Data retrieval prediction method and apparatus, electronic device, and readable medium

Abstract

Embodiments of the present application disclose a data retrieval prediction method and device, electronic equipment and readable medium. The method comprises: determining data storage path information used by a data object in a target query time period; determining a target operation object experienced by the data object when writing from a source end to a destination end from the data storage path information; and predicting the storage condition of the data object in the target query time period by performing storage influence event analysis on the target operation object. According to the application, the data object itself does not need to be directly retrieved, but the object experienced by the data object when writing from the source end to the destination end is used to perform storage influence event analysis to predict the data storage condition, thereby dispersing the system service pressure caused by a large number of concurrent data retrievals.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to the technical field of computer, and particularly relate to a data retrieval prediction method and device, electronic equipment and readable medium. BACKGROUND

[0002] At present, the importance of security systems and data is increasing, and security systems are developing in the direction of super large, with a scale of tens of thousands of cameras. In some cases, such as image retrieval process, large-scale concurrent query of stored images and intelligent historical data analysis process are usually required, and the system bears the huge business pressure of image retrieval.

[0003] In related technologies, the system periodically polls all camera-defined time periods for images, and stores the results in the database, memory and disk respectively. When querying the stored images, the memory is queried first, then the database is queried, and finally the disk is queried. Although a certain layering is performed through the memory, database and disk, the database pressure bottleneck is significant in the case of high business concurrency, and the memory size is limited, which cannot resolve the system pressure caused by a large number of concurrent retrievals. SUMMARY

[0004] In the embodiments of the present application, a data retrieval prediction method, device, electronic equipment and readable medium are provided to intelligently predict the data storage situation and reduce the concurrent pressure of the overall system.

[0005] In a first aspect, a data retrieval prediction method is provided in the embodiments of the present application, and the method comprises:

[0006] determining data storage path information used by a data object in a target query time period;

[0007] determining a target operation object experienced by the data object from a source end to a destination end from the data storage path information;

[0008] predicting and determining the storage situation of the data object in the target query time period by performing storage influence event analysis on the target operation object.

[0009] In a second aspect, a data retrieval prediction device is also provided in the embodiments of the present application, and the device comprises:

[0010] a storage path determination module configured to determine data storage path information used by a data object in a target query time period;

[0011] an operation object determination module configured to determine a target operation object experienced by the data object from a source end to a destination end from the data storage path information;

[0012] The data storage prediction module is configured to determine the storage condition of the data object in the target query time period by performing storage influence event analysis on the target operation object.

[0013] In a third aspect, an electronic device is provided in embodiments of the present application, comprising:

[0014] one or more processing devices;

[0015] a storage device configured to store one or more programs;

[0016] When the one or more programs are executed by the one or more processing devices, the one or more processing devices implement the data retrieval prediction method in embodiments of the present application.

[0017] In a fourth aspect, a computer readable medium is provided in embodiments of the present application, which stores a computer program that is executed by a processing device to implement the data retrieval prediction method in embodiments of the present application.

[0018] A data retrieval prediction method is provided in embodiments of the present application, which determines the data storage path information used by a data object in a target query time period in a data retrieval scenario, and determines the target operation object experienced by the data object indicated by the data storage path information when writing from a source end to a destination end, and analyzes whether the target operation object is disturbed by a storage influence event to predict the storage condition of the data object in the target query time period. The present application does not need to directly retrieve the stored data object itself, but uses the object experienced by the data object when writing from the source end to the destination end to analyze the storage influence event to predict the data storage condition, thereby dispersing the system business pressure caused by a large number of concurrent data retrievals.

