Search data synchronization method and apparatus, device, medium, and product

Abstract

The application discloses a search data synchronization method and device, equipment, medium and product, the method comprises the following steps: in response to the search data increment event acting on the business database, obtaining a plurality of incremental search data, and determining the independent station of the e-commerce corresponding to the incremental search data; counting the incremental data flow of the independent station of the e-commerce, verifying whether the incremental data flow meets the data flow limiting rule, if not, pushing the incremental search data to the data version verifier; when the incremental data flow meets the data flow limiting rule, the incremental search data is pushed to the flow limiting pusher, so as to drive the flow limiting pusher to limit the speed of pushing the incremental search data to the data version verifier based on the speed limiting push rule; driving the data version verifier to verify the data version of each incremental search data, and pushing the incremental search data with the later data version to the e-commerce search service. The application can limit the transmission speed of concurrent search data to improve the stability of data synchronization service.

Description

Technical Field

[0001] This application relates to the field of online e-commerce, and in particular to a method for synchronizing search data. It also relates to the corresponding apparatus, equipment, non-volatile storage medium, and computer program products. Background Technology

[0002] Existing online e-commerce independent website platforms provide search services to the independent e-commerce websites on their platforms. This allows buyers to search for relevant products or order information on these independent e-commerce websites. Moreover, the search service provided by the online e-commerce independent website platform to most of the independent e-commerce websites on the platform is a shared search service. That is, all independent e-commerce websites on the platform share the same search service maintained by the same server cluster, which facilitates the platform's maintenance of the search service.

[0003] When any e-commerce independent website lists a new product or generates a new order, it stores the product data or order data in the corresponding business database. This data is then synchronized to the search service by the platform, allowing buyers to search for newly listed products or make online purchases. However, when an e-commerce independent website lists a large number of products or generates a large number of orders, the massive concurrent data can put a heavy burden on the data synchronization service, potentially causing it to crash. This would prevent buyers from searching for newly listed products or their order information through the search system. Furthermore, since the search service is a shared service, a crash in the data synchronization service would also affect other e-commerce independent websites on the platform.

[0004] In view of the problems existing in the data synchronization service that operates on the search service plane in handling concurrent data, the applicant has made corresponding explorations in order to solve these problems. Summary of the Invention

[0005] The purpose of this application is to provide a search data synchronization method to meet user needs, and also relates to the corresponding apparatus, device, non-volatile storage medium and computer program product.

[0006] To achieve the objectives of this application, the following technical solution is adopted:

[0007] A search data synchronization method proposed for the purposes of this application includes the following steps:

[0008] In response to incremental search data events acting on the business database, obtain multiple incremental search data corresponding to the incremental search data event, and determine the e-commerce independent websites corresponding to these incremental search data.

[0009] The incremental data traffic of the e-commerce independent website is counted, and it is verified whether the incremental data traffic meets the preset data throttling rules. If it does not meet the rules, the incremental search data is pushed to the data version verifier.

[0010] When the incremental data traffic meets the data rate limiting rule, each incremental search data is pushed to the rate limiting pusher to drive the rate limiting pusher to push each incremental search data to the data version verifier based on the rate limiting push rule.

[0011] The data version validator is driven to verify the data version of each incremental search data, and the incremental search data with the later data version is pushed to the e-commerce search service.

[0012] In a further embodiment, the step of responding to a search data increment event acting on the business database, obtaining multiple increment search data corresponding to the search data increment event, and determining the e-commerce independent website corresponding to these increment search data includes the following steps:

[0013] In response to the incremental search data event, obtain the data operation log corresponding to the incremental search data event;

[0014] Based on the multiple business data identifiers contained in the data operation log, the incremental search data corresponding to these business data identifiers is obtained from the business database;

[0015] Identify the e-commerce independent website corresponding to the data operation log, and push each incremental search data to the queue of data to be consumed.

[0016] In a further embodiment, the step of counting the incremental data traffic of the e-commerce independent website and verifying whether the incremental data traffic meets the preset data throttling rules, or pushing each incremental search data to the throttling pusher when the incremental data traffic meets the data throttling rules, includes the following steps:

[0017] Within a preset statistical time window, count the number of incremental search data corresponding to the current e-commerce independent website in the queue of data to be consumed;

[0018] Determine whether the number of incremental search data exceeds the preset flow limit data volume. If it does not exceed the limit, push the incremental search data corresponding to the current e-commerce independent site in the pending consumption data queue to the data version verifier.

[0019] When the amount of incremental search data exceeds the preset limit data amount, the incremental search data corresponding to the current e-commerce independent website in the pending consumption data queue is pushed to the limit pusher within the preset limit time window.

[0020] In a further embodiment, the step of driving the rate-limiting pusher to push each incremental search data to the data version verifier at a limited rate based on the rate-limiting push rules includes the following steps:

[0021] Store the latest incremental search data in the first position of the rate-limited data queue;

[0022] The incremental search data at the end of the rate-limited data queue is pushed to the data version verifier;

[0023] Similarly, the storage and push of incremental search data applied to the rate-limited data queue are processed, and the push speed of incremental search data is controlled according to the preset data push speed.

[0024] In a further embodiment, the step of driving the data version validator to verify the data version of each incremental search data and pushing the incremental search data with a later data version to the e-commerce search service includes the following steps:

[0025] Determine the data storage timestamp and data feature information of the latest acquired incremental search data, and store the data storage timestamp, data feature information and the incremental search data in the version verification cache space. The data feature information includes the e-commerce independent website identifier and data attribute identifier.

[0026] Query out multiple target incremental search data with the same data characteristics in the version verification cache space, and compare the data storage timestamps of these target incremental search data.

[0027] The target incremental search data with a later data storage timestamp is pushed to the e-commerce search service, and other target incremental search data is removed from the version verification cache space.

[0028] In a further embodiment, the method includes the following post-step:

[0029] In response to the incremental search data event, obtain the data operation log corresponding to the incremental search data event;

[0030] Based on the multiple business data identifiers contained in the data operation log, the incremental search data corresponding to these business data identifiers is obtained from the business database;

[0031] The e-commerce independent site corresponding to the data operation log is determined. When the e-commerce independent site is a traffic-limited e-commerce independent site, the incremental search data is pushed to the traffic-limiting pusher.

