Data processing methods, apparatus and equipment

Abstract

This specification discloses a data processing method, apparatus, and device through one or more embodiments. The method includes: receiving first repository information sent by application instances other than a target application instance in an application cluster; the application cluster includes multiple application instances, which are used to load data from the database of the target application to form repository information; constructing a message statistics table based on the received first repository information; the message statistics table includes the number of times the first repository information has been received, where the number of times the first repository information has been received by the target application instance; determining the target repository information that has been received the most times among the first repository information based on the message statistics table; performing a consistency check on the target repository information and second repository information of the target application instance; and performing anomaly detection on the second repository information of the target application instance based on the result of the consistency check.

Description

Technical Field

[0001] This specification relates to the field of data processing technology, and in particular to a data processing method, apparatus and device. Background Technology

[0002] Currently, most applications have servers that use repositories to cache local data. Furthermore, many applications deploy their servers in clusters, forming application clusters. In this deployment scenario, the consistency of repository information loading across multiple application instances is crucial. However, during the repository information loading process, inconsistencies may occur for various reasons. Although this is a low-probability event, its occurrence can have serious consequences, leading to online failures and impacting user experience. Therefore, ensuring the consistency of repository information loading has become an urgent problem to be solved.

[0003] To address this, current solutions rely on external systems to verify the consistency of warehouse information. However, this increases the cost of verification, and system failures can prevent the verification process from proceeding. Therefore, there is an urgent need for a more reliable solution for verifying warehouse information consistency. Summary of the Invention

[0004] On one hand, one or more embodiments of this specification provide a data processing method, including: receiving first repository information sent by application instances other than a target application instance in an application cluster, the application cluster including multiple application instances, the application instances being used to load data from the database of the target application to form repository information; constructing a message statistics table based on the received first repository information, the message statistics table including the number of times the first repository information was received, the number of times the first repository information was received by the target application instance; determining the target repository information with the most received times among the first repository information based on the message statistics table; performing a consistency check on the target repository information and second repository information of the target application instance; and performing anomaly detection on the second repository information of the target application instance based on the result of the consistency check.

[0005] On the other hand, one or more embodiments of this specification provide a data processing apparatus, comprising: a receiving module, configured to receive first repository information sent by application instances other than a target application instance in an application cluster, the application cluster including multiple application instances, the application instances being used to load data from the database of the target application to form repository information; a construction module, configured to construct a message statistics table based on the received first repository information, the message statistics table including the number of times the first repository information was received, the number of times the first repository information was received by the target application instance; a determining module, configured to determine the target repository information with the most received times among the first repository information based on the message statistics table; a consistency verification module, configured to perform consistency verification between the target repository information and second repository information of the target application instance; and an anomaly detection module, configured to perform anomaly detection on the second repository information of the target application instance based on the result of the consistency verification.

[0006] Furthermore, one or more embodiments of this specification provide a data processing device, including a processor and a memory electrically connected to the processor. The memory stores a computer program, and the processor is configured to call and execute the computer program from the memory to: receive first repository information sent by other application instances besides a target application instance in an application cluster, the application cluster including multiple application instances, the application instances being used to load data from the database of the target application to form repository information; construct a message statistics table based on the received first repository information, the message statistics table including the number of times the first repository information was received, the number of times the first repository information was received by the target application instance; determine the target repository information with the most received times among the first repository information based on the message statistics table; perform a consistency check on the target repository information and the second repository information of the target application instance; and perform anomaly detection on the second repository information of the target application instance based on the result of the consistency check.

[0007] Furthermore, embodiments of this specification provide a storage medium for storing a computer program that can be executed by a processor to implement the following process: receiving first repository information sent by application instances other than a target application instance in an application cluster, the application cluster including multiple application instances, the application instances being used to load data from the database of the target application to form repository information; constructing a message statistics table based on the received first repository information, the message statistics table including the number of times the first repository information was received, the number of times the first repository information was received by the target application instance; determining the target repository information with the most received times among the first repository information based on the message statistics table; performing a consistency check on the target repository information and the second repository information of the target application instance; and performing anomaly detection on the second repository information of the target application instance based on the result of the consistency check. Attached Figure Description

[0008] To more clearly illustrate the technical solutions in one or more embodiments of this specification or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in one or more embodiments of this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0009] Figure 1 This is a schematic diagram of a warehouse information consistency verification method in related technologies;

[0010] Figure 2 This is a schematic diagram of another warehouse information consistency verification method in related technologies;

[0011] Figure 3 This is a schematic block diagram of a data processing system according to an embodiment of this specification;

[0012] Figure 4 This is a schematic flowchart of a data processing method according to an embodiment of this specification;

[0013] Figure 5 This is a schematic block diagram of the data structure of a message statistics table according to an embodiment of this specification;

[0014] Figure 6 This is a schematic swimlane diagram of a data processing method according to an embodiment of this specification;

[0015] Figure 7 This is a schematic block diagram of a data processing apparatus according to an embodiment of this specification;

[0016] Figure 8This is a schematic diagram of the structure of a data processing device according to an embodiment of this specification. Detailed Implementation

[0017] This specification provides one or more embodiments of a data processing method, apparatus, and device to solve the problem of unreliability in existing warehouse information consistency verification methods.

[0018] To enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of one or more embodiments of this specification.

[0019] Currently, most applications have servers that use repositories to cache local data. Furthermore, many applications deploy their servers in clusters, forming application clusters. In this deployment scenario, ensuring the consistency of repository information loading across multiple application instances of the same application is crucial. However, during the repository information loading process, inconsistencies may occur for various reasons. Although this is a low-probability event, it can have serious consequences, leading to online failures and impacting user experience. Therefore, ensuring the consistency of repository information loading has become an urgent problem to be solved.

[0020] To address this, two schemes for consistency verification of warehouse information have been proposed in related technologies. One scheme is as follows: Figure 1 As shown, consistency checks on warehouse information are triggered either by scheduled tasks or manually via DRM (Distributed Resource Management, dynamic configuration). Each application instance 110 ( Figure 1The diagram schematically illustrates application instance 1, application instance 2, and application instance N. Other application instances between application instance 2 and application instance N are represented by "...". It should be understood that the consistency verification process performed within each application instance is similar. Data is loaded from the application's database 120 into the application instance's JVM (Java Virtual Machine) to form a temporary repository. The consistency verification result is obtained by comparing the already loaded repository information with the temporary repository. This approach, because a temporary repository needs to be generated for each verification, results in high server memory consumption, potentially causing server instability. Furthermore, with a large number of application instances, loading numerous temporary repositories from the database can also cause database instability. In addition, the loading of temporary repositories may also be problematic, leading to inaccurate consistency verification results for the repository information.

