Method and system for determining cache evaluation data

Abstract

The invention discloses a method and system for determining cache evaluation data, and relates to the technical field of data processing.The method comprises the steps that multiple pieces of access data of a business service program in a target platform are obtained, and the access data comprise a cache key corresponding to an access request, an operation type and an access result; determining a data category identifier of the cache key; classifying the multiple pieces of access data at least based on the data category identifier and the operation type of the cache key to obtain at least one data group; based on the access results corresponding to the access data in the data set, determining the hit number of the access requests hit the cache system and the miss number of the access requests miss the cache system in the data set; and determining the data category identifier, the operation type, the hit quantity and the miss quantity corresponding to the data group as a piece of cache evaluation data of the business service program. According to the scheme provided by the invention, the evaluation data which more comprehensively and accurately reflects the cache quality can be obtained.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, and in particular to a method and system for determining cache evaluation data. BACKGROUND

[0002] At present, cache technology has been widely applied in various Internet platforms such as video servers or shopping platforms.

[0003] In the case of using cache technology in an Internet platform, if there is a data access demand (such as receiving a data request of a client) in the Internet platform, the cache system (such as a distributed cache system or a cache cluster) corresponding to the Internet platform can be accessed first. If the cache system caches the data requested by the data request, the database does not need to be accessed, thereby improving the data access performance. In order to be able to optimize the cache system in a timely manner, it is necessary to analyze the cache quality of the cache system. Therefore, how to obtain evaluation data that can reflect the cache quality is a technical problem to be solved by those skilled in the art. SUMMARY

[0004] In view of the above problems, the present application provides a method and system for determining cache evaluation data to obtain evaluation data that can comprehensively and accurately reflect the cache quality. The specific scheme is as follows:

[0005] The first aspect of the present application provides a method for determining cache evaluation data, comprising:

[0006] obtaining a plurality of access data of a business service program in a target platform, wherein each access data corresponds to an access request initiated by the business service program to a cache system of the target platform, and the access data comprises a cache key corresponding to the access request, an operation type and an access result, the cache key is used to identify cache data required to be accessed by the access request, and the access result is used to represent whether the access request hits the cache system;

[0007] determining a data category identifier possessed by the cache key in the access data, the data category identifier being used to represent a data category to which the cache data identified by the cache key belongs;

[0008] performing classification processing on the plurality of access data based on at least the data category identifier possessed by the cache key and the operation type, to obtain at least one data group, the data group comprising at least one access data, and the data category identifier and the operation type corresponding to each access data in the data group being the same;

[0009] determining, based on the access result corresponding to each access data in the data group, a hit number of the cache system in the access request corresponding to the data group and a miss number of the cache system in the access request corresponding to the data group.

[0010] The data category identifier corresponding to the data group, the operation type, the hit number and the miss number are determined as a piece of cache evaluation data of the service program.

[0011] In a possible implementation, the access data further includes a response duration corresponding to the access request.

[0012] The plurality of pieces of access data are classified based on at least the data category identifier and the operation type possessed by the cache key, and the classification processing includes:

[0013] The plurality of pieces of access data are classified based on the data category identifier, the operation type and the response duration possessed by the cache key, wherein the response durations corresponding to the access data in the same data group belong to the same response duration interval, and the response duration intervals corresponding to different data groups are different.

[0014] The data category identifier corresponding to the data group, the operation type, the hit number and the miss number are determined as a piece of cache evaluation data of the service program.

[0015] The data category identifier corresponding to the data group, the operation type, the hit number and the miss number are determined as a piece of cache evaluation data of the service program.

[0016] In another possible implementation, the access data further includes a cache capacity occupied by the cache data required to be accessed by the access request.

[0017] The plurality of pieces of access data are classified based on at least the data category identifier and the operation type possessed by the cache key, and the classification processing includes:

[0018] The plurality of pieces of access data are classified based on the data category identifier, the operation type, the cache capacity and the response duration possessed by the cache key, wherein the cache capacities corresponding to the access data in the data group belong to the same cache capacity interval.

[0019] The data category identifier corresponding to the data group, the operation type, the hit number and the miss number are determined as a piece of cache evaluation data of the service program.

[0020] The data category identifier corresponding to the data group, the operation type, the hit number and the miss number are determined as a piece of cache evaluation data of the service program.

[0021] In another possible implementation, after the cache evaluation data is determined, the method further includes:

[0022] In response to a data presentation request initiated by the target platform for the business service program, based on the number of hits and the number of misses in the cache evaluation data, a hit rate corresponding to the data category identifier and the operation type in the cache evaluation data is determined;

[0023] The data category identifier, the operation type, the number of hits, the number of misses and the hit rate in each piece of cache evaluation data corresponding to the business service program are output to the target platform.

[0024] In yet another possible implementation, the determination of the data category identifier possessed by the cache key in the access data includes at least one of the following:

[0025] Based on the at least one historical data category identifier determined in history, a historical data category identifier matched with the cache key of the access data is determined as the data category identifier possessed by the cache key in the access data.

[0026] For at least two pieces of access data in the plurality of pieces of access data for which no historical data category identifier is matched, based on the cache keys of the at least two pieces of access data, a data category identifier possessed by each cache key in the at least two pieces of access data is extracted by using an intelligent model.

[0027] In yet another possible implementation, before the plurality of pieces of access data of the business service program in the target platform are obtained, the method further includes:

[0028] The access request initiated by the business service program to the cache system is detected by the sampling code inserted in the business service program, the access request is intercepted, and the cache key and the operation type corresponding to the access request are determined.

[0029] In response to the response result returned by the cache system for the access request, the access result corresponding to the access request is determined by the sampling code.

[0030] The cache key, the operation type and the access result corresponding to the access request are stored as a piece of access data corresponding to the business service program by the sampling code.

[0031] In yet another possible implementation, the determination of the cache key and the operation type corresponding to the access request includes:

[0032] If the access request is determined to be a to-be-sampled access request based on the sampling rate corresponding to the business service program, the cache key and the operation type corresponding to the access request are determined.