[0032] A search data synchronization device proposed for the purposes of this application includes:

[0033] The incremental data acquisition module is used to respond to incremental search data events that act on the business database, acquire multiple incremental search data corresponding to the incremental search data event, and determine the e-commerce independent websites corresponding to these incremental search data.

[0034] The data traffic verification module is used to count the incremental data traffic of the e-commerce independent website and verify whether the incremental data traffic meets the preset data traffic limiting rules. If it does not meet the rules, the incremental search data is pushed to the data version verifier.

[0035] The data rate limiting push module is used to push each incremental search data to the rate limiting pusher when the incremental data traffic meets the data rate limiting rules, so as to drive the rate limiting pusher to push each incremental search data to the data version verifier based on the rate limiting push rules.

[0036] The data version verification module is used to drive the data version verifier to verify the data version of each incremental search data and push the incremental search data with the later data version to the e-commerce search service.

[0037] In a further embodiment, the incremental data acquisition module includes:

[0038] The operation log acquisition submodule is used to respond to the search data increment event and acquire the data operation log corresponding to the search data increment event;

[0039] The business data acquisition submodule is used to acquire incremental search data corresponding to multiple business data identifiers contained in the data operation log from the business database.

[0040] The incremental data storage submodule is used to determine the e-commerce independent website corresponding to the data operation log and push each incremental search data to the data queue to be consumed.

[0041] In a further embodiment, the data traffic verification module includes:

[0042] The data quantity statistics submodule is used to count the number of incremental search data corresponding to the current e-commerce independent site in the pending consumption data queue within a preset statistical time window;

[0043] The data quantity verification submodule is used to determine whether the quantity of incremental search data exceeds the preset flow limit data quantity. If it does not exceed the limit, the incremental search data corresponding to the current e-commerce independent site in the data queue to be consumed is pushed to the data version verifier.

[0044] The rate-limited data push submodule is used to push the incremental search data corresponding to the current e-commerce independent website in the pending consumption data queue to the rate-limited pusher within a preset rate-limited time window when the number of incremental search data exceeds the preset rate-limited data volume.

[0045] In a further embodiment, the data rate limiting push module includes:

[0046] The data storage submodule is used to store the latest incremental search data in the first storage position of the rate-limited data queue;

[0047] The data push submodule is used to push the incremental search data at the end of the rate-limited data queue to the data version verifier.

[0048] The push speed control submodule is used to process the storage and push of incremental search data applied to the rate-limited data queue, and to control the push speed of incremental search data according to the preset data push speed.

[0049] In a further embodiment, the data version verification module includes:

[0050] The mapping data cache submodule is used to determine the data storage timestamp and data feature information of the latest acquired incremental search data, and to store the data storage timestamp, data feature information and the incremental search data in the version verification cache space. The data feature information includes the e-commerce independent website identifier and data attribute identifier.

[0051] The storage time comparison submodule is used to query multiple target incremental search data with the same data feature information in the version verification cache space, and compare the data storage timestamps of these target incremental search data.

[0052] The incremental data push submodule is used to push target incremental search data with later data storage timestamps to the e-commerce search service, and remove other target incremental search data from the version verification cache space.

[0053] To address the aforementioned technical problems, this application also provides a computer device, including a memory and a processor. The memory stores computer-readable instructions, which, when executed by the processor, cause the processor to perform the steps of the aforementioned search data synchronization method.

[0054] To address the aforementioned technical problems, this application also provides a storage medium storing computer-readable instructions, which, when executed by one or more processors, cause the one or more processors to perform the steps of the search data synchronization method described above.

[0055] To address the aforementioned technical problems, this application also provides a computer program product, including a computer program and computer instructions. When the computer program and computer instructions are executed by a processor, the processor performs the steps of the aforementioned search data synchronization method.

[0056] Compared with existing technologies, the advantages of this application are as follows:

[0057] This application can limit the data flow of e-commerce independent websites with massive incremental search data to prevent the data synchronization service from being unable to handle the high volume of incremental search data, causing system crashes and preventing newly added business data from being pushed to the e-commerce search service. By responding to incremental events, the application obtains the latest added business data from the business database as incremental search data and performs data traffic statistics on the e-commerce independent websites to which this data belongs to determine whether the incremental data for that e-commerce independent website is excessive. If so, the application treats that e-commerce independent website as a rate-limited e-commerce independent website and applies rate-limited push processing to its incremental search data. Therefore, this application can limit the push of incremental data from any e-commerce independent website on the platform to the e-commerce search service without globally pushing incremental data from all e-commerce independent websites on the platform. This prevents the impact on the data push of other e-commerce independent websites with normal incremental data traffic, ensuring that buyers on other e-commerce independent websites with normal traffic can quickly use the e-commerce search service to search for newly listed products or their newly generated orders.

[0058] Secondly, this application will perform data version verification on incremental search data to filter out the latest version of data for push. By using a data version verifier, the latest incremental search data of the same data type from the same e-commerce independent website will be pushed to the e-commerce search service to ensure that the data obtained by the e-commerce search service is timely and that the search results obtained by buyers through the e-commerce search service are the latest products or orders. Attached Figure Description

[0059] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0060] Figure 1 A typical network deployment architecture diagram related to the implementation of the technical solution of this application;

[0061] Figure 2 This is a flowchart illustrating a typical embodiment of the search data synchronization method of this application;

[0062] Figure 3 This is a flowchart illustrating the specific implementation method for obtaining incremental search data corresponding to incremental search data events in this application;

[0063] Figure 4 This is a flowchart illustrating the specific implementation method for verifying whether the incremental data traffic of an e-commerce independent website meets the data flow limiting rules in this application.

[0064] Figure 5 This is a flowchart illustrating the specific implementation method of the rate-limiting pusher for pushing incremental search data based on rate-limiting push rules in this application.

[0065] Figure 6 This is a flowchart illustrating a specific implementation of the data version validator for verifying the data version of incremental search data in this application.

[0066] Figure 7 This is a flowchart illustrating the specific implementation method for subsequent traffic limiting processing of incremental search data from e-commerce independent websites in this application.