[0019] The above summary of the application is only a summary of the technical solutions of the present application. In order to more clearly understand the technical means of the present application, the present application can be implemented according to the content of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the following specific embodiments of the present application are described in detail. BRIEF DESCRIPTION OF DRAWINGS

[0020] Other features, objects and advantages of the present application will become more apparent from the following detailed description of non-limiting embodiments, made with reference to the accompanying drawings. The drawings are only for the purpose of illustrating preferred embodiments and are not considered to be limiting of the present application. Moreover, the same reference numerals are used throughout the drawings to designate the same components. In the drawings:

[0021] Figure 1 is a flowchart of a data retrieval prediction method provided in embodiments of the present application;

[0022] Figure 2is a flow chart of another data retrieval prediction method provided in the embodiments of the present application;

[0023] Figure 3 is a structural block diagram of a data retrieval prediction device provided in the embodiments of the present application;

[0024] Figure 4 is a structural schematic diagram of an electronic device provided in the embodiments of the present application. DETAILED DESCRIPTION

[0025] The present application will be further described below in conjunction with the drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the present application, but not to limit the present application. In addition, it should be noted that, for the convenience of description, only the parts related to the present application are shown in the drawings, but not all the structures.

[0026] Before the example embodiments are discussed in more detail, it should be mentioned that some example embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe the operations (or steps) as sequential processes, many of the operations (or steps) can be implemented in parallel, concurrently or simultaneously. In addition, the order of the operations can be rearranged. The processes can be terminated when their operations are completed, but can also have additional steps not included in the drawings. The processes can correspond to methods, functions, procedures, subroutines, etc.

[0027] The data retrieval prediction method, device, electronic device and readable medium provided in the present application scheme will be described in detail below through embodiments and optional schemes of the embodiments.

[0028] Figure 1 is a flow chart of a data retrieval prediction method provided in the embodiments of the present application. The technical solution of the present embodiment can be applied to the case of querying the data storage situation in the data storage device due to data demand. The method can be executed by a data retrieval prediction device, which can be realized in software and / or hardware and integrated on any electronic device with network communication function. As shown in Figure 1 The data retrieval prediction method in the embodiments of the present application can include the following steps:

[0029] S110, determining the data storage path information used by the data object in the target query time period.

[0030] S120, determining the target operation object experienced by the data object from the source end to the destination end from the data storage path information.

[0031] In the security system, taking a photographed image as an example of a data object, a front-end collection device can collect photographed image data, and the collected image data is transmitted through a network and written into a storage-end device, so as to realize storage of the photographed image; for example, video data collected by a front-end camera IPC (Internet Protocol Camera) is transmitted through a network and written into a storage device. Alternatively, when data storage is performed, the front-end collection device is taken as a starting point, and the storage-end device is taken as a destination point, and a data stream of the data object passes through network and device nodes, units, modules and various operations in the security system to realize data storage. For example, an image stream of a photographed image passes through a front-end collection device, a switch device and a storage-end device in sequence from a source end to a destination end.

[0032] All nodes, units, modules and operations in the security system are pre-defined as objects. For example, server devices, switch devices, storage-end devices, storage-end device groups, disks, arrays, user start-stop storage operations and alarm linkage start-stop storage operations involved in the security system are defined as operation objects, as shown in Table 1. Meanwhile, a unique object number can be set for each operation object, and each operation object is described to distinguish the operation objects.

[0033] Table 1: Operation object pre-definition

[0034] Object Number Object Description 001 IPC 002 Switch 003 Router 004 Server 005 Storage Device 006 Array 007 Disk 008 User Start / Stop Storage Operation 009 Alarm Linkage Start / Stop Storage Operation …… ……

[0035] When data storage is performed, a data stream of a data object passes through one or more operation objects in the security system from a source end to a destination end for storage, so as to form a corresponding data storage path; for example, an example of a data storage path in data storage path information shown in Table 2, for each pre-set data storage path in the data storage path information, a corresponding path code can be set, and each data storage path can include at least two operation objects.

[0036] Table 2: Data storage path information

[0037]

[0038] Alternatively, the data storage path information used by a data object at different times can be the same or different, that is, the operation objects experienced by the data object from a source end to a destination end at different time periods can be fixed, and of course, part of the operation objects experienced by the data object from the source end to the destination end at different time periods can also be different.

