CN114996351A - Database elastic method, database elastic device and database elastic service system - Google Patents
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Abstract
The disclosure relates to a database elastic method, a database elastic device and a database elastic service system, which are applied to the technical field of display and can improve the elastic efficiency of a local disk database under a cloud native architecture. The method comprises the following steps: receiving an elastic request for a target database in a local disk, wherein the target database comprises a first database serving as a standby database and a second database serving as a main database; determining an elastic configuration scheme for the target database; wherein, the elastic matching scheme comprises: performing elastic transformation and configuration processing on the first database to obtain a transformed and configured third database; switching the third database and the second database between a master database and a standby database, switching the third database into the master database of the target database, and switching the second database into the standby database of the target database; and performing elastic transformation and matching processing on the second database to obtain a fourth database after transformation and matching so as to obtain the target database after elastic transformation and matching based on the third database serving as the main database and the fourth database serving as the standby database.
Description
Technical Field
The embodiment of the application relates to a data processing technology. And more particularly, to a database resiliency method, a database resiliency device, and a database resiliency service system.
Background
Currently, elasticity under a cloud native architecture generally refers to elastic scheduling of stateless nodes, including capacity expansion of running application containers. Because the elasticity under the cloud native architecture does not relate to data migration, a scheduling scheme of firstly creating and then deleting can realize the rapid elasticity based on stateless nodes or cloud disks under the cloud native architecture.
Although the local disk is the most widely used database structure with the best performance, the local disk database is a stateful node, and the cloud native architecture has poor support for the local disk, so how to implement the rapid elasticity of the local disk database under the cloud native architecture is an urgent problem to be solved.
Because the elasticity of the local disk database relates to data migration, if a scheduling scheme used by stateless nodes and created first and then deleted is used as an elastic scheduling scheme of the local disk database under a cloud native architecture, a large amount of time is consumed for data migration, so that the data migration affects the performance of the original database, the corresponding service of an application program process in accessing the database is affected, the advantage of the cloud native architecture is lost, and the elastic efficiency of the local disk database under the cloud native architecture is low.
Disclosure of Invention
In order to solve the above technical problems or at least partially solve the above technical problems, the present application provides a database flexible method, a database flexible apparatus, a database flexible service system, a service device, a storage medium, and a program product, which can improve the flexible efficiency of a local disk database under a cloud native architecture.
In a first aspect, an embodiment of the present application provides a database flexible method, including: receiving an elastic request for a target database in a local disk, wherein the target database comprises a first database serving as a standby database and a second database serving as a main database; determining an elastic configuration scheme for the target database; wherein, the elastic matching scheme comprises: performing elastic transformation and configuration processing on the first database to obtain a transformed third database; switching the third database and the second database between a master database and a standby database, switching the third database into the master database of the target database, and switching the second database into the standby database of the target database; and performing elastic transformation and matching processing on the second database to obtain a fourth database after transformation and matching so as to obtain the target database after elastic transformation and matching based on the third database serving as the main database and the fourth database serving as the standby database.
In a second aspect, the present application provides a database elastic apparatus, comprising: a receiving module and a determining module; the receiving module is used for receiving an elastic request for a target database in the local disk, wherein the target database comprises a first database serving as a standby database and a second database serving as a main database; the determining module is used for determining an elastic configuration scheme for the target database; wherein, the elastic matching scheme comprises: performing elastic transformation and configuration processing on the first database to obtain a transformed and configured third database; switching the third database and the second database between a master database and a standby database, switching the third database into the master database of the target database, and switching the second database into the standby database of the target database; and performing elastic transformation and matching processing on the second database to obtain a fourth database after transformation and matching so as to obtain the target database after elastic transformation and matching based on the third database serving as the main database and the fourth database serving as the standby database.
In a third aspect, the present application provides a database elastic service system, including: a resource management microservice module configured to: receiving a target request aiming at a target database, wherein the target request is an elastic request or an elastic evaluation request, and the target database comprises a first database serving as a standby database and a second database serving as a main database; a data service module configured to: providing first resource information on a first host device where a target instance corresponding to the target database is located, wherein the target instance comprises at least one of the following items: a first database, a second database; the first resource information comprises computing resources occupied by each instance and storage resources occupied by each instance on the first host device, idle computing resources of the first host device, and a computing resource overload threshold of the first host device; a resource assessment module configured to: under the condition that the target request is a related request for capacity expansion and transformation, acquiring first resource information from the data service module based on the target request, and determining a target evaluation result for capacity expansion and transformation of the target instance according to the first resource information, wherein the target evaluation result comprises any one of the following items: direct elasticity evaluation results, first-bullet-then-migration evaluation results, first-migration-then-bullet evaluation results, and direct migration evaluation results; under the condition that the target request is an elastic evaluation request, sending the target evaluation result to the resource management micro-service module; a resource pool data module configured to: providing second resource information corresponding to each target host device in at least one target host device in the resource pool, wherein the second resource information comprises idle computing resources of the corresponding target host device; a scheduling policy determination module configured to: obtaining the target evaluation result from the resource evaluation module; the target evaluation result includes any one of the following: determining a migration scheduling policy corresponding to a migration scheme for performing capacity expansion and transformation on the target instance based on the target evaluation result and second resource information acquired from the resource pool data module under the conditions of a first-bounce-before-migration evaluation result, a first-bounce-after-bounce evaluation result and a direct migration evaluation result, wherein the scheduling policy comprises a migration instance corresponding to the migration scheme and target host equipment to which the migration instance needs to be migrated; a resource scheduling module configured to: executing an elastic scheduling strategy corresponding to a scheme related to the target instance in an elastic transformation scheme under the condition that the target request is an elastic request corresponding to the capacity reduction transformation; executing an elastic scheduling strategy corresponding to a scheme related to the target instance in an elastic transformation and distribution scheme under the condition that the target request is a capacity expansion request and the target evaluation result is a direct elastic evaluation result; when the target request is a capacity expansion request, the target evaluation result includes any one of the following items: executing an elastic scheduling strategy corresponding to a scheme related to the target instance in an elastic transformation and configuration scheme under the conditions of a first-bomb-after-migration evaluation result, a first-migration-after-bomb evaluation result and a direct migration evaluation result, and executing the migration scheduling strategy corresponding to the target evaluation result; wherein, the elastic matching scheme comprises: performing elastic transformation and configuration processing on the first database to obtain a transformed and configured third database; switching the third database and the second database between a master database and a standby database, switching the third database into the master database of the target database, and switching the second database into the standby database of the target database; and performing elastic transformation and matching processing on the second database to obtain a fourth database after transformation and matching so as to obtain the target database after elastic transformation and matching based on the third database serving as the main database and the fourth database serving as the standby database.
In a fourth aspect, the present application provides a service device, comprising a processor, a memory and a computer program stored on the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the database resiliency method according to the first aspect.
In a fifth aspect, the present application provides a computer-readable storage medium comprising: the computer-readable storage medium has stored thereon a computer program which, when executed by a processor, implements the database resiliency method as shown in the second aspect.
In a sixth aspect, the present application provides a computer program product comprising: when the computer program product is run on a computer, the computer is caused to implement the database resiliency method as shown in the second aspect.
Compared with the prior art, the technical scheme provided by the embodiment of the application has the following advantages: in the embodiment of the application, an elastic request for a target database in a local disk is received, wherein the target database comprises a first database serving as a standby database and a second database serving as a main database; determining an elastic configuration scheme for the target database; wherein, the elastic matching scheme comprises: performing elastic transformation and configuration processing on the first database to obtain a transformed and configured third database; switching the third database and the second database between a master database and a standby database, switching the third database into the master database of the target database, and switching the second database into the standby database of the target database; and performing elastic transformation and matching processing on the second database to obtain a fourth database after transformation and matching so as to obtain the target database after elastic transformation and matching based on the third database serving as the main database and the fourth database serving as the standby database. Therefore, for elasticity of the local disk database, the embodiment of the present application proposes that the main library and the standby library are respectively modified in the elasticity process, the elastic modification processing is performed on the standby library first, which does not affect the application program accessing the service corresponding to the application program in the main library, then the main-standby switching is performed on the modified standby library and the original main library (the modified standby library is switched to the main library to obtain the modified main library, and the original main library is switched to the standby library), after the switching, the application program can continue to access the service corresponding to the application program in the modified main library, and then the elastic modification processing is performed on the switched standby library to obtain the modified configuration library, so that the elasticity of the database is completed, and in the elasticity process of the database, the influence on the service corresponding to the application program is minimal, and the elasticity efficiency can be improved.
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In order to more clearly illustrate the embodiments of the present application or the implementation manner in the related art, a brief description will be given below of the drawings required for the description of the embodiments or the related art, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art according to the drawings.