[0021] Another option is as follows Figure 2 As shown, a centralized temporary repository 210 is built using Redis (Remote Dictionary Server), and various application instances 220 ( Figure 2 The diagram schematically illustrates application instance 1, application instance 2, and application instance N. Other application instances between application instance 2 and application instance N are represented by "...". It should be understood that the consistency verification process performed within each application instance is similar. The diagram compares the already loaded repository information with the centralized temporary repository 210 to obtain the consistency verification result of the repository information. While this method eliminates the need for each application instance to load the temporary repository, reducing server-side resource overhead, it increases the cost of repository information consistency verification due to the introduction of an external system (i.e., the centralized temporary repository). Furthermore, because it relies on an external system, if the external system fails, the repository information consistency verification cannot be performed, thus making this method of repository information consistency verification less reliable. Therefore, embodiments of this specification provide a data processing method, apparatus, and device.

[0022] Figure 3 This is a schematic block diagram of a data processing system according to an embodiment of this specification, which includes multiple application instances 310. Figure 3 The diagram schematically illustrates application instance 1, application instance 2, and application instance N. Multiple application instances 310 belong to one or more servers within an application cluster. These one or more servers are servers for the same application (the target application in this embodiment), meaning that multiple application instances 310 belong to the same application.

[0023] Each application instance 310 loads data from the target application's database to form repository information. In the embodiments of this specification, the target application can be of any type, and this specification does not limit this. Repository information is a general term for caching local data in program design; simply put, it is caching. After the application instances in the application cluster load data from the target application's database to form repository information, they can determine the first repository information corresponding to the repository information and send the first repository information to other application instances in the application cluster via a multicast protocol.

[0024] In this embodiment, the target application instance (i.e., any one of the multiple application instances 310) among the multiple application instances 310 can receive first repository information sent by other application instances in the application cluster besides the target application instance. Based on the received first repository information, a message statistics table is constructed. The message statistics table includes the number of times the first repository information has been received, which is the number of times the first repository information has been received by the target application instance. Therefore, based on the message statistics table, the target repository information with the most received first repository information is determined. A consistency check is then performed between the target repository information and the second repository information of the target application instance. Furthermore, based on the consistency check result, anomaly detection is performed on the second repository information of the target application instance. It should be understood that the consistency check process performed within each application instance is similar.

[0025] In one embodiment, the application cluster is associated with monitoring system 320. For example... Figure 3 As shown, the monitoring system 320 can obtain monitoring logs from each application instance 310. For example, the monitoring logs may contain anomaly alerts sent by application instance 1 indicating that its storage information is abnormal.

[0026] The following details the specific operations performed by the target application instance (i.e., any one of the multiple application instances 310) in the data processing system during the data processing process. Figure 4 This is a schematic flowchart illustrating a data processing method according to an embodiment of this specification. In this embodiment, the data processing method is applied to, for example... Figure 3 The target application instances shown in the diagram are included in the application cluster. These target application instances are used to load data from the database of the target application to form repository information.

[0027] like Figure 4 As shown, the method may include:

[0028] S402, receives first storage information sent by other application instances besides the target application instance in the application cluster.

[0029] In the embodiments of this specification, the storage information loaded by other application instances is collectively referred to as the first storage information. For example, other application instances include application instance 2 and application instance 3. Application instance 2 loads storage information 1 and storage information 2, and application instance 3 loads storage information 1 and storage information 3. Then, storage information 1, storage information 2, and storage information 3 are collectively referred to as the first storage information. That is to say, the first storage information includes multiple storage information entries.

[0030] Optionally, the first repository information may include device identification information of the device sending the first repository information, repository type of the first repository information, repository information summary, and timestamp of sending the first repository information. The device identification information of the device sending the first repository information may be the identification information of the server to which the application instance sending the first repository information belongs, such as the server IP (Internet Protocol). The repository type of the first repository information is related to its content. For example, if the content of the first repository information is user data, then the repository type is user-type repository; similarly, if the content of the first repository information is server data, then the repository type is server-type repository. The repository information summary can be obtained by processing the first repository information using a preset summary generation method, such as MD5 (Message-Digest Algorithm 5). In the embodiments of this specification, the repository information summary can be used to determine whether the contents of any two pieces of the first repository information are the same. Regarding the timestamp for sending the first repository information, if the current application instance periodically sends the first repository information to other application instances, then this first repository information may include multiple repository information loaded by the current application instance. In this case, the sending time of multiple repository information is consistent, all being the timestamp for sending this first repository information. If the current application instance sends the first repository information to other application instances in real time, then this first repository information will include one repository information loaded by the current application instance, and the sending time of this repository information will be the timestamp for sending this first repository information.

[0031] S404, Based on the received first storage information, construct a message statistics table. The message statistics table includes the number of times the first storage information was received, which is the number of times the first storage information was received by the target application instance.

[0032] Since the first repository information is a collective term for repository information loaded by other application instances, meaning the first repository information includes multiple repository information entries with identical or different content, if the received first repository information is not organized, information redundancy will occur, consuming server-side cache resources and hindering the target application instance from using the first repository information to perform self-verification of repository information consistency in subsequent steps. Therefore, this embodiment constructs a message statistics table based on the received first repository information, realizing statistical processing of the received first repository information, which helps avoid information redundancy and facilitates the target application instance's self-verification of repository information consistency in subsequent steps.

[0033] Specifically, the number of times the first warehouse information is received includes the number of times warehouse information with different content is received. The number of times warehouse information is received can be obtained by directly adding the newly received warehouse information with the same content as the warehouse information already counted in the message statistics table as one count to the warehouse information already counted in the message statistics table.

[0034] S406, Based on the message statistics table, determine the target warehouse information that has been received the most times in the first warehouse information.

[0035] S408 performs a consistency check on the target warehouse information and the second warehouse information of the target application instance.

[0036] It should be noted that in the embodiments of this specification, "first repository information" refers to repository information received by the target application instance and loaded by other application instances, and "second repository information" refers to repository information loaded by the target application instance. The terms "first," "second," etc., are used to distinguish similar objects and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate so that the embodiments of this specification can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited. For example, there may be one or more first repository information.