[0033] In another possible implementation, after detecting that the business service program has initiated an access request to the cache system, the method further includes: counting the cumulative number of access requests initiated by the business service program within the current sampling period;

[0034] The acquisition of multiple access data entries from the business service programs on the target platform includes:

[0035] Obtain multiple access data entries from the business service system on the target platform within the most recent sampling period, and determine the total number of the multiple access data entries;

[0036] After obtaining multiple access data entries from the business service programs on the target platform, the following is also included:

[0037] If the difference between the total number and the set expected number of samples exceeds a set threshold, the target sampling rate is determined based on the expected number of samples and the cumulative number.

[0038] Adjust the sampling rate corresponding to the business service program to the target sampling rate.

[0039] In another possible implementation, before the sampling code detects that the business service program has initiated an access request to the caching system, the following is also included:

[0040] In response to the publishing system publishing the business service program to the target platform, the sampling code is obtained and injected into the business service program.

[0041] A second aspect of this application provides a system for determining cached evaluation data, comprising:

[0042] The data acquisition unit is used to acquire multiple access data entries of a business service program in the target platform. Each access data entry corresponds to an access request initiated by the business service program to the cache system of the target platform. The access data includes: the cache key, operation type, and access result corresponding to the access request. The cache key is used to identify the cached data to be accessed by the access request, and the access result is used to indicate whether the access request hits the cache system.

[0043] An identifier determination unit is used to determine the data category identifier of the cache key in the access data, wherein the data category identifier is used to characterize the data category to which the cache data identified by the cache key belongs;

[0044] A classification processing unit is used to classify the multiple access data based at least on the data category identifier of the cache key and the operation type to obtain at least one data group, wherein the data group includes at least one access data, and the data category identifier and the operation type corresponding to each access data in the data group are the same;

[0045] The result determination unit is used to determine the number of hits that hit the cache system and the number of misses that do not hit the cache system in the access requests corresponding to the data group based on the access results corresponding to each access data in the data group.

[0046] The data determination unit is used to determine the data category identifier, operation type, number of hits and number of misses corresponding to the data group as a cached evaluation data of the business service program.

[0047] A third aspect of this application provides a method for determining cached evaluation data, including a computer program product and computer-readable instructions, which, when executed on an electronic device, cause the electronic device to implement the first aspect or any implementation thereof.

[0048] A fourth aspect of this application provides a computer-readable storage medium carrying one or more computer programs that, when executed by an electronic device, enable the electronic device to implement the method for determining cached evaluation data as described in the first aspect or any implementation thereof.

[0049] Using the above technical solution, this application can obtain multiple access data entries from the business service program in the target platform. Each access data entry includes a cache key, operation type, and access result for an access request. Based on this, this application determines the data category identifier of the cache key in the access data, and categorizes multiple access data entries based on the data category identifier and operation type of the cache key, grouping access data entries with the same data category identifier and the same operation type into the same data group. Since the data category identifier represents the data category of the cached data requested by the access request corresponding to the access data, counting the number of hits and misses of access requests that hit the cache system for each data group is essentially analyzing the number of hits and misses of access requests from the two dimensions of the data category accessed by the access request and the operation type of the access request. Therefore, by identifying the data category identifier, operation type, hit count, and miss count corresponding to each data group as a cache evaluation data for a business service program, the different cache evaluation data based on the business service program can reflect the hit status of the business service program accessing the cache system in a more granular and comprehensive way from the two dimensions of data operation category and operation type. This provides a more granular and comprehensive data basis for analyzing the cache quality of the cache system. Attached Figure Description

[0050] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0051] Figure 1 A flowchart illustrating the method for determining cached evaluation data provided in this application;

[0052] Figure 2 Another flowchart illustrating the method for determining cached evaluation data provided in this application;

[0053] Figure 3 This is an example diagram illustrating the interaction of the solution in this application scenario;

[0054] Figure 4 A schematic diagram of the structural composition of a system for determining cached evaluation data provided in this application;

[0055] Figure 5 This is another schematic diagram of the structure of the system for determining cached evaluation data provided in this application. Detailed Implementation

[0056] The embodiments of this application are described below with reference to the accompanying drawings. The terminology used in the implementation section of this application is only for explaining specific embodiments and is not intended to limit the application. Those skilled in the art will recognize that, with technological advancements and the emergence of new scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0057] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such terms are interchangeable where appropriate; this is merely a way of distinguishing objects with the same attributes in the embodiments of this application. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, so that a process, method, system, product, or apparatus that comprises a series of elements is not necessarily limited to those elements, but may include other elements not explicitly listed or inherent to those processes, methods, products, or apparatuses.

[0058] like Figure 1This illustration shows a flowchart of a method for determining cached evaluation data provided in this application. The method of this embodiment can be applied to a data analysis platform, which is a distributed system or cluster system composed of computer devices, servers, or at least one device node outside the target platform of the caching system; there are no limitations on this. The method of this embodiment may include:

[0059] S101, obtain multiple access data entries from the business service program on the target platform.

[0060] The target platform is an internet platform that uses an application caching system to cache data. This can be a web server, a service system providing video or webpage access, or a distributed system, without limitation. The caching system of the target platform can be a distributed caching system, a caching cluster, or a cache storage device within a single device on the target platform, without limitation.

[0061] The target platform can run one or more business service programs, each providing at least one business service. These programs can offer services such as video access, website page access, or data querying; there are no restrictions on the specific services offered. When providing services to clients, these programs need to access data in a cache system. Therefore, the programs will send access requests to the cache system to request cached data. For example, in response to a client's data request, a program might send an access request to the cache system to obtain the data the client needs.

[0062] In this application, each piece of access data corresponds to an access request initiated by the business service program to the target platform's caching system. This access data includes at least: the cache key, operation type, and access result corresponding to the access request.

[0063] The cache key is used to identify the cached data requested in the access request. The caching system uses key-value pairs to cache data; therefore, each cached data item corresponds to a unique key, i.e., the cache key. For example, the cache key is an index string used to uniquely identify and retrieve cached data.

[0064] The operation type corresponding to the access request refers to the type of operation that the access request needs to perform on the cached data in the caching system. For example, the operation types corresponding to access requests supported by the caching system may include, but are not limited to, one or more of the following: read operation, write operation, and delete operation.

[0065] The access result of an access request indicates whether the access request hits the cache system. For example, if the access result is a cache hit, it means that the data requested by the access request exists in the cache system; if the access result is a cache miss, it means that the data requested by the access request does not exist in the cache system.