[0067] Figure 8 This is a schematic block diagram of a typical embodiment of the search data synchronization device of this application;

[0068] Figure 9 This is a basic structural block diagram of a computer device according to an embodiment of this application. Detailed Implementation

[0069] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0070] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this application means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or wireless coupling. The term “and / or” as used herein includes all or any units and all combinations of one or more associated listed items.

[0071] Those skilled in the art will understand that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0072] Those skilled in the art will understand that the terms "client," "terminal," and "terminal device" as used herein include both devices that receive wireless signals, devices that only possess wireless signal receiver capabilities without transmission capabilities, and devices with receiving and transmitting hardware, devices that have receiving and transmitting hardware capable of bidirectional communication over a bidirectional communication link. Such devices may include: cellular or other communication devices such as personal computers or tablets, having single-line displays, multi-line displays, or cellular or other communication devices without multi-line displays; PCS (Personal Communications Service) that can combine voice, data processing, fax, and / or data communication capabilities; PDA (Personal Digital Assistant) that may include a radio frequency receiver, pager, internet / intranet access, web browser, notepad, calendar, and / or GPS (Global Positioning System) receiver; and traditional laptop and / or handheld computers or other devices that have and / or include radio frequency receivers. As used herein, "client," "terminal," and "terminal device" can be portable, transportable, installed in a means of transportation (air, sea, and / or land), or suitable and / or configured to operate locally and / or in a distributed manner, operating in any other location on Earth and / or in space. "Client," "terminal," and "terminal device" as used herein can also be a communication terminal, an internet access terminal, or a music / video playback terminal, such as a PDA, a MID (Mobile Internet Device), and / or a mobile phone with music / video playback capabilities, or a smart TV, set-top box, etc.

[0073] The hardware referred to by the names "server," "client," and "work node" in this application is essentially an electronic device with the equivalent capabilities of a personal computer. It is a hardware device with the necessary components revealed by the von Neumann architecture, such as a central processing unit (including an arithmetic logic unit and a control unit), memory, input devices, and output devices. The computer program is stored in its memory, and the central processing unit loads the program stored in the secondary storage into the main memory to run it, executes the instructions in the program, and interacts with the input and output devices to complete specific functions.

[0074] It should be noted that the concept of "server" used in this application can also be extended to the case of server clusters. Based on the network deployment principles understood by those skilled in the art, the servers should be logically divided. Physically, these servers can be independent of each other but accessible through interfaces, or they can be integrated into a single physical computer or a computer cluster. Those skilled in the art should understand this flexibility and should not use it to constrain the implementation of the network deployment method in this application.

[0075] Please see Figure 1 The hardware infrastructure required for implementing the technical solutions of this application can be deployed according to the architecture shown in the figure. The server 80 mentioned in this application is deployed in the cloud and acts as an online server. It can further connect to relevant data servers and other servers providing related support, thereby forming a logically related service cluster to provide services to relevant terminal devices such as the smartphone 81 and personal computer 82 shown in the figure, or third-party servers (not shown). Both the smartphone and personal computer can access the Internet through known network access methods and establish a data communication link with the cloud server 80 to run terminal applications related to the services provided by the server.

[0076] For servers, the application is usually built as a service process, with corresponding program interfaces exposed for remote calls by applications running on various terminal devices. The relevant technical solutions in this application that are suitable for running on servers can be implemented in servers in this way.

[0077] The application mentioned refers to an application running on a server or terminal device. This application implements the relevant technical solutions of this application in a programmed manner. Its program code can be stored in a non-volatile storage medium that can be recognized by a computer in the form of computer-executable instructions, and is loaded into memory by the central processing unit for execution. The relevant device of this application is constructed by the operation of the application on the computer.

[0078] Those skilled in the art will understand that although the various methods in this application are described based on the same concept and thus present commonality among them, they can be performed independently unless otherwise specified. Similarly, the various embodiments disclosed in this application are all based on the same inventive concept; therefore, concepts expressed in the same way, as well as concepts that are appropriately changed for convenience but are expressed differently, should be understood equivalently.

[0079] Please see Figure 2 The present application discloses a search data synchronization method, which, in a typical embodiment, includes the following steps:

[0080] Step S11: In response to the incremental search data event acting on the business database, obtain multiple incremental search data corresponding to the incremental search data event, and determine the e-commerce independent websites corresponding to these incremental search data:

[0081] The aforementioned independent e-commerce websites differ from e-commerce shops within traditional online e-commerce platforms. Independent e-commerce websites offer independent online e-commerce services and can be viewed as a form of traditional e-commerce platform. The buyers of an independent e-commerce website are its own user base, unlike the buyers of individual e-commerce shops on a traditional platform who are the platform's users. However, the independent e-commerce platform provides corresponding e-commerce functions to its member websites, such as search functionality. Each independent website can use this search function to provide its own buyer base with e-commerce search services for products or orders within the independent website.

[0082] The business database is used to store the business data of each e-commerce independent website in the platform, such as product data and order data. The business database maps and stores each business data with a business data identifier that represents the corresponding e-commerce independent website and business data type. This allows the server to query the business data corresponding to the business data identifier from the business database based on the business data identifier, and then transmit the business data as the incremental search data to the e-commerce search service.

[0083] The aforementioned incremental search data event refers to an event triggered by the storage of new business data in the business database. For e-commerce independent website platforms, when any e-commerce independent website on the platform lists a new product, the server stores the product data of the newly listed product in the business database, which will trigger the incremental search data event acting on these product data. Alternatively, when one or more buyer users make online purchases on any e-commerce independent website, corresponding order data will be generated. This order data will be stored by the server in the business database, triggering the incremental search data event acting on these order data.

[0084] The incremental search data event has a corresponding data operation log. This data operation log records the business data identifiers corresponding to the newly stored business data in the business database, and also records the e-commerce independent websites to which these business data belong. After the server responds to the incremental search data event, it will obtain the data operation log corresponding to the incremental search data event, and query the business data corresponding to these business data identifiers from the business database based on the multiple business data identifiers contained in the data operation log as the incremental search data, thereby determining the e-commerce independent website corresponding to the data operation log.