[0037] S410, based on the consistency verification results, performs anomaly detection on the second storage information of the target application instance.

[0038] By employing one or more embodiments of the technical solution described in this specification, first repository information is received from application instances other than the target application instance in an application cluster. In this technical solution, the application cluster includes multiple application instances, each of which can load data from the database of the target application to form repository information. Therefore, this technical solution can send the repository information already loaded by each application instance of the same application to other application instances in the application cluster of that application. Consequently, the target application instance can construct a message statistics table based on the received first repository information. The message statistics table includes the number of times the first repository information has been received, where the number of receptions represents the number of times the first repository information has been received by the target application instance. The system calculates the number of times a message is received and, based on the message statistics table, identifies the target warehouse information that receives the most messages in the first warehouse information. It then performs a consistency check on the target warehouse information and the second warehouse information of the target application instance. Based on the consistency check results, it performs anomaly detection on the second warehouse information of the target application instance. This achieves a self-checking effect of warehouse information consistency through comparison between application instances, avoiding reliance on external systems to verify warehouse information consistency. This decentralized warehouse information consistency check scheme ensures that the consistency check process is no longer affected by external system failures, thus achieving a more reliable warehouse information consistency check scheme. Furthermore, since the repository information is only sent to the target application instance after other application instances load data to form the repository information, the target repository information that the target application instance receives the most times is the repository information that has been loaded by the most application instances in the application cluster. Compared with other repository information, this repository information has a lower probability of being abnormal and a higher reliability. In the process of self-verification of repository information consistency, this technical solution uses the target repository information, which has a lower probability of being abnormal and a higher reliability, to perform consistency verification with the repository information of the current application instance, rather than using any repository information received by the current application instance. This avoids the occurrence of random events, makes the consistency verification result more reliable, improves the reliability of the self-verification process of repository information consistency, and thus makes the anomaly detection of the repository information of the current application instance more accurate.

[0039] In one embodiment, after an application instance in the application cluster loads data from the database of the target application to form repository information, it can determine the first repository information corresponding to the repository information and send the first repository information to other application instances in the application cluster through a multicast protocol.

[0040] One approach is to determine the multicast group of the target application by setting the same multicast address for each server corresponding to the target application in the application cluster. This allows each application instance of the target application to send the first repository information to other application instances in the multicast group via the multicast protocol.

[0041] Optionally, the first repository information generated by the application instance can be sent directly or periodically to other application instances in the application cluster via a multicast protocol. The first repository information may include the device identifier information sending the repository information, the repository type, the repository information digest, and the timestamp of the repository information. The device identifier information sending the repository information can be the identifier information of the server to which the application instance sending the repository information belongs, such as the server IP address. The repository type is related to the content of the repository information. The repository information digest can be obtained by processing the repository information using a preset digest generation method, such as MD5. The timestamp of the repository information is the timestamp of the first repository information being sent.

[0042] For example, if application instance 1 loads 3 repositories, including repositories 1, 2 and 3, and after the repositories are loaded, the first repositories are generated periodically and sent to other application instances. In this application instance, the server IP is "192.168.34.5", the timestamp for sending the first repository information is 1669278242000, the repository type (repositoryType) for repository information 1 is type1, and the repository digest is "E47CBC7F862B0C1AE0C65922CEE8427E". The repository type for repository information 2 is type2, and the repository digest is "8CC6275DA914C22D71A29B097F68F642". The repository type for repository information 3 is typeN, and the repository digest is "DD84AA9AEB750A102FC212F13DDEB470". Therefore, the data structure for the first repository information sent by application instance 1 to other application instances in the application cluster can be as follows:

[0043] {

[0044] IP address: 192.168.34.5

[0045] "timeStamp":1669278242000,

[0046] “repositories”:{

[0047] {

[0048] "repositoryType":"type1",

[0049] "repositoryDigest":"E47CBC7F862B0C1AE0C65922CEE8427E"

[0050] },

[0051] {

[0052] "repositoryType":"type2",

[0053] "repositoryDigest":"8CC6275DA914C22D71A29B097F68F642"

[0054] },

[0055] {

[0056] "repositoryType":"typeN",

[0057] "repositoryDigest":"DD84AA9AEB750A102FC212F13DDEB470"

[0058] }

[0059] }

[0060] }

[0061] In this embodiment, the storage information loaded by each application instance is sent to the multicast group of the application through the multicast protocol, providing a data foundation for self-verification of storage information consistency by comparing storage information between application instances.

[0062] In one embodiment, the first storage information may include the device identification information that sent the first storage information, the storage type of the first storage information, and a storage information summary. Based on the received first storage information, a message statistics table is constructed (i.e., S404), which can be performed as follows: steps A1-A3:

[0063] Step A1: Based on the received warehouse information summary of the first warehouse information, count the number of times the warehouse information summary has been received.

[0064] The first warehouse information summary is obtained by processing the first warehouse information using a preset summary generation method. Therefore, if other embodiments load warehouse information with the same content and send it to the target embodiment after processing it using the preset summary generation method, the target embodiment will receive multiple first warehouse information messages with identical summaries. To avoid information redundancy, the first warehouse information messages corresponding to the same summary can be merged and counted in a message statistics table, i.e., the counts are accumulated, thereby achieving statistical processing of the received first warehouse information.

[0065] For example, regarding the first warehouse information received by the target application instance, which has a warehouse information digest of "8CC6275DA914C22D71A29B097F68F642" sent by application instance 1, a warehouse information digest of "8CC6275DA914C22D71A29B097F68F642" sent by application instance 2, and a warehouse information digest of "E47CBC7F862B0C1AE0C65922CEE8427E" sent by application instance 3... The first warehouse information includes the warehouse information sent in application example 4 with a warehouse information summary of "8CC6275DA914C22D71A29B097F68F642", the warehouse information sent in application example 5 with a warehouse information summary of "E47CBC7F862B0C1AE0C65922CEE8427E", and the warehouse information sent in application example 6 with a warehouse information summary of "DD84AA9AEB750A102FC212F13DDEB470". Based on the different warehouse information digests, it can be determined that the warehouse information digest "8CC6275DA914C22D71A29B097F68F642" was received 3 times, the warehouse information digest "E47CBC7F862B0C1AE0C65922CEE8427E" was received 2 times, and the warehouse information digest "DD84AA9AEB750A102FC212F13DDEB470" was received 1 time.