[0066] In one possible implementation, to obtain cache evaluation data for evaluating the caching system in a timely and stable manner, this application can periodically obtain and process access data from the business service system. Based on this, this application can obtain multiple access data entries from the business service program in the most recent sampling period. For example, according to a set sampling period, the current sampling time is determined, and multiple access data entries from the business service system within the most recent sampling period are obtained.

[0067] S102, determine the data category identifier of the cache key in the accessed data.

[0068] The data category identifier is used to characterize the data category to which the cached data identified by the cache key belongs. For example, the data category of each cached data in the caching system can include, but is not limited to, multiple categories such as video, audio, web pages, and documents, without any specific restrictions.

[0069] It is understood that a cache key in a caching system consists of two parts: a data category identifier to identify the data type, and a parameter part to identify the cached data. While the data category identifier is fixed in the caching system, the parameter part changes depending on the storage location of the cached data within the caching system. Therefore, this application needs to identify the data category identifier within the cache key to obtain the data category identifier in the cache key.

[0070] In this application, there are multiple possibilities for determining the data category identifier from the cache key, and no restriction is imposed on this.

[0071] For example, in one possible implementation, considering that in practical applications, the position, order, and distribution of data category identifiers and parameter parts in the cache key may differ in different caching systems, but for the same caching system, the positional distribution of data category identifiers in the cache key is fixed, based on this, this application can utilize trained intelligent models such as large language models to extract data category identifiers from the cache key.

[0072] For example, since a business service system may have multiple access requests for the same data category within each sampling period, and the data category identifiers in the cache keys corresponding to these access requests are identical, the common string portion in the cache keys corresponding to these access requests is the data category identifier. Based on this, the multiple access data from the business service system are input into the intelligent model. The intelligent model can identify the characters corresponding to the data category identifiers in each cache key and extract the data category identifiers from each cache key.

[0073] Of course, there are other possibilities for using intelligent models to extract data category identifiers from cache keys, and there are no restrictions on this.

[0074] Furthermore, considering that intelligent model operation requires significant resources and time, to reduce resource consumption and improve recognition efficiency, after obtaining the access data, this application can first match the cache key with historically determined historical data category identifiers. Accordingly, based on at least one historically determined historical data category identifier, the historical data category identifier matching the cache key of the access data can be determined as the data category identifier possessed by the cache key in the access data. For example, regular expressions can be used to match whether the cache key includes a historical data category identifier.

[0075] The historical data category identifiers can be those identified using intelligent models in the past. For example, each time the intelligent model identifies a new data category identifier, it stores it in a designated storage area or execution database. Of course, if the data categories in the caching system are limited, the identifiers of each data category that may exist in the cache key of the caching system can be pre-configured manually, and the configured data category identifiers can be used as historical data category identifiers.

[0076] Considering that historical data category identifiers may not be comprehensive, for at least two access data entries that do not match historical data category identifiers, this application can also use an intelligent model to extract the data category identifiers of each cache key in the at least two access data entries based on the cache keys of the at least two access data entries.

[0077] In practical applications, the intelligent model can be used to extract the data category identifier of the cache key in the accessed data, and the cache key can be matched with the historical data category identifier. These methods can be used separately or in combination, without any restrictions.

[0078] S103, based at least on the data category identifier and operation type of the cache key, classify multiple accessed data to obtain at least one data group.

[0079] Each data group includes at least one accessed data record, and all accessed data records within a data group share the same data category identifier and operation type. Conversely, at least one of the data category identifier and operation type differs between different data groups.

[0080] For example, data group A and data group B may correspond to the same data category identifier, but have different operation types. This means that the access data in these two data groups are generated by access requests for cached data of the same data category, but the types of operations performed on the cached data of the same data category by these two data groups are different. For example, data group A may include access data corresponding to each access request for reading video cached data, while data group B may include access data corresponding to each access request for writing video cached data.

[0081] Of course, data group A and data group B can also have different data category identifiers and operation types.

[0082] In this application, there are various possible implementations for classifying and processing multiple access data, and no restrictions are imposed on them.

[0083] For example, this application can cluster multiple access data based on the data category identifier and operation type of the cache key to obtain at least one clustered data group. Alternatively, this application can first use the data category identifier as the primary classification criterion to group access data with the same data category identifier into the same data set, obtaining at least one data set; then, for each data set, it can further group access data with the same operation type into a group based on the operation type, ultimately obtaining at least one data group.

[0084] S104, For each data group, based on the access results corresponding to each accessed data in the data group, determine the number of hits in the cache system and the number of misses in the access requests corresponding to the data group.

[0085] As we can understand, the access result of data access represents whether the access request corresponding to the accessed data hit the cache system. Therefore, for an access request, its result can only be a cache hit or a cache miss. Based on this, if the access request hits the cache system, it means that the access request successfully obtained the cached data from the cache system. Therefore, the hit count is the number of access requests in the data group that successfully accessed the cache system. Conversely, if the access request misses the cache system, it means that the access request failed to obtain the required cached data from the cache system. Therefore, the miss count is the number of access requests in the data group that failed to access the cache system.

[0086] S105, the data category identifier, operation type, number of hits and number of misses corresponding to the data group are determined as a cached evaluation data of the business service program.

[0087] In this application, each data group corresponds to one cached evaluation data. Therefore, multiple different data groups must correspond to multiple different cached evaluation data, thus obtaining at least one cached evaluation data of the business service system.

[0088] Since the data category identifier and operation type corresponding to each cached evaluation data in the business service system are not completely the same, different cached evaluation data can reflect the cache hit situation when the business service system performs different operation types on cached data of different data categories. This can reflect the cache access situation of the business service system in terms of data category and operation type in a relatively fine-grained manner.

[0089] For example, by combining various cache evaluation data, it is possible not only to determine the number of hits and misses corresponding to each combination of data category identifier and operation type, but also to calculate the total number of hits and total number of misses corresponding to each data category identifier (regardless of operation type).

[0090] Specifically, before step S105, for each data group, this application can also determine the hit rate of each access request to the cache system corresponding to that data group by combining the hit count and miss count. Accordingly, the data category identifier, operation type, hit count, miss count, and hit rate corresponding to the data group can be determined as a cache evaluation data.