[0085] The incremental search data refers to business data that needs to be synchronously pushed to the e-commerce search service. By pushing the newly added business data in the business database to the e-commerce search service, buyers can use the e-commerce search service to query newly listed products on a certain e-commerce independent website or orders generated by buyers shopping on a certain e-commerce platform.

[0086] Step S12: Count the incremental data traffic of the e-commerce independent website, and verify whether the incremental data traffic meets the preset data throttling rules. If it does not meet the rules, push each incremental search data to the data version validator.

[0087] After the server obtains the incremental search data corresponding to the incremental search data event and determines the e-commerce independent website corresponding to the incremental search data, it will count the incremental data traffic of the e-commerce independent website. The incremental data traffic refers to the amount of incremental search data that needs to be pushed to the e-commerce search service for the e-commerce independent website per unit time. For the incremental search data of e-commerce independent websites with large incremental data traffic, the server needs to limit the push speed of these incremental search data to prevent the massive concurrent data transmission from affecting the stability of the data synchronization service performed by the server.

[0088] After the server obtains the incremental search data of any e-commerce independent website, these incremental search data are stored in the pending consumption data queue to form a data stream, which facilitates the server to count the incremental data traffic of each e-commerce independent website. Specifically, the server counts the number of incremental search data corresponding to each e-commerce independent website in the pending consumption data queue within a preset statistical time window, and determines whether the number of incremental search data exceeds the preset traffic-limiting data volume. If it does not exceed the limit, the server pushes the incremental search data corresponding to the current e-commerce independent website in the pending consumption data queue to the data version validator. If it exceeds the limit, the server pushes the incremental search data corresponding to the current e-commerce independent website in the pending consumption data queue to the traffic-limiting pusher within the preset traffic-limiting time window.

[0089] The data rate limiting rules pre-set a corresponding data rate limiting amount so that the server can verify whether the incremental data traffic of each e-commerce independent website exceeds the data rate limiting amount. For e-commerce independent websites whose incremental data traffic exceeds the data rate limiting amount, it will be determined that they meet the data rate limiting rules. For e-commerce independent websites whose incremental data traffic does not exceed the data rate limiting amount, it will be determined that they do not meet the data rate limiting rules.

[0090] In one embodiment, an e-commerce independent website whose incremental data traffic is determined to meet the data throttling rules will be assigned a throttling identifier to characterize it as a throttling independent website. After the server obtains the incremental search data of the e-commerce independent website with the throttling identifier, it will directly push the incremental search data to the throttling pusher without having to count the incremental data traffic of the e-commerce independent website for throttling verification.

[0091] The data version validator is used to verify the data version of the search incremental data to prevent the latest search incremental data stored in the business database from being overwritten by the earlier stored search incremental data, that is, to filter the latest search incremental data for the e-commerce search service; please refer to the following steps for the specific implementation of the data version validator, which will not be described in detail here.

[0092] Step S13: When the incremental data traffic meets the data rate limiting rule, each incremental search data is pushed to the rate limiting pusher, so that the rate limiting pusher pushes each incremental search data to the data version verifier based on the rate limiting push rule.

[0093] If the incremental data traffic of the e-commerce independent website to which the currently acquired incremental search data belongs meets the data rate limiting rules, the server will push the incremental search data to the rate limiting pusher to control the push speed of these incremental search data.

[0094] The rate-limiting pusher pushes the received incremental search data at a rate-limited speed based on the rate-limiting push rules. The rate-limiting push rules include corresponding data push speeds to control the push speed of each incremental search data. The rate-limiting pusher queues and pushes the incremental search data according to the rate-limiting push rules. Specifically, after the server obtains the latest received incremental search data, it stores the incremental search data at the beginning of the rate-limiting data queue and pushes the incremental search data in order based on the first-in-first-out rule of the queue. Correspondingly, the rate-limiting pusher pushes the incremental search data stored at the end of the rate-limiting data queue to the data version verifier. This process continues, with the rate-limiting pusher storing each received incremental search data in the rate-limiting data queue and pushing the data stored in the queue. The push speed of each incremental search data in the rate-limiting data queue to the data version verifier is controlled according to the preset data push speed in the rate-limiting push rules.

[0095] Step S14: Drive the data version validator to verify the data version of each incremental search data, and push the incremental search data with the later data version to the e-commerce search service:

[0096] The data version verifier will perform data version verification on each incremental search data it receives. After receiving the incremental search data, the search data version verifier will obtain the data storage timestamp and data feature information of the incremental search data. The data storage timestamp refers to the storage time of the incremental search data stored in the business database. The data feature information includes an e-commerce independent website identifier and a data attribute identifier. The e-commerce independent website identifier is used to represent the e-commerce independent website to which the incremental search data belongs. The data attribute identifier is used to represent the data attributes of the incremental search data. For example, when the incremental search data is order data, the data attribute identifier will represent the order number or other unique identifier that represents the corresponding order. When the incremental search data is product data, the data attribute identifier will represent the product number or other unique identifier that represents the corresponding product.

[0097] The data version validator acquires the data storage timestamp and data feature information of the incremental search data, and stores the incremental search data, the data storage timestamp, and data feature information as incremental mapping relationship data in the version verification cache space. The version verification cache space caches multiple incremental mapping relationship data, so that the data version validator can perform version verification on these incremental search data according to the data storage timestamp and data feature information corresponding to each incremental search data mapping in the version verification cache space. Specifically, the data version validator queries multiple target incremental search data with the same data feature information in the version verification cache space, that is, incremental search data from the same e-commerce independent website with the same data attribute identifier, and compares the data storage timestamps of these target incremental search data. The target incremental search data with the later data storage timestamp is determined as the incremental search data with the later data version and pushed to the e-commerce search service, while other target incremental search data with the earlier data version is removed from the version verification cache space.

