CN111104406A - Hierarchical service data storage method and device, computer equipment and storage medium - Google Patents
Hierarchical service data storage method and device, computer equipment and storage medium Download PDFInfo
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
- G06F16/2228—Indexing structures
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
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- G06F16/24552—Database cache management
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/282—Hierarchical databases, e.g. IMS, LDAP data stores or Lotus Notes
Abstract
The application relates to a hierarchical service data storage method, a hierarchical service data storage device, a computer device and a storage medium. The method comprises the following steps: acquiring service data to be written, wherein the service data to be written comprises attribute information; determining the hierarchy attribute and the associated field information of the service data to be written according to the attribute information; writing the service data into a hierarchical structure table in a service database according to the hierarchical attribute and the associated field information; calling a cache scheduling model to perform cache decision analysis on the service data to obtain a corresponding cache strategy; and determining the service data to be cached in the service database according to the caching strategy, and generating asynchronous caching tasks for the service data to be cached, scheduling and caching the asynchronous caching tasks into a service caching database. By adopting the method, the service data storage efficiency can be effectively improved so as to reduce the pressure of the data database.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a method and an apparatus for storing hierarchical service data, a computer device, and a storage medium.
Background
With the rapid development of internet technology, massive data is also generated in various business applications. In web service development, a hierarchical data structure is often adopted, that is, a hierarchical structure is constructed in a database by describing each node so as to store mass data.
However, in the conventional data structure storage method, multiple searches need to be performed across levels when data is acquired, when the access amount of the database is large, the operation pressure of the database is large, which easily causes a system performance bottleneck, and the storage efficiency of the hierarchical data is low, which results in low data acquisition efficiency.
Disclosure of Invention
In view of the foregoing, there is a need to provide a hierarchical business data storage method, apparatus, computer device and storage medium capable of effectively improving business data storage efficiency to reduce database pressure.
A hierarchical traffic data storage method, the method comprising:
acquiring service data to be written, wherein the service data to be written comprises attribute information;
determining the hierarchy attribute and the associated field information of the service data to be written according to the attribute information;
writing the service data into a hierarchical structure table in a service database according to the hierarchical attribute and the associated field information;
calling a cache scheduling model to perform cache decision analysis on the service data to obtain a corresponding cache strategy;
and determining the service data to be cached in the service database according to the caching strategy, and generating asynchronous caching tasks for the service data to be cached, scheduling and caching the asynchronous caching tasks into a service caching database.
In one embodiment, before the business data is written into the hierarchical table in the business database, the method further comprises: determining corresponding key fields and associated fields according to the service types of the service data; adding an array structure corresponding to the associated field to the tree-shaped hierarchical structure of the service type; and constructing a service data structure corresponding to the service type and a corresponding hierarchical structure table according to the hierarchical relationship according to the tree hierarchical structure added with the array structure.
In one embodiment, the attribute information includes a service type, and the determining, according to the attribute information, the hierarchy attribute and the associated field information of the service data to be written includes: determining the associated field of the service data to be written according to the service type; performing hierarchy analysis on the service data to be written according to the attribute information to obtain hierarchy attributes and hierarchy relations of the service data to be written; and determining the associated field information of the associated field according to the hierarchical attribute and the hierarchical relation.
In one embodiment, the writing the service data into a hierarchical structure table in a service database according to the hierarchical attribute and the associated field information includes: determining a hierarchical path of the service data to be written according to the hierarchical attribute and the hierarchical relationship; determining the position of a hierarchical structure in a service database according to the hierarchical relation of the service data to be written; and writing the service data into a hierarchical structure table of the service database according to the hierarchical path.
In one embodiment, the method further comprises: acquiring update service data, wherein the update service data comprises attribute information; determining the hierarchy attribute and the associated attribute information of the updated service data according to the attribute information; and correcting the associated field information of the corresponding service data in the service database according to the hierarchy attribute and the associated attribute information to obtain updated service data.
In one embodiment, the invoking the cache scheduling model to perform cache decision analysis on the service data to obtain the corresponding cache policy includes: calling a cache scheduling model, and monitoring service data in a service database and a service cache library through the cache scheduling model to obtain service state information and cache state information; determining the weight and the access frequency of the service data according to the service state information and the cache state information; and deciding a caching strategy of the service data according to the weight and the access frequency.
In one embodiment, the generating asynchronous cache task scheduling and caching the to-be-cached service data into a service cache library includes: obtaining a hierarchy path of the service data to be cached, and calling an asynchronous task frame to generate an asynchronous caching task of the service data to be cached according to the hierarchy path; calling an asynchronous thread to distribute the asynchronous cache task to a corresponding task queue; and caching the service data to be cached into a service cache library according to the task queue.
In one embodiment, the method further comprises: determining the service data to be cleaned in the service cache library according to the cache state information and the cache strategy through the cache scheduling model; and calling an asynchronous task frame to generate an asynchronous cache cleaning task of the service data to be cleaned, and cleaning the service data to be cleaned according to the asynchronous cache cleaning task.
In one embodiment, the method further comprises: receiving a data acquisition request sent by a user terminal, wherein the data acquisition request carries a service data identifier; searching matched service data from a service data cache library according to the service data identifier; and sending the service data to the user terminal.
In one embodiment, the method further comprises: if the service data matched with the query request is not queried in the service data cache library, acquiring the matched service data from the service database according to the service data identifier; and calling the cache scheduling model to schedule and cache the service data into the service cache library, and sending the service data in the service cache library to the user terminal.