[0066] Step A2: Determine the number of times the warehouse information summary is received as the number of times the first warehouse information is received.

[0067] Since the warehouse information summary is obtained by processing the first warehouse information through a preset summary generation method, the number of times the warehouse information summary is received is actually the number of times the first warehouse information corresponding to the warehouse information summary is received.

[0068] Step A3: Construct a message statistics table based on the storage type of the first storage information, the storage information summary of the first storage information, the number of times the first storage information is received, and the device identification information that sent the first storage information.

[0069] In this embodiment, for different first storage information with the same storage information summary, the number of times is counted and entered into the message statistics table instead of being directly written into the message statistics table. This simplifies the message statistics table, avoids information redundancy, and facilitates the self-verification of storage information consistency by the target application instance using the first storage information in subsequent steps.

[0070] In one embodiment, constructing a message statistics table based on the storage type of the first storage information, the storage information summary of the first storage information, the number of times the first storage information is received, and the device identification information of the device sending the first storage information (i.e., step A3) can be performed as follows: using the storage type of the first storage information as the key of the message statistics table, and using the storage information summary of the first storage information, the number of times the first storage information is received, and the device identification information of the device sending the first storage information to construct the value of the message statistics table, so as to generate the message statistics table.

[0071] Specifically, the values ​​in the message statistics table are constructed using the storage information summary of the first storage information as the nesting key and the number of times the first storage information is received and the device identification information that sent the first storage information as the nesting value.

[0072] For example, the data structure of the message statistics table is as follows: Figure 5 As shown, repositoryType is the key of the message statistics table, and repositoryDigest is the repository information digest, and the number of times the first repository information was received (i.e., Figure 5 The number of votes (vote) shown in the warehouse information summary and the device identification information (i.e., the device that sent the first warehouse information) are also included. Figure 5 The list of IP devices voting (List) is the value of the message statistics table, and the repository digest is the nested key within the value. The vote count (vote) and the list of IP devices voting (List) are nested values ​​within the value. In applications such as... Figure 5 When retrieving the first warehouse information from the message statistics table shown, you can first search by warehouse type. For multiple values ​​corresponding to a warehouse type, you can search by warehouse information summary to obtain the number of votes and the list of voting devices corresponding to each warehouse information summary.

[0073] In this embodiment, the message statistics table is constructed using a key-value nesting method, which facilitates quick retrieval of data from the message statistics table and improves the efficiency of self-verification of warehouse information consistency.

[0074] In one embodiment, the target application instance is configured with a scheduled verification task. Based on the message statistics table, the target repository information that has been received most frequently in the first repository information is determined. A consistency verification (i.e., S406-S408) is performed between the target repository information and the second repository information of the target application instance, which can be executed as follows: steps B1-B3:

[0075] Step B1: In response to the timed verification task corresponding to the target application instance, determine the target warehouse information digest with the most reception times under each warehouse type based on the warehouse type of the first warehouse information, the warehouse information digest of the first warehouse information, and the number of times the first warehouse information is received.

[0076] Since an application can load multiple different types of repository information simultaneously, the consistency of repository information for each type cannot be guaranteed during the self-verification process if the repository type is not considered. To address this, this technical solution identifies the target repository information digest that has been received most frequently within each repository type. This means it identifies the repository information loaded by the largest number of application instances in the application cluster. Compared to other repository information, this information is less likely to be abnormal and has higher reliability, providing a better data foundation for the self-verification process.

[0077] Step B2: Determine the storage information summary corresponding to the second storage information of the target application instance based on the summary generation method consistent with that used to generate the storage information summary of the first storage information.

[0078] Since the message statistics table counts the storage information summary of the first storage information, this technical solution uses the same summary generation method as that used to generate the storage information summary of the first storage information to determine the storage information summary corresponding to the second storage information of the target application instance. This is beneficial for comparing the storage information summary corresponding to the second storage information with the storage information summary retrieved from the message statistics table during the storage information consistency self-verification process, thereby quickly determining whether the two are consistent.

[0079] Step B3: For each warehouse type, perform a consistency check on the target warehouse information digest and the warehouse information digest corresponding to the target application instance.

[0080] Optionally, each application instance in the application cluster has its own scheduled verification task. The timing interval of each application instance's scheduled verification task can be the same as or different from that of other application instances. In practical applications, if the timing intervals are the same, the target storage information determined by multiple application instances may be consistent, leading to repeated verification of the consistency of the same storage information by application instances. Therefore, the timing intervals can be set differently to avoid repeated verification of the consistency of the same storage information.

[0081] In this embodiment, by identifying the most frequently received warehouse information digest for each warehouse type and comparing its consistency with the warehouse information digest already loaded by the target application instance, it is beneficial to determine the consistency of warehouse information for each warehouse type, thereby helping to ensure the consistency of warehouse information loaded by the application instance for each warehouse type.

[0082] In one embodiment, based on the consistency check result, anomaly detection (i.e., S410) is performed on the second repository information of the target application instance, which can be executed as follows: C1-C3:

[0083] Step C1: If the consistency check result is successful, then the second storage information of the target application instance is loaded normally.

[0084] Step C2: If the consistency check fails, determine whether the target application instance has loaded new repository information after the scheduled check task started.

[0085] In this embodiment, since the target application instance continues to load repository information in real time after the scheduled verification task begins, the repository information may be updated, potentially causing verification failure. Therefore, this technical solution treats newly loaded repository information as correctly loaded repository information if it is determined that the target application instance has loaded new repository information after the scheduled verification task begins. Optionally, the newly loaded repository information can be sent to each application instance within the application cluster, allowing each application instance to update its already loaded repository information based on this correctly loaded repository information, thereby ensuring the consistency and integrity of the repository information loaded by multiple application instances within the application cluster.

[0086] Step C3: If it is determined that the target application instance has not loaded any new repository information after the scheduled verification task starts, then the second repository information loading of the target application instance is determined to be abnormal, and an abnormal alarm message is sent to the monitoring system associated with the application cluster.

[0087] In this embodiment, based on the consistency verification results of the target storage information and the second storage information of the target application instance, if the verification fails, it can further determine whether the target application instance has newly loaded storage information after the start of the timed verification task. This avoids misjudgment caused by the update of the storage information of the target application instance, effectively ensuring the accuracy of the judgment on whether the storage information of the target application instance is abnormal. This is beneficial for technicians to perform accurate maintenance on the server to which the application instance belongs based on the abnormal alarm information received by the monitoring system.