[0091] Of course, by combining various cache evaluation data, this application can also determine other evaluation metrics for the caching system according to actual needs. For example, from multiple cache evaluation data corresponding to the business service program, candidate evaluation data with the same data category identifier can be identified. Based on the first number of candidate evaluation data with read operation type and the second number of candidate evaluation data with write operation type in each candidate evaluation data, the read-write ratio of the access request corresponding to that data category identifier can be determined. By combining various cache evaluation data, different evaluation metrics can be generated according to actual needs, and the specific implementation is not limited.

[0092] It should be noted that multiple business service programs can run on the target platform. However, the process of determining the cached evaluation data of each business service program is the same. This application is used as an example to illustrate the determination of the cached evaluation data of any one business service program.

[0093] As described above, this application can obtain multiple access data entries from the business service program on the target platform. Each access data entry includes a cache key, operation type, and access result for an access request. Based on this, this application determines the data category identifier of the cache key in the access data and categorizes multiple access data entries based on the data category identifier and operation type of the cache key, grouping access data entries with the same data category identifier and the same operation type into the same data group. Since the data category identifier represents the data category of the cached data requested by the access request corresponding to the access data, counting the number of hits and misses of access requests that hit the cache system for each data group is essentially analyzing the number of hits and misses of access requests from the two dimensions of the data category accessed by the access request and the operation type of the access request. Therefore, by identifying the data category identifier, operation type, hit count, and miss count corresponding to each data group as a cache evaluation data for a business service program, the different cache evaluation data based on the business service program can reflect the hit status of the business service program accessing the cache system in a more granular and comprehensive way from the two dimensions of data operation category and operation type. This provides a more granular and comprehensive data basis for analyzing the cache quality of the cache system.

[0094] Understandably, to enable maintenance personnel or cache management personnel of the target platform to intuitively understand the quality of the caching system and effectively implement corresponding cache optimization strategies, in this application, after determining the cache evaluation data corresponding to the business service program, the target platform can also send a data display request to the data analysis platform of this application. Correspondingly, in response to the data display request initiated by the target platform for the business service program, this application can also determine the hit rate corresponding to the data category identifier and operation type in the cache evaluation data based on the number of hits and misses in the cache evaluation data. Of course, if the cache evaluation data already includes the hit rate, then the operation of determining the hit rate mentioned here is unnecessary.

[0095] Based on this, in response to data display requests, the system can output the data category identifier, operation type, number of hits, number of misses, and hit rate of each cached evaluation data corresponding to the business service program to the target platform. This allows the target platform to display information such as the number of hits, number of misses, and hit rate of access requests under different data categories and different operation categories.

[0096] It is understandable that the quality of a caching system is related not only to the number of cache hits and the hit rate of access requests, but also to the response time of access requests to the cache system.

[0097] Therefore, in order to obtain more comprehensive evaluation data for the caching system, this application may also include the execution time of the access request. The access data for the business service program may also include the response time of the access request. The response time is the time required from when the business service program initiates an access request to when the caching system returns a response to that access request.

[0098] Building upon this, this application can further categorize multiple access data entries corresponding to a business service program based on the data category identifier, operation type, and response duration of the cache key. Accordingly, each categorized data group includes at least one access data entry. Within the same data group, the data category identifier and operation type of each access data entry are the same, and the response durations of each access data entry within the same data group belong to the same response duration range. Of course, different data groups may correspond to different response duration ranges. Based on this, the data category identifier, operation type, response duration range, number of hits, and number of misses corresponding to a data group can be determined as a cache evaluation data entry for that business service program.

[0099] In this embodiment, the specific implementation of classifying multiple access data can also be found in the previous description, and the specific classification method is not limited.

[0100] The response time intervals for different data groups can have the same or different durations, without any restrictions. For example, the size of each response time interval can be preset, or different response time intervals can be pre-defined, and multiple access data can be categorized based on the pre-configured response time intervals or the size of each response time interval.

[0101] Understandably, categorizing multiple access data entries from a business service program by combining data category identifiers, operation types, and response durations allows access requests that access the same data category, have the same operation type, and similar response durations to be grouped into a single data group. Based on this, after determining the data category, operation type, response duration, hit count, and miss count corresponding to the same data group as a single cache evaluation data entry for the business service program, it's possible to determine not only the operation type corresponding to access requests accessing cached data of the same data category, but also the response duration range for different operation types under each data category. This allows for analysis of any abnormal access times or other anomalies. Furthermore, for each data category, it's possible to determine the number of commands and miss counts corresponding to different operation types and different response duration ranges, providing more granular data reflecting cache hit status.

[0102] Of course, by combining the number of hits and misses in each cache evaluation data that contains the same data category identifier, we can also analyze the total number of cache system hits, the total number of cache system misses, and the overall hit rate in each access request corresponding to that data category identifier.

[0103] Furthermore, considering that the size of the cached data requested by the access request varies, which will also affect the response time of the access request, in order to enable the cache evaluation data to more accurately reflect the cache quality of the caching system, in this application, the access data also includes: the cache capacity occupied by the cached data required by the access request. Accordingly, multiple access data can be classified based on the data category identifier, operation type, cache capacity, and response time of the cache key. Furthermore, in addition to having the same data category identifier and operation type, and corresponding response times belonging to the same response time range, the access data corresponding to the same data group also have cache capacities belonging to the same cache capacity range.

[0104] Based on this, the data category identifier, operation type, response time range, cache capacity range, number of hits, and number of misses corresponding to the data group can be determined as a cache evaluation data of the business service program.

[0105] Since the cache capacity range represents the size of the cached data accessed by the access request corresponding to the data group, this application can analyze the specific response time and the possible number of cache hits when accessing different sizes of cached data under different data category identifiers and operation types, based on each cache evaluation data, provided that each cache evaluation data includes a cache capacity range.

[0106] It is understandable that, given that each cached evaluation data entry includes a data category identifier, operation type, cache capacity range, response time range, hit count, and miss count, in response to a data display request initiated by the target platform for the business service program, the data category identifier, operation type, hit count, and miss count from each cached evaluation data entry corresponding to the business service program are output to the target platform, so that the target platform can display each cached evaluation data entry of the business service platform. Of course, if this application can pre-calculate the hit rate corresponding to each cached evaluation data entry, or calculate the hit rate corresponding to the cached evaluation data entry in response to a data display request and output it to the target platform, further details are omitted.