FIG. 1 illustrates a stateless node resiliency diagram in accordance with some embodiments;
FIG. 2 illustrates a local disk database resiliency diagram based on a stateless node resiliency scheduling scheme, in accordance with some embodiments;
FIG. 3 illustrates a database resiliency system diagram according to some embodiments;
FIG. 4 illustrates one of the flow diagrams of a database resiliency method according to some embodiments;
FIG. 5 illustrates a second flow diagram of a database resiliency method according to some embodiments;
FIG. 6 illustrates a third flow diagram of a database resiliency method according to some embodiments;
FIG. 7 illustrates a fourth flowchart of a database resiliency method according to some embodiments;
FIG. 8 illustrates a fifth flowchart of a database resiliency method according to some embodiments;
FIG. 9 illustrates a migration instance selection and destination host device selection diagram of a migration scheme according to some embodiments;
FIG. 10 shows a schematic diagram of the results of a database elastic apparatus according to some embodiments;
FIG. 11 illustrates a schematic diagram of a database elasticity service system, in accordance with some embodiments;
FIG. 12 illustrates a scheduling policy determination flow diagram according to some embodiments;
FIG. 13 illustrates a structural schematic of a service device according to some embodiments.
Detailed Description
To make the purpose and embodiments of the present application clearer, the following will clearly and completely describe the exemplary embodiments of the present application with reference to the attached drawings in the exemplary embodiments of the present application, and it is obvious that the described exemplary embodiments are only a part of the embodiments of the present application, and not all of the embodiments.
It should be noted that the brief descriptions of the terms in the present application are only for the convenience of understanding the embodiments described below, and are not intended to limit the embodiments of the present application. These terms should be understood in their ordinary and customary meaning unless otherwise indicated.
The terms "first," "second," "third," and the like in the description and claims of this application and in the above-described drawings are used for distinguishing between similar or analogous objects or entities and not necessarily for describing a particular sequential or chronological order, unless otherwise indicated. It is to be understood that the terms so used are interchangeable under appropriate circumstances.
The terms "comprises" and "comprising," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a product or apparatus that comprises a list of elements is not necessarily limited to all elements expressly listed, but may include other elements not expressly listed or inherent to such product or apparatus.
The host device and the service device provided in the embodiments of the present application may have various implementation forms, for example, may be a television, a mobile phone, a tablet computer, a notebook computer, a palm computer, a computer device, and the like, and may be determined specifically according to an actual situation, which is not limited herein.
The following first explains some of the nouns or terms referred to in the claims and the specification of the present invention.
Local disk database: even if a database architecture that stores data using local disks is used, a database cluster usually includes a master library and a backup library, and the master library and the backup library of the database cluster may or may not be on the same host device.
Example (c): if a host device comprises a main database and a standby database of a database, the corresponding examples of the database on the host device are the main database and the standby database of the database; if only one master library of the database is included on one host device, the corresponding instance of the database on the host device is the master library of the database; if only one standby database is included in one host device, the corresponding instance of the database on the host device is the standby database of the database.
Node (node): for the local disk, one node represents one host device (physical machine), and the data of the database is stored in the disk of the host device. The disk of the host device comprises data of a plurality of main libraries and/or data of a plurality of standby libraries.
Pod: one or a combination of a plurality of containers, wherein one container comprises a main library or a standby library.
Kubernets, commonly referred to as k8s, is an open source container cluster management system for automatically deploying, expanding, and managing containerized applications. The system constructs a scheduling service of a Container based on a Container Runtime Interface (CRI) (such as an open source application Container engine (Docker), a Container Storage Interface (CSI), and the like). Kubernets may automatically select a working container for use in a container cluster. It is intended to provide a "platform for automated deployment, expansion, and running of application containers across a host cluster". It supports a range of container tools including Docker, CRI-O, etc.
Because the stateless node under the cloud native architecture has no special state, the request for accessing the stateless service is processed indiscriminately for the server (the stateless service can be deployed on any server and has no influence on the service, and the server needs to have data as different as a database), and the data migration is not involved, so that in order to reduce the influence on the application program service as much as possible in the elastic process, the elastic stateless node under the cloud native architecture adopts a scheduling scheme of firstly creating and then deleting.
As shown in fig. 1, taking an elastic request as an expansion request as an example, the capacity expansion and change configuration scheme of a stateless node in a cloud native architecture is a scheduling scheme that is created first and then deleted, and specifically includes that a service device receives capacity expansion requests for pod1 and pod2 of which the computing resources are 2c4g, the capacity expansion requests require that the computing resources are expanded from 2c4g to 4c8g, a "1" indicates that the service device creates a pod3 and a pod4 of which the new computing resources are 4c8g according to the capacity expansion requests, a "2" indicates that the service device forwards the capacity expansion requests to newly-created pod3 and pod4, and a "3" indicates that the service device deletes (drops) the original pod1 and pod 2.
With the performance development and network optimization of the current cloud disk, the storage and computation separation mode of the cloud disk database is relatively mature, and the cloud native architecture better supports the storage and computation separation mode of the cloud disk database, which is equivalent to sinking a stateful part to a storage layer, so that the elasticity of the cloud disk database under the cloud native architecture can also adopt a scheduling scheme of creating the cloud disk database first and then deleting the cloud disk database, and the specific process is not repeated here. However, the performance of the cloud disk database still cannot exceed that of the local disk database, and the local disk database form is still the mainstream nowadays. However, the local disk database is a stateful node, and how to implement elasticity of the local disk database under the cloud native architecture is an urgent problem to be solved.
As shown in fig. 2, for example, an elastic request is taken as an expansion request, a main library and a standby library of a database are on the same host device, assuming that an expansion and transformation scheme of a local disk database under a cloud native architecture is a scheduling scheme of stateless nodes, which is created first and then deleted, a service device receives an expansion request for the database in node3, a flag "4" indicates that the service device newly creates the main library and the standby library in node4, a flag "5" indicates that the service device performs data migration on data in the database, a flag "6" indicates that the service device forwards the expansion request to the newly created main library and the newly created standby library in node4, and a flag "7" indicates that the service device drops the original main library and the original standby library. The process has the following problems: the data migration speed is low, the migration time required by the data migration is long, the migration time is long when the data volume is large, the migration time is long, 1T data needs to be migrated for more than ten hours, the elasticity efficiency is low, the data migration affects the performance of an original database, the database business is affected, and the advantages of a cloud native architecture are lost.
As shown in fig. 3, an embodiment of the present application provides a database elastic system, which includes a service device 310 and a plurality of host devices 321 in a resource pool 320, where the service device 310 is configured to manage a database in each host device 321 in the resource pool 320, provide a reasonable elastic allocation scheme for each database elastic allocation, and provide an elastic scheduling policy corresponding to the elastic allocation scheme.
For more detailed explanation of the present solution, the following description will be made with reference to fig. 4 to 9 by way of example, and it is understood that the steps involved in fig. 4 to 9 may include more steps or fewer steps in actual implementation, and the order between the steps may also be different, so as to enable the database flexible method provided in the embodiment of the present application.
Fig. 4 is a flowchart of steps of a method for implementing database resiliency according to one or more embodiments of the present application, where an execution subject of the method for implementing database resiliency may be a service device, or a functional module or a functional entity capable of implementing the method for implementing database resiliency in the service device, which is not limited herein. The database resiliency method may include:
401. a resilience request is received for a target database in a local disk.
The target database comprises a first database serving as a standby database and a second database serving as a main database.
402. An elastic variant to the target database is determined.
Wherein, the elastic matching scheme comprises: performing elastic transformation and configuration processing on the first database to obtain a transformed and configured third database; switching the third database and the second database between a master database and a standby database, switching the third database into the master database of the target database, and switching the second database into the standby database of the target database; and performing elastic transformation and matching processing on the second database to obtain a fourth database after transformation and matching so as to obtain the target database after elastic transformation and matching based on the third database serving as the main database and the fourth database serving as the standby database.
As shown in fig. 5, the process of performing elastic matching on the target database based on the elastic matching scheme includes:
501. and stopping the application program process corresponding to the first database.
502. And calling k8s api to perform first data elastic transformation processing to obtain a third database.
Wherein, the Application Programming Interface is Application Programming Interface, abbreviated as api.
503. The third database is pulled up.
504. And calling the HA service to perform master-slave switching, switching the third database into a master library, and switching the second database into a slave library.
Wherein, the high availability is high availability, abbreviated as HA.
505. And stopping the application program process corresponding to the second database.
506. And calling k8s api to perform elastic change processing on the second database to obtain a fourth database.
507. The fourth database is pulled up.
Through the steps 501 to 507, elastic change of the target database is realized, the first database is used as a standby database, the second database is used as a target database of the main database, and elastic change is performed to obtain a target database, the third database is used as the main database, and the fourth database is used as the standby database.
In the embodiment of the application, aiming at elasticity of a local disk database, the main library and the standby library are respectively modified in an elasticity process, the elastic modification processing is performed on the standby library firstly, service corresponding to an application program in the main library is not influenced when the application program accesses the main library, then the main-standby switching is performed on the modified standby library and the original main library (the modified standby library is switched into the main library to obtain the modified main library, and the original main library is switched into the standby library), after the switching, the application program can continuously access the service corresponding to the application program in the modified main library, then the elastic modification processing is performed on the switched standby library to obtain the modified configuration library, so that the elasticity of the database is completed, and in the elasticity process of the database, the influence on the service corresponding to the application program is minimum, and the elasticity efficiency can be improved.