[0098] The e-commerce search service refers to the product or order search service provided by the online e-commerce independent website platform to each independent e-commerce website under the platform. This search service is generally a shared search service. Buyers on independent e-commerce websites can use the e-commerce search service to search for products available on the independent e-commerce website or the corresponding orders they have placed online on the independent e-commerce website. For example, for an e-commerce search service that provides product search, after a buyer enters the corresponding search text through the search function of their independent website, a search request containing the search text can be generated and pushed to the e-commerce search service. The e-commerce search service obtains the business data of one or more products corresponding to the search text as search results and pushes them to the buyer's client so that the buyer's client can receive the business data and output the corresponding product objects to the graphical user interface for display, thereby allowing the buyer on the client to browse these product objects and make online purchases.

[0099] As can be seen from the typical embodiments of this method, this method can limit the data flow of e-commerce independent websites with massive incremental search data, preventing the data synchronization service from being unable to handle the high volume of incremental search data, which could lead to system crashes and prevent newly added business data from being pushed to the e-commerce search service. By responding to incremental events, the method obtains the latest added business data in the business database as incremental search data and performs data traffic statistics on the e-commerce independent websites to which this data belongs to determine whether the incremental data of the e-commerce independent website exceeds the limit. If so, the e-commerce independent website should be treated as a rate-limited e-commerce independent website and its incremental search data should be pushed with data flow limited. Therefore, this method can limit the incremental data of any e-commerce independent website on the platform to push to the e-commerce search service without globally pushing the incremental data of all e-commerce independent websites on the platform. This prevents the impact on the data push of other e-commerce independent websites with normal incremental data traffic, ensuring that buyers of other e-commerce independent websites with normal traffic can quickly use the e-commerce search service to search for newly listed products or their newly generated orders.

[0100] Secondly, this method will perform data version verification on incremental search data to filter out the latest version of data for push. Through the data version verifier, the latest incremental search data of the same data type from the same e-commerce independent website will be pushed to the e-commerce search service, ensuring that the data obtained by the e-commerce search service is timely and that the search results obtained by buyers through the e-commerce search service are the latest products or orders.

[0101] The above typical embodiments and their variations fully disclose the implementation scheme of the search data synchronization method of this application. However, various variations of the method can still be derived by changing and expanding some technical means. Other embodiments are briefly described below:

[0102] In one embodiment, please refer to Figure 3 The steps involved in responding to incremental search data events acting on the business database, acquiring multiple incremental search data corresponding to the incremental search data event, and determining the e-commerce independent websites corresponding to these incremental search data include the following:

[0103] Step S111: In response to the search data increment event, obtain the data operation log corresponding to the search data increment event:

[0104] The data operation log refers to the log that records incremental business data stored in the business database. The data operation log stores the business data identifiers of each incremental business data stored in the business database, and the data operation log has an independent site identifier that represents the e-commerce independent site to which it belongs.

[0105] Step S112: Based on the multiple business data identifiers contained in the data operation log, retrieve the incremental search data corresponding to these business data identifiers from the business database:

[0106] The business data identifier indicates the storage location of the corresponding business data in the business database. The server queries the business data in the business database that corresponds to these business data identifiers and uses these business data as the incremental search data for data synchronization processing.

[0107] Step S113: Determine the e-commerce independent website corresponding to the data operation log, and push each incremental search data to the pending consumption data queue:

[0108] The queue of data to be consumed is used to store the incremental search data obtained by the server from the business database. The server will use the queue of data to be consumed to count the incremental data traffic of each e-commerce independent site, and push each incremental search data to the rate limiting pusher or data version verifier in the form of a data stream through the queue of data to be consumed.

[0109] In this embodiment, the data operation log records the business data newly stored in the business database. This data operation log is used to obtain new incremental data as incremental search data for data synchronization. The incremental search data is pushed in a data stream manner through the data queue to be consumed, so as to push each incremental search data in an orderly manner and prevent data congestion caused by disordered push.

[0110] In one embodiment, please refer to Figure 4 The steps of counting the incremental data traffic of the e-commerce independent website, verifying whether the incremental data traffic meets the preset data throttling rules, or pushing each incremental search data to the throttling pusher when the incremental data traffic meets the data throttling rules, include the following steps:

[0111] Step S121: Within a preset statistical time window, count the number of incremental search data corresponding to the current e-commerce independent website in the pending consumption data queue.

[0112] The statistical time window is generally set within a time range of 10-15 seconds, or within a time range of 1-2 minutes. Those skilled in the art can flexibly design the time range of the statistical time window, which will not be elaborated here.

[0113] After the server obtains the incremental search data from any e-commerce independent website, the incremental search data is stored in the queue of data to be consumed to form a data stream so that the server can count the number of incremental search data from each e-commerce independent website.

[0114] Step S122: Determine whether the amount of incremental search data exceeds the preset data limit. If it does not exceed the limit, push the incremental search data corresponding to the current e-commerce independent website in the data queue to be consumed to the data version verifier.

[0115] After the server counts the incremental search data of any e-commerce independent website, it will determine whether the incremental search data exceeds the preset traffic limit. The traffic limit is designed based on the statistical time window. Different time units will have corresponding traffic limit data. For example, when the statistical time window is generally set within a time range of 10 seconds, the traffic limit is generally set within the range of 500 to 1000 data.

[0116] For e-commerce independent websites whose incremental search data volume does not exceed the traffic-limited data volume, the incremental search data of these e-commerce independent websites will be directly pushed to the data version verifier, without needing to be pushed to the traffic-limiting pusher to restrict the data push speed.

[0117] Step S123: When the amount of incremental search data exceeds the preset limit data amount, the incremental search data corresponding to the current e-commerce independent website in the pending consumption data queue is pushed to the limit pusher within the preset limit time window.

[0118] The aforementioned rate limiting time window is generally set within a time range of 5-10 or 20-30 minutes. For e-commerce independent websites whose incremental search data exceeds the rate limiting data volume, these e-commerce independent websites will be pushed to the rate limiting pusher within the rate limiting time window, so that the rate limiting pusher can push the incremental search data of these e-commerce independent websites concurrently at a limited speed.

[0119] In this embodiment, the amount of incremental search data pushed by each e-commerce independent website in the platform is counted in real time. In this way, the incremental search data of e-commerce independent websites with excessive data volume is pushed to the speed limit pusher for speed limit push, so as to prevent the data synchronization service from crashing due to the concurrent data volume push.