[0107] In the above embodiments of this application, there are various ways to obtain access data of business service programs in the target platform, and this application does not impose any restrictions on this.

[0108] In one possible implementation, to avoid requiring adaptive adjustments to the target platform due to the acquisition of access data, this application provides a non-intrusive data acquisition method. Specifically, this application can inject sampling code into the business service program. Based on this, if the sampling code inserted into the business service program detects an access request from the business service program to the caching system, the access request can be intercepted, and the cache key and operation type corresponding to the access request can be determined. Correspondingly, in response to the caching system returning a response result for the access request, the access result corresponding to the access request can be determined through the sampling code. Based on this, the cache key, operation type, and access result corresponding to the access request can be stored as a single access data entry for the business service program using the sampling code.

[0109] It is understandable that each access request initiated by the business service program can be processed in the above way to generate an access data record. Based on this, multiple access data records corresponding to the business service program can be obtained within a certain period of time (such as within the sampling period).

[0110] In this application, the sampling code can send the access data to the data analysis platform for storage after it identifies each access data. However, this will result in a large consumption of resources and may affect the efficiency of the sampling code in collecting access data.

[0111] Based on this, in one possible implementation, the sampling code can store the accessed data in a target storage area on the target platform. For example, the target storage area could be the target platform's database or a designated storage area—any storage area that the data analysis platform has access to—without restriction. On this basis, when the data analysis platform needs to analyze the accessed data, it can retrieve multiple access data entries corresponding to the business service program stored in the target storage area.

[0112] Specifically, considering that the business service program may initiate a large number of access requests within a certain period of time, analyzing and storing the data corresponding to each access request would not only involve a large amount of data processing but also a large amount of data storage. Therefore, to reduce the data storage and processing volume, this application can pre-configure the sampling rate for the collected data for the business service program. Correspondingly, only if the access request is determined to be a sampled access request based on the sampling rate corresponding to the business service program will the cache key and operation type corresponding to that access request be determined.

[0113] In this embodiment, there are various ways to inject sampling code into the business service program. To ensure that developers of the business service program do not need to adjust the program, and that each target platform does not need to add a separate adapter, this application can configure an insertion program for inserting sampling code on the publishing system that publishes the business service program. The publishing system injects the sampling code into the business service program by running the insertion program. The publishing system can be a server or cluster software publishing system capable of publishing various software packages to different target platforms.

[0114] Specifically, in response to the publishing system publishing a business service program to the target platform, the system obtains sampling code and injects it into the business service program. For example, the publishing system obtains sampling code from the data analysis platform through this insertion program and injects it into the business service program. Based on this, after the business service program is published to the target platform, the business service program running on the target platform will have sampling code inserted into it, enabling it to obtain and access data.

[0115] To facilitate understanding, the method for determining cached evaluation data in this application will be described below using one possible implementation as an example. For example... Figure 2 This illustration shows another flowchart of the method for determining cached evaluation data provided in this application. The method in this embodiment may include:

[0116] S201, in response to the publishing system publishing a business service program to the target platform, the sampling code is obtained through the insertion program in the publishing system, and the sampling code is injected into the business service program so that the publishing system publishes the business service program injected with the sampling code to the target platform.

[0117] This step S201 can be executed on the publishing system side, specifically through an insert program (or insert component, etc.) deployed on the publishing system.

[0118] For ease of understanding, combined with Figure 3 The scenario architecture shown will be introduced.

[0119] Depend on Figure 3 As can be seen, an insertion component has been added to the publishing system. Before publishing the business service program to the target platform, the publishing system builds an image of the business service program. Based on this image, this application can obtain sampling code from the data analysis platform using the insertion component and inject the sampling code into the business service program. Correspondingly, the publishing system will publish the business service program injected with the sampling code to the target platform.

[0120] S202: After the business service program runs on the target platform, if the sampling code inserted in the business service program detects that the business service program is sending an access request to the cache system, the access request is intercepted.

[0121] Understandably, after the business service program runs on the target platform, the sampling code inserted in the business service program will also be executed, enabling the sampling code to monitor whether the business service program initiates an access request. If so, it will intercept the access request in order to subsequently determine information such as the cache key and operation type corresponding to the access request.

[0122] S203, if the access request is determined to be an access request to be sampled based on the sampling rate corresponding to the business service program, determine the cache key and operation type corresponding to the access request.

[0123] The access request can carry a cache key and indicate the type of operation on the cached data. Understandably, after determining the cache key and operation type corresponding to the access request, the sampling code releases the access request so that the business service program can continue to send the access request to the caching system.

[0124] S204, in response to the caching system returning a response result for the access request, the access result and access duration corresponding to the access request, as well as the cache capacity occupied by the cached data required by the access request, are determined by sampling code.

[0125] The access result of the access request is used to characterize whether the access request hits the cache system.

[0126] The access duration can be determined based on the first time the business service program initiates the access request and the second time the caching system returns the response result.

[0127] The cache capacity corresponding to the cached data requested by the access request can be determined based on the size of the cached data returned by the caching system for the access request, or it can be determined by querying the cache capacity of the cached data corresponding to the cache key from the caching system. Of course, there are other implementation methods, and there are no restrictions on them.

[0128] S205 uses sampling code to store the cache key, operation type, access result, access duration, and cache capacity corresponding to the access request as a piece of access data corresponding to the business service program in the target storage area of ​​the target platform.

[0129] It is understandable that steps S202 to S205 above are performed by sampling code running on the target platform. In practical applications, since the sampling code intercepts the access request every time the business service system initiates an access request, steps S202 to S205 above can be executed multiple times within a sampling period.

[0130] Combination Figure 3 To provide an explanation, by Figure 3As can be seen, after the business service program on the target platform sends an access request to the caching system, the sampling code can sample and record the access data.

[0131] S206, according to the set sampling period, the sampling time is determined, and the data analysis platform obtains multiple access data of the business service system in the most recent sampling period from the target storage area of ​​the target platform.

[0132] As mentioned above, each piece of access data corresponds to an access request, and each piece of access data includes: the cache key corresponding to the access request, the operation type, the access result, the access duration, and the cache capacity.