The first host device comprises a target instance corresponding to the target database, and the target instance comprises at least one of the following items: a first database and a second database.
It is to be understood that if the target database includes a first database and a second database that are both on the first host device, the target instance is the first database and the second database; if only a first database included in the target database is on the first host device, the target instance is the first database; the target instance is the second database if only the second database comprised by the target database is on the first host device.
Optionally, the elastic request is a capacity reduction request, the elastic adaptation is capacity reduction adaptation, and the capacity reduction adaptation is to reduce the computing resources occupied by the target instance on the first host device, so that the capacity reduction adaptation can be directly performed on the first host device without involving instance migration, and the capacity reduction efficiency of the local disk database can be improved.
Optionally, the elastic request is a capacity expansion request, the elastic transformation is capacity expansion transformation, and the capacity expansion transformation is to expand the computing resources occupied by the target instance on the first host device, so that directly performing capacity expansion transformation on the target instance on the first host device may cause the computing resources occupied by each instance on the first host device to exceed the total computing resources on the first host device. Since k8s supports the over-sale of certain resources for a short time, it can be considered whether to move first and then to play or move first and then to play according to the actual situation. Further, it may also be considered to migrate other instances on the first host device or migrate a target instance on the first host device according to actual situations.
Exemplarily, in combination with fig. 4, as shown in fig. 6, before the step 402, the database flexible method provided in the embodiment of the present application may further include:
403. and acquiring first resource information based on the capacity expansion request.
The first resource information includes a computing resource occupied by each instance and a storage resource occupied by each instance on the first host device, as well as a free computing resource of the first host device and a computing resource overload threshold of the first host device.
404. And determining a target evaluation result for carrying out capacity expansion and transformation and configuration on the target instance according to the first resource information.
Wherein different target evaluation results correspond to different elasticity schemes.
It should be noted that the first resource information is a real-time online resource, and the target evaluation result is an online resource evaluation result for the first host device.
In the embodiment of the application, the target evaluation result is obtained by performing capacity expansion and transformation and distribution evaluation on the target instance according to the first resource information, and different target evaluation results correspond to different elastic schemes, so that a proper elastic scheme can be determined by performing capacity expansion and transformation and distribution evaluation to improve the elastic efficiency of the database.
Optionally, the target evaluation result includes any one of: direct elasticity evaluation results, first-bullet-then-migration evaluation results, first-migration-then-bullet evaluation results, and direct migration evaluation results.
Wherein the direct elasticity evaluation result comprises: the adjusted computing resources required by the target instance for the capacity change are less than or equal to the free computing resources of the first host device (indicating that the computing resources on the first host device are sufficient), and the scheme related to the target instance in the elastic change scheme is executed on the first host device.
It is understood that, in the case that the free resources on the first host device are sufficient, the elastic scheme is a scheme related to the target instance in the elastic adaptation scheme executed directly on the first host device, so that the elastic efficiency of the target database can be improved.
The implementation of the elastic configuration scheme on the first host device, which is related to the target instance, may specifically be understood as: if the target instance is a first database and a second database in the target database, executing the elastic configuration scheme on the first host equipment; if the target instance is only the first database in the target database, executing a scheme related to the first database in the elastic transformation scheme on the first host device (for example, performing elastic transformation processing on the first database to obtain a third database, and then switching the third database from the standby database to the main database); if the target instance is only the second database in the target database, executing a scheme related to the second database in the elastic transformation scheme on the first host device (for example, the second database is switched from the main database to the standby database, and the second database switched to the standby database is subjected to elastic transformation processing to obtain a fourth database).
Wherein, should play first and move the assessment result afterwards and include: the adjusted computing resource is greater than an idle computing resource of the first host device (indicating that the computing resource on the first host device is insufficient) and less than or equal to a target resource (indicating that the target instance is allowed to perform capacity expansion and transformation on the first host device under the condition that the resource of the first host device is over-sold), a scheme related to the target instance in the elastic transformation scheme is executed on the first host device, then a first migration scheme is executed, the target resource is the sum of the idle computing resource of the first host device and the computing resource overload threshold, and the first migration scheme is to migrate the first instance on the first host device from the first host device to the second host device.
It is understood that, in the case of insufficient computing resources on the first host device but resource oversubscription, the target instance is allowed to perform capacity expansion and configuration on the first host device, and the elastic scheme is to execute a scheme related to the target instance in the elastic configuration scheme on the first host device first and then execute the first migration scheme.
Wherein, should move earlier afterwards bullet evaluation result includes: the adjusted computing resource is larger than the target resource (it is indicated that the target instance is not allowed to perform capacity expansion and transformation on the first host device under the condition that the first host device resource is over-sold), and the storage resource occupied by the target instance is larger than or equal to the storage resource occupied by the first instance (it is indicated that the storage resource occupied by the first host device is smaller than the target instance, and the first instance which does not overload the first host device due to capacity expansion and transformation on the target instance after migration), a first migration scheme is executed on the first host device, and then a scheme related to the target instance in the elastic transformation scheme is executed.
Wherein the computing resources occupied by the first instance are greater than or equal to the difference between the adjusted computing resources and the idle computing resources of the first host device.
It can be understood that, under the condition that the resource of the first host device is over-sold, the target instance is not allowed to perform capacity expansion and configuration on the first host device, and the first host device includes a suitable first instance, the first migration scheme may be executed on the first instance first, and then the scheme related to the target instance in the elastic configuration scheme may be executed on the target instance.
It should be noted that, in the embodiment of the present application, the first migration and then ejection evaluation result may further include: the adjusted computing resource is larger than the target resource, and the storage resource occupied by the target instance is larger than or equal to the storage resource occupied by the first instance, a first migration scheme is executed on the first host device, then a scheme related to the target instance in the elastic change scheme is executed, and finally a third migration scheme is executed.
It is understood that after the first migration scheme is executed, in the case of overspill of the first host device, capacity expansion and configuration of the target instance may be implemented, and then the third migration scheme is executed so that the computing resources occupied by the instances on the first host device are less than or equal to the total computing resources on the first host device.
In this embodiment of the application, the migration-before-ejection evaluation result corresponds to the scheme related to the target instance in the first migration scheme and the elastic adaptation scheme, or corresponds to the scheme related to the target instance in the first migration scheme and the elastic adaptation scheme and the third migration scheme, and may be determined according to specific situations, which is not limited herein.
Wherein the direct migration evaluation result comprises: the adjusted computing resource is larger than the target resource (it is stated that the target instance is not allowed to perform capacity expansion and configuration change on the first host device under the condition that the first host device resource is over-sold), and the storage resource occupied by the target instance is smaller than the storage resource occupied by any second instance on the first host (it is stated that there is no suitable migratable instance on the first host device, and the target instance is the most suitable migratable instance on the first host device), the scheme related to the target instance in the flexible scheduling scheme is executed while the second migration scheme is executed, and the second migration scheme is to migrate the target instance from the first host device to the third host device.
It should be noted that, in the embodiment of the present application, when the target instance includes the first database and the second database in the target database, the storage resource occupied by the target instance is the storage resource occupied by the first database, and the executing the scheme related to the target instance in the flexible scheduling scheme while executing the second migration scheme specifically includes: and then, the second database is migrated from the first host device to the third host device, and the elastic change-over processing is executed, so that a fourth database on the third host device is obtained.
It should be noted that, when the target evaluation result is the direct migration evaluation result, and the target instance includes the first database and the second database in the target database, assuming that the first database serving as the backup database is migrated and subjected to capacity expansion and transformation, and the second database serving as the primary database can implement capacity expansion and transformation on the first host device, only the first database may be migrated and subjected to capacity expansion and transformation, and the second database is directly subjected to capacity expansion and transformation on the first host device; or the first database may be migrated and subjected to capacity expansion and transformation, the second database may be migrated and subjected to capacity expansion and transformation, and the first database (the third database) and the second database (the fourth database) after migration and capacity expansion and transformation are still on the same host device.
It should be noted that, in the embodiment of the present application, when the target instance only includes the first database in the target database, the storage resource occupied by the target instance is the storage resource occupied by the first database; in the embodiment of the present application, when the target instance only includes the second database in the target database, the storage resource occupied by the target instance is the storage resource occupied by the second database.
It should be noted that, taking the execution of the elastic change configuration process while migrating the first database from the first host device to the third host device as an example, a scenario related to the target instance in the elastic scheduling scheme while executing the second migration scheme is described, where the process includes: creating an instance corresponding to a third database on a third host device, copying data corresponding to the first database (which may be remote backup data or data stored in a storage resource of the first host device) to an idle storage resource of the third host device, mounting data corresponding to the first database stored in the storage resource of the third host device to a container corresponding to the third data, pulling up the third database on the third host device, and deleting the first database on the first host device (deleting the container corresponding to the first database, and deleting the data in the storage resource occupied by the first database).
And the computing resource occupied by each second instance is greater than or equal to the difference between the adjusted computing resource and the idle computing resource of the first host device.
