN 107968810B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
- H04L67/1004—Server selection for load balancing
- H04L67/1008—Server selection for load balancing based on parameters of servers, e.g. available memory or workload
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
- H04L67/1004—Server selection for load balancing
- H04L67/1012—Server selection for load balancing based on compliance of requirements or conditions with available server resources
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
- H04L67/1029—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers using data related to the state of servers by a load balancer
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
- H04L67/1031—Controlling of the operation of servers by a load balancer, e.g. adding or removing servers that serve requests
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Abstract
The embodiment of the application provides a resource scheduling method, a device and a system for a server cluster, wherein the method comprises the following steps: determining one or more target servers in a server cluster; when a first preset condition is met, resources are distributed for the offline application object from the one or more target servers; and when the second preset condition is met, recovering the resources on the one or more target servers, so that the offline application objects can share the resources of the target servers, and the utilization rate of the server resources is improved.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a resource scheduling method for a server cluster, a resource scheduling apparatus for a server cluster, and a resource scheduling system for a server cluster.
Background
Resource scheduling refers to finding out appropriate server resources from a data center (machine room) when an application object is deployed, and then allocating the server resources to the application object for use. In general, application objects may include both online application objects and offline application objects.
In order to improve the utilization rate of server resources, in the prior art, a plurality of different application objects can be deployed on the same server, so that the plurality of application objects run simultaneously, and the CPU, the memory and the disk resources required by the application objects with different processes are dynamically adjusted by analyzing and predicting historical data.
However, different service scenarios have different requirements for server resources, and sharing server resources according to the above method cannot meet the requirements of specific services. Taking e-commerce as an example, the e-commerce generally involves a plurality of links such as seller, buyer, logistics, payment, etc., and has higher requirements for the dependency relationship and data consistency on the business, except for the need of fast responding to the user's needs, the data related to the transaction cannot be wrong, otherwise, errors of the goods and fund data will be brought, and huge losses are caused to the system and the user.
Therefore, if the online application object for the e-commerce service is mixed with other application objects and deployed on the same server according to the method, there is a great risk of data errors when switching between the online application object and the offline application object. In addition, from the perspective of resource utilization, the appeal of the online application object and the appeal of the offline application object to the resource are obviously different, and the priority level of the online application object is generally higher and more standardized; and the priority of the off-line application object is lower, the off-line application object is more personalized, and the direct dependence degree on the underlying system of the server is different. Therefore, the mixed deployment scheme in the prior art is easy to cause the conflict between the online application object and the offline application object in the environment.
Disclosure of Invention
In view of the above problems, embodiments of the present application are provided to provide a resource scheduling method for a server cluster, a resource scheduling apparatus for a server cluster, and a corresponding resource scheduling system for a server cluster, which overcome or at least partially solve the above problems.
In order to solve the above problem, the present application discloses a resource scheduling system of a server cluster, including: the system comprises an identification unit, a scheduling unit and a plurality of servers;
the identification unit determines one or more target servers from the plurality of servers;
when meeting a first preset condition, the scheduling unit allocates resources for the offline application objects from the one or more target servers; and when a second preset condition is met, recovering the resources on the one or more target servers.
In order to solve the above problem, the present application further discloses a resource scheduling method for a server cluster, including:
determining one or more target servers in a server cluster;
when a first preset condition is met, resources are distributed for the offline application object from the one or more target servers;
and when a second preset condition is met, recovering the resources on the one or more target servers.
Optionally, the step of determining one or more target servers in the server cluster includes:
acquiring one or more online servers in a server cluster, wherein one or more online servers are respectively provided with one or more online application objects;
counting the quantity of offline resources of the one or more online application objects;
and determining one or more target servers according to the quantity of the offline resources.
Optionally, the step of counting the number of offline resources of the one or more online application objects includes:
acquiring load data of the one or more online application objects;
and counting the quantity of offline resources of the one or more online application objects according to the load data.
Optionally, the step of determining one or more target servers according to the number of downline resources includes:
and stopping the operation of one or more online servers according to the quantity of the offline resources to obtain one or more target servers.
Optionally, before the step of determining one or more target servers in the server cluster, the method further includes:
the server cluster is divided into an online resource cluster and an offline resource cluster.
Optionally, the step of dividing the server cluster into an online resource cluster and an offline resource cluster includes:
acquiring current resource state information of one or more servers in a server cluster;
and dividing the server cluster into an online resource cluster and an offline resource cluster according to the current resource state information of the one or more servers.
Optionally, the step of obtaining current resource status information of one or more servers in the server cluster includes:
respectively acquiring one or more application objects which are currently operated on the one or more servers, wherein the one or more application objects respectively have corresponding application attribute information, and the application attribute information comprises online application information or offline application information;
and respectively determining the current resource state information of the one or more servers according to the online application information or the offline application information.
Optionally, when the first preset condition is satisfied, the step of allocating resources for the offline application object from the one or more target servers includes:
and when the first preset condition is met, distributing resources for the offline application object from one or more target servers in the offline resource cluster.