[0133] In this embodiment, the data analysis platform acquires multiple access data entries when the sampling time is determined based on a set sampling period. However, in practical applications, the user can also trigger the analysis of access data. Correspondingly, in response to the data analysis command, the data analysis platform obtains the multiple access data entries from the target storage area. Of course, the implementation of the data analysis platform obtaining multiple access data entries through other methods is also applicable to this embodiment, and there is no limitation thereto.

[0134] In one possible implementation, to avoid excessive data processing by the data analysis platform due to too much access data collected in a sampling period, or to avoid insufficient access data collected in a sampling period resulting in the determined cache evaluation data failing to accurately reflect the quality of the cache system, this application can also dynamically adjust the sampling rate of the business service program.

[0135] To reasonably determine the appropriate sampling rate for the business service program, this application can also count the cumulative number of access requests initiated by the business service program within the current sampling period after detecting that the business service program has initiated an access request to the caching system. For example, within a sampling period, whenever the business service program initiates an access request, the cumulative number of access requests is incremented by one.

[0136] Accordingly, after obtaining multiple access data entries of the business service program based on the sampling period, this application can also determine the total number of these multiple access data entries. Based on this, if the difference between the total number and the set expected sampling number exceeds a set threshold, a target sampling rate can be determined based on the expected sampling number and the cumulative number, and the sampling rate corresponding to the business service program can be adjusted to the target sampling rate.

[0137] The threshold can be set according to actual needs, such as 20 or 30.

[0138] The target sampling rate can be the ratio of the expected number of samples to the current cumulative number. For example, if the expected number of samples is 100 and the current cumulative number is 1000, then the target sampling rate is 1 / 10, meaning that samples are taken once for every 10 access requests.

[0139] Specifically, the data analysis platform can send a target sampling rate to the sampling code of the business service program based on the interface provided by the target platform, so as to adjust the sampling rate of the sampling code to sample the access requests of the business service program to the target sampling rate.

[0140] like Figure 3 After the data analysis platform obtains the original data table containing multiple access requests, and there is a deviation between the expected sampling number and the total number of access requests in the original data table (i.e., the actual sampling number) and the expected sampling number (i.e., the sampling rate needs to be adjusted), it can calculate and adjust the appropriate sampling rate based on the cumulative number of access requests initiated by the business service program and the expected sampling number.

[0141] S207, The data analysis platform determines the data category identifier of the cache key in each accessed data.

[0142] The cache key has a data category identifier that is used to characterize the data category to which the cached data identified by the cache key belongs.

[0143] In particular, after determining the data category identifier of the cache key for each accessed data, this application replaces the cache key in the accessed data with the data category identifier to reduce the amount of data stored. This also means that when the data analysis platform obtains the accessed data again, it does not need to repeatedly determine the data category identifier of the cache key in the accessed data.

[0144] S208, the data analysis platform classifies multiple accessed data based on the data category identifier, operation type, cache capacity and response time of the cache key, and obtains at least one data group.

[0145] Each data group includes at least one accessed data item. Within the same data group, all accessed data items share the same data category identifier and operation category. Furthermore, the response times for all accessed data items within the same data group fall within the same response time range, and the cache capacities for all accessed data items within the same data group fall within the same cache capacity range.

[0146] S209, For each data group, the data analysis platform determines the number of hits and misses in the access requests corresponding to the data group based on the access results of each accessed data in the data group.

[0147] S210, for each data group, the data analysis platform determines the data category identifier, operation type, number of hits and number of misses corresponding to the data group as a cached evaluation data for the business service program.

[0148] The data analysis platform can also store the identified cached evaluation data locally, or store the cached evaluation data in the target storage area of ​​the target platform, without any restrictions.

[0149] Specifically, if the cached evaluation data is saved to the target storage area of ​​the target platform, this application can retain only the access data of the business service program in the most recent sampling period in the target storage area. However, since the data size of a cached evaluation data is smaller than that of an access data, this application can store the cached evaluation data determined by the business service program in multiple sampling periods, so that the target platform can view the cached evaluation data in different sampling periods at any time.

[0150] It is understood that, in this embodiment, for each sampling period, the data analysis platform can also determine various evaluation indicators based on the cache evaluation data of the business service program within that sampling period, such as determining the cache hit rate of access requests corresponding to different data categories and operation types, and determining the read / write ratio of access requests corresponding to different data categories.

[0151] Of course, the data analysis platform can also determine each evaluation indicator after detecting that the target platform has issued a data analysis request for the business service program, and display each evaluation indicator while showing each cached evaluation data to the target platform, without any specific restrictions.

[0152] Combination Figure 3 The application scenarios shown will be briefly explained.

[0153] Depend on Figure 3 As can be seen, after the sampling code collects the access data, it can store the access data in the original data table of the target storage area of ​​the target platform. When the data analysis platform needs to analyze the access data corresponding to this business service program, it can obtain each access data record in the original data table within the most recent sampling period.

[0154] For each piece of accessed data, the data analytics platform determines the corresponding data category identifier, operation type, cache capacity range, response time range, and the number of hits and misses. This determined data is then stored as a cache evaluation data entry in a new data table. This new data table can be located in the target storage area or locally on the data analytics platform; there are no restrictions.

[0155] Based on this, if the target platform sends a data analysis request for its business service program to the data analysis platform, the data analysis platform will retrieve the cached evaluation data from a new data table that stores the cached evaluation data and output it to the target platform for display. Of course, the data analysis platform can also determine other metrics such as hit rate and read / write ratio based on the cached evaluation data and output them to the target platform, without any specific restrictions.

[0156] In the above embodiments of this application, after determining the cached evaluation data, if the target platform issues a data analysis request for the business service program, the data analysis platform can also combine the cached evaluation data of other business service platforms to determine that there is abnormal cached evaluation data on the business service platform, and mark the abnormal cached evaluation data while outputting each cached evaluation data to the target platform.

[0157] For example, for a combination of data category identifier and data type, the data analysis platform can obtain the average hit count corresponding to this combination of data category identifier and data type in other business service platforms. If the difference between the hit count corresponding to this combination of data category identifier and data type in the business service program and the average hit count exceeds the target count, it can be determined that there is an anomaly in the hit count of the access data containing this data category identifier and data type.

[0158] On the other hand, in accordance with the method for determining cached evaluation data provided in this application, this application also provides a system for determining cached evaluation data.