[0039] From the operation objects indicated by the data storage path information, an operation object experienced by the data object from the source end to the destination end is selected, which is denoted as a target operation object. Considering that the data storage path information used by the data object in the target query time period involves multiple operation objects, the influences of different operation objects on data storage in different query time periods can be different, for example, some operation objects have a greater influence on data storage, and some operation objects usually have little influence on data storage. Alternatively, the operation object experienced by the data object from the source end to the destination end in the target query time period and satisfying a preset influence condition can be selected as the target operation object from the operation objects indicated by the data storage path information, so as to avoid wasting analysis resources for event analysis of invalid operation objects and to make the data retrieval prediction more accurate.

[0040] As an optional solution, the operation object experienced by the data object from the source end to the destination end in the target query time period can include at least two of the following contents: a front-end acquisition device, a server, a switch device, a storage end device, a storage end device group, a disk, an array, a user start-stop storage operation, and an alarm linkage start-stop storage operation.

[0041] In S130, the storage condition of the data object in the target query time period is predicted and determined by performing storage influence event analysis on the target operation object.

[0042] Among the operation objects experienced by the data stream of the data object from the source end to the destination end in the target query time period, the target operation object is a necessary item that needs to be experienced by data storage. If a storage influence event occurs in the target operation object during data storage, the data storage process of the data object from the source end to the destination end will usually be affected, resulting in an abnormal data storage of the data object from the source end to the destination end. Therefore, the case that the target operation object has an influence on data storage is captured, and then whether the target operation object experienced by the data object from the source end to the destination end will have a storage influence event in the target query time period is analyzed to predict the storage condition of the data object in the target query time period.

[0043] As an optional solution, various influence factors of each operation object on data storage in the data storage process can be predefined, for example, but not limited to, network disconnection, power failure, device restart, service restart, user operation, and the like, as shown in Table 3. On this basis, the storage influence event analysis can be performed on the operation object to determine whether the operation object has a storage influence event corresponding to the predefined influence factor in the query time period. For the target operation object, the storage influence event of the target operation object can include at least one of network disconnection, power failure, device offline restart, service offline restart, and user operation.

[0044] Table 3: Predefined influence factors of operation objects

[0045] Pre-set Influence Factor Code Pre-set Influence Factor Description 10001 Power Off 10002 Network Disconnection 10003 Crash 10004 …… 10005 Disk Offline 10006 …… 10007 …… 10008 XX Service Down 10009 User Operation 1 …… ……

[0046] According to the data retrieval prediction method provided in the embodiments of the present application, the target operation object experienced by the data object from the source end to the destination end in the target query time period is determined, and whether the target operation object is disturbed by the storage influencing event is analyzed to predict the storage condition of the data object in the target query time period. The data object itself does not need to be directly retrieved, but the operation object experienced by the data object from the source end to the destination end is used to analyze the storage influencing event to predict the data storage condition, and the system service pressure caused by a large number of concurrent data retrievals is dispersed.

[0047] Figure 2 is a flowchart of another data retrieval prediction method provided in the embodiments of the present application. The embodiments of the present application are further optimized on the basis of the above-mentioned embodiments, and the embodiments of the present application can be combined with each optional scheme in one or more of the above-mentioned embodiments. As shown in Figure 2 The data retrieval prediction method provided in the embodiments of the present application can include the following steps:

[0048] S210, data storage path information used by the data object in the target query time period is determined.

[0049] S220, the target operation object experienced by the data object from the source end to the destination end is determined from the data storage path information.

[0050] S230, the target operation object experienced by the data object from the source end to the destination end is analyzed based on the pre-updated storage influencing event configuration information.

[0051] The influencing event configuration information includes the storage influencing event record of the data object from the source end to the destination end, and the storage influencing event record includes the operation object identifier influencing the data storage, the influencing event description, and the influencing event start and end time.