A hierarchical business data storage apparatus, the apparatus comprising:
the data acquisition module is used for acquiring service data to be written, and the service data to be written comprises attribute information;
the data storage module is used for determining the hierarchy attribute and the associated field information of the service data to be written according to the attribute information; writing the service data into a hierarchical structure table in a service database according to the hierarchical attribute and the associated field information;
the scheduling decision module is used for calling a cache scheduling model to perform cache decision analysis on the service data to obtain a corresponding cache strategy;
and the data caching module is used for determining the service data to be cached in the service database according to the caching strategy and generating asynchronous caching tasks for the service data to be cached to be scheduled and cached in the service caching database.
A computer device comprising a memory storing a computer program and a processor implementing the steps of the hierarchical service data storage method provided in any one of the embodiments of the present application when executing the computer program.
A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the hierarchical business data storage method provided in any one of the embodiments of the present application.
After the hierarchical service data storage method, the hierarchical service data storage device, the computer equipment and the storage medium acquire the service data to be written, determining the hierarchical attribute and the associated field information of the service data to be written according to the attribute information of the service data to be written; writing the service data into a hierarchical structure table in a service database according to the hierarchical attribute and the associated field information; because the business database comprises an array structure of redundant associated fields, the business data and the associated field information can be effectively stored in the business database. The server further calls a cache scheduling model to perform cache decision analysis on the service data, so that a corresponding cache strategy can be effectively obtained; determining the service data to be cached in the service database according to the caching strategy, and generating asynchronous caching tasks for the service data to be cached, scheduling and caching the asynchronous caching tasks into the service caching database. The service data are stored in the service database comprising the redundant field structure, and the service data are scheduled and cached through the cache scheduling model, so that the scheduling and caching can be effectively performed according to the associated field information, the scheduling and caching efficiency of the service data is effectively improved, the database access pressure caused by the hierarchical data is effectively reduced, and the storage efficiency of the service data is effectively improved.
Drawings
Fig. 1 is a diagram illustrating an application scenario of a hierarchical service data storage method according to an embodiment;
FIG. 2 is a flow diagram illustrating a method for storing hierarchical service data in accordance with one embodiment;
FIG. 3 is a flow diagram that illustrates the steps of constructing a business data structure, in one embodiment;
FIG. 4 is a flow diagram illustrating the steps of updating business data in one embodiment;
FIG. 5 is a flowchart illustrating the step of scheduling cache in one embodiment;
FIG. 6 is a flow diagram illustrating the business data query step in one embodiment;
FIG. 7 is a block diagram of a hierarchical service data storage device in one embodiment;
FIG. 8 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The hierarchical service data storage method provided by the application can be applied to the application environment shown in fig. 1. Wherein the terminal 102 communicates with the server 104 via a network. After acquiring the service data to be written, the server 104 determines the hierarchy attribute and the associated field information of the service data to be written according to the attribute information of the service data to be written; and writing the service data into a hierarchical structure table in the service database according to the hierarchical attribute and the associated field information. The server 104 further calls a cache scheduling model to perform cache decision analysis on the service data to obtain a corresponding cache strategy; determining the service data to be cached in the service database according to the caching strategy, and generating asynchronous caching tasks for the service data to be cached, scheduling and caching the asynchronous caching tasks into the service caching database. The terminal 102 may send a data acquisition request to the server 104 to acquire corresponding service data from the service cache library. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices, and the server 104 may be implemented by an independent server or a server cluster formed by a plurality of servers.
In one embodiment, as shown in fig. 2, a hierarchical service data storage method is provided, which is described by taking the method as an example applied to the server in fig. 1, and includes the following steps:
The service data may be hierarchical data. The service data may represent related data generated or required in processing related services, and the service data may be hierarchical data. The service data may also include data to be stored sent by the terminal, and may also include service data to be stored, which is acquired by the server from a third-party platform or the server. The server can store, schedule and cache the service data through the service data storage system. The business data storage system can comprise a business database and a business cache library, and can also comprise a hierarchical data processing model and a cache scheduling model. The service database may be deployed in a hard disk, and the service cache library may be deployed in a memory. The service system can generate service data in the operation process, and the service database and the service cache library can store the hierarchical service data by adopting a hierarchical data structure. The hierarchical data processing model can be used for processing the to-be-written business data such as hierarchical relation analysis, path analysis, data correction and the like. The cache scheduling model can be used for monitoring service data, performing cache policy decision analysis, cleaning a cache and the like.
The hierarchical data structure is a directed tree or forest of record type nodes, and one of the main characteristics of the tree is that any node has one or more father nodes except a root node. The population represented by the parent node and the population of the child node must be in one-to-many relationship, i.e., one parent record corresponds to a plurality of child records, and one child record corresponds to only one parent record.
After acquiring the service data generated in the service processing process, the server determines the data to be stored in the service database as service data to be written, wherein the service data to be written comprises attribute information. The attribute information may include information such as a service type, a right attribute, and the like.
The traffic database may be a tree-like hierarchical data structure including a plurality of redundant fields. For example, when constructing a service database with a tree hierarchy, the server may perform flattening processing on the tree hierarchy, determine an association hierarchy field, and add an array structure corresponding to the association hierarchy field to the tree hierarchy, thereby constructing the service database.
And step 204, determining the hierarchy attribute and the associated field information of the service data to be written according to the attribute information.
Wherein, the hierarchy attribute can represent the hierarchy category of the business data in the organization structure of the corresponding business type. The associated field information may be important field information in the hierarchy that requires redundancy.