[0159] like Figure 4 This diagram illustrates a possible architecture of a system for determining cached evaluation data provided in this application. The system in this embodiment may include:

[0160] The data acquisition unit 401 is used to acquire multiple access data of the business service program in the target platform. Each access data corresponds to an access request initiated by the business service program to the cache system of the target platform. The access data includes: the cache key, operation type and access result corresponding to the access request. The cache key is used to identify the cache data to be accessed by the access request, and the access result is used to indicate whether the access request hits the cache system.

[0161] The identifier determination unit 402 is used to determine the data category identifier of the cache key in the access data, wherein the data category identifier is used to characterize the data category to which the cache data identified by the cache key belongs;

[0162] The classification processing unit 403 is used to classify the multiple access data based at least on the data category identifier of the cache key and the operation type to obtain at least one data group. The data group includes at least one access data, and the data category identifier and the operation type corresponding to each access data in the data group are the same.

[0163] The result determination unit 404 is used to determine the number of hits that hit the cache system and the number of misses that do not hit the cache system in the access requests corresponding to the data group based on the access results corresponding to each access data in the data group.

[0164] The data determination unit 405 is used to determine the data category identifier, operation type, number of hits and number of misses corresponding to the data group as a cached evaluation data of the business service program.

[0165] In this application, the above-mentioned data acquisition unit, identification determination unit, classification processing unit, result determination unit, and data determination unit can be deployed in the aforementioned data analysis platform.

[0166] In one possible implementation, the access data obtained by the data acquisition unit further includes: the response time corresponding to the access request;

[0167] This classification processing unit includes:

[0168] The classification processing subunit is used to classify the multiple access data based on the data category identifier, operation type and response time of the cache key, wherein the response time of each access data in the same data group belongs to the same response time range, and the response time ranges of different data groups are different.

[0169] The data determination unit includes:

[0170] The data determination subunit is used to determine the data category identifier, operation type, response time range, number of hits and number of misses corresponding to the data group as a cached evaluation data of the business service program.

[0171] In another possible implementation, the access data also includes: the cache capacity occupied by the cached data to be accessed by the access request;

[0172] Specifically, the classification processing subunit is used to classify the multiple access data based on the data category identifier, operation type, cache capacity and response time of the cache key, wherein the cache capacity corresponding to each access data in the data group belongs to the same cache capacity range.

[0173] The data determination sub-unit is specifically used to determine the data category identifier, operation type, response time range, cache capacity range, number of hits and number of misses corresponding to the data group as a cache evaluation data of the business service program.

[0174] In yet another possible implementation, the system for determining cached evaluation data also includes:

[0175] The indicator determination unit is used to, after the data determination unit determines the cached evaluation data, respond to the data display request initiated by the target platform for the business service program, and determine the hit rate corresponding to the data category identifier and operation type in the cached evaluation data based on the number of hits and misses in the cached evaluation data.

[0176] The data output unit is used to output to the target platform the data category identifier, operation type, number of hits, number of misses, and hit rate of each cached evaluation data corresponding to the business service program.

[0177] In another possible implementation, such as Figure 5 This illustrates another structural diagram of the system for determining cached evaluation data provided in this application, which is related to... Figure 4 The difference between the embodiments is:

[0178] In addition to the aforementioned data acquisition unit 401, identification determination unit 402, classification processing unit 403, result determination unit 404, and data determination unit 405, the system for determining cached evaluation data also includes:

[0179] The interception processing unit 406 is used to detect, through sampling code inserted in the business service program, the access request initiated by the business service program to the cache system before the data acquisition unit obtains multiple access data of the business service program in the target platform, intercept the access request, and determine the cache key and operation type corresponding to the access request;

[0180] The information determination unit 407 is used to determine the access result corresponding to the access request by means of the sampling code in response to the caching system returning a response result for the access request.

[0181] The data storage unit 408 is used to store the cache key, operation type and access result corresponding to the access request as a piece of access data corresponding to the business service program through the sampling code.

[0182] The interception processing unit, information determination unit, and data storage unit can be deployed on the target platform.

[0183] In another possible implementation, the information determining unit is specifically configured to, in response to the caching system returning a response result for the access request, determine the cache key and operation type corresponding to the access request if the access request is determined to be an access request to be sampled based on the sampling rate corresponding to the business service program.

[0184] In yet another possible implementation, the system for determining cached evaluation data also includes:

[0185] The data statistics unit is used to count the cumulative number of access requests initiated by the business service program within the current sampling period after the interception and processing unit detects that the business service program has initiated an access request to the cache system.

[0186] This data acquisition unit includes:

[0187] The data acquisition subunit is used to acquire multiple access data entries from the business service system in the target platform within the most recent sampling period, and to determine the total number of the multiple access data entries.

[0188] The system also includes:

[0189] The sampling rate determination unit is used to determine the target sampling rate based on the expected sampling number and the cumulative number after the data acquisition subunit obtains multiple access data of the business service program in the target platform. If the difference between the total number and the set expected sampling number exceeds a set threshold, the target sampling rate is determined.

[0190] The sampling rate adjustment unit is used to adjust the sampling rate corresponding to the business service program to the target sampling rate.

[0191] In yet another possible implementation, the system for determining the cached evaluation data also includes:

[0192] The code injection unit 409 is used to, in response to the publishing system publishing the business service program to the target platform, obtain the sampling code and inject the sampling code into the business service program before the interception processing unit detects that the business service program has initiated an access request to the caching system through the sampling code.

[0193] Code injection can hopefully be deployed in the deployment system.

[0194] This application also provides a computer program product including computer-readable instructions, which, when executed on an electronic device, cause the electronic device to implement any of the methods for determining cached evaluation data provided in this application.

[0195] This application also provides a computer-readable storage medium carrying one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement any of the methods for determining cached evaluation data provided in this application.

[0196] It should also be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. In addition, in the device embodiment drawings provided in this application, the connection relationship between modules indicates that they have a communication connection, which can be implemented as one or more communication buses or signal lines.

[0197] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware, or it can be implemented by special-purpose hardware including application-specific integrated circuits, special-purpose CPUs, special-purpose memory, special-purpose components, etc. Generally, any function performed by a computer program can be easily implemented by corresponding hardware, and the specific hardware structure used to implement the same function can also be diverse, such as analog circuits, digital circuits, or special-purpose circuits. However, for this application, software program implementation is more often the preferred implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a readable storage medium, such as a computer floppy disk, USB flash drive, mobile hard disk, ROM, RAM, magnetic disk, or optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, training equipment, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0198] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product.