Optionally, when a second preset condition is met, the step of recovering the resources on the one or more target servers includes:
when a second preset condition is met, stopping running of the offline application objects on the one or more target servers;
and allocating the target server after the running of the offline application object is stopped to the online application object.
Optionally, the first preset condition is that a resource scheduling request of an offline application object is received; the second preset condition is that a preset time point is reached.
Optionally, the one or more target servers have one or more online application objects thereon, and after the step of allocating resources for the offline application objects from the one or more target servers when the first preset condition is met, the method further includes:
performing an update operation on the one or more online application objects on the one or more target servers.
In order to solve the above problem, the present application further discloses a resource scheduling method for a server cluster, including:
acquiring one or more online servers in a server cluster, wherein one or more online servers are respectively provided with one or more online application objects;
counting the quantity of offline resources of the one or more online application objects;
determining one or more target servers according to the quantity of the offline resources;
and when the first preset condition is met, allocating resources for the offline application object from the one or more target servers.
In order to solve the above problem, the present application further discloses a resource scheduling method for a server cluster, including:
when a second preset condition is met, stopping running of the offline application objects on one or more target servers in the server cluster;
and allocating the target server after the running of the offline application object is stopped to the online application object.
In order to solve the above problem, the present application further discloses a resource scheduling apparatus for a server cluster, including:
the determining module is used for determining one or more target servers in the server cluster;
the distribution module is used for distributing resources for the offline application objects from the one or more target servers when a first preset condition is met;
and the recovery module is used for recovering the resources on the one or more target servers when a second preset condition is met.
Optionally, the determining module includes:
the acquisition submodule is used for acquiring one or more online servers in the server cluster, and one or more online application objects are respectively deployed on the one or more online servers;
the statistics submodule is used for counting the quantity of offline resources of the one or more online application objects;
and the determining submodule is used for determining one or more target servers according to the quantity of the off-line resources.
Optionally, the statistics submodule includes:
an obtaining unit, configured to obtain load data of the one or more online application objects;
and the counting unit is used for counting the quantity of offline resources of the one or more online application objects according to the load data.
Optionally, the determining sub-module includes:
and the stopping unit is used for stopping the operation of one or more online servers according to the quantity of the offline resources to obtain one or more target servers.
Optionally, the method further comprises:
and the dividing module is used for dividing the server cluster into an online resource cluster and an offline resource cluster.
Optionally, the dividing module includes:
the resource state information acquisition submodule is used for acquiring the current resource state information of one or more servers in the server cluster;
and the resource cluster dividing submodule is used for dividing the server cluster into an online resource cluster and an offline resource cluster according to the current resource state information of the one or more servers.
Optionally, the resource status information obtaining sub-module includes:
an application attribute information obtaining unit, configured to obtain one or more application objects currently running on the one or more servers, where the one or more application objects have corresponding application attribute information, respectively, and the application attribute information includes online application information or offline application information;
and the resource state information determining unit is used for respectively determining the current resource state information of the one or more servers according to the online application information or the offline application information.
Optionally, the allocation module comprises:
and the offline distribution submodule is used for distributing resources for the offline application object from one or more target servers in the offline resource cluster when a first preset condition is met.
Optionally, the recycling module comprises:
the stopping submodule is used for stopping the running of the off-line application objects on the one or more target servers when a second preset condition is met;
and the online distribution submodule is used for distributing the target server after the running of the offline application object is stopped to the online application object.
Optionally, the first preset condition is that a resource scheduling request of an offline application object is received; the second preset condition is that a preset time point is reached.
Optionally, the one or more target servers have one or more online application objects thereon, and the apparatus further includes:
an update module to perform an update operation on the one or more online application objects on the one or more target servers.
In order to solve the above problem, the present application further discloses a resource scheduling apparatus for a server cluster, including:
the server acquisition module is used for acquiring one or more online servers in the server cluster, and one or more online application objects are respectively deployed on the one or more online servers;
the offline resource counting module is used for counting the quantity of offline resources of the one or more online application objects;
the target server determining module is used for determining one or more target servers according to the quantity of the off-line resources;
and the offline resource allocation module is used for allocating resources for the offline application object from the one or more target servers when a first preset condition is met.
In order to solve the above problem, the present application further discloses a resource scheduling apparatus for a server cluster, including:
the offline application object stopping module is used for stopping the operation of the offline application objects on one or more target servers in the server cluster when a second preset condition is met;
and the online resource allocation module is used for allocating the target server after the running of the offline application object is stopped to the online application object.
Compared with the background art, the embodiment of the application has the following advantages:
according to the method and the device, one or more target servers in the server cluster are determined, when a first preset condition is met, resources are distributed for the offline application object from the one or more target servers, and when a second preset condition is met, the resources on the one or more target servers are recovered, so that the offline application object can share the resources of the target servers, and the utilization rate of the server resources is improved.