After the server acquires the service data to be written, the server identifies the hierarchy attribute of the service data to be written according to the attribute information of the service data, and determines corresponding associated field information according to the hierarchy attribute.
For example, when the service data to be written acquired by the server is employee information, the employee information may include attribute information such as an employee identifier, an employee name, and an employee position. The server may determine the employee identifier as a primary key identifier, and the server may also determine a corresponding hierarchical attribute according to an employee position attribute in the employee information, where the hierarchical attribute may be a level of the employee in a company organization architecture, and the associated field information may include field information corresponding to a plurality of associated fields such as a hierarchical field, a hierarchical path, and an identification path.
And step 206, writing the service data into a hierarchical structure table in the service database according to the hierarchical attribute and the associated field information.
And after determining the hierarchy attribute and the associated field information of the service data to be written according to the attribute information, the server writes the service data into a hierarchy structure table in a service database according to the hierarchy attribute and the associated field information. Specifically, the server may determine a hierarchical relationship and a hierarchical path of the service data to be written in the hierarchical structure according to the hierarchical attribute, determine a position of the hierarchical structure to be written in the service database according to the hierarchical relationship, and write the service data in the hierarchical structure table of the service database by the hierarchical path.
And step 208, calling a cache scheduling model to perform cache decision analysis on the service data to obtain a corresponding cache strategy.
The cache scheduling model can be a plug-in-based cache scheduler, and is used for monitoring the service database and the service cache library, deciding a cache strategy of the service cache library, and performing cache scheduling on service data according to the cache strategy.
After the server stores the service data to be written into the service database, the cache scheduling model can be called to monitor the database states of the service database and the service cache library in real time. Specifically, the server monitors the service data in the service database and the service cache library through a cache scheduling model to obtain service state information and cache state information, determines the weight and the access frequency of the service data according to the cache state information and the service state information, and decides the cache strategy of the service data in the service database according to the priority and the access frequency.
After the server decides a cache strategy by using the cache scheduling model, the server can determine the service data to be cached in the service database according to the cache strategy, obtain the hierarchical path of the service data to be cached, call the asynchronous task framework to generate the asynchronous cache task of the service data to be cached according to the hierarchical path, and then schedule and cache the generated asynchronous cache task of the service data to be cached into the service cache library. The service data are stored in the service database comprising the redundant field structure, and the scheduling cache is carried out on the service data through the cache scheduling model, so that the scheduling cache can be effectively carried out according to the associated field information, and the database access pressure caused by the hierarchical data is effectively reduced by using the space replacement time.
For example, the hierarchical service data storage method in this embodiment may be implemented based on a Django framework. Django is a Web application framework of open source code, namely a Python Web framework. Django is an open source model driven by Python programming language and derived from an open source community, and also comprises a plurality of third-party plug-ins. The architecture is easy to maintain and drive the database and has strong expandability. In building the database, code components that can be implemented through the Django framework cooperate with the Celery distribution framework. The Django framework can comprise a hierarchical data processing and data storage part and a plug-in corresponding to a cache scheduler, so that hierarchical service data can be effectively stored, and the service data can be scheduled and cached in a cache.
In the hierarchical service data storage method, after the server acquires the service data to be written, the server determines the hierarchical attribute and the associated field information of the service data to be written according to the attribute information of the service data to be written; writing the service data into a hierarchical structure table in a service database according to the hierarchical attribute and the associated field information; because the business database comprises an array structure of redundant associated fields, the business data and the associated field information can be effectively stored in the business database. The server further calls a cache scheduling model to perform cache decision analysis on the service data, so that a corresponding cache strategy can be effectively obtained; determining the service data to be cached in the service database according to the caching strategy, and generating asynchronous caching tasks for the service data to be cached, scheduling and caching the asynchronous caching tasks into the service caching database. The service data are stored in the service database comprising the redundant field structure, and the service data are scheduled and cached through the cache scheduling model, so that the scheduling and caching can be effectively performed according to the associated field information, the scheduling and caching efficiency of the service data is effectively improved, the database access pressure caused by the hierarchical data is effectively reduced, and the storage efficiency of the service data is effectively improved.
In one embodiment, as shown in fig. 3, before the service data is written into the hierarchical structure table in the service database, the method further includes a step of constructing a service data structure, where the step specifically includes the following steps:
And step 304, adding an array structure corresponding to the associated field to the tree-shaped hierarchical structure of the service type.
And step 306, constructing a service data structure corresponding to the service type and a corresponding hierarchical structure table according to the tree hierarchical structure added with the array structure and the hierarchical relationship.
Before the server writes the service data into the service database, a corresponding hierarchical structure table needs to be constructed in the service database for storing the corresponding service data.
Specifically, the server may determine the key field and the associated field in advance for the service type of each service data. The key field may be a primary key, for example, a corresponding primary key identifier in the data table. The primary key, which may also be referred to as a primary key, may be composed of one or more fields, and may be used to uniquely identify a row of data in a table or to uniquely identify an entity. The primary key can be configured in advance according to the service type, and the server can be configured in advance and generate a service configuration table. Further, important associated fields required by the service type can be configured in advance in the service configuration table. The associated field may be important field information that needs redundancy in a hierarchical structure corresponding to the service type.
The hierarchical service data includes corresponding hierarchical structure information, such as organization structure information. The server can directly determine a corresponding tree hierarchy according to the organization structure information, and the tree hierarchy includes corresponding hierarchy relations. And the server acquires a corresponding service configuration table according to the service type of the service data, and determines a key field and an associated field corresponding to the service data of the service type from the service configuration table. And the server flattens the tree hierarchy according to the key field and the associated field. The association field may then be represented as a tree hierarchy of flattened description information.