[0199] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, training device, or data center to another website, computer, training device, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a training device or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives (SSDs)).

Claims

1. A method for determining cached evaluation data, characterized in that, include: Obtain multiple access data entries from a business service program on the target platform. Each access data entry corresponds to an access request initiated by the business service program to the caching system of the target platform. The access data includes: the cache key, operation type, and access result corresponding to the access request. The cache key is used to identify the cached data to be accessed by the access request, and the access result is used to indicate whether the access request hits the caching system. Determine the data category identifier of the cache key in the accessed data, wherein the data category identifier is used to characterize the data category to which the cached data identified by the cache key belongs; Based at least on the data category identifier of the cache key and the operation type, the multiple access data are classified to obtain at least one data group. The data group includes at least one access data, and the data category identifier and operation type corresponding to each access data in the data group are the same. Based on the access results corresponding to each access data in the data group, determine the number of hits that hit the cache system and the number of misses that do not hit the cache system in the access requests corresponding to the data group; The data category identifier, operation type, number of hits, and number of misses corresponding to the data group are determined as a cached evaluation data of the business service program.

2. The method for determining cached evaluation data according to claim 1, characterized in that, The access data also includes: the response time corresponding to the access request; The process of classifying the multiple access data based at least on the data category identifier of the cache key and the operation type includes: Based on the data category identifier, operation type, and response duration of the cache key, the multiple access data are classified and processed. Among them, the response durations of each access data in the same data group belong to the same response duration range, and the response duration ranges of different data groups are different. The step of determining the data category identifier, operation type, number of hits, and number of misses corresponding to the data group as a cached evaluation data of the business service program includes: The data category identifier, operation type, response time range, number of hits, and number of misses corresponding to the data group are determined as a cached evaluation data of the business service program.

3. The method for determining cached evaluation data according to claim 2, characterized in that, The access data also includes: the cache capacity occupied by the cached data required by the access request; The process of classifying the multiple access data based on the data category identifier, operation type, and response duration of the cache key includes: Based on the data category identifier, operation type, cache capacity, and response time of the cache key, the multiple access data are classified and processed, wherein the cache capacity corresponding to each access data in the data group belongs to the same cache capacity range; The step of determining the data category identifier, operation type, response time range, number of hits, and number of misses corresponding to the data group as a cached evaluation data of the business service program includes: The data category identifier, operation type, response time range, cache capacity range, number of hits, and number of misses corresponding to the data group are determined as a cache evaluation data of the business service program.

4. The method for determining cached evaluation data according to claim 1, characterized in that, After determining the cache evaluation data, the process also includes: In response to the data display request initiated by the target platform for the business service program, the hit rate corresponding to the data category identifier and operation type in the cached evaluation data is determined based on the number of hits and misses in the cached evaluation data. Output the data category identifier, operation type, number of hits, number of misses, and hit rate of each cached evaluation data corresponding to the business service program to the target platform.

5. The method for determining cached evaluation data according to claim 1, characterized in that, The determination of the data category identifier of the cache key in the accessed data includes at least one of the following: Based on at least one historical data category identifier determined historically, the historical data category identifier that matches the cache key of the accessed data is determined as the data category identifier of the cache key in the accessed data; For at least two access data entries that do not match a historical data category identifier, the data category identifier of each cache key in the at least two access data entries is extracted using an intelligent model based on the cache key of the at least two access data entries.

6. The method for determining cached evaluation data according to claim 1, characterized in that, Before obtaining multiple access data entries from the business service program in the target platform, the method further includes: The sampling code inserted into the business service program detects that the business service program initiates an access request to the cache system, intercepts the access request, and determines the cache key and operation type corresponding to the access request; In response to the caching system returning a response result for the access request, the access result corresponding to the access request is determined by the sampling code; The sampling code stores the cache key, operation type, and access result corresponding to the access request as a single access data entry for the business service program.

7. The method for determining cached evaluation data according to claim 6, characterized in that, Determining the cache key and operation type corresponding to the access request includes: If the access request is determined to be an access request to be sampled based on the sampling rate corresponding to the business service program, the cache key and operation type corresponding to the access request are determined.

8. The method for determining cached evaluation data according to claim 7, characterized in that, After detecting that the business service program has initiated an access request to the caching system, the method further includes: counting the cumulative number of access requests initiated by the business service program within the current sampling period; The acquisition of multiple access data entries from the business service programs on the target platform includes: Obtain multiple access data entries from the business service system on the target platform within the most recent sampling period, and determine the total number of the multiple access data entries; After obtaining multiple access data entries from the business service programs on the target platform, the following is also included: If the difference between the total number and the set expected number of samples exceeds a set threshold, the target sampling rate is determined based on the expected number of samples and the cumulative number. Adjust the sampling rate corresponding to the business service program to the target sampling rate.

9. The method for determining cached evaluation data according to claim 6 or 7, characterized in that, Before detecting the business service program's access request to the caching system through sampling code, the following is also included: In response to the publishing system publishing the business service program to the target platform, the sampling code is obtained and injected into the business service program.

10. A system for determining cached evaluation data, characterized in that, include: The data acquisition unit is used to acquire multiple access data entries of a business service program in the target platform. Each access data entry corresponds to an access request initiated by the business service program to the cache system of the target platform. The access data includes: the cache key, operation type, and access result corresponding to the access request. The cache key is used to identify the cached data to be accessed by the access request, and the access result is used to indicate whether the access request hits the cache system. An identifier determination unit is used to determine the data category identifier of the cache key in the access data, wherein the data category identifier is used to characterize the data category to which the cache data identified by the cache key belongs; A classification processing unit is used to classify the multiple access data based at least on the data category identifier of the cache key and the operation type to obtain at least one data group, wherein the data group includes at least one access data, and the data category identifier and the operation type corresponding to each access data in the data group are the same; The result determination unit is used to determine the number of hits that hit the cache system and the number of misses that do not hit the cache system in the access requests corresponding to the data group based on the access results corresponding to each access data in the data group. The data determination unit is used to determine the data category identifier, operation type, number of hits and number of misses corresponding to the data group as a cached evaluation data of the business service program.

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