[0088] In one embodiment, the first repository information includes a timestamp of the first repository information being sent. After determining that the second repository information of the target application instance is loaded normally (i.e., step C1), the following can be performed: the second repository information is sent to each application instance in the application cluster. The application instances are used to update the loaded repository information according to the second repository information, and based on the timestamp of the first repository information being sent and the start time of the scheduled verification task, the first repository information received before the start of the scheduled verification task is removed from the message statistics table.

[0089] In this embodiment, by sending the correctly loaded second repository information to each application instance within the application cluster, each application instance updates its own loaded repository information based on this correctly loaded repository information. This helps ensure the consistency and integrity of the repository information loaded by multiple application instances within the application cluster. Furthermore, after the target application instance sends the correctly loaded repository information to each application instance within the application cluster, it can remove the first repository information received before the start of the scheduled verification task from the message statistics table. Since this part of the first repository information is data that has already been used during the repository information consistency self-verification process, it is not very meaningful to continue retaining it. Therefore, removing this part of the first repository information will not affect the repository information consistency self-verification process and can save server-side cache resources.

[0090] The data processing method provided in this specification is illustrated below through a specific application scenario. In this embodiment, the application cluster includes application instance 1, application instance 2, application instance 3, and application instance 4. Application instance 1, application instance 2, application instance 3, and application instance 4 belong to the same application, and the server to which each application instance belongs is not limited in this embodiment. Each application instance is used to load data from the database of the target application to form repository information, determine the first repository information corresponding to the repository information, and send the first repository information to other application instances in the application cluster through a multicast protocol. The application cluster is associated with a monitoring system. Specifically, the monitoring system can obtain monitoring logs from each application instance. The monitoring logs are, for example, abnormal alarm information sent by application instance 4 indicating that its repository information is abnormal. It should be understood that the consistency verification process executed within each application instance is similar. This embodiment uses the consistency verification process in application instance 4 as an example for illustration, while application instance 1, application instance 2, and application instance 3 are other application instances. Figure 6 The illustrated embodiment uses this scenario as an example for explanation.

[0091] Figure 6 This is a schematic swimlane diagram illustrating a data processing method according to an embodiment of this specification. Figure 6 As shown, the data processing method may include the following steps S6.1-S6.11:

[0092] S6.1, other application instances in the application cluster send the first storage information to application instance 4.

[0093] The first storage information may include the device identification information that sent the first storage information, the storage type of the first storage information, the storage information summary, and the timestamp of the first storage information.

[0094] S6.2, Application Example 4 constructs a message statistics table based on the received first storage information. The message statistics table includes the number of times the first storage information was received, which is the number of times the first storage information was received by the target application instance.

[0095] In application example 4, the number of times the warehouse information summary is received can be counted based on the warehouse information summary of the received first warehouse information. The number of times the warehouse information summary is received can be determined as the number of times the first warehouse information is received. Then, a message statistics table can be constructed based on the warehouse type of the first warehouse information, the warehouse information summary of the first warehouse information, the number of times the first warehouse information is received, and the device identification information of the device that sent the first warehouse information.

[0096] S6.3, Application Example 4 responds to the set timed verification task, and determines the target warehouse information digest with the most received times under each warehouse type based on the warehouse type, warehouse information digest of the first warehouse information, and the number of times the first warehouse information is received in the message statistics table.

[0097] S6.4, Application Example 4 determines the warehouse information summary corresponding to the second warehouse information of the target application instance based on the summary generation method consistent with the warehouse information summary generated by the first warehouse information.

[0098] S6.5, Application Example 4: For each warehouse type, perform a consistency check on the target warehouse information digest and the warehouse information digest corresponding to the target application instance. If the consistency check passes, proceed to S6.6; if the consistency check fails, proceed to S6.9.

[0099] S6.6, Application Example 4 confirms that the second warehouse information of the target application instance is loaded normally.

[0100] S6.7, Application Example 4 sends the second warehouse information to other application examples.

[0101] Other application instances are used to update the loaded storage information based on the second storage information.

[0102] S6.8, Application Example 4: Based on the timestamp of the first storage information sent and the start time of the scheduled verification task, remove the first storage information received before the start of the scheduled verification task from the message statistics table.

[0103] S6.9, Application Example 4: Determine whether new warehouse information has been loaded after the scheduled verification task starts; if not, execute S6.10; if yes, execute S6.11.

[0104] S6.10, Application Instance 4 determines that the second warehouse information loading of the target application instance is abnormal and sends an abnormal alarm message to the monitoring system.

[0105] S6.11, Application Instance 4 sends the newly loaded warehouse information as normally loaded warehouse information to other application instances.

[0106] Other application instances are used to update their own loaded repository information based on this successfully loaded repository information, thereby ensuring the consistency and integrity of the repository information loaded by multiple application instances within the application cluster.

[0107] The specific processes of S6.1-S6.11 described above have been explained in detail in the above embodiments and will not be repeated here.

[0108] By employing the technical solutions of one or more embodiments of this specification, the warehousing information already loaded by each application instance of the same application can be sent to other application instances in the application cluster of that application. This facilitates self-verification of warehousing information consistency by comparing warehousing information between application instances, avoiding reliance on external systems to verify whether warehousing information is consistent. This achieves a decentralized warehousing information consistency verification scheme, ensuring that the warehousing information consistency verification process is no longer affected by external system failures, thus realizing a more reliable warehousing information consistency verification scheme. Furthermore, since the repository information is only sent to the target application instance (i.e., any application instance in the application cluster, such as application instance 4) after other application instances load data to form the repository information, the target repository information that the target application instance receives the most times is the repository information that has been loaded by the most application instances in the application cluster. Compared with other repository information, this repository information has a lower probability of being abnormal and a higher reliability. In the process of self-verification of repository information consistency, this technical solution uses the target repository information with a lower probability of being abnormal and a higher reliability to perform consistency verification with the repository information of the current application instance, rather than using any repository information received by the current application instance. This avoids the occurrence of accidental events, makes the consistency verification result more reliable, improves the reliability of the self-verification process of repository information consistency, and thus makes the anomaly detection of the repository information of the current application instance more accurate. Furthermore, by sending the properly loaded repository information to every application instance within the application cluster, each application instance can update its own loaded repository information based on this properly loaded repository information. This helps ensure the consistency and integrity of the repository information loaded by multiple application instances within the application cluster. Moreover, after the target application instance sends the properly loaded repository information to every application instance within the application cluster, the first repository information received before the start of the scheduled verification task in the message statistics table can be removed. Since this first repository information is data that has already been used during the repository information consistency self-verification process, it is not very meaningful to continue retaining it. Therefore, removing this first repository information will not affect the repository information consistency self-verification process and can save server-side cache resources.