Specifically, the server adds an array structure corresponding to the associated field to the tree-shaped hierarchical structure corresponding to the service type, and constructs a corresponding service data structure and a corresponding hierarchical structure table according to the hierarchical relationship according to the tree-shaped hierarchical structure to which the array structure is added. The constructed service data structure may include a tree-shaped hierarchical data structure of a plurality of redundancy associated fields, and the server may further generate a plurality of hierarchical tables corresponding to the service data structure, where the hierarchical tables are used to store service data of corresponding hierarchies. By adding the array structure corresponding to the associated hierarchical field after flattening the tree structure, when the hierarchical structure of the service data changes, the corresponding hierarchical data can be modified only by modifying the field value corresponding to the hierarchical path, so that the database pressure of modifying the data can be effectively relieved, and the service database with higher storage performance and query efficiency can be effectively constructed.
For example, if the service type of the service data to be written is commodity information, commodity category information may be configured in a service configuration table corresponding to the service type, such as "first-level classification: daily necessities, secondary classification: food, three-level classification: edible oil and other commodity classification information. The tree-shaped hierarchical structure corresponding to the service type may only include a commodity identifier, a commodity name, and a previous-layer node identifier. After the server performs flattening processing on the tree structure, an array structure corresponding to the associated level field is added, for example, the field to be added may include an array structure corresponding to the associated field, such as the level field, the name path field, and the identification path field. Thereby effectively utilizing the amplified service database to store the service data.
In one embodiment, the attribute information includes a service type, and determining the hierarchy attribute and the associated field information of the service data to be written according to the attribute information includes: performing hierarchy analysis on the service data to be written according to the attribute information to obtain hierarchy attributes and hierarchy relations of the service data to be written; determining a hierarchy path of the service data to be written according to the hierarchy attribute and the hierarchy relation; and determining the associated field information of the associated field according to the hierarchy attribute and the hierarchy relation.
Wherein, the hierarchy attribute can represent the hierarchy category of the business data in the organization structure of the corresponding business type. The associated field information may be important field information in the hierarchy that requires redundancy. The attribute information of the service data to be written also includes the service type.
And after acquiring the service data to be written in, the server acquires a service configuration table corresponding to the service type, and determines a key field and an associated field corresponding to the service data of the service type from the service configuration table. And the server further performs hierarchical analysis on the service data to be written through a hierarchical data processing model deployed in the service data storage system. The server can analyze the attribute information of the service data to be written through the hierarchical data processing model, the attribute information of the service data to be written comprises the service type, and the hierarchical attribute and the hierarchical relation of the service data to be written are identified according to the hierarchical organization structure of the service type.
The server further determines field information corresponding to the associated field according to the hierarchy attribute and the hierarchy relationship, where the associated field information may include field information corresponding to a plurality of associated fields, such as a hierarchy field, a hierarchy path, and an identification path. The associated field information may include field information corresponding to a plurality of associated fields, such as a hierarchy field, a hierarchy path, and an identification path. Therefore, the hierarchical path of the service data to be written can be effectively analyzed, and the service data can be effectively stored according to the hierarchical path.
In one embodiment, writing the service data into the hierarchy table in the service database according to the hierarchy attribute and the associated field information comprises: determining a hierarchy path of the service data to be written according to the hierarchy attribute and the hierarchy relation; determining the position of a hierarchical structure in a service database according to the hierarchical relation of service data to be written; and writing the service data into a hierarchical structure table of the service database according to the hierarchical path.
The server analyzes the attribute information of the service data to be written through the hierarchical data processing model, after the hierarchical attribute and the hierarchical relationship of the service data to be written are identified, the path of the hierarchical organization structure is split, the corresponding hierarchy and path are determined according to the hierarchical attribute and the hierarchical relationship of the service data to be written, and the hierarchical path of the service data to be written is generated.
And after determining the hierarchical path of the service data to be written according to the hierarchical attribute and the hierarchical relationship, the server further determines the hierarchical structure position in the service database according to the hierarchical relationship of the service data to be written. The server writes the service data into a hierarchical structure table of the service database according to the hierarchical path and the hierarchical structure position. Because the business database comprises an array structure of redundant associated fields, the business data and the associated field information can be effectively stored in a corresponding hierarchical structure table of the business database.
In an embodiment, as shown in fig. 4, the method further includes a step of updating the service data, where the step specifically includes the following steps:
And step 404, determining the hierarchy attribute and the associated attribute information of the updated service data according to the attribute information.
And step 406, correcting the field information of the corresponding service data in the service database according to the hierarchy attribute and the associated attribute information to obtain updated service data.
The update service data refers to data that needs to be updated to the service data in the service database. The updated service data includes corresponding attribute information, for example, the attribute information may include information of service type, original permission attribute, updated permission attribute, and the like.
After the server acquires the service data to be written, the server determines the hierarchy attribute and the associated field information of the service data to be written according to the attribute information of the service data to be written, and writes the service data into a hierarchy structure table in a service database according to the hierarchy attribute and the associated field information, so that the service data and the associated field information can be effectively stored in the service database. After the server stores the service data in the service database, when the service data is changed, the server can update the service data stored in the service database.