[0120] In one embodiment, please refer to Figure 5 The step of driving the rate-limiting pusher to push each incremental search data to the data version verifier at a limited rate based on the rate-limiting push rules includes the following steps:

[0121] Step S131: Store the latest acquired incremental search data at the first storage position of the rate-limited data queue.

[0122] The rate-limited data queue is used to store incremental search data pushed to the data version verifier. The rate-limited data queue pushes the stored incremental search data to the data version verifier in sequence according to the first-in-first-out rule. The rate-limited pusher will determine the reception time of each incremental search data it receives and store the incremental search data with the earliest reception time in the data push queue first.

[0123] Step S132: Push the incremental search data at the end of the rate-limited data queue to the data version validator.

[0124] The rate-limiting pusher pushes incremental search data currently at the end of the rate-limiting data push queue to the data version verifier according to the first-in-first-out rule.

[0125] Step S133, and so on, processes the storage and push of incremental search data applied to the rate-limiting data queue, and controls the push speed of incremental search data according to a preset data push speed:

[0126] The rate-limiting pusher prioritizes dequeuing the incremental search data that was first enqueued in the rate-limiting data queue and pushes it to the data version verifier to form a data stream for pushing each incremental search data to the data version verifier.

[0127] The rate-limiting pusher pushes incremental search data in the rate-limiting data queue at a preset data push speed, which is generally set to 500 to 1000 data points per second. Those skilled in the art can flexibly design the data push speed, which will not be elaborated here.

[0128] In this embodiment, incremental search data from e-commerce independent websites with high concurrency is pushed at a limited rate to prevent high-emission data push from blocking the data communication link and to ensure that the data version verifier can stably process incremental search data. At the same time, data is pushed in a queue to form a data stream, which facilitates the data receiving order of the data version verifier.

[0129] In one embodiment, please refer to Figure 6 The step of driving the data version validator to verify the data version of each incremental search data and pushing the incremental search data with the later data version to the e-commerce search service includes the following steps:

[0130] Step S141: Determine the data storage timestamp and data feature information of the latest acquired incremental search data, and store the data storage timestamp, data feature information, and the incremental search data in the version verification cache space. The data feature information includes the e-commerce independent website identifier and data attribute identifier.

[0131] The data storage timestamp refers to the storage time of the incremental search data stored in the business database. The data feature information includes an e-commerce independent website identifier and a data attribute identifier. The e-commerce independent website identifier is used to represent the e-commerce independent website to which the incremental search data belongs, and the data attribute identifier is used to represent the data attributes of the incremental search data. For example, when the incremental search data is order data, the data attribute identifier will represent the order number or other unique identifier that represents the corresponding order. When the incremental search data is product data, the data attribute identifier will represent the product number or other unique identifier that represents the corresponding product.

[0132] The data version verifier obtains the data storage timestamp and data feature information of the incremental search data, and stores the incremental search data, the data storage timestamp and data feature information as incremental mapping relationship data in the version verification cache space. The version verification cache space caches multiple incremental mapping relationship data, so that the data version verifier can perform version verification on these incremental search data based on the data storage timestamp and data feature information stored in the version verification cache space according to the mapping of each incremental search data.

[0133] Step S142: Query multiple target incremental search data with the same data feature information in the version verification cache space, and compare the data storage timestamps of these target incremental search data.

[0134] The data version validator determines the latest business data stored in the business database among incremental search data with the same data characteristics and information from the same e-commerce independent website and the same data attributes by comparing the data storage timestamps of multiple incremental search data with the same data characteristics in the version verification cache space.

[0135] Step S143: Push the target incremental search data with the later data storage timestamp to the e-commerce search service, and remove other target incremental search data from the version verification cache space:

[0136] The target incremental search data with a later data storage timestamp is the latest business data stored in the business database. This target incremental search data is the incremental search data with the highest data version among the same type of data. The data version validator pushes the latest incremental search data to the e-commerce search service and removes other incremental search data with lower data versions compared to the target incremental search data from the version verification cache space, saving storage space and preventing data chaos.

[0137] In this embodiment, by comparing the data storage timestamps of incremental search data from the same e-commerce independent website and with the same data attributes, the incremental search data with the latest data version is determined and pushed to ensure that the e-commerce search service obtains the latest data and ensures the timeliness of the data.

[0138] In one embodiment, please refer to Figure 7 This method includes the following post-steps:

[0139] Step S15: In response to the search data increment event, obtain the data operation log corresponding to the search data increment event:

[0140] The data operation log refers to the log that records incremental business data stored in the business database. The data operation log stores the business data identifiers of each incremental business data stored in the business database, and the data operation log has an independent site identifier that represents the e-commerce independent site to which it belongs.

[0141] Step S16: Based on the multiple business data identifiers contained in the data operation log, retrieve the incremental search data corresponding to these business data identifiers from the business database:

[0142] The business data identifier indicates the storage location of the corresponding business data in the business database. The server queries the business data in the business database that corresponds to these business data identifiers and uses these business data as the incremental search data for data synchronization processing.

[0143] Step S17: Determine the e-commerce independent website corresponding to the data operation log. When the e-commerce independent website is a rate-limited e-commerce independent website, push each incremental search data to the rate-limiting pusher.

[0144] The e-commerce independent website subject to rate limiting refers to an e-commerce independent website whose incremental data traffic meets the data rate limiting rules. It will be assigned the rate limiting identifier to identify itself as a rate-limited independent website. After the server obtains the incremental search data of the e-commerce independent website with the rate limiting identifier, it will directly push the incremental search data to the rate limiting pusher without having to count the incremental data traffic of the e-commerce independent website for rate limiting verification.

[0145] In this embodiment, e-commerce independent websites whose incremental data traffic meets the data throttling rules will have a throttling identifier indicating that they need to be throttled. Their incremental search data will be directly pushed to the search throttling pusher without the need for secondary incremental data traffic statistics, thereby improving the execution efficiency of data throttling and saving unnecessary computing resources.