Secondly, by dividing the online resource cluster and the offline resource cluster, the embodiment of the application can effectively isolate the online application object and the offline application object, ensure data security, and meanwhile, the offline application object can fully utilize the resources of the whole server, and the operation environment of the online application object cannot be influenced in the operation process.
Drawings
Fig. 1 is a flowchart illustrating a first step of a resource scheduling method of a server cluster according to the present application;
FIG. 2 is a functional block diagram of a resource scheduling method of a server cluster according to the present application;
FIG. 3 is a schematic diagram of an online resource application of the present application;
FIG. 4 is a schematic diagram of an offline resource application of the present application;
fig. 5 is a flowchart illustrating steps of a second embodiment of a resource scheduling method for a server cluster according to the present application;
fig. 6 is a flowchart illustrating a third step of a resource scheduling method of a server cluster according to the present application;
fig. 7 is a flowchart illustrating a fourth step of a resource scheduling method of a server cluster according to the present application;
fig. 8 is a block diagram of a first embodiment of a resource scheduling apparatus for a server cluster according to the present application;
fig. 9 is a block diagram illustrating a second embodiment of a resource scheduling apparatus for a server cluster according to the present application;
fig. 10 is a block diagram of a third embodiment of a resource scheduling apparatus for a server cluster according to the present application;
fig. 11 is a block diagram of a resource scheduling system of a server cluster according to an embodiment of the present disclosure.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, the present application is described in further detail with reference to the accompanying drawings and the detailed description.
Referring to fig. 1, a flowchart illustrating a first step of a resource scheduling method of a server cluster according to the present application is shown, where the method may specifically include the following steps:
in general, a server cluster may refer to a resource pool composed of a plurality of servers, and may support the operation of different services or services by providing resources for various application objects, where the services may include online services or offline services or services.
The off-line business or service can be the business or service mainly used for off-line big data calculation, and the off-line business or service has a large number of tasks and a short life cycle. The online business or service is mainly used for online service, and is characterized by relatively small number of tasks, long life cycle of the tasks, and few offline tasks once the tasks are online, and can generally run for 3-5 years or even longer, so that the online business or service has higher requirements on stability and is more sensitive to response time.
Thus, the server cluster may further include an online resource cluster and an offline resource cluster.
Generally, a plurality of different application objects may be deployed on different servers, and when the application objects deployed on a certain server are all services or services for executing online, the server may be determined as an online server, and a cluster formed by a plurality of online servers is an online resource cluster; similarly, when all application objects deployed on a certain server are services or services for performing offline, the server may be determined as an offline server, and a cluster formed by a plurality of offline servers is an offline resource cluster.
In a preferred embodiment of the present application, before the step of determining one or more target servers in the server cluster, the method may further include the following steps:
s11, dividing the server cluster into an online resource cluster and an offline resource cluster.
In a specific implementation, the servers in the server cluster may be divided into an online resource cluster and an offline resource cluster according to the current resource state information of the servers. The current resource status information of the server may be determined according to the application object running on the server, for example, for a server mainly running an online application object, the server may be divided into an online resource cluster, and the remaining other servers may be divided into offline resource clusters.
It should be noted that, in the embodiment of the present application, dividing the servers into the online resource cluster and the offline resource cluster is mainly a logical division, rather than a physical division.
Generally, after a server cluster is divided into an online resource cluster and an offline resource cluster, corresponding resource lists may also be generated respectively for recording server information in the cluster, where the resource lists may include an online resource list and an offline resource list.
In a specific implementation, when an application object is generated, corresponding application attribute information may be marked for the application object, where the application attribute information may include online application information or offline application information, and it may be determined that the application object is an application object for executing an online service or service, or an application object for executing an offline service or service through the application attribute information.
After the servers are divided into online resource clusters and offline resource clusters, one or more idle target servers may be determined from the online resource clusters.
In this embodiment of the present application, the target server may refer to an idle server in the online resource cluster, and the idle server may refer to a server state when resources on the server may be provided for other application objects to be used, and in this state, the online application object on the server only occupies storage and a hard disk of the resources, and does not occupy computing resources such as a Central Processing Unit (CPU).
102, when a first preset condition is met, distributing resources for the offline application object from the one or more target servers;
in this embodiment of the present application, the first preset condition may be that a resource scheduling request of an offline application object is received.
Fig. 2 is a schematic block diagram of a resource scheduling method for a server cluster according to the present application. When a resource scheduling request of an offline application object is received, resources can be allocated to the offline application object from a target server in an idle state.
Fig. 3 is a schematic diagram of an online resource request according to the present application. Typically, the online Application object may initiate an online resource request through a WEB (internet) page or an API (Application Programming Interface). The WEB page application means that displayed parameters are manually filled in a WEB page by a user, and in the API application, the parameters are automatically acquired by the system. Generally, WEB pages are usually executed serially, and APIs are executed concurrently, and the difference between the two is mainly in the form of service export of resource applications.
The content of the request may include: resource information, such as the number of CPUs, the size of a memory, the size of a disk and the size of network bandwidth; deployment information, such as machine room information, rack information, switch information; and the application information comprises the conditions of no state, no asset loss, starting speed, online and offline properties and the like.