Specifically, after acquiring the updated service data of the part to be updated, the server determines the hierarchy attribute and the associated attribute information of the updated service data according to the attribute information, and determines the attribute information of the part to be updated according to the hierarchy attribute and the associated attribute information. The server can also identify corresponding service data to be updated in the service database, and further correct the field information of the corresponding service data in the service database by using the attribute information of the part to be updated, specifically, the server can determine the field to be updated of the service data to be updated and the corresponding hierarchical structure position according to the hierarchical attribute and the associated attribute information of the updated service data, and further correct and update the content of the field to be updated according to the hierarchical structure position by using the attribute information of the part to be updated, so that the field information in the hierarchical structure table in the service database is directly corrected and updated, and the updated service data is obtained. And the field information of the hierarchical field can be directly corrected and updated, so that the hierarchical structure of the service data is directly updated.
Furthermore, when the server updates the service data, the asynchronous thread can be called to generate a corresponding data updating task to update the service data, so that the efficiency of updating the service data is effectively improved.
For example, if the business data in a hierarchical table is related to other data and the hierarchical table is changed, the server may generate an asynchronous update task to update the corresponding business data. For example, taking the user information as an example, if the user and the organization structure are in a many-to-one hierarchical relationship, the user table redundantly stores the information of the organization structure or the association table of the user and the organization, and when the organization structure changes, the organization to which the user belongs also changes. At this time, the server can start an asynchronous update task to update and process the data of the hierarchical structure table corresponding to the user and the organization table or the user-organization association table, so that the service data can be effectively updated.
In one embodiment, invoking the cache scheduling model to perform cache decision analysis on the service data, and obtaining the corresponding cache policy includes: calling a cache scheduling model, and monitoring service data in a service database and a service cache library through the cache scheduling model to obtain service state information and cache state information; determining the weight and the access frequency of the service data according to the service state information and the cache state information; and deciding a caching strategy of the service data according to the weight and the access frequency.
After acquiring the service data to be written, the server determines the hierarchy attribute and the associated field information of the service data to be written according to the attribute information of the service data to be written; and writing the service data into a hierarchical structure table in the service database according to the hierarchical attribute and the associated field information, thereby effectively storing the service data and the associated field information into the service database.
And after the server stores the service data to be written into the service database, the server further calls a cache scheduling model to perform cache decision analysis on the service data, and specifically, the server calls the cache scheduling model to perform real-time monitoring on the service database and the service data in the service cache library through the cache scheduling model. Specifically, the server calls a cache scheduling model to monitor the service data in the service database in real time, and cache state information and service state information are obtained. The service state information may include state information such as priority and access information of service data in the service database, and the cache state information may include state information such as a cache cycle and a cache number of the service data cached in the service cache library.
The server further determines the weight and the access frequency of the service data according to the service state information and the cache state information, for example, the weight of the service data can be determined according to the priority of the service data, the corresponding access frequency is calculated according to the access information of the service data, and the server performs cache decision analysis on the service data according to the weight and the access frequency, so as to decide a cache strategy of the service data. The caching strategy of the service data may include a caching scheduling strategy of the service data in the service database, and a scheduling strategy of the service data in the service caching database. Therefore, the corresponding cache strategy can be effectively obtained.
And the server determines the service data to be cached in the service database according to the caching strategy, and generates asynchronous caching tasks for the service data to be cached, schedules and caches the asynchronous caching tasks into the service caching database. The server can also perform processing such as cache cleaning on the service data in the service cache library according to a scheduling policy of the service data in the service cache library. After the cache strategy is decided through the cache scheduling model, the cache scheduling processing can be effectively carried out on the service data according to the cache strategy, and the cache scheduling processing efficiency of the service data is effectively improved.
In an embodiment, as shown in fig. 5, the step of generating an asynchronous cache task from the service data to be cached and scheduling and caching the asynchronous cache task in the service cache library specifically includes the following steps:
After acquiring the service data to be written, the server determines the hierarchy attribute and the associated field information of the service data to be written according to the attribute information of the service data to be written; and writing the service data into a hierarchical structure table in the service database according to the hierarchical attribute and the associated field information. The server further calls a cache scheduling model to perform cache decision analysis on the service data, so that a corresponding cache strategy can be effectively obtained; determining the service data to be cached in the service database according to the caching strategy, and generating asynchronous caching tasks for the service data to be cached, scheduling and caching the asynchronous caching tasks into the service caching database. The server can determine the weight and the access frequency of the service data according to the service state information and the cache state information, and decide the cache strategy of the service data according to the weight and the access frequency. For example, the server may determine the service data with higher weight and the service data with higher access frequency as the service data to be cached, which needs to be cached in the service cache library.
Specifically, after determining the service data to be cached in the service database according to the caching policy, the server obtains a hierarchical path of the service data to be cached, and the hierarchical path may also be used to represent a storage path of the service data in the service database. And the server calls the asynchronous task framework to generate a corresponding asynchronous cache task according to the hierarchical path of the service data to be cached. The server can simultaneously generate a plurality of asynchronous cache tasks and other asynchronous processing tasks, and simultaneously calls a plurality of asynchronous threads to respectively distribute the asynchronous cache tasks, distributes each asynchronous cache task to a corresponding task queue, performs cache scheduling processing according to the task queues through the asynchronous threads, and caches service data to be cached in the asynchronous cache tasks into the service cache library. For example, the server may adopt a Celery-based asynchronous framework, and the Celery asynchronous framework may be used to process the asynchronous task queues in real time and perform task scheduling processing on the asynchronous tasks.
The asynchronous task is generated for the service data through the cache scheduling model to perform scheduling and caching, so that the load balance of the data scheduling task with large data volume can be effectively performed, the service data can be effectively scheduled and cached, and the scheduling and caching efficiency of the service data is effectively improved.