[0109] In summary, specific embodiments of this subject matter have been described. Other embodiments are within the scope of the appended claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing can be advantageous.

[0110] The above describes a data processing method provided by one or more embodiments of this specification. Based on the same idea, one or more embodiments of this specification also provide a data processing device.

[0111] Figure 7 This is a schematic block diagram of a data processing apparatus according to an embodiment of this specification. Please refer to... Figure 7 The data processing device may include:

[0112] The receiving module 710 is used to receive first repository information sent by other application instances besides the target application instance in the application cluster; the application cluster includes multiple application instances, which are used to load data from the database of the target application to form repository information;

[0113] Module 720 is used to build a message statistics table based on the received first storage information; the message statistics table includes the number of times the first storage information is received, which is the number of times the first storage information is received by the target application instance;

[0114] The determination module 730 is used to determine the target warehouse information that has been received the most times in the first warehouse information based on the message statistics table;

[0115] The consistency verification module 740 is used to perform consistency verification between the target warehouse information and the second warehouse information of the target application instance.

[0116] The anomaly detection module 750 is used to perform anomaly detection on the second storage information of the target application instance based on the consistency verification results.

[0117] In one embodiment, the first storage information includes device identification information for sending the first storage information, storage type of the first storage information, and storage information summary; the construction module 720 includes:

[0118] The statistics unit is used to count the number of times the warehouse information summary is received based on the warehouse information summary of the first warehouse information received;

[0119] The first determining unit is used to determine the number of times the warehouse information summary is received as the number of times the first warehouse information is received;

[0120] The construction unit is used to construct a message statistics table based on the storage type of the first storage information, the storage information summary of the first storage information, the number of times the first storage information is received, and the device identification information that sends the first storage information.

[0121] In one embodiment, the building unit is specifically used for:

[0122] The message statistics table is generated by using the storage type of the first storage information as the key and constructing the values ​​of the message statistics table with the storage information summary of the first storage information, the number of times the first storage information is received, and the device identification information that sent the first storage information.

[0123] Specifically, the values ​​in the message statistics table are constructed using the storage information summary of the first storage information as the nesting key and the number of times the first storage information is received and the device identification information that sent the first storage information as the nesting value.

[0124] In one embodiment, the target application instance is configured with a scheduled verification task; the determination module 730 and the consistency verification module 740 include:

[0125] The second determining unit is used to respond to the timed verification task corresponding to the target application instance, and determine the target warehouse information digest with the most received times under each warehouse type based on the warehouse type of the first warehouse information, the warehouse information digest of the first warehouse information, and the number of times the first warehouse information is received.

[0126] The third determining unit is used to determine the warehouse information summary corresponding to the second warehouse information of the target application instance based on the summary generation method consistent with the warehouse information summary that generates the first warehouse information;

[0127] The consistency verification unit is used to perform consistency verification between the target warehouse information digest and the warehouse information digest corresponding to the target application instance for each warehouse type.

[0128] In one embodiment, the anomaly detection module 750 includes:

[0129] The fourth determining unit is used to determine that the second storage information of the target application instance is loaded normally if the consistency verification result is that the verification passes.

[0130] The fifth determining unit is used to determine whether the target application instance has newly loaded the storage information after the scheduled verification task starts if the consistency verification result is that the verification fails.

[0131] The determination and sending unit is used to determine if the second repository information loading of the target application instance is abnormal, and to send the abnormal alarm information to the monitoring system associated with the application cluster if the condition is not met.

[0132] In one embodiment, the first storage information further includes a timestamp of the time the first storage information was sent; the anomaly detection module 750 further includes:

[0133] The sending unit is used to send the second repository information to each application instance in the application cluster after determining that the second repository information of the target application instance is loaded normally. The application instances are used to update the loaded repository information according to the second repository information.

[0134] The removal unit is used to remove the first storage information received before the start of the timed verification task from the message statistics table based on the timestamp of the first storage information sent and the start time of the timed verification task.

[0135] In one embodiment, after an application instance in the application cluster loads data from the database of the target application to form repository information, it determines the first repository information corresponding to the repository information and sends the first repository information to other application instances in the application cluster via a multicast protocol.

[0136] By employing one or more embodiments of the technical solution described in this specification, first repository information is received from application instances other than the target application instance in an application cluster. In this technical solution, the application cluster includes multiple application instances, each of which can load data from the database of the target application to form repository information. Therefore, this technical solution can send the repository information already loaded by each application instance of the same application to other application instances in the application cluster of that application. Consequently, the target application instance can construct a message statistics table based on the received first repository information. The message statistics table includes the number of times the first repository information has been received, where the number of receptions represents the number of times the first repository information has been received by the target application instance. The system calculates the number of times a message is received and, based on the message statistics table, identifies the target warehouse information that receives the most messages in the first warehouse information. It then performs a consistency check on the target warehouse information and the second warehouse information of the target application instance. Based on the consistency check results, it performs anomaly detection on the second warehouse information of the target application instance. This achieves a self-checking effect of warehouse information consistency through comparison between application instances, avoiding reliance on external systems to verify warehouse information consistency. This decentralized warehouse information consistency check scheme ensures that the consistency check process is no longer affected by external system failures, thus achieving a more reliable warehouse information consistency check scheme. Furthermore, since the repository information is only sent to the target application instance after other application instances load data to form the repository information, the target repository information that the target application instance receives the most times is the repository information that has been loaded by the most application instances in the application cluster. Compared with other repository information, this repository information has a lower probability of being abnormal and a higher reliability. In the process of self-verification of repository information consistency, this technical solution uses the target repository information, which has a lower probability of being abnormal and a higher reliability, to perform consistency verification with the repository information of the current application instance, rather than using any repository information received by the current application instance. This avoids the occurrence of random events, makes the consistency verification result more reliable, improves the reliability of the self-verification process of repository information consistency, and thus makes the anomaly detection of the repository information of the current application instance more accurate.