It can be understood that, under the condition that the resource of the first host device is over-sold, the target instance is not allowed to perform capacity expansion and configuration on the first host device, and the target instance is the most suitable migratable instance on the first host device, the second migration scheme is executed while the scheme related to the target instance in the flexible scheduling scheme is executed, so that the time required for migrating the target instance is shorter than the time required for migrating any second instance because the storage resource occupied by the target instance is shorter than the storage resource occupied by any second instance on the first host, so that the time for migrating the target instance can be saved, the flexible efficiency of the target instance can be improved, and the flexible efficiency of the target database can be improved.
Illustratively, as shown in fig. 7, the process of performing the capacity expansion and transformation assessment on the target instance includes:
700. and acquiring first resource information.
701. It is determined whether the adjusted computing resource is less than or equal to a free computing resource of the first host device.
If the adjusted computing resources are less than or equal to the idle computing resources of the first host device, then step 702 is performed, otherwise step 703 is performed.
702. Determining a direct elasticity evaluation result.
703. And judging whether the adjusted computing resource is less than or equal to the target resource.
If the adjusted computing resource is less than or equal to the target resource, then step 704 is performed, otherwise step 705 is performed.
704. And determining the evaluation result of first-bounce and later-migration.
705. And judging whether the storage resources occupied by the target instance are larger than or equal to the storage resources occupied by the first instance.
If the storage resources occupied by the target instance are greater than or equal to the storage resources occupied by the first instance, then step 706 is performed, otherwise step 707 is performed.
706. And determining the evaluation result of the bullet after the migration.
707. Determining a direct migration evaluation result.
Optionally, in this embodiment of the present application, the elastic change processing may be processing after deletion, or processing after creation.
Optionally, the target evaluation result includes any one of the following: and under the conditions of direct elasticity evaluation results, first-bullet-then-migration evaluation results and first-migration-then-bullet evaluation results, the elasticity transformation processing is first deletion and then creation processing. In this case, the flexible configuration processing is deletion-first and then creation processing, and it can be ensured that the scheduling resource of the host device where the target instance is located is sufficient to the greatest extent, so that the target instance can execute the flexible configuration scheme on the host device, and the flexible efficiency of the target database can be improved.
Optionally, in a case that the target evaluation result includes a direct migration evaluation result, the elastic migration processing is a create-before-delete processing. It can be understood that, in this case, because the instance migration involves data migration, and the data migration takes a long time, if the backup library is deleted first, if the primary library is abnormal in the migration process, the service corresponding to the application program process is unavailable, and the deletion processing after the creation can avoid this problem, so as to improve the elastic efficiency of the database.
After determining the target evaluation result, the corresponding elastic policy may be determined according to the target evaluation result, which may specifically refer to the following related description in fig. 12, and is not described herein again. After determining the elasticity policy, whether to migrate, which instance to migrate, and migrate the corresponding destination host device are determined according to the corresponding elasticity policy, which may be specifically described in association with steps 405 and 406, or steps 405 and 407, described below.
Optionally, the target evaluation result includes any one of: the method comprises the following steps of firstly carrying out bomb-to-transfer evaluation results, firstly carrying out transfer-to-bomb evaluation results and directly carrying out transfer evaluation results; with reference to fig. 6 and as shown in fig. 8, the database resiliency method provided in the embodiment of the present application may further include:
405. and acquiring second resource information corresponding to each target host device in at least one target host device in the resource pool based on the capacity expansion request.
The at least one target host device may be selected from the resource pool according to any criteria, which is not limited in the embodiment of the present application.
Wherein the second resource information includes idle computing resources of the corresponding target host device.
406. And under the condition that the target evaluation result is the first-bullet-after-migration evaluation result or the first-bullet-after-migration evaluation result, determining a first instance meeting a first condition from instances on the first host device based on the first resource information and the second resource information, and determining a second host device meeting a second condition from the at least one target host device.
Wherein the first condition comprises: the occupied computing resources are greater than or equal to an instance of a difference between the adjusted computing resources and the idle computing resources of the first host device, that is, the first instance is an instance of the occupied computing resources on the first host device being greater than or equal to a difference between the adjusted computing resources and the idle computing resources of the first host device. Thus, after the first instance is migrated to the second host device and the target instance is subjected to the capacity expansion transformation, the computing resources occupied by the respective instances on the first host device do not exceed the total computing resources on the first host device.
Wherein the second condition comprises: the idle computing resources are greater than or equal to the target host device of the computing resources occupied by the first instance, that is, the second host device is a target host device of at least one target host device having idle computing resources greater than or equal to the computing resources occupied by the first instance, so that after the first instance is migrated to the second host device, the computing resources occupied by the respective instances on the second host device do not exceed the total computing resources on the second host device.
In the embodiment of the application, by setting the appropriate first condition and the second condition, the migration scheduling policy corresponding to the reasonable first migration scheme is determined, so that the elastic efficiency of the target database can be better ensured, and the influence on the service corresponding to the application process of other examples can be reduced.
407. In a case where the target evaluation result is the direct migration evaluation result, a third host device that satisfies a third condition is determined from the at least one target host device based on the first resource information and the second resource information.
Wherein the third condition comprises: the idle computing resource is greater than or equal to the target host device of the sum of the computing resource occupied by the target instance and the adjusted computing resource, that is, the third host device is a target host device of at least one target host device of which the idle computing resource is greater than or equal to the sum of the computing resource occupied by the target instance and the adjusted computing resource, so that after the target instance is migrated to the third host device, the computing resource occupied by each instance on the third host device does not exceed the total computing resource on the second host device.
In the embodiment of the application, by setting a suitable third condition, a migration scheduling policy corresponding to a reasonable second migration scheme is determined, so that the elastic efficiency of the target database can be better ensured, and the influence on the service corresponding to the application program process of the target instance can be reduced.
Optionally, the second resource information includes a free storage resource of the corresponding target host device; in a case that the target evaluation result is the shot-before-migration evaluation result or the shot-before-migration evaluation result, the first condition specifically includes any one of: in an instance in which the occupied computing resource is greater than or equal to the difference between the adjusted computing resource and the idle computing resource of the first host device, the occupied computing resource is the smallest; the occupied computing resources are greater than or equal to the difference between the adjusted computing resources and the idle computing resources of the first host device, and the occupied storage resources are minimal.
It is to be appreciated that the first instance is the instance with the least computing resource occupied in the instance where the adjusted computing resource is greater than or equal to the difference between the adjusted computing resource and the free computing resource of the first host device (and thus the most suitable first instance can be determined from a computing resource perspective), or the first instance is the instance with the least storage resource occupied in the instance where the adjusted computing resource is greater than or equal to the difference between the adjusted computing resource and the free computing resource of the first host device (and thus the most suitable first instance can be determined in combination of the computing resource perspective and the storage resource perspective, and the data migration duration can be reduced). Thus, after the first instance is migrated to the second host device and the target instance is subjected to the capacity expansion transformation, the computing resources occupied by the respective instances on the first host device do not exceed the total computing resources on the first host device.
Optionally, the second resource information includes a free storage resource of the corresponding target host device; the second condition specifically includes any one of: the target host equipment with the largest idle computing resource in the target host equipment with the idle computing resource larger than or equal to the computing resource occupied by the first instance; and the target host equipment with the idle computing resources larger than or equal to the computing resources occupied by the first instance has the largest weighted value of the idle computing resources and the idle storage resources.
It is understood that the second host device is the target host device with the largest idle computing resource among the at least one target host device having idle computing resources greater than or equal to the computing resources occupied by the first instance (thus, the most suitable second host device can be determined from the perspective of the idle computing resources), or the second host device is the target host device with the largest weighting values of the idle computing resources and the idle storage resources among the at least one target host device having idle computing resources greater than or equal to the computing resources occupied by the first instance (thus, the most suitable second host device can be determined from the perspective of the idle computing resources and the perspective of the idle storage resources, and the data migration speed can be increased, and the data migration duration can be decreased), so that after the first instance is migrated to the second host device, the computing resources occupied by the instances on the second host device do not exceed the total computing resources on the second host device.
In the embodiment of the application, by setting the more appropriate first condition and second condition, the migration scheduling policy corresponding to the more reasonable first migration scheme is determined, so that the elastic efficiency of the target database can be better ensured, and the influence on the service corresponding to the application process of other instances can be reduced.
Optionally, the second resource information includes a free storage resource of the corresponding target host device; in a case where the target evaluation result is the direct migration evaluation result, the third condition specifically includes any one of: the target host equipment with the maximum idle computing resource is selected from the target host equipment with the idle computing resource more than or equal to the sum of the computing resource occupied by the target instance and the adjusting computing resource; and the idle computing resource is greater than or equal to the sum of the computing resource occupied by the target instance and the adjusted computing resource, and the weighted value of the idle computing resource and the idle storage resource is the largest target host equipment.