In one embodiment, the method further comprises: determining service data to be cleaned in a service cache library according to cache state information and a cache strategy through a cache scheduling model; and calling the asynchronous task framework to generate an asynchronous cache cleaning task of the service data to be cleaned, and cleaning the service data to be cleaned according to the asynchronous cache cleaning task.
The server stores the service data into the service database, schedules and caches the service data to be cached in the service database into the service cache library, and then continuously monitors the service database and the cache state information of the service data in the service cache library in real time through the cache scheduling model. The cache state information may include state information such as a cache cycle, a cache number, and the like of the service data cached in the service cache library.
The server further determines service data to be cleaned in the service cache library according to the cache state information and the cache strategy, and calls an asynchronous task frame through a cache scheduling model to generate asynchronous cache cleaning tasks of the service data to be cleaned, the server calls asynchronous threads to respectively distribute the asynchronous cache cleaning tasks, distributes the asynchronous cache cleaning tasks to corresponding task queues, and performs cache cleaning processing according to the task queues through the asynchronous threads, so that the cache service data in the cache library is effectively cleaned and updated.
For example, when the hierarchy of the service data is changed or the cache period of the service data is too long, the server may perform batch cleaning and updating on the hierarchies with different update frequencies according to the cache policy through the cache scheduling model. For example, a plurality of pages in a certain service system refer to information of all streets in a certain area for a plurality of times, and the street information is cached to the service cache library, so that when a large number of users access, the information of the hierarchical structure can be directly obtained from the service cache library, thereby effectively reducing the access pressure of the service database and effectively improving the performance of the service system.
Further, the server may also perform cleaning and updating on the service cache library at regular time according to the preset frequency, for example, the server may perform formatting cleaning on all cached service data in the service cache library according to the preset frequency, so as to re-decide a caching policy of all service data, and schedule and cache the service data to be cached according to the caching policy. The expired service data and the invalid service data can be timely and effectively cleaned by regularly cleaning and updating the service cache library, so that the effectiveness of the service data in the service cache library can be effectively ensured.
In an embodiment, as shown in fig. 6, the method further includes a service data query step, which specifically includes the following steps:
And step 604, searching the matched service data from the service data cache library according to the service data identifier.
The server stores the service data into a service database according to the hierarchy attribute and the associated field information of the service data, and after the service data to be cached in the service database is scheduled and cached to a service cache library according to a cache strategy through a cache scheduling model, a user can initiate a data acquisition request to the server through a corresponding user terminal based on a service system. The data acquisition request may be a data query request, a data access request, and other operation requests based on service data, and the data acquisition request carries a service data identifier.
And after receiving a data acquisition request sent by the user terminal, the server searches the service data matched with the service data identifier from the service data cache library according to the service data identifier. After the server acquires the service data matched with the service data identifier from the service cache library, the server returns the service data from the service cache library to the user terminal, and by acquiring the corresponding service data from the service cache library, the query and acquisition efficiency of the service data can be effectively improved, and the pressure of the service database is effectively reduced.
In one embodiment, the method further comprises: if the business data matched with the query request is not queried in the business data cache library, acquiring the matched business data from the business database according to the business data identifier; and calling a cache scheduling model to schedule and cache the service data into a service cache library, and sending the service data in the service cache library to the user terminal.
And after receiving a data acquisition request sent by the user terminal, the server searches the service data matched with the service data identifier from the service data cache library according to the service data identifier. And after the server acquires the service data matched with the service data identifier from the service cache library, the server returns the service data to the user terminal from the service cache library.
Further, when the server does not inquire the service data matched with the inquiry request in the service data cache library, the service data is cached in the service cache library. The server immediately calls the cache scheduling model to acquire the matched service data from the service database according to the service data identification, generates an asynchronous cache task from the service data, schedules and caches the service data into the service cache library through the asynchronous cache task, and then sends the matched service data to the user terminal from the service cache library. The unmatched service data are scheduled and cached in the service cache library in real time, so that the service data can be effectively scheduled to the service cache library in time and returned to the user terminal, and meanwhile, the service data can be effectively and directly acquired from the service cache library when the service data are subsequently accessed, so that the query and acquisition efficiency of the service data is effectively improved, and the pressure of the service database is effectively relieved.
It should be understood that although the various steps in the flow charts of fig. 2-6 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-6 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternating with other steps or at least some of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 7, there is provided a hierarchical service data storage apparatus including: a data acquisition module 702, a data storage module 704, a scheduling decision module 706, and a data caching module 708, wherein:
a data obtaining module 702, configured to obtain service data to be written, where the service data to be written includes attribute information;
a data storage module 704, configured to determine, according to the attribute information, a hierarchy attribute and associated field information of the service data to be written; writing the service data into a hierarchical structure table in a service database according to the hierarchical attribute and the associated field information;
the scheduling decision module 706 is configured to invoke a cache scheduling model to perform cache decision analysis on the service data, so as to obtain a corresponding cache policy;
the data caching module 708 is configured to determine to-be-cached service data in the service database according to the caching policy, and generate an asynchronous cache task for the to-be-cached service data and schedule and cache the asynchronous cache task into the service cache database.
In one embodiment, the device further comprises a service database construction module, configured to determine corresponding key fields and associated fields according to service types of the service data; adding an array structure corresponding to the associated field to the tree-shaped hierarchical structure of the service type; and constructing a service data structure corresponding to the service type and a corresponding hierarchical structure table according to the tree hierarchical structure added with the array structure and the hierarchical relationship.