The offline resource application is mainly oriented to an external scheduling system, so that the offline application object which needs to perform the resource application mainly initiates a resource scheduling request through an API interface. Fig. 4 is a schematic diagram of an offline resource application according to the present application.
Unlike the online resource request, the offline resource request is to provide the entire server resource for resource sharing, and therefore, the content included in the offline resource request does not have parameters such as application characteristic data and stability data.
In a specific implementation, when there are idle server resources, an offline application object can sense the available size and available time period of the idle server resources, and when the available size and available time period of the idle server resources can meet the requirements of the offline application object, the offline application object may initiate a corresponding resource scheduling request to request allocation of the idle server resources to the offline application object.
It should be noted that not any idle server resource can be allocated to the offline application object, and the offline application object will initiate a corresponding resource scheduling request only when the idle server resource reaches a certain scale or can meet the corresponding requirement of the offline application object.
And 103, when a second preset condition is met, recovering the resources on the one or more target servers.
In this embodiment of the application, the second preset condition may refer to that a preset time point is reached, for example, 6 am every day is set, and when the time point is reached, the resource on the target server provided for the offline application object to use may be recovered back so as to be reallocated to the online application object to use.
In specific implementation, when a preset time point is reached, the shared resources can be recycled by gradually stopping the operation of the offline application objects on the target server.
In the embodiment of the application, one or more target servers in a server cluster are determined, resources are allocated to the offline application object from the one or more target servers when a first preset condition is met, and the resources on the one or more target servers are recovered when a second preset condition is met, so that the offline application object can share the resources of the target servers, and the utilization rate of the server resources is improved.
Referring to fig. 5, a flowchart illustrating steps of a second embodiment of a resource scheduling method for a server cluster according to the present application is shown, which may specifically include the following steps:
in general, a server cluster may refer to a resource pool composed of a plurality of servers, and may support the operation of different services or services by providing resources for various application objects, where the services may include online services or offline services or services.
Thus, the server cluster may further include an online resource cluster and an offline resource cluster.
In this embodiment of the present application, in order to divide the server cluster into an online resource cluster and an offline resource cluster, current resource state information of one or more servers in the server cluster may be first obtained.
In a preferred embodiment of the present application, the step of obtaining current resource status information of one or more servers in a server cluster may specifically include the following sub-steps:
substep 5011, respectively acquiring one or more application objects currently running on the one or more servers, where the one or more application objects respectively have corresponding application attribute information, and the application attribute information includes online application information or offline application information;
substep 5012, determining the current resource status information of the one or more servers according to the online application information or the offline application information.
Generally, a plurality of different application objects may be deployed on different servers, and when the application objects are generated, the application objects are marked with corresponding application attribute information, where the application attribute information may include online application information or offline application information, and it may be determined through the application attribute information that the application objects are application objects for executing online business or service or application objects for executing offline business or service, for example, an application object marked with online application information is generally an online application object, and an application object marked with offline application information is generally an offline application object.
Then, the resource state information of the server may be determined according to the attribute information of the application object deployed on the server, for example, when the server mainly runs the online application object, the resource state information of the server may be considered as an online resource, and when the server mainly runs the offline application object, the resource state information of the server may be considered as an offline resource, and then it may be determined that the resource provided by the server is used for an online task or an offline task through the resource state information.
In a specific implementation, when all application objects deployed on a certain server are used for executing online services or services, the server may be determined as an online server, and a cluster formed by a plurality of online servers is an online resource cluster; similarly, when all application objects deployed on a certain server are services or services for performing offline, the server may be determined as an offline server, and a cluster formed by a plurality of offline servers is an offline resource cluster.
in this embodiment of the present application, one or more target servers in an idle state may be determined from servers in an online resource cluster, and on the target server, an online application object only occupies storage and a hard disk of resources, but does not occupy computing resources such as a Central Processing Unit (CPU).
In a preferred embodiment of the present application, the step of determining one or more target servers in the server cluster may specifically include the following sub-steps:
substep 5031, acquiring one or more online servers in the server cluster, wherein one or more online servers are respectively provided with one or more online application objects;
substep 5032, counting the number of offline resources of the one or more online application objects;
substep 5033, determining one or more target servers according to the quantity of the offline resources.
In the embodiment of the application, on the premise that the server capacity required by the online application object is sufficient, the number of corresponding instances of the online application object exceeding the lowest capacity level can be reduced. The capacity may refer to a minimum number of instances required by an application object to complete a certain task or service request.
In a specific implementation, the same capacity water level calculation can be performed on a batch of online application objects, the number of instances that each application can reduce the capacity is obtained, the number of off-line resources of each application object is determined, and then the off-line processing is performed on the corresponding off-line instances according to the number of the off-line resources.
It should be noted that, when offline processing is performed on an offline instance, multiple offline instances on the same server machine may be preferentially offline, so as to ensure that as many complete server resources as possible are vacated, and then one or more complete servers that are vacated may be added to the offline resource cluster.