It is understood that the third host device is the target host device with the largest idle computing resource among the target host devices with the idle computing resource larger than or equal to the sum of the computing resource occupied by the target instance and the adjusted computing resource in at least one target host device (thus, the most suitable third host device can be determined from the idle computing resource), or the third host device is the target host device with the largest weight of the idle computing resource and the idle storage resource among the target host devices with the idle computing resource larger than or equal to the sum of the computing resource occupied by the target instance and the adjusted computing resource in at least one target host device (thus, the most suitable third host device can be determined by combining the idle computing resource angle and the idle storage resource angle, and the data migration speed can be increased, and the data migration duration can be reduced), thus, after the target instance is migrated to the third host device, the computing resources occupied by the respective instances on the third host device do not exceed the total computing resources on the second host device.
In the embodiment of the application, by setting a more appropriate third condition, a more reasonable migration scheduling policy corresponding to the second migration scheme is determined, so that the elastic efficiency of the target database can be better ensured, and the influence on the service corresponding to the application process of the target instance can be reduced.
Optionally, the first resource information further includes a fixed tag of each instance on the first host device, where the fixed tag is used to indicate a host device that the corresponding instance allows migration; the second resource information further includes a device tag of the corresponding target host device; matching the fixed tag of the first instance with the device tag of the second host device under the condition that the target evaluation result is the first-bomb-then-migration evaluation result or the first-bomb-after-migration evaluation result; in a case where the target evaluation result is the direct migration evaluation result, the fixed tag of the target instance matches the device tag of the third host device.
It can be understood that, by combining the fixed tag and the device tag, a more reasonable first instance, second host device, or third host device can be determined, so that the elastic efficiency of the target database can be better ensured, and the influence on the service corresponding to the application program process of the target instance can be reduced.
Optionally, the first migration scheme comprises: creating a first instance on a second host device; copying the remote backup data corresponding to the first instance to an idle storage resource of the second host device (i.e., mounting (mount) the remote backup data corresponding to the first instance to the container of the first instance on the second host device) at a maximum network speed and a maximum read-write speed (IOPS) of the container (the container corresponding to the first instance newly built on the second host device), where the remote backup data corresponding to the first instance is updated data within a preset time duration; pulling up the first instance; the first instance on the first host device is deleted.
The first example may include a main library and a standby library of one database, may also include only a main library of a data viewer, and may also include only a standby library of a database, which may be determined according to actual situations, and is not limited herein.
It can be understood that, if the first database includes a primary library and a backup library of a database, the migration of the first instance includes first migrating the backup library in the first instance, and then switching between the primary library and the backup library, and migrating the old primary library in the first instance, where the description corresponding to the migration of the first instance may refer to the above description related to the migration of the target instance, and details are not described here again.
Optionally, the second migration scheme comprises: creating an expansion and transformation configured instance corresponding to the target instance on third host equipment; copying the remote backup data corresponding to the target instance to an idle storage resource of the third host device at a maximum network speed and a maximum read-write speed of a container (a container corresponding to a newly-built capacity-expanded and modified instance on the third host device) (i.e., mounting the remote backup data corresponding to the target instance to the container of the capacity-expanded and modified instance on the third host device), where the remote backup data corresponding to the target instance is updated data within the preset time length; pulling up the instance after the capacity expansion and the transformation; the target instance on the first host device is deleted.
The preset time length may be determined according to an actual situation, and is not limited herein.
In the embodiment of the application, the remote backup data corresponding to the instance is the updated data within the preset time, and the copied remote backup data can be copied at the maximum network speed and the maximum read-write speed of the container compared with the data on the host equipment where the original instance is migrated, so that the data copying speed can be increased, and the instance migration efficiency can be improved. But also to reduce the impact on the traffic of the instances (first instance or target instance, and other instances) on the first host device.
Optionally, the first migration scheme comprises: creating a first instance on a second host device; copying data corresponding to a first instance on first host equipment to idle storage resources of second host equipment at a limited network speed and a limited read-write speed (namely migrating the data on the host equipment where the original instance is located); pulling up the first instance; the first instance on the first host device is deleted.
Optionally, the second migration scheme comprises: creating an expansion and transformation configured instance corresponding to the target instance on third host equipment; copying data corresponding to the target instance on the first host device to idle storage resources of a third host device at a limited network speed and a limited read-write speed (namely, migrating the data on the host device where the original instance is located); pulling up the instance after the capacity expansion and the transformation; the target instance on the first host device is deleted.
The limited network speed and the limited read-write speed may be determined according to actual conditions, and are not limited herein.
In the embodiment of the application, under the condition that the remote backup data corresponding to the instance is not the updated data within the preset time, the data on the host equipment where the original instance is located is migrated, so that the data can be ensured to be the latest, and the influence on the service of the first instance or the target instance can be reduced.
It should be noted that, in the embodiment of the present application, the target evaluation result may be any one of a direct elasticity evaluation result, a first-bullet-later-migration evaluation result, a first-migration-later-bullet evaluation result, and a direct migration evaluation result; the target evaluation result can be any one of a direct elasticity evaluation result and a first-to-last-to-live evaluation result (in this case, the over-selling condition of the host equipment is not considered, and the condition of directly migrating the target instance is not considered); the target evaluation result may also be any one of a direct elasticity evaluation result, a migration-to-missile evaluation result and a direct migration evaluation result (in this case, the over-selling situation of the host device is not considered); the target evaluation result may be free of other feasibility evaluation results. That is to say, any target evaluation result type may be set under the inventive concept of the embodiment of the present application, which may be determined according to actual situations, and the embodiment of the present application is not limited.
For example, because the cloud environment is a private cloud environment, the database resource pool is deployed in a balanced load mode, in order to achieve the fastest migration, an instance (a first instance or a target instance) with the smallest data amount (occupying storage resources) on the first host device is selected for migration, and the migration destination device selection rule is to select the target host device with the largest remaining idle resources. The specific migration manner is shown in fig. 9.
As can be seen in fig. 9, the serving device treats the target database instance resource on the first host device as a dynamic vector, which contains N1: CPU, N2: memory size, N3: fixed label, N4: the method comprises the steps that a storage space is used for conducting ascending sequencing on all N4 vectors on first host equipment, and then a first N1-N3 qualified example is selected as a to-be-migrated example (a first example or a target example); taking the second resource information of each target host device as a static vector, wherein the static vector comprises S1: CPU allocation ratio (i.e., CPU idle resource ratio), S2: memory allocation ratio (i.e., memory free resource ratio), S3: disk allocation ratio (i.e., disk free resource ratio), S4: the device label firstly filters out the host devices which do not meet the inverse affinity policy of the to-be-migrated instance in the vector S4, performs weighting processing on vectors S1-S3 of the remaining host devices (S1+ S2+ S3)/3, and selects the target host device with the minimum S as the target host device (i.e., the second host device or the third host device).
Fig. 10 is a block diagram illustrating a structure of a database elastic apparatus according to an embodiment of the present disclosure, where as shown in fig. 10, the apparatus includes: a receiving module 1001 and a determining module 1002; the receiving module 1001 is configured to receive an elastic request for a target database in a local disk, where the target database includes a first database serving as a standby database and a second database serving as a primary database; the determining module 1002 is configured to determine an elastic configuration scheme for the target database; wherein, the elastic matching scheme comprises: performing elastic transformation and configuration processing on the first database to obtain a transformed and configured third database; switching the third database and the second database between a master database and a standby database, switching the third database into the master database of the target database, and switching the second database into the standby database of the target database; and performing elastic transformation and matching processing on the second database to obtain a fourth database after transformation and matching so as to obtain the target database after elastic transformation and matching based on the third database serving as the main database and the fourth database serving as the standby database.
Optionally, the elastic request is a capacity expansion request, the elastic transformation and configuration is capacity expansion and configuration transformation, the first host device includes a target instance corresponding to the target database, and the target instance includes at least one of the following: a first database, a second database; the device also includes: an obtaining module, configured to obtain first resource information based on the capacity expansion request before determining an elastic configuration scheme for the target database, where the first resource information includes a computing resource occupied by each instance on the first host device, a storage resource occupied by each instance, an idle computing resource of the first host device, and a computing resource overload threshold of the first host device; the determining module 1002 is further configured to determine a target evaluation result of capacity expansion and transformation of the target instance according to the first resource information.
Optionally, the target evaluation result includes any one of: direct elasticity evaluation results, first-bullet-then-migration evaluation results, first-migration-then-bullet evaluation results, and direct migration evaluation results; wherein the direct elasticity assessment result comprises: the adjustment computing resource required by the target instance for the capacity expansion and the transformation is less than or equal to the idle computing resource of the first host device, and the scheme related to the target instance in the elastic transformation scheme is executed on the first host device; the first-bullet-later-migration evaluation result comprises the following steps: the adjusted computing resource is larger than the idle computing resource of the first host device and smaller than or equal to a target resource, a scheme related to the target instance in the elastic change scheme is executed on the first host device, then a first migration scheme is executed, the target resource is the sum of the idle computing resource of the first host device and the computing resource overload threshold, and the first migration scheme is to migrate the first instance on the first host device from the first host device to the second host device; the migration-before-bomb evaluation result comprises: the adjusted computing resource is larger than the target resource, and the storage resource occupied by the target instance is larger than or equal to the storage resource occupied by the first instance, a first migration scheme is executed on the first host device, and then a scheme related to the target instance in the elastic change scheme is executed; the direct migration evaluation results include: and executing a second migration scheme, namely migrating the target instance from the first host equipment to a third host equipment, wherein the adjusted computing resource is larger than the target resource, the storage resource occupied by the target instance is smaller than the storage resource occupied by any second instance on the first host, and the scheme related to the target instance in the elastic scheduling scheme is executed while the second migration scheme is executed.