In an embodiment, the attribute information includes a service type, and the data storage module 704 is further configured to determine an associated field of the service data to be written according to the service type; performing hierarchy analysis on the service data to be written according to the attribute information to obtain hierarchy attributes and hierarchy relations of the service data to be written; and determining the associated field information of the associated field according to the hierarchy attribute and the hierarchy relation.
In one embodiment, the data storage module 704 is further configured to determine a hierarchical path of the service data to be written according to the hierarchical attribute and the hierarchical relationship; determining the position of a hierarchical structure in a service database according to the hierarchical relation of service data to be written; and writing the service data into a hierarchical structure table of the service database according to the hierarchical path.
In one embodiment, the apparatus further includes a service data updating module, configured to obtain updated service data, where the updated service data includes attribute information; determining the hierarchy attribute and the associated attribute information of the updated service data according to the attribute information; and correcting the associated field information of the corresponding service data in the service database according to the hierarchy attribute and the associated attribute information to obtain the updated service data.
In one embodiment, the scheduling decision module 706 is further configured to invoke a cache scheduling model, and monitor the service database and the service data in the service cache library through the cache scheduling model to obtain service state information and cache state information; determining the weight and the access frequency of the service data according to the service state information and the cache state information; and deciding a caching strategy of the service data according to the weight and the access frequency.
In one embodiment, the data caching module 708 is further configured to obtain a hierarchical path of the service data to be cached, and invoke the asynchronous task framework to generate an asynchronous caching task of the service data to be cached according to the hierarchical path; calling an asynchronous thread to distribute the asynchronous cache task to a corresponding task queue; and caching the service data to be cached into a service cache library according to the task queue.
In one embodiment, the apparatus further includes a cache cleaning module, configured to determine, according to the cache state information and the cache policy, to-be-cleaned service data in the service cache library through a cache scheduling model; and calling the asynchronous task framework to generate an asynchronous cache cleaning task of the service data to be cleaned, and cleaning the service data to be cleaned according to the asynchronous cache cleaning task.
In one embodiment, the apparatus further includes a data query module, configured to receive a data acquisition request sent by a user terminal, where the data acquisition request carries a service data identifier; searching matched service data from a service data cache library according to the service data identifier; and sending the service data to the user terminal.
In one embodiment, the data query module is further configured to, if service data matching the query request is not queried in the service data cache library, obtain the matching service data from the service database according to the service data identifier; and calling a cache scheduling model to schedule and cache the service data into a service cache library, and sending the service data in the service cache library to the user terminal.
For specific limitations of the hierarchical service data storage device, reference may be made to the above limitations of the hierarchical service data storage method, which are not described herein again. The respective modules in the hierarchical service data storage apparatus may be wholly or partially implemented by software, hardware, and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 8. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium, and may include a service cache library. The database of the computer device is used for storing data such as a service database and service data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement the steps of the hierarchical service data storage method provided in any one of the embodiments of the present application.
Those skilled in the art will appreciate that the architecture shown in fig. 8 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the hierarchical traffic data storage method provided in any one of the embodiments of the present application.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (13)
1. A hierarchical traffic data storage method, the method comprising:
acquiring service data to be written, wherein the service data to be written comprises attribute information;
determining the hierarchy attribute and the associated field information of the service data to be written according to the attribute information;
writing the service data into a hierarchical structure table in a service database according to the hierarchical attribute and the associated field information;
calling a cache scheduling model to perform cache decision analysis on the service data to obtain a corresponding cache strategy;
and determining the service data to be cached in the service database according to the caching strategy, and generating asynchronous caching tasks for the service data to be cached, scheduling and caching the asynchronous caching tasks into a service caching database.
2. The method of claim 1, wherein before the business data is written to a hierarchically structured table in a business database, the method further comprises:
determining corresponding key fields and associated fields according to the service types of the service data;
adding an array structure corresponding to the associated field to the tree-shaped hierarchical structure of the service type;
and constructing a service data structure corresponding to the service type and a corresponding hierarchical structure table according to the hierarchical relationship according to the tree hierarchical structure added with the array structure.
3. The method according to claim 1, wherein the attribute information includes a service type, and the determining the hierarchy attribute and the associated field information of the service data to be written according to the attribute information includes:
determining the associated field of the service data to be written according to the service type;
performing hierarchy analysis on the service data to be written according to the attribute information to obtain hierarchy attributes and hierarchy relations of the service data to be written;
and determining the associated field information of the associated field according to the hierarchical attribute and the hierarchical relation.
4. The method of claim 3, wherein the writing the service data into a hierarchy table in a service database according to the hierarchy attribute and associated field information comprises:
determining a hierarchical path of the service data to be written according to the hierarchical attribute and the hierarchical relationship;
determining the position of a hierarchical structure in a service database according to the hierarchical relation of the service data to be written;
and writing the service data into a hierarchical structure table of the service database according to the hierarchical path.
5. The method of claim 1, further comprising:
acquiring update service data, wherein the update service data comprises attribute information;
determining the hierarchy attribute and the associated attribute information of the updated service data according to the attribute information;
and correcting the associated field information of the corresponding service data in the service database according to the hierarchy attribute and the associated attribute information to obtain updated service data.
6. The method of claim 1, wherein invoking the cache scheduling model to perform cache decision analysis on the service data to obtain a corresponding cache policy comprises:
calling a cache scheduling model, and monitoring service data in a service database and a service cache library through the cache scheduling model to obtain service state information and cache state information;
determining the weight and the access frequency of the service data according to the service state information and the cache state information;
and deciding a caching strategy of the service data according to the weight and the access frequency.