[0137] Those skilled in the art will understand that the above-described data processing apparatus can be used to implement the data processing method described above, and the detailed description therein should be similar to the description in the method section above. To avoid being cumbersome, it will not be repeated here.

[0138] Based on the same idea, one or more embodiments of this specification also provide a data processing device, such as... Figure 8As shown. Data processing devices can vary considerably depending on configuration or performance, and may include one or more processors 801 and memory 802. Memory 802 may store one or more application programs or data. Memory 802 may be temporary or persistent storage. The application programs stored in memory 802 may include one or more modules (not shown), each module including a series of computer-executable instructions for the data processing device. Furthermore, processor 801 may be configured to communicate with memory 802 and execute the series of computer-executable instructions in memory 802 on the data processing device. The data processing device may also include one or more power supplies 803, one or more wired or wireless network interfaces 804, one or more input / output interfaces 805, and one or more keyboards 806.

[0139] Specifically, in this embodiment, the data processing device includes a memory and one or more programs, wherein one or more programs are stored in the memory, and one or more programs may include one or more modules, and each module may include a series of computer-executable instructions for the data processing device, and is configured to be executed by one or more processors. The one or more programs include computer-executable instructions for performing the following:

[0140] Receive first repository information sent by application instances other than the target application instance in the application cluster; the application cluster includes multiple application instances, which are used to load data from the database of the target application to form repository information;

[0141] Based on the received first storage information, construct a message statistics table; the message statistics table includes the number of times the first storage information was received, which is the number of times the first storage information was received by the target application instance;

[0142] Based on the message statistics table, identify the target warehouse information that received the most messages in the first warehouse information;

[0143] Perform a consistency check between the target warehouse information and the second warehouse information of the target application instance;

[0144] Based on the consistency verification results, anomaly detection is performed on the second storage information of the target application instance.

[0145] By employing one or more embodiments of the technical solution described in this specification, first repository information is received from application instances other than the target application instance in an application cluster. In this technical solution, the application cluster includes multiple application instances, each of which can load data from the database of the target application to form repository information. Therefore, this technical solution can send the repository information already loaded by each application instance of the same application to other application instances in the application cluster of that application. Consequently, the target application instance can construct a message statistics table based on the received first repository information. The message statistics table includes the number of times the first repository information has been received, where the number of receptions represents the number of times the first repository information has been received by the target application instance. The system calculates the number of times a message is received and, based on the message statistics table, identifies the target warehouse information that receives the most messages in the first warehouse information. It then performs a consistency check on the target warehouse information and the second warehouse information of the target application instance. Based on the consistency check results, it performs anomaly detection on the second warehouse information of the target application instance. This achieves a self-checking effect of warehouse information consistency through comparison between application instances, avoiding reliance on external systems to verify warehouse information consistency. This decentralized warehouse information consistency check scheme ensures that the consistency check process is no longer affected by external system failures, thus achieving a more reliable warehouse information consistency check scheme. Furthermore, since the repository information is only sent to the target application instance after other application instances load data to form the repository information, the target repository information that the target application instance receives the most times is the repository information that has been loaded by the most application instances in the application cluster. Compared with other repository information, this repository information has a lower probability of being abnormal and a higher reliability. In the process of self-verification of repository information consistency, this technical solution uses the target repository information, which has a lower probability of being abnormal and a higher reliability, to perform consistency verification with the repository information of the current application instance, rather than using any repository information received by the current application instance. This avoids the occurrence of random events, makes the consistency verification result more reliable, improves the reliability of the self-verification process of repository information consistency, and thus makes the anomaly detection of the repository information of the current application instance more accurate.

[0146] One or more embodiments of this specification also provide a storage medium storing one or more computer programs, the one or more computer programs including instructions that, when executed by an electronic device including multiple applications, enable the electronic device to perform various processes of the above-described data processing method embodiments, and specifically for performing:

[0147] Receive first repository information sent by application instances other than the target application instance in the application cluster; the application cluster includes multiple application instances, which are used to load data from the database of the target application to form repository information;

[0148] Based on the received first storage information, construct a message statistics table; the message statistics table includes the number of times the first storage information was received, which is the number of times the first storage information was received by the target application instance;

[0149] Based on the message statistics table, identify the target warehouse information that received the most messages in the first warehouse information;

[0150] Perform a consistency check between the target warehouse information and the second warehouse information of the target application instance;

[0151] Based on the consistency verification results, anomaly detection is performed on the second storage information of the target application instance.

[0152] By employing one or more embodiments of the technical solution described in this specification, first repository information is received from application instances other than the target application instance in an application cluster. In this technical solution, the application cluster includes multiple application instances, each of which can load data from the database of the target application to form repository information. Therefore, this technical solution can send the repository information already loaded by each application instance of the same application to other application instances in the application cluster of that application. Consequently, the target application instance can construct a message statistics table based on the received first repository information. The message statistics table includes the number of times the first repository information has been received, where the number of receptions represents the number of times the first repository information has been received by the target application instance. The system calculates the number of times a message is received and, based on the message statistics table, identifies the target warehouse information that receives the most messages in the first warehouse information. It then performs a consistency check on the target warehouse information and the second warehouse information of the target application instance. Based on the consistency check results, it performs anomaly detection on the second warehouse information of the target application instance. This achieves a self-checking effect of warehouse information consistency through comparison between application instances, avoiding reliance on external systems to verify warehouse information consistency. This decentralized warehouse information consistency check scheme ensures that the consistency check process is no longer affected by external system failures, thus achieving a more reliable warehouse information consistency check scheme. Furthermore, since the repository information is only sent to the target application instance after other application instances load data to form the repository information, the target repository information that the target application instance receives the most times is the repository information that has been loaded by the most application instances in the application cluster. Compared with other repository information, this repository information has a lower probability of being abnormal and a higher reliability. In the process of self-verification of repository information consistency, this technical solution uses the target repository information, which has a lower probability of being abnormal and a higher reliability, to perform consistency verification with the repository information of the current application instance, rather than using any repository information received by the current application instance. This avoids the occurrence of random events, makes the consistency verification result more reliable, improves the reliability of the self-verification process of repository information consistency, and thus makes the anomaly detection of the repository information of the current application instance more accurate.