Optionally, the target evaluation result includes any one of the following: and under the conditions of direct elasticity evaluation results, first-bullet-then-migration evaluation results and first-migration-then-bullet evaluation results, the elasticity transformation processing is first deletion and then creation processing.
Optionally, in a case that the target evaluation result includes a direct migration evaluation result, the elastic migration processing is a create-before-delete processing.
Optionally, the target evaluation result includes any one of: the method comprises the following steps of firstly carrying out bomb-to-transfer evaluation results, firstly carrying out transfer-to-bomb evaluation results and directly carrying out transfer evaluation results; the obtaining module is further configured to obtain, based on the capacity expansion request, second resource information corresponding to each target host device in at least one target host device in the resource pool, where the second resource information includes idle computing resources of the corresponding target host device; the determining module 1002 is further configured to determine, based on the first resource information and the second resource information, a first instance meeting a first condition from instances on the first host device and a second host device meeting a second condition from the at least one target host device, when the target evaluation result is the migration-after-migration evaluation result or the migration-after-migration evaluation result; the first condition includes: instances in which the occupied computing resources are greater than or equal to a difference between the adjusted computing resources and idle computing resources of the first host device; the second condition includes: a target host device having idle computing resources greater than or equal to the computing resources occupied by the first instance; the determining module 1002 is further configured to determine, if the target evaluation result is the direct migration evaluation result, a third host device that meets a third condition from the at least one target host device based on the first resource information and the second resource information; the third condition includes: a target host device having idle computing resources greater than or equal to a sum of computing resources occupied by the target instance and the adjusted computing resources.
Optionally, the second resource information includes a free storage resource of the corresponding target host device; when the target evaluation result is the migration-after-ammunition evaluation result or the migration-after-ammunition evaluation result, the first condition specifically includes any one of: in an instance in which the occupied computing resource is greater than or equal to the difference between the adjusted computing resource and the idle computing resource of the first host device, the occupied computing resource is the smallest; an instance that occupies computing resources greater than or equal to a difference between the adjusted computing resources and idle computing resources of the first host device and occupies minimal storage resources; the second condition specifically includes any one of: the target host equipment with the largest idle computing resource in the target host equipment with the idle computing resource larger than or equal to the computing resource occupied by the first instance; in the target host equipment of which the idle computing resources are greater than or equal to the computing resources occupied by the first instance, the target host equipment with the largest weighted value of the idle computing resources and the idle storage resources; in a case where the target evaluation result is the direct migration evaluation result, the third condition specifically includes any one of: the target host equipment with the maximum idle computing resource is selected from the target host equipment with the idle computing resource more than or equal to the sum of the computing resource occupied by the target instance and the adjusting computing resource; and the idle computing resource is greater than or equal to the target host equipment with the largest weighted value of the idle computing resource and the idle storage resource in the target host equipment with the sum of the computing resource occupied by the target instance and the adjusting computing resource.
Optionally, the first resource information further includes a fixed tag of each instance on the first host device, where the fixed tag is used to indicate a host device that the corresponding instance allows migration; the second resource information further includes a device tag of the corresponding target host device; when the target evaluation result is the first-missile and second-migration evaluation result or the first-migration and second-missile evaluation result, the fixed tag of the first instance is matched with the device tag of the second host device; in a case where the target evaluation result is the direct migration evaluation result, the fixed tag of the target instance matches the device tag of the third host device.
Optionally, the first migration scheme comprises: creating a first instance on a second host device; copying the remote backup data corresponding to the first example into an idle storage resource of the second host device at the maximum network speed and the maximum read-write speed of the container, wherein the remote backup data corresponding to the first example is updated data within a preset time length; pulling up the first instance; the first instance on the first host device is deleted.
Optionally, the second migration scheme comprises: creating an expansion and transformation configured instance corresponding to the target instance on third host equipment; copying the remote backup data corresponding to the target instance into an idle storage resource of a third host device at the maximum network speed and the maximum read-write speed of the container, wherein the remote backup data corresponding to the target instance is updated data within the preset time; pulling up the instance after the capacity expansion and the transformation; the target instance on the first host device is deleted.
Optionally, the first migration scheme comprises: creating a first instance on a second host device; copying data corresponding to a first instance on first host equipment to idle storage resources of second host equipment at a limited network speed and a limited read-write speed; pulling up the first instance; the first instance on the first host device is deleted.
Optionally, the second migration scheme comprises: creating an expansion and transformation configured instance corresponding to the target instance on third host equipment; copying data corresponding to the target instance on the first host device to idle storage resources of a third host device at a limited network speed and a limited read-write speed; pulling up the instance after the capacity expansion and the transformation; the target instance on the first host device is deleted.
In the embodiment of the present application, each module of the database elastic apparatus can implement the database elastic method provided in the above method embodiment, and can achieve the same technical effect, and is not described here again to avoid repetition.
Fig. 11 is a block diagram illustrating a structure of a database elasticity service system according to an embodiment of the present disclosure, and as shown in fig. 11, the system includes: a resource management microservice module 1101 configured to: receiving a target request aiming at a target database, wherein the target request is an elastic request or an elastic evaluation request, and the target database comprises a first database serving as a standby database and a second database serving as a main database; a data services module 1102 configured to: providing first resource information on a first host device where a target instance corresponding to the target database is located, wherein the target instance comprises at least one of the following items: a first database, a second database; the first resource information comprises computing resources occupied by each instance and storage resources occupied by each instance on the first host device, idle computing resources of the first host device, and a computing resource overload threshold of the first host device; a resource assessment module 1103 configured to: under the condition that the target request is a related request for capacity expansion and transformation, acquiring first resource information from the data service module based on the target request, and determining a target evaluation result for capacity expansion and transformation of the target instance according to the first resource information, wherein the target evaluation result comprises any one of the following items: direct elasticity evaluation results, first-bullet-then-migration evaluation results, first-migration-then-bullet evaluation results, and direct migration evaluation results; under the condition that the target request is an elastic evaluation request, sending the target evaluation result to the resource management micro-service module; a resource pool data module 1104 configured to: providing second resource information corresponding to each target host device in at least one target host device in the resource pool, wherein the second resource information comprises idle computing resources of the corresponding target host device; a scheduling policy determination module 1105 configured to: obtaining the target evaluation result from the resource evaluation module; the target evaluation result includes any one of the following: determining a migration scheduling policy corresponding to a migration scheme for performing capacity expansion change on the target instance based on the target evaluation result and second resource information acquired from the resource pool data module under the conditions of a first-bounce-before-migration evaluation result, a first-migration after-bounce evaluation result and a direct migration evaluation result, wherein the scheduling policy comprises a migration instance corresponding to the migration scheme and target host equipment to which the migration instance needs to be migrated; a resource scheduling module 1106 configured to: executing an elastic scheduling strategy corresponding to a scheme related to the target instance in an elastic transformation scheme under the condition that the target request is an elastic request corresponding to the capacity reduction transformation; executing an elastic scheduling strategy corresponding to a scheme related to the target instance in an elastic transformation and distribution scheme under the condition that the target request is a capacity expansion request and the target evaluation result is a direct elastic evaluation result; when the target request is a capacity expansion request, the target evaluation result includes any one of the following items: executing an elastic scheduling strategy corresponding to a scheme related to the target instance in an elastic transformation scheme under the conditions of a first-bounce and second-migration evaluation result, a first-migration and second-bounce evaluation result and a direct migration evaluation result, and executing the migration scheduling strategy corresponding to the target evaluation result; wherein, the elastic matching scheme comprises: performing elastic transformation and configuration processing on the first database to obtain a transformed and configured third database; switching the third database and the second database between a master database and a standby database, switching the third database into the master database of the target database, and switching the second database into the standby database of the target database; and performing elastic transformation and matching processing on the second database to obtain a fourth database after transformation and matching, so as to obtain the target database after elastic transformation and matching based on the third database serving as the main database and the fourth database serving as the standby database.
In the embodiment of the present application, each module of the database elastic service system may implement the database elastic method provided in the foregoing method embodiment, and may achieve the same technical effect, and for avoiding repetition, details are not repeated here.
In the embodiment of the application, the rapid elasticity of the local disk form of the database under the cloud native architecture is mainly optimized, a database elastic service system is introduced and is responsible for resource assessment and output scheduling strategies, the scheduling strategy system can assess an optimal elastic scheme according to the current resource use condition and the expected resource amount, the optimal elastic scheme is divided into four scenes, the host where the cloud database is located is sufficient in resources, the resources are insufficient but not exceeding an overload threshold value, the resources are insufficient but better selected, the resources are insufficient but not better selected, different rapid elastic scheduling schemes are made for different scenes, and a resource assessment strategy, a resource scheduling strategy and a resource scheduling method are provided.