7. The method according to claim 1, wherein the generating asynchronous cache task scheduling cache of the service data to be cached into a service cache library comprises:
obtaining a hierarchy path of the service data to be cached, and calling an asynchronous task frame to generate an asynchronous caching task of the service data to be cached according to the hierarchy path;
calling an asynchronous thread to distribute the asynchronous cache task to a corresponding task queue;
and caching the service data to be cached into a service cache library according to the task queue.
8. The method of claim 6, further comprising:
determining the service data to be cleaned in the service cache library according to the cache state information and the cache strategy through the cache scheduling model;
and calling an asynchronous task frame to generate an asynchronous cache cleaning task of the service data to be cleaned, and cleaning the service data to be cleaned according to the asynchronous cache cleaning task.
9. The method according to any one of claims 1 to 8, further comprising:
receiving a data acquisition request sent by a user terminal, wherein the data acquisition request carries a service data identifier;
searching matched service data from a service data cache library according to the service data identifier;
and sending the service data to the user terminal.
10. The method of claim 9, further comprising:
if the service data matched with the query request is not queried in the service data cache library, acquiring the matched service data from the service database according to the service data identifier;
and calling the cache scheduling model to schedule and cache the service data into the service cache library, and sending the service data in the service cache library to the user terminal.
11. A hierarchical business data storage apparatus, the apparatus comprising:
the data acquisition module is used for acquiring service data to be written, and the service data to be written comprises attribute information;
the data storage module is used for determining the hierarchy attribute and the associated field information of the service data to be written according to the attribute information; writing the service data into a hierarchical structure table in a service database according to the hierarchical attribute and the associated field information;
the scheduling decision module is used for calling a cache scheduling model to perform cache decision analysis on the service data to obtain a corresponding cache strategy;
and the data caching module is used for determining the service data to be cached in the service database according to the caching strategy and generating asynchronous caching tasks for the service data to be cached to be scheduled and cached in the service caching database.
12. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor realizes the steps of the method of any one of claims 1 to 10 when executing the computer program.
13. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 10.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111708778A (en) * | 2020-06-09 | 2020-09-25 | 樊馨 | Big data management method and system |
| CN111782148A (en) * | 2020-06-30 | 2020-10-16 | 中国工商银行股份有限公司 | Data storage control method and device, electronic equipment and storage medium |
| CN112433792A (en) * | 2020-11-12 | 2021-03-02 | 金蝶软件（中国）有限公司 | Interface loading method and device, computer equipment and storage medium |
| CN112579833A (en) * | 2020-12-14 | 2021-03-30 | 北京宝兰德软件股份有限公司 | Service association relation obtaining method and device based on user operation data |
| CN113420050A (en) * | 2021-06-28 | 2021-09-21 | 平安普惠企业管理有限公司 | Data query management method and device, computer equipment and readable storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103595776A (en) * | 2013-11-05 | 2014-02-19 | 福建网龙计算机网络信息技术有限公司 | Distributed type caching method and system |
| CN109299037A (en) * | 2018-08-16 | 2019-02-01 | 北京炎黄盈动科技发展有限责任公司 | Document handling method and device |
| CN109614347A (en) * | 2018-10-22 | 2019-04-12 | 中国平安人寿保险股份有限公司 | Processing method, device, storage medium and the server of multi-level buffer data |
| CN109637602A (en) * | 2018-11-23 | 2019-04-16 | 金色熊猫有限公司 | Medical data storage and querying method, device, storage medium and electronic equipment |
-
2019
- 2019-12-10 CN CN201911257875.9A patent/CN111104406A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103595776A (en) * | 2013-11-05 | 2014-02-19 | 福建网龙计算机网络信息技术有限公司 | Distributed type caching method and system |
| CN109299037A (en) * | 2018-08-16 | 2019-02-01 | 北京炎黄盈动科技发展有限责任公司 | Document handling method and device |
| CN109614347A (en) * | 2018-10-22 | 2019-04-12 | 中国平安人寿保险股份有限公司 | Processing method, device, storage medium and the server of multi-level buffer data |
| CN109637602A (en) * | 2018-11-23 | 2019-04-16 | 金色熊猫有限公司 | Medical data storage and querying method, device, storage medium and electronic equipment |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111708778A (en) * | 2020-06-09 | 2020-09-25 | 樊馨 | Big data management method and system |
| CN111708778B (en) * | 2020-06-09 | 2021-06-29 | 黄克颖 | Big data management method and system |
| CN111782148A (en) * | 2020-06-30 | 2020-10-16 | 中国工商银行股份有限公司 | Data storage control method and device, electronic equipment and storage medium |
| CN111782148B (en) * | 2020-06-30 | 2023-09-05 | 中国工商银行股份有限公司 | Data storage control method and device, electronic equipment and storage medium |
| CN112433792A (en) * | 2020-11-12 | 2021-03-02 | 金蝶软件（中国）有限公司 | Interface loading method and device, computer equipment and storage medium |
| CN112579833A (en) * | 2020-12-14 | 2021-03-30 | 北京宝兰德软件股份有限公司 | Service association relation obtaining method and device based on user operation data |
| CN112579833B (en) * | 2020-12-14 | 2024-02-23 | 北京宝兰德软件股份有限公司 | Service association relation acquisition method and device based on user operation data |
| CN113420050A (en) * | 2021-06-28 | 2021-09-21 | 平安普惠企业管理有限公司 | Data query management method and device, computer equipment and readable storage medium |
| CN113420050B (en) * | 2021-06-28 | 2023-08-25 | 深圳华科讯通科技有限公司 | Data query management method, device, computer equipment and readable storage medium |
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