In an embodiment of the present application, the sub-step of counting the number of offline resources of the one or more online application objects may further include:
s21, acquiring load data of the one or more online application objects;
s22, according to the load data, counting the quantity of the offline resources of the one or more online application objects.
In a specific implementation, load data of the online application object, for example, a current CPU resource, a memory resource, a disk resource, and the like used by the online application object, may be obtained, and then the load data is used to calculate the number of off-line resources. In general, the offline resource data of the application object can be determined according to the current total resource data of the application object and the minimum resource amount of the application object. The current total resource quantity of the application object can be directly obtained through a resource control system, and the resource control system can be used for recording all data records generated in the resource application and destruction processes of the application object.
Generally, after a server cluster is divided into an online resource cluster and an offline resource cluster, corresponding resource lists may also be generated respectively for recording server information in the cluster, where the resource lists may include an online resource list and an offline resource list.
In an embodiment of the present application, the sub-step of determining one or more target servers according to the number of downline resources may further include:
and S31, stopping the operation of one or more online servers according to the quantity of the off-line resources, and acquiring one or more target servers.
In a specific implementation, the resources occupied by the online application object may be adjusted according to the number of offline resources of the servers in the online resource cluster, so that the offline resources are preferentially concentrated on each whole online server, and then the server that stops the operation of the online application object may be identified as the target server and added to the offline resource cluster.
in this embodiment of the present application, the meeting of the first preset condition may refer to that when a resource scheduling request of an offline application object is received, at this time, a resource on a target server in an offline resource cluster may be allocated to the offline application object for use.
Generally, when there are idle server resources, an offline application object can sense the available size and available time period of the idle server resources, and when the available size and available time period of the idle server resources can meet the requirements of the offline application object, the offline application object may initiate a corresponding resource scheduling request to request allocation of the idle server resources to the offline application object.
In a specific implementation, the offline application object mainly initiates a resource scheduling request through an API interface, where the request may include resource information, such as the number of CPUs, the size of a memory, the size of a disk, and the size of a network bandwidth; deployment information, such as machine room information, rack information, switch information; and the application information comprises the conditions of no state, no asset loss, starting speed, online and offline properties and the like.
It should be noted that, after the resources on the target server are allocated to the offline application object, the update operation may be performed on the one or more target servers on the one or more online application objects.
In this embodiment of the application, the second preset condition may refer to that the running of the offline application object on the target server is stopped when a preset time point is reached, that is, the preset time point is reached, so that the resource of the target server is recovered and reallocated to the online application object, so as to meet the use requirement of the online application object for the resource.
In the embodiment of the application, the server resources can arrange and isolate the idle resources through elastic management according to the running state of the online application object, so that the whole idle resources can be shared by the offline application object, meanwhile, according to convention, after the sharing time is over, the running of the offline application object is finished, the idle resources are recovered, added into the online resource cluster, and distributed to the online application object again for use, and the use efficiency of the resources is improved.
Referring to fig. 6, a flowchart illustrating a third step of the embodiment of the resource scheduling method for a server cluster according to the present application is shown, which may specifically include the following steps:
601, acquiring one or more online servers in a server cluster, wherein one or more online servers are respectively provided with one or more online application objects;
since steps 601 to 603 are similar to sub-steps 5031 to 5033 in the above embodiment, they can refer to each other, and this embodiment is not described again.
And step 604, when a first preset condition is met, allocating resources for the offline application object from the one or more target servers.
In this embodiment of the present application, the meeting of the first preset condition may refer to that when a resource scheduling request of an offline application object is received, at this time, a resource on a target server in an offline resource cluster may be allocated to the offline application object for use.
In the embodiment of the application, by acquiring the online servers in the server cluster, then counting the quantity of offline resources in the online servers, and determining one or more target servers according to the quantity of the offline resources, when a resource scheduling request of an offline application object is received, resources can be allocated to the offline application object from the target servers, so that idle online server resources are shared with the offline application object, and the utilization rate of server resources is improved.
Referring to fig. 7, a flowchart illustrating a fourth step of the resource scheduling method for a server cluster according to the present application is shown, which may specifically include the following steps:
in this embodiment of the present application, the second preset condition may refer to that a preset time point is reached, and the target server may be a server that shares idle online server resources with an offline application object.
Generally, the server resources used by the offline application object have a certain timeliness, for example, for a server cluster mainly providing the online resources, the online application object may be in a dormant state within a certain time period, such as 3 to 6 am each day, at which time the corresponding server resources may be shared and provided for the offline application object to use, and after the time period is exceeded, the operation of the offline application object may be stopped, and the shared server resources may be recovered.
In the embodiment of the application, when the offline application object on the shared server resource stops running, the recovered server resource can be reallocated to the online application object.
In the embodiment of the application, when the second preset condition is met, the shared server resources can be recovered and reallocated to the online application object, so that the utilization rate of idle resources is improved, and meanwhile, the resources are recovered again when the preset time point is reached, and the use requirement of the online application object on the resources is ensured.