As shown in fig. 11, the database elastic service system request entry sends a target request to the resource evaluation module after the resource management micro-service module receives the target request (capacity expansion evaluation request or capacity expansion request) for the target database, the resource evaluation module interacts with the data micro-service module to obtain the example resource information (e.g. the first resource information on the first host device) on the host device where the target database is located after receiving the target request, the resource evaluation module makes detailed evaluation information of the resource according to the example resource information on the host device where the target database is located (obtains a target evaluation result, and returns the target evaluation result to the resource management micro-service module if the target request is the capacity expansion evaluation request), and obtains the second resource information of each target host device in at least one target host device in the resource pool from the resource pool data module, and submitting the target evaluation result and the at least one piece of second resource information to a scheduling policy module, wherein the scheduling policy module submits an optimal scheduling policy to the scheduling policy module according to the target evaluation result and the at least one piece of second resource information, and sends the optimal scheduling policy to the resource scheduling module, and the resource scheduling module performs corresponding resource scheduling according to the optimal scheduling policy.
The resource evaluation module is mainly used for carrying out multi-dimensional resource evaluation according to related data and is divided into host computer computing resource evaluation, storage resource evaluation and resource pool resource evaluation. The resource evaluation of the local device (such as the first host device where the target instance is located) is online evaluation, the local computing resources (cpu and memory) are evaluated each time according to the evaluation request parameters, the occupied resources of the local instance are removed during evaluation, and in order to complete the local elasticity to the maximum extent, all elastic operations of the local elasticity follow a strategy of deleting and then creating so as to enable the local resources to reach the highest utilization. The storage resources are evaluated in an offline combination mode, the local storage can calculate real-time quantity online, and the non-local storage can use offline data. All the resources of the resource pool use offline data, and the part of data is imported by the monitoring and collecting module in a time-sharing manner. The whole evaluation flow is shown in fig. 7, and there are four evaluation results.
The scheduling strategy module mainly executes the decision of the scheduling strategy, the scheduling core does not move data as much as possible, the data has to be moved as little as possible, and the flexibility is completed in the most efficient mode. The part mainly aims at the scheduling strategy optimization of the elastic condition which cannot be completed by the local machine, and is divided into three optimization strategies: the first is a strategy of first bounce and then migration, aiming at a scene that a host does not exceed a load threshold, the requirement of the example is preferentially met to complete the elasticity of the local computer, and then an offline migration scheduling task is issued to finally reach the goal; the second type is a strategy of first migration and then ejection, the local computer evaluates all database examples on the local computer when the local computer cannot meet the elasticity condition, finds the example which is most suitable for migration to perform data migration, and then performs local elasticity on the example; the third is the migration policy of this example, which is the most suitable example for migration, and data migration scheduling and flexible scheduling are performed for this example.
Illustratively, as shown in fig. 12, the decision process of the scheduling policy module to execute the scheduling policy includes:
1201. and acquiring a target evaluation result.
1202. And judging whether the target evaluation result is a direct elastic evaluation result.
If the target evaluation result is the direct elasticity evaluation result, the following step 1203 is executed, otherwise the following step 1204 is executed.
1203. A direct native resiliency policy is determined.
1204. And judging whether the target evaluation result is a shot-before-migration evaluation result.
If the target evaluation result is the first bounce and then migration evaluation result, the following step 1205 is executed, otherwise, the following step 1206 is executed.
1205. And determining a first-bounce and later-migration elasticity strategy.
1206. And judging whether the target evaluation result is a first-migration-first-ejection evaluation result or not.
If the target evaluation result is a migration-first and ejection-last evaluation result, the following step 1207 is performed, otherwise, the following step 1208 is performed.
1207. And determining a first-migration-then-elastic strategy.
1208. A direct migration resilience policy is determined.
The resource scheduling module is an executor, performs instance scheduling according to the scheduling strategy output by the scheduling strategy module, and is divided into local scheduling and migration scheduling, and the local scheduling adopts a mode of deleting firstly and then creating, so that the sufficiency of local scheduling resources is ensured to the greatest extent; and the migration scheduling adopts a backup data priority mode, and after the remote backup data mount is locally copied, the data is quickly copied by the largest network and IOPS of the container and the instance is pulled up.
For example, if the backup library is 2c4g before being flexible and is to be flexible to 4c8g, the direct flexible strategy is that if the host device where the backup library is located has spare resources of 2c4g, the flexible strategy is directly performed on the first host device, the backup library is changed to 4c8g, the master-backup switching is performed, the original master library is flexible in the same way, and thus, data do not need to be migrated, and the whole time is about 1 minute; the method comprises the steps of firstly popping and then migrating, if the host equipment where the standby library is located does not have idle resources of 2c4g, judging whether the host equipment exceeds an overload threshold value set in advance if the host equipment is subjected to an elastic strategy, and if the host equipment can exceed the overload threshold value set in advance, for example, if the host equipment sets that the resources can exceed 4c8g, carrying out capacity expansion by using the same method of a direct elastic strategy, and finding out a proper instance on the host after capacity expansion; in the scheme of migration and ejection, if an elastic strategy is carried out on the host equipment, and the host equipment exceeds an overload threshold value and is not enough to expand capacity, an example which is most suitable for migration is found for migration, and after migration, the capacity of the standby library to be expanded at present is expanded by the same method of a direct elastic strategy; in the direct migration scheme, the current standby library is the most suitable for migration, and the standby library is directly migrated.
Fig. 13 is a schematic structural diagram of a service device provided in the embodiment of the present disclosure, which is used to exemplarily illustrate a service device that implements any database resiliency method in the embodiment of the present disclosure, and should not be construed as a specific limitation to the embodiment of the present disclosure.
As shown in fig. 13, service device 1300 may include a processor (e.g., central processing unit, graphics processor, etc.) 1301, which may perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)1302 or a program loaded from a storage device 1308 into a Random Access Memory (RAM) 1303. In the RAM 1303, various programs and data necessary for the operation of the service apparatus 1300 are also stored. The processor 1301, the ROM 1302, and the RAM 1303 are connected to each other via a bus 1304. An input/output (I/O) interface 1305 is also connected to bus 1304.
Generally, the following devices may be connected to the I/O interface 1305: input devices 1306 including, for example, touch screens, touch pads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, and the like; an output device 1307 including, for example, a Liquid Crystal Display (LCD), speaker, vibrator, etc.; storage devices 1308 including, for example, magnetic tape, hard disk, etc.; and a communication device 1309. The communication means 1309 may allow the serving device 1300 to communicate wirelessly or by wire with other devices to exchange data. While the service apparatus 1300 is shown with various means, it is to be understood that not all of the means shown are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a non-transitory computer readable medium, the computer program containing program code for performing the method illustrated by the flow chart. In such embodiments, the computer program may be downloaded and installed from a network via the communication means 1309, or installed from the storage device 1308, or installed from the ROM 1302. The computer program, when executed by the processor 1301, may perform the functions defined in any of the methods provided by the embodiments of the present disclosure.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the disclosure herein is not limited to the particular combination of features described above, but also encompasses other combinations of features described above or equivalents thereof without departing from the spirit of the disclosure. For example, the above features and (but not limited to) the features disclosed in this disclosure having similar functions are replaced with each other to form the technical solution.
Claims (10)
1. A database resiliency method, comprising:
receiving an elastic request for a target database in a local disk, wherein the target database comprises a first database serving as a standby database and a second database serving as a main database;
determining an elastic configuration scheme for the target database;
wherein the elastic fitting scheme comprises: performing elastic transformation and configuration processing on the first database to obtain a transformed third database;
performing active-standby switching on the third database and the second database, switching the third database to be a main database of the target database, and switching the second database to be a standby database of the target database;
and performing elastic transformation and configuration processing on the second database to obtain a fourth database after transformation and configuration, so as to obtain the target database after elastic transformation and configuration based on the third database serving as a main database and the fourth database serving as a standby database.
2. The method of claim 1, wherein the elastic request is a capacity expansion request, the elastic configuration is a capacity expansion configuration, and the first host device includes a target instance corresponding to the target database, where the target instance includes at least one of: the first database, the second database;
before the determining the elastic variation scheme for the target database, the method further comprises:
based on the capacity expansion request, acquiring first resource information, where the first resource information includes a computing resource occupied by each instance on the first host device, a storage resource occupied by each instance, an idle computing resource of the first host device, and a computing resource overload threshold of the first host device;
and determining a target evaluation result for carrying out capacity expansion and transformation and configuration on the target instance according to the first resource information.