[0052] For all nodes, units, modules and operations in the security system, a set of all possible information that may affect the data storage is defined in advance, which is referred to as influencing event configuration information. As shown in Table 4, in the process of the data object from the source end to the destination end, a storage influencing event record is generated for each operation object that may affect the storage of the data object, and the generated storage influencing event record is added to the influencing event configuration information. Each storage influencing event record includes the event number of the storage influencing event, the operation object identifier influencing the data storage, the influencing event description, and the influencing event start and end time.

[0053] Table 4 Impact event configuration information table

[0054]

[0055] After obtaining the pre-stored impact event configuration information, each stored impact event record recorded in the impact event configuration information can be queried, and whether the target operation object experienced by the data object written from the source end to the destination end is recorded in the impact event configuration information is determined by querying each stored impact event record, so as to realize event analysis on the target operation object experienced by the data object written from the source end to the destination end. Alternatively, the influence of each operation object on data storage in the security system can be captured in real time through a data capture technology, and the impact event configuration information is updated in real time based on the capture result; for example, data capture can be performed on log records.

[0056] In an optional solution of the embodiment, based on the pre-stored impact event configuration information, the storage impact event analysis on the target operation object experienced by the data object written from the source end to the destination end includes steps A1-A2:

[0057] Step A1, if the target operation object is found to exist in the impact event configuration information, the impact event start and end time period of the target operation object recorded in the storage impact event record of the impact event configuration information is determined.

[0058] Step A2, if the impact event start and end time period of the target operation object overlaps with the target query time period, it is predicted that the data object has abnormal storage in the overlapping time period.

[0059] For the security system, the front-end acquisition device is in normal acquisition and storage. When the user or the intelligent system performs data retrieval according to the required query time, all target operation objects experienced by the data object written from the source end to the destination end in the target query time period are queried. Then, the impact event configuration information is iterated or directionally queried to determine whether the storage impact event record corresponding to the target operation object is included in the impact event configuration information. If the storage impact event record corresponding to the target operation object is included, the impact event start and end time period of the target operation object recorded in the storage impact event record of the impact event configuration information is queried. If the storage impact event record corresponding to the target operation object is not included, it is considered that the target operation object has no storage impact, and accordingly the data object has no abnormal storage in the target query time period.

[0060] For each target operation object, the influence event start and end time period is compared with the target query time period to determine whether the two time periods overlap. If the influence event start and end time period of the target operation object overlaps with the target query time period, it is predicted that the data object has abnormal storage in the overlapping time period, indicating that the condition affecting data storage has occurred in the overlapping time period. Therefore, it is determined that the data object has abnormal storage in the overlapping time period of the target query time period, and it is determined that there is no stored data object in the overlapping time period. If the influence event start and end time period of the target operation object does not overlap with the target query time period, it is determined that the data object has no abnormal storage in the target query time period, and it is determined that there is a stored data object in the target query time period.

[0061] In another optional solution of the embodiment, based on the pre-stored influence event configuration information, the target operation object experienced by the data object written from the source end to the destination end is stored for influence event analysis, including steps B1-B2:

[0062] Step B1, if the influence event start and end time period recorded in the query influence event configuration information matches the target query time period, the operation object corresponding to the overlapping time period of the influence event start and end time period and the target query time period is queried from the storage influence event record of the influence event configuration information.

[0063] Step B2, if the operation object corresponding to the overlapping time period of the influence event start and end time period and the target query time period overlaps with the target operation object, it is predicted that the data object has abnormal storage in the overlapping time period.

[0064] By using the above solution, the pre-defined storage influence events corresponding to the influence factors of each node, level and module of the system are used in combination with the pre-defined storage influence events of each object in the entire path from the storage source end to the destination end to predict the data storage situation, so that the data retrieval prediction result tends to be accurate, the business pressure caused by high concurrency data retrieval of the system is dispersed, and the data storage situation can be more intuitively confirmed.

[0065] S240, according to the storage influence event analysis result of the target operation object, the storage situation of the data object in the target query time period is predicted and determined.

[0066] Referring to Table 4, the storage influence event analysis result of the target operation object can include that the target operation object has a storage influence event in a time period partially overlapping with the target query time period in the influence event start and end time period, causing abnormal storage of the data object in at least a part of the target query time period; or the target operation object has no influence event start and end time period or no overlapping time period with the target query time period, and the data object has no abnormal storage in the target query time period.