It should be noted that, for simplicity of description, the method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the embodiments are not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the embodiments. Further, those skilled in the art will also appreciate that the embodiments described in the specification are presently preferred and that no particular act is required of the embodiments of the application.
Referring to fig. 8, a block diagram of a first embodiment of a resource scheduling apparatus for a server cluster according to the present application is shown, where the apparatus may specifically include the following modules:
a determining module 801, configured to determine one or more target servers in a server cluster;
an allocating module 802, configured to allocate resources for the offline application object from the one or more target servers when a first preset condition is met;
and the recycling module 803 is configured to recycle the resources on the one or more target servers when a second preset condition is met.
In this embodiment of the application, the determining module 801 may specifically include the following sub-modules:
the acquisition submodule is used for acquiring one or more online servers in the server cluster, and one or more online application objects are respectively deployed on the one or more online servers;
the statistics submodule is used for counting the quantity of offline resources of the one or more online application objects;
and the determining submodule is used for determining one or more target servers according to the quantity of the off-line resources.
In this embodiment, the statistical submodule may specifically include the following units:
an obtaining unit, configured to obtain load data of the one or more online application objects;
and the counting unit is used for counting the quantity of offline resources of the one or more online application objects according to the load data.
In this embodiment of the present application, the determining sub-module may specifically include the following units:
and the stopping unit is used for stopping the operation of one or more online servers according to the quantity of the offline resources to obtain one or more target servers.
In this embodiment, the apparatus may further include the following modules:
and the dividing module is used for dividing the server cluster into an online resource cluster and an offline resource cluster.
In this embodiment, the dividing module may specifically include the following sub-modules:
the resource state information acquisition submodule is used for acquiring the current resource state information of one or more servers in the server cluster;
and the resource cluster dividing submodule is used for dividing the server cluster into an online resource cluster and an offline resource cluster according to the current resource state information of the one or more servers.
In this embodiment of the present application, the resource status information obtaining sub-module may specifically include the following units:
an application attribute information obtaining unit, configured to obtain one or more application objects currently running on the one or more servers, where the one or more application objects have corresponding application attribute information, respectively, and the application attribute information includes online application information or offline application information;
and the resource state information determining unit is used for respectively determining the current resource state information of the one or more servers according to the online application information or the offline application information.
In this embodiment of the present application, the allocating module 802 may specifically include the following sub-modules:
and the offline distribution submodule is used for distributing resources for the offline application object from one or more target servers in the offline resource cluster when a first preset condition is met.
In this embodiment, the recycling module 803 may specifically include the following sub-modules:
the stopping submodule is used for stopping the running of the off-line application objects on the one or more target servers when a second preset condition is met;
and the online distribution submodule is used for distributing the target server after the running of the offline application object is stopped to the online application object.
In this embodiment of the present application, the first preset condition may be that a resource scheduling request of an offline application object is received; the second preset condition may be that a preset time point is reached.
In this embodiment, the one or more target servers may have one or more online application objects thereon, and the apparatus may further include the following modules:
an update module to perform an update operation on the one or more online application objects on the one or more target servers.
Referring to fig. 9, a block diagram of a second embodiment of a resource scheduling apparatus for a server cluster according to the present application is shown, where the apparatus may specifically include the following modules:
a server obtaining module 901, configured to obtain one or more online servers in a server cluster, where the one or more online servers are respectively deployed with one or more online application objects;
a offline resource counting module 902, configured to count the number of offline resources of the one or more online application objects;
a target server determining module 903, configured to determine one or more target servers according to the number of offline resources;
and the offline resource allocation module 904 is configured to allocate resources for the offline application object from the one or more target servers when a first preset condition is met.
Referring to fig. 10, a block diagram of a third embodiment of a resource scheduling apparatus for a server cluster according to the present application is shown, where the apparatus may specifically include the following modules:
an offline application object stopping module 1001, configured to stop running of an offline application object on one or more target servers in the server cluster when a second preset condition is met;
an online resource allocation module 1002, configured to allocate the target server after stopping running of the offline application object to the online application object.
For the device embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.
Referring to fig. 11, a block diagram of a resource scheduling system of a server cluster according to an embodiment of the present application is shown, where the system may specifically include an identification unit 1101, a scheduling unit 1102, and multiple servers;
the identification unit 1101 may determine one or more target servers from the plurality of servers;
the scheduling unit 1102 may allocate resources to the offline application object from the one or more target servers when a first preset condition is met; and when a second preset condition is met, recovering the resources on the one or more target servers.
The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
As will be appreciated by one of skill in the art, embodiments of the present application may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
In a typical configuration, the computer device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory. The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium. Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include non-transitory computer readable media (fransitory media), such as modulated data signals and carrier waves.
Embodiments of the present application are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present application have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including the preferred embodiment and all such alterations and modifications as fall within the true scope of the embodiments of the application.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or terminal that comprises the element.