3. The method of claim 2, wherein the target assessment result comprises any one of: direct elasticity evaluation results, first-bullet-then-migration evaluation results, first-migration-then-bullet evaluation results, and direct migration evaluation results;
wherein the direct elasticity assessment result comprises: the adjustment computing resource required by the target instance for the capacity expansion change is less than or equal to the idle computing resource of the first host device, and the scheme related to the target instance in the elastic change scheme is executed on the first host device;
the first-bullet and later-migration evaluation result comprises the following steps: the adjusted computing resource is larger than an idle computing resource of the first host device and smaller than or equal to a target resource, a scheme related to the target instance in the flexible configuration scheme is executed on the first host device, and then a first migration scheme is executed, wherein the target resource is the sum of the idle computing resource of the first host device and the computing resource overload threshold, and the first migration scheme is to migrate the first instance on the first host device from the first host device to a second host device;
the migration-before-bomb evaluation result comprises: the adjusting computing resource is larger than the target resource, the storage resource occupied by the target instance is larger than or equal to the storage resource occupied by the first instance, the first migration scheme is executed on the first host device, and then the scheme related to the target instance in the elastic change scheme is executed;
the direct migration evaluation result comprises: and the adjusting computing resource is larger than the target resource, the storage resource occupied by the target instance is smaller than the storage resource occupied by any second instance on the first host, and a scheme related to the target instance in the flexible scheduling scheme is executed while a second migration scheme is executed, wherein the second migration scheme is to migrate the target instance from the first host equipment to a third host equipment.
4. The method according to claim 3, wherein the target evaluation result comprises any one of: under the conditions of direct elasticity evaluation results, first-bullet-then-migration evaluation results and first-migration-then-bullet evaluation results, the elasticity transformation and configuration processing is first deletion and then creation processing;
and in the case that the target evaluation result comprises a direct migration evaluation result, the elastic morphing process is a creation-first and deletion-second process.
5. The method of claim 3, wherein the target assessment result comprises any one of: the method comprises the following steps of firstly carrying out bomb-to-transfer evaluation results, firstly carrying out transfer-to-bomb evaluation results and directly carrying out transfer evaluation results;
the method further comprises the following steps:
based on the capacity expansion request, second resource information corresponding to each target host device in at least one target host device in a resource pool is obtained, wherein the second resource information comprises idle computing resources of the corresponding target host device;
determining the first instance satisfying a first condition from instances on the first host device based on the first resource information and the second resource information, and determining the second host device satisfying a second condition from the at least one target host device, if the target evaluation result is the bomb-first-then-migration evaluation result or the bomb-first-then-migration evaluation result; the first condition includes: instances in which the occupied computing resources are greater than or equal to a difference between the adjusted computing resources and free computing resources of the first host device; the second condition includes: a target host device having idle computing resources greater than or equal to the computing resources occupied by the first instance;
determining the third host device satisfying a third condition from the at least one target host device based on the first resource information and the second resource information in a case where the target evaluation result is the direct migration evaluation result; the third condition includes: a target host device having idle computing resources greater than or equal to a sum of computing resources occupied by the target instance and the adjusted computing resources.
6. The method of claim 5, wherein the second resource information comprises free storage resources of the corresponding target host device;
when the target evaluation result is the shot-before-migration evaluation result or the shot-before-migration evaluation result, the first condition specifically includes any one of:
in an instance in which the occupied computing resource is greater than or equal to the difference between the adjusted computing resource and the idle computing resource of the first host device, the occupied computing resource is the smallest;
an instance that occupies computing resources greater than or equal to a difference between the adjusted computing resources and idle computing resources of the first host device and occupies minimal storage resources;
the second condition specifically includes any one of:
the target host equipment with the largest idle computing resource in the target host equipment with the idle computing resource larger than or equal to the computing resource occupied by the first instance;
in the target host equipment of which the idle computing resources are greater than or equal to the computing resources occupied by the first instance, the target host equipment with the largest weighted value of the idle computing resources and the idle storage resources;
in a case where the target evaluation result is the direct migration evaluation result, the third condition specifically includes any one of:
the idle computing resource is larger than or equal to the target host equipment with the largest idle computing resource in the target host equipment with the sum of the computing resource occupied by the target instance and the adjusting computing resource;
and the idle computing resources are greater than or equal to the target host equipment with the largest weighted value of the idle computing resources and the idle storage resources in the target host equipment with the sum of the computing resources occupied by the target instance and the adjusted computing resources.
7. The method of claim 6, wherein the first resource information further comprises a fixed tag for each instance on the first host device, the fixed tag indicating the host device that the corresponding instance allows migration;
the second resource information further comprises a device tag of the corresponding target host device;
when the target evaluation result is the first-missile and second-migration evaluation result or the first-migration and second-missile evaluation result, the fixed tag of the first instance is matched with the device tag of the second host device;
and in the case that the target evaluation result is the direct migration evaluation result, matching the fixed tag of the target instance with the device tag of the third host device.
8. The method according to any one of claims 3 to 7, wherein the first migration scheme comprises:
creating the first instance on the second host device;
copying the remote backup data corresponding to the first instance to an idle storage resource of the second host device at the maximum network speed and the maximum read-write speed of a container, wherein the remote backup data corresponding to the first instance is updated data within a preset time length;
pulling up the first instance;
deleting the first instance on the first host device;
the second migration scheme comprises:
creating an expansion and transformation example corresponding to the target example on the third host device;
copying the remote backup data corresponding to the target instance into an idle storage resource of the third host device at the maximum network speed and the maximum read-write speed of the container, wherein the remote backup data corresponding to the target instance is updated data within the preset time;
pulling up the instance after the capacity expansion and the transformation;
deleting the target instance on the first host device.
9. A database elastic apparatus, characterized in that the apparatus comprises: a receiving module and a determining module;
the receiving module is used for receiving an elastic request for a target database in a local disk, wherein the target database comprises a first database serving as a standby database and a second database serving as a main database;
the determining module is used for determining an elastic configuration scheme for the target database;
wherein the elastic fitting scheme comprises: performing elastic transformation and configuration processing on the first database to obtain a transformed third database;
performing active-standby switching on the third database and the second database, switching the third database into a main database of the target database, and switching the second database into a standby database of the target database;
and performing elastic transformation and configuration processing on the second database to obtain a fourth database after transformation and configuration, so as to obtain the target database after elastic transformation and configuration based on the third database serving as a main database and the fourth database serving as a standby database.
10. A database elastic service system, characterized in that the system comprises:
a resource management microservice module configured to: receiving a target request aiming at a target database, wherein the target request is an elastic request or an elastic evaluation request, and the target database comprises a first database serving as a standby database and a second database serving as a main database;
a data service module configured to: providing first resource information on a first host device where a target instance corresponding to the target database is located, wherein the target instance comprises at least one of the following items: the first database, the second database; the first resource information includes computing resources occupied by each instance and storage resources occupied by each instance on the first host device, idle computing resources of the first host device, a computing resource overload threshold of the first host device;
a resource assessment module configured to: under the condition that the target request is a related request of capacity expansion and transformation, acquiring the first resource information from the data service module based on the target request, and determining a target evaluation result of capacity expansion and transformation of the target instance according to the first resource information, wherein the target evaluation result comprises any one of the following items: direct elasticity evaluation results, first-bullet-then-migration evaluation results, first-migration-then-bullet evaluation results, and direct migration evaluation results;
under the condition that the target request is an elastic evaluation request, sending the target evaluation result to the resource management micro-service module;
a resource pool data module configured to: providing second resource information corresponding to each target host device in at least one target host device in a resource pool, wherein the second resource information comprises idle computing resources of the corresponding target host device;
a scheduling policy determination module configured to: obtaining the target evaluation result from the resource evaluation module;
the target evaluation result comprises any one of the following items: under the conditions of a first-bomb-second-migration evaluation result, a first-migration-second-bomb evaluation result and a direct migration evaluation result, determining a migration scheduling strategy corresponding to a migration scheme for performing capacity expansion and transformation on the target instance based on the target evaluation result and second resource information acquired from the resource pool data module, wherein the scheduling strategy comprises the migration instance corresponding to the migration scheme and target host equipment to which the migration instance needs to be migrated;
a resource scheduling module configured to: executing an elastic scheduling strategy corresponding to a scheme related to the target instance in an elastic variant scheme under the condition that the target request is an elastic request corresponding to the capacity reduction variant;
executing an elastic scheduling strategy corresponding to a scheme related to the target instance in an elastic transformation and distribution scheme under the condition that the target request is a capacity expansion request and the target evaluation result is a direct elastic evaluation result;
when the target request is a capacity expansion request, and the target evaluation result includes any one of: executing an elastic scheduling strategy corresponding to a scheme related to the target instance in an elastic transformation and configuration scheme under the conditions of a first-bomb-after-migration evaluation result, a first-migration-after-bomb evaluation result and a direct migration evaluation result, and executing the migration scheduling strategy corresponding to the target evaluation result;
wherein the elastic fitting scheme comprises: performing elastic transformation and configuration processing on the first database to obtain a transformed third database;
performing active-standby switching on the third database and the second database, switching the third database to be a main database of the target database, and switching the second database to be a standby database of the target database;
and performing elastic transformation and configuration processing on the second database to obtain a fourth database after transformation and configuration, so as to obtain the target database after elastic transformation and configuration based on the third database serving as a main database and the fourth database serving as a standby database.
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