[0146] Furthermore, by functionalizing the various steps in the methods disclosed in the above embodiments, a search data synchronization device of this application can be constructed. Following this approach, please refer to... Figure 8 In one typical embodiment, the device includes: an incremental data acquisition module 11, used to respond to an incremental search data event acting on the business database, acquire multiple incremental search data corresponding to the incremental search data event, and determine the e-commerce independent website corresponding to these incremental search data; a data traffic verification module 12, used to count the incremental data traffic of the e-commerce independent website, verify whether the incremental data traffic meets the preset data rate limiting rules, and if not, push each incremental search data to the data version verifier; a data rate limiting push module 13, used to push each incremental search data to the rate limiting pusher when the incremental data traffic meets the data rate limiting rules, so as to drive the rate limiting pusher to push each incremental search data to the data version verifier based on the rate limiting push rules; and a data version verification module 14, used to drive the data version verifier to verify the data version of each incremental search data, and push the incremental search data with the later data version to the e-commerce search service.

[0147] In one embodiment, the incremental data acquisition module 11 includes: an operation log acquisition submodule, used to respond to the incremental search data event and acquire the data operation log corresponding to the incremental search data event; a business data acquisition submodule, used to acquire incremental search data corresponding to multiple business data identifiers contained in the data operation log from the business database; and an incremental data storage submodule, used to determine the e-commerce independent website corresponding to the data operation log and push each incremental search data to the pending consumption data queue.

[0148] In one embodiment, the data traffic verification module 12 includes: a data quantity statistics submodule, used to count the number of incremental search data corresponding to the current e-commerce independent website in the pending consumption data queue within a preset statistical time window; a data quantity verification submodule, used to determine whether the number of incremental search data exceeds a preset traffic-limiting data volume, and if it does not exceed it, push the incremental search data corresponding to the current e-commerce independent website in the pending consumption data queue to the data version verifier; and a traffic-limiting data push submodule, used to push the incremental search data corresponding to the current e-commerce independent website in the pending consumption data queue to the traffic-limiting pusher within a preset traffic-limiting time window when the number of incremental search data exceeds the preset traffic-limiting data volume.

[0149] In one embodiment, the data rate limiting push module 13 includes: a data storage submodule, used to store the latest acquired incremental search data at the first storage position of the rate limiting data queue; a data push submodule, used to push the incremental search data at the last storage position in the rate limiting data queue to the data version verifier; and a push speed control submodule, used to process the storage and push of incremental search data acting on the rate limiting data queue in the same manner, and control the push speed of incremental search data according to a preset data push speed.

[0150] In a further embodiment, the data version verification module 14 includes: a mapping data cache submodule, used to determine the data storage timestamp and data feature information of the latest acquired incremental search data, and store the data storage timestamp, data feature information and the incremental search data in a version verification cache space, wherein the data feature information includes an e-commerce independent website identifier and a data attribute identifier; a storage time comparison submodule, used to query multiple target incremental search data with the same data feature information in the version verification cache space, and compare the data storage timestamps of these target incremental search data; and an incremental data push submodule, used to push the target incremental search data with a later data storage timestamp to the e-commerce search service, and remove other target incremental search data from the version verification cache space.

[0151] To address the aforementioned technical problems, this application also provides a computer device for running a computer program implemented according to the search data synchronization method. Please refer to the following for details. Figure 9 , Figure 9 This is a basic structural block diagram of the computer device in this embodiment.

[0152] like Figure 9 The diagram shows the internal structure of a computer device. The computer device includes a processor, non-volatile storage medium, memory, and a network interface connected via a system bus. The non-volatile storage medium stores the operating system, database, and computer-readable instructions. The database may store control information sequences. When the computer-readable instructions are executed by the processor, they enable the processor to implement a data synchronization search method. The processor provides computing and control capabilities, supporting the operation of the entire computer device. The memory stores computer-readable instructions, which, when executed by the processor, enable the processor to implement a data synchronization search method. The network interface of the computer device is used for communication with a terminal. Those skilled in the art will understand that… Figure 9The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0153] In this embodiment, the processor executes the specific functions of each module / submodule in the search data synchronization device of this application, and the memory stores the program code and various types of data required to execute the above modules. The network interface is used for data transmission between the user terminal and the server. In this embodiment, the memory stores the program code and data required to execute all modules / submodules in the search data synchronization device, and the server can call the server's program code and data to execute the functions of all submodules.

[0154] This application also provides a non-volatile storage medium in which the search data synchronization method is written as a computer program and stored in the storage medium in the form of computer-readable instructions. When the computer-readable instructions are executed by one or more processors, it means that the program is running in the computer, thereby causing one or more processors to perform the steps of the search data synchronization method of any of the above embodiments.

[0155] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, or read-only memory (ROM), or random access memory (RAM).

[0156] In summary, this application can limit the data flow of e-commerce independent websites with massive incremental search data, so as to prevent the data synchronization service from being unable to handle the high volume of incremental search data and causing the system to crash. In addition, it can perform data version verification on incremental search data to select the latest version of data for push, ensuring that the search results of buyers through e-commerce search services are the latest products or orders.

[0157] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0158] Those skilled in the art will understand that the steps, measures, and solutions in the various operations, methods, and processes discussed in this application can be alternated, modified, combined, or deleted. Furthermore, other steps, measures, and solutions in the various operations, methods, and processes discussed in this application can also be alternated, modified, rearranged, decomposed, combined, or deleted. Furthermore, steps, measures, and solutions in the prior art that are similar to those disclosed in this application can also be alternated, modified, rearranged, decomposed, combined, or deleted.