The foregoing describes in detail a resource scheduling method for a server cluster, a resource scheduling apparatus for a server cluster, and a resource scheduling system for a server cluster, which are provided by the present application, and specific examples are applied herein to explain the principle and the implementation of the present application, and the descriptions of the foregoing examples are only used to help understand the method and the core idea of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (25)
1. The resource scheduling system of the server cluster is characterized by comprising an identification unit, a scheduling unit and a plurality of servers;
the identification unit determines one or more target servers from the plurality of servers;
when meeting a first preset condition, the scheduling unit allocates resources for the offline application objects from the one or more target servers; when a second preset condition is met, recovering resources on the one or more target servers;
the plurality of servers belong to a server cluster, the server cluster comprises an online resource cluster and an offline resource cluster, the online resource cluster is used for providing resources for online application objects, and the offline resource cluster is used for providing resources for offline application objects;
the target server is a server in the online resource cluster.
2. A resource scheduling method for a server cluster is characterized by comprising the following steps:
determining one or more target servers in a server cluster;
when a first preset condition is met, resources are distributed for the offline application object from the one or more target servers;
when a second preset condition is met, recovering resources on the one or more target servers;
before the step of determining one or more target servers in the server cluster, the method further includes:
dividing the server cluster into an online resource cluster and an offline resource cluster, wherein the online resource cluster is used for providing resources for an online application object, and the offline resource cluster is used for providing resources for an offline application object;
the target server is a server in the online resource cluster.
3. The method of claim 2, wherein the step of determining one or more target servers in the server cluster comprises:
acquiring one or more online servers in a server cluster, wherein one or more online servers are respectively provided with one or more online application objects;
counting the quantity of offline resources of the one or more online application objects;
and determining one or more target servers according to the quantity of the offline resources.
4. The method of claim 3, wherein the step of counting the number of downline resources of the one or more online application objects comprises:
acquiring load data of the one or more online application objects;
and counting the quantity of offline resources of the one or more online application objects according to the load data.
5. The method of claim 3 or 4, wherein the step of determining one or more target servers according to the amount of downline resources comprises:
and stopping the operation of one or more online servers according to the quantity of the offline resources to obtain one or more target servers.
6. The method of claim 2, wherein the step of dividing the server cluster into an online resource cluster and an offline resource cluster comprises:
acquiring current resource state information of one or more servers in a server cluster;
and dividing the server cluster into an online resource cluster and an offline resource cluster according to the current resource state information of the one or more servers.
7. The method of claim 6, wherein the step of obtaining current resource status information of one or more servers in the server cluster comprises:
respectively acquiring one or more application objects which are currently operated on the one or more servers, wherein the one or more application objects respectively have corresponding application attribute information, and the application attribute information comprises online application information or offline application information;
and respectively determining the current resource state information of the one or more servers according to the online application information or the offline application information.
8. The method of claim 2, wherein the step of allocating resources for the offline application object from the one or more target servers when the first preset condition is satisfied comprises:
and when the first preset condition is met, distributing resources for the offline application object from one or more target servers in the offline resource cluster.
9. The method of claim 8, wherein the step of reclaiming resources on the one or more target servers when a second preset condition is satisfied comprises:
when a second preset condition is met, stopping running of the offline application objects on the one or more target servers;
and allocating the target server after the running of the offline application object is stopped to the online application object.
10. The method according to claim 9, wherein the first preset condition is that a resource scheduling request of an offline application object is received; the second preset condition is that a preset time point is reached.
11. The method of claim 2, wherein the one or more target servers have one or more online application objects thereon, and wherein after the step of allocating resources for the offline application objects from the one or more target servers when the first predetermined condition is met, the method further comprises:
performing an update operation on the one or more online application objects on the one or more target servers.
12. A resource scheduling method for a server cluster is characterized by comprising the following steps:
acquiring one or more online servers in a server cluster, wherein one or more online servers are respectively provided with one or more online application objects;
counting the quantity of offline resources of the one or more online application objects;
determining one or more target servers according to the quantity of the offline resources;
when a first preset condition is met, resources are distributed for the offline application object from the one or more target servers;
before the step of determining one or more target servers in the server cluster, the method further includes:
dividing the server cluster into an online resource cluster and an offline resource cluster, wherein the online resource cluster is used for providing resources for an online application object, and the offline resource cluster is used for providing resources for an offline application object;
the target server is a server in the online resource cluster.
13. A resource scheduling method for a server cluster is characterized by comprising the following steps:
when a second preset condition is met, stopping running of the offline application objects on one or more target servers in the server cluster;
allocating the target server after stopping the running of the off-line application object to the on-line application object;
the server cluster comprises an online resource cluster and an offline resource cluster, wherein the online resource cluster is used for providing resources for online application objects, and the offline resource cluster is used for providing resources for offline application objects;
the target server is a server in the online resource cluster.
14. A resource scheduling apparatus for a server cluster, comprising:
the determining module is used for determining one or more target servers in the server cluster;
the distribution module is used for distributing resources for the offline application objects from the one or more target servers when a first preset condition is met;
the recovery module is used for recovering the resources on the one or more target servers when a second preset condition is met;
the device further comprises:
the dividing module is used for dividing the server cluster into an online resource cluster and an offline resource cluster, wherein the online resource cluster is used for providing resources for an online application object, and the offline resource cluster is used for providing resources for an offline application object;
the target server is a server in the online resource cluster.