[0067] In an alternative of the embodiment, the data retrieval prediction method provided in the embodiment can further include the following steps:

[0068] The storage influence event record of the operation object having data storage influence in the influence event configuration information is updated and corrected by the bystander device associated with the operation object having data storage influence.

[0069] Optionally, the bystander device and the operation object having data storage influence are not in the same data storage path, or cannot observe each other.

[0070] When retrieving the data object, the prediction mechanism has a small probability of uncertainty, so the bystander confirmation mechanism is introduced to make the first result non-confirmation, forming a two-way identification. The bystander is defined as a subject in a non-storage process, who does not participate in the storage process, but has a direct association with the storage subject, i.e., the operation object. For example, a data storage path is IPC-switch 1-switch 2-server 1-storage device 1, and the bystander of the operation object switch 2 can be the server 5 connected to it, which allows the server 5 to confirm whether the switch 2 is running normally, such as whether the communication is normal.

[0071] A bystander device and a bystander event are predefined for each operation object in a preset data storage path. Optionally, the operation objects in the same data storage path do not observe each other, or the bystander device and the operation object having data storage influence are not in the same data storage path, and the above two conditions can be met or only one of them is met to increase the credibility. The storage influence event record of the operation object having abnormal storage in the influence event configuration information is updated and corrected by the bystander device associated with the operation object having data storage influence. For example, as shown in Table 5, the object number, the bystander number, and the confirmation information number of the bystander to the operation object are recorded during the updating and correction.

[0072] Table 5 Bystander event configuration information

[0073] Object Identification Spectator Device Identification Confirmation Information Number IPC_001 Switch_010 Port Flow IPC_… …… …… IPC_XXX …… …… Switch Server_099 Communication Normal Switch …… …… Switch …… …… Server …… …… …… …… ……

[0074] The result of the influence event configuration information is corrected using the bystander mechanism. If the determination result of the bystander on the operation object of the storage influence event record within the influence event starting time of the storage influence event record is consistent with the result recorded in the influence event configuration information, it is considered that no video recording is performed in this time period. If it is inconsistent with the obtained determination result, a real data query is started, and the query result is taken as the final result. For example, there is a storage influence event record indicating that a server is disconnected, and the bystander of the server also records that the server loses communication at the same time period. It is considered that the results are consistent, and it is determined that no image data is stored in this time period. If it is inconsistent, the image data in this time period is queried to confirm the result.

[0075] Optionally, in the influence event configuration information, the bystander does not exist in the storage influence event record generated by manual start-stop storage and alarm linkage start-stop storage, and the credibility of the storage influence event record does not need to be authenticated by the bystander. The information queried in the storage influence event record is directly determined to be credible.

[0076] By using the above scheme, the confirmation mechanism of the bystander and the continuous supplement mechanism of the influence event are used, the bystander is used to confirm the storage influence event record recorded in the influence event configuration information, and the storage influence event record in the influence event configuration information is continuously learned and updated, so that the prediction tends to be accurate.

[0077] In an optional scheme of the embodiment, the data retrieval prediction method provided in the embodiment can further include the following steps:

[0078] In a non-high-concurrency time period of data retrieval prediction, a new operation object causing data storage influence is determined by data retrieval sampling, and a new storage influence event record is formed and added to the influence event configuration information.

[0079] Video retrieval sampling is performed on the time period considered to have data storage. The sampling algorithm can satisfy the condition of not increasing the system pressure, and can cover all cameras IPC in a period of time. For example, the data of the important time period of the camera (for example, the important time period of school monitoring is school and school, etc.) is queried in batches in the time period when the system is relatively idle. If no video recording time period is found in the sampling, the reason needs to be found (which can be manually positioned and recorded), and the storage influence event record formed due to the new data storage influence is found and added to the influence event configuration information, so as to accumulate more influence event configuration information