[0153] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0154] For ease of description, the above apparatus is described by dividing it into various functional units. Of course, when implementing one or more embodiments of this specification, the functions of each unit can be implemented in one or more software and / or hardware.

[0155] Those skilled in the art will understand that one or more embodiments of this specification can be provided as a method, system, or computer program product. Therefore, one or more embodiments of this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, one or more embodiments of this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0156] This specification describes one or more embodiments of methods, apparatus (systems), and computer program products according to embodiments of this specification with reference to flowchart illustrations and / or block diagrams. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, produce a machine for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0157] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0158] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0159] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0160] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0161] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0162] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0163] One or more embodiments of this specification can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a particular task or implement a particular abstract data type. This specification can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0164] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0165] The above description is merely one or more embodiments of this specification and is not intended to limit this application. Various modifications and variations can be made to the one or more embodiments of this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of one or more embodiments of this specification should be included within the scope of the claims of one or more embodiments of this specification.

Claims

1. A data processing method, comprising: Receive first repository information sent by application instances other than the target application instance in the application cluster; The application cluster includes multiple application instances, which are used to load data from the database of the target application to form warehousing information; Based on the received first storage information, a message statistics table is constructed; the message statistics table includes the number of times the first storage information is received, the number of times the first storage information is received by the target application instance; Based on the message statistics table, determine the target warehouse information that has been received the most times in the first warehouse information; Perform a consistency check on the target warehouse information and the second warehouse information of the target application instance; Based on the results of the consistency check, anomaly detection is performed on the second storage information of the target application instance.

2. The method according to claim 1, wherein the first storage information includes device identification information for sending the first storage information, storage type of the first storage information, and storage information summary; the step of constructing a message statistics table based on the received first storage information includes: Based on the received warehouse information digest of the first warehouse information, count the number of times the warehouse information digest has been received; The number of times the warehouse information summary is received is determined as the number of times the first warehouse information is received; The message statistics table is constructed based on the storage type of the first storage information, the storage information summary of the first storage information, the number of times the first storage information is received, and the device identification information that sent the first storage information.

3. The method according to claim 2, wherein constructing the message statistics table based on the storage type of the first storage information, the storage information summary of the first storage information, the number of times the first storage information was received, and the device identification information that sent the first storage information includes: The message statistics table is generated by using the storage type of the first storage information as the key and constructing the values ​​of the message statistics table using the storage information summary of the first storage information, the number of times the first storage information was received, and the device identification information that sent the first storage information. Specifically, the values ​​in the message statistics table are constructed using the storage information summary of the first storage information as the nesting key and the number of times the first storage information is received and the device identification information that sent the first storage information as the nesting value.

4. The method according to claim 3, wherein the target application instance is configured with a timed verification task; and the target warehouse information that is received most frequently in the first warehouse information is determined according to the message statistics table; Perform a consistency check on the target storage information and the second storage information of the target application instance, including: In response to the timed verification task corresponding to the target application instance, based on the storage type of the first storage information, the storage information summary of the first storage information, and the number of times the first storage information is received, the target storage information summary with the most received times in the storage information summary under each storage type is determined; Based on the summary generation method consistent with that used to generate the first warehouse information summary, the warehouse information summary corresponding to the second warehouse information of the target application instance is determined; For each warehouse type, a consistency check is performed on the target warehouse information digest and the warehouse information digest corresponding to the target application instance.

5. The method according to claim 4, wherein the step of performing anomaly detection on the second warehouse information of the target application instance based on the result of the consistency check includes: If the consistency check result is a pass, then it is determined that the second storage information of the target application instance is loaded normally; If the consistency check result is that the check fails, then determine whether the target application instance has newly loaded the storage information after the scheduled check task starts; If not, then it is determined that the second storage information of the target application instance is abnormally loaded, and an abnormal alarm message is sent to the monitoring system associated with the application cluster.

6. The method according to claim 5, wherein the first storage information further includes a timestamp of sending the first storage information; after determining that the second storage information of the target application instance is loaded normally, the method further includes: The second storage information is sent to each application instance in the application cluster, and the application instance is used to update the loaded storage information according to the second storage information; Based on the timestamp of sending the first storage information and the start time of the scheduled verification task, the first storage information received before the start of the scheduled verification task in the message statistics table is removed.

7. The method according to claim 1, After the application instances in the application cluster load data from the database of the target application to form storage information, they determine the first storage information corresponding to the storage information and send the first storage information to other application instances in the application cluster through a multicast protocol.

8. A data processing apparatus, comprising: The receiving module is used to receive first repository information sent by other application instances besides the target application instance in the application cluster. The application cluster includes multiple application instances, which are used to load data from the database of the target application to form warehousing information; A construction module is used to construct a message statistics table based on the received first storage information; the message statistics table includes the number of times the first storage information is received, the number of times the first storage information is received by the target application instance; The determination module is used to determine the target warehouse information that has been received the most times in the first warehouse information based on the message statistics table; The consistency verification module is used to perform consistency verification on the target warehousing information and the second warehousing information of the target application instance. An anomaly detection module is used to perform anomaly detection on the second storage information of the target application instance based on the result of the consistency verification.

9. A data processing device, comprising: processor; as well as A memory configured to store computer-executable instructions, which, when executed, enable the processor to: Receive first repository information sent by application instances other than the target application instance in the application cluster; the application cluster includes multiple application instances, which are used to load data from the database of the target application to form repository information; Based on the received first storage information, a message statistics table is constructed; the message statistics table includes the number of times the first storage information is received, the number of times the first storage information is received by the target application instance; Based on the message statistics table, determine the target warehouse information that has been received the most times in the first warehouse information; Perform a consistency check on the target warehouse information and the second warehouse information of the target application instance; Based on the results of the consistency check, anomaly detection is performed on the second storage information of the target application instance.

10. A storage medium for storing computer-executable instructions, which, when executed by a processor, perform the following process: Receive first repository information sent by application instances other than the target application instance in the application cluster; the application cluster includes multiple application instances, which are used to load data from the database of the target application to form repository information; Based on the received first storage information, a message statistics table is constructed; the message statistics table includes the number of times the first storage information is received, the number of times the first storage information is received by the target application instance; Based on the message statistics table, determine the target warehouse information that has been received the most times in the first warehouse information; Perform a consistency check on the target warehouse information and the second warehouse information of the target application instance; Based on the results of the consistency check, anomaly detection is performed on the second storage information of the target application instance.

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