15. The apparatus of claim 14, wherein the determining module comprises:
the acquisition submodule is used for acquiring one or more online servers in the server cluster, and one or more online application objects are respectively deployed on the one or more online servers;
the statistics submodule is used for counting the quantity of offline resources of the one or more online application objects;
and the determining submodule is used for determining one or more target servers according to the quantity of the off-line resources.
16. The apparatus of claim 15, wherein the statistics submodule comprises:
an obtaining unit, configured to obtain load data of the one or more online application objects;
and the counting unit is used for counting the quantity of offline resources of the one or more online application objects according to the load data.
17. The apparatus of claim 15 or 16, wherein the determining sub-module comprises:
and the stopping unit is used for stopping the operation of one or more online servers according to the quantity of the offline resources to obtain one or more target servers.
18. The apparatus of claim 14, wherein the partitioning module comprises:
the resource state information acquisition submodule is used for acquiring the current resource state information of one or more servers in the server cluster;
and the resource cluster dividing submodule is used for dividing the server cluster into an online resource cluster and an offline resource cluster according to the current resource state information of the one or more servers.
19. The apparatus of claim 18, wherein the resource status information obtaining sub-module comprises:
an application attribute information obtaining unit, configured to obtain one or more application objects currently running on the one or more servers, where the one or more application objects have corresponding application attribute information, respectively, and the application attribute information includes online application information or offline application information;
and the resource state information determining unit is used for respectively determining the current resource state information of the one or more servers according to the online application information or the offline application information.
20. The apparatus of claim 14, wherein the assignment module comprises:
and the offline distribution submodule is used for distributing resources for the offline application object from one or more target servers in the offline resource cluster when a first preset condition is met.
21. The apparatus of claim 20, wherein the recovery module comprises:
the stopping submodule is used for stopping the running of the off-line application objects on the one or more target servers when a second preset condition is met;
and the online distribution submodule is used for distributing the target server after the running of the offline application object is stopped to the online application object.
22. The apparatus according to claim 21, wherein the first preset condition is that a resource scheduling request of an offline application object is received; the second preset condition is that a preset time point is reached.
23. The apparatus of claim 14, wherein the one or more target servers have one or more online application objects thereon, the apparatus further comprising:
an update module to perform an update operation on the one or more online application objects on the one or more target servers.
24. A resource scheduling apparatus for a server cluster, comprising:
the server acquisition module is used for acquiring one or more online servers in the server cluster, and one or more online application objects are respectively deployed on the one or more online servers;
the offline resource counting module is used for counting the quantity of offline resources of the one or more online application objects;
the target server determining module is used for determining one or more target servers according to the quantity of the off-line resources;
the offline resource allocation module is used for allocating resources for the offline application objects from the one or more target servers when a first preset condition is met;
the device further comprises:
the dividing module is used for dividing the server cluster into an online resource cluster and an offline resource cluster, wherein the online resource cluster is used for providing resources for an online application object, and the offline resource cluster is used for providing resources for an offline application object;
the target server is a server in the online resource cluster.
25. A resource scheduling apparatus for a server cluster, comprising:
the offline application object stopping module is used for stopping the operation of the offline application objects on one or more target servers in the server cluster when a second preset condition is met;
the online resource allocation module is used for allocating the target server after the operation of the offline application object is stopped to the online application object;
the server cluster comprises an online resource cluster and an offline resource cluster, wherein the online resource cluster is used for providing resources for online application objects, and the offline resource cluster is used for providing resources for offline application objects;
the target server is a server in the online resource cluster.
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| CN108881495B (en) * | 2018-08-13 | 2022-07-22 | 中国平安财产保险股份有限公司 | Resource allocation method, device, computer equipment and storage medium |
| CN110881058B (en) * | 2018-09-06 | 2022-04-12 | 阿里巴巴集团控股有限公司 | Request scheduling method, device, server and storage medium |
| CN110955501B (en) * | 2018-09-27 | 2024-06-14 | 北京京东尚科信息技术有限公司 | Service request processing method, device, electronic equipment and readable medium |
| CN109597688A (en) * | 2018-11-23 | 2019-04-09 | 金色熊猫有限公司 | Online resource management method, device, storage medium and electronic equipment |
| CN109412874B (en) * | 2018-12-21 | 2021-11-02 | 腾讯科技（深圳）有限公司 | Equipment resource configuration method, device, server and storage medium |
| CN111506414B (en) * | 2019-01-30 | 2023-04-25 | 阿里巴巴集团控股有限公司 | Resource scheduling method, device, equipment, system and readable storage medium |
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| CN112269641B (en) * | 2020-11-18 | 2023-09-15 | 网易（杭州）网络有限公司 | Scheduling method, scheduling device, electronic equipment and storage medium |
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