[0159] The above description is only a partial embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for synchronizing search data, characterized in that, Includes the following steps: In response to an incremental search data event acting on the business database, the system retrieves multiple incremental search data corresponding to the incremental search data event and identifies the e-commerce independent websites corresponding to these incremental search data events. This includes: in response to the incremental search data event, retrieving the data operation log corresponding to the incremental search data event; retrieving the incremental search data corresponding to the multiple business data identifiers contained in the data operation log from the business database; identifying the e-commerce independent websites corresponding to the data operation log; and pushing each incremental search data item to a queue of data to be consumed. The process involves: 1) Statistically analyzing the incremental data traffic of the e-commerce independent website; 2) Verifying whether the incremental data traffic meets the preset data throttling rules; 3) Pushing each incremental search data item to the data version validator if it does not meet the rules. This includes: 4) Statistically analyzing the number of incremental search data items corresponding to the current e-commerce independent website in the pending consumption data queue within a preset statistical time window; 5) Determining whether the number of incremental search data items exceeds the preset throttling data limit; 6) Pushing the incremental search data items corresponding to the current e-commerce independent website in the pending consumption data queue to the data version validator if the number of incremental search data items exceeds the preset throttling data limit; 7) Pushing the incremental search data items corresponding to the current e-commerce independent website in the pending consumption data queue to the throttling pusher within the preset throttling time window. When the incremental data traffic meets the data rate limiting rule, each incremental search data is pushed to the rate limiting pusher to drive the rate limiting pusher to push each incremental search data to the data version verifier based on the rate limiting push rule. The process of driving the data version validator to verify the data version of each incremental search data and pushing the incremental search data with a later data version to the e-commerce search service includes: determining the data storage timestamp and data feature information of the latest acquired incremental search data; storing the data storage timestamp and data feature information in the version verification cache space, where the data feature information includes the e-commerce independent website identifier and data attribute identifier; querying multiple target incremental search data with the same data feature information in the version verification cache space; comparing the data storage timestamps of these target incremental search data; pushing the target incremental search data with a later data storage timestamp to the e-commerce search service; and removing the other target incremental search data from the version verification cache space. The business database is used to store the business data of each e-commerce independent website in the platform. The business database maps and stores each business data with a business data identifier that represents the corresponding e-commerce independent website and business data type. This allows the server to query the business data corresponding to the business data identifier from the business database based on the business data identifier, and then transmit the business data as incremental search data to the e-commerce search service. The incremental search data event refers to the event triggered by storing new business data in the business database. The incremental data traffic refers to the amount of incremental search data that needs to be pushed to the e-commerce search service for each e-commerce independent website per unit of time.

2. The method according to claim 1, characterized in that, The steps of driving the rate-limiting pusher to push each incremental search data to the data version verifier at a limited rate based on the rate-limiting push rules include the following steps: Store the latest incremental search data in the first position of the rate-limited data queue; The incremental search data at the end of the rate-limited data queue is pushed to the data version verifier; Similarly, the storage and push of incremental search data applied to the rate-limited data queue are processed, and the push speed of incremental search data is controlled according to the preset data push speed.

3. The method according to claim 1 or 2, characterized in that, This method includes the following post-steps: In response to the incremental search data event, obtain the data operation log corresponding to the incremental search data event; Based on the multiple business data identifiers contained in the data operation log, the incremental search data corresponding to these business data identifiers is obtained from the business database; The e-commerce independent site corresponding to the data operation log is determined. When the e-commerce independent site is a traffic-limited e-commerce independent site, the incremental search data is pushed to the traffic-limiting pusher.

4. A search data synchronization device, characterized in that, include: The incremental data acquisition module is used to respond to incremental search data events acting on the business database, acquire multiple incremental search data corresponding to the incremental search data event, and determine the e-commerce independent websites corresponding to these incremental search data. This includes: responding to the incremental search data event and acquiring the data operation log corresponding to the incremental search data event; acquiring the incremental search data corresponding to the multiple business data identifiers contained in the data operation log from the business database; determining the e-commerce independent websites corresponding to the data operation log; and pushing each incremental search data to the pending consumption data queue. The data traffic verification module is used to count the incremental data traffic of the e-commerce independent website and verify whether the incremental data traffic meets the preset data throttling rules. If it does not meet the rules, the incremental search data is pushed to the data version verifier. This includes: counting the number of incremental search data corresponding to the current e-commerce independent website in the pending consumption data queue within a preset statistical time window; determining whether the number of incremental search data exceeds the preset throttling data volume; if it does not exceed the preset throttling data volume, the incremental search data corresponding to the current e-commerce independent website in the pending consumption data queue is pushed to the data version verifier; when the number of incremental search data exceeds the preset throttling data volume, the incremental search data corresponding to the current e-commerce independent website in the pending consumption data queue is pushed to the throttling pusher within the preset throttling time window. The data rate limiting push module is used to push each incremental search data to the rate limiting pusher when the incremental data traffic meets the data rate limiting rules, so as to drive the rate limiting pusher to push each incremental search data to the data version verifier based on the rate limiting push rules. The data version verification module is used to drive the data version verifier to verify the data version of each incremental search data, and push the incremental search data with a later data version to the e-commerce search service. It includes: a mapping data cache submodule, used to determine the data storage timestamp and data feature information of the latest acquired incremental search data, and store the data storage timestamp and data feature information in a version verification cache space corresponding to the incremental search data. The data feature information includes an e-commerce independent website identifier and a data attribute identifier; a storage time comparison submodule, used to query multiple target incremental search data with the same data feature information in the version verification cache space, and compare the data storage timestamps of these target incremental search data; and an incremental data push submodule, used to push the target incremental search data with a later data storage timestamp to the e-commerce search service, and remove other target incremental search data from the version verification cache space. The business database is used to store the business data of each e-commerce independent website in the platform. The business database maps and stores each business data with a business data identifier that represents the corresponding e-commerce independent website and business data type. This allows the server to query the business data corresponding to the business data identifier from the business database based on the business data identifier, and then transmit the business data as the incremental search data to the e-commerce search service. The incremental search data event refers to the event triggered by storing new business data in the business database.

5. The search data synchronization device according to claim 4, characterized in that, The data rate limiting and push module includes: The data storage submodule is used to store the latest incremental search data in the first storage position of the rate-limited data queue; The data push submodule is used to push the incremental search data at the end of the data limit queue to the data version verifier. The push speed control submodule is used to process the storage and push of incremental search data applied to the rate-limited data queue, and to control the push speed of incremental search data according to the preset data push speed.

6. An electronic device comprising a central processing unit and a memory, characterized in that, The central processing unit is used to invoke and run a computer program stored in the memory to perform the steps of the method as described in any one of claims 1 to 3.

7. A non-volatile storage medium, characterized in that, It stores, in the form of computer-readable instructions, a computer program implemented according to any one of claims 1 to 3, which, when invoked by a computer, performs the steps included in the method.

8. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method according to any one of claims 1 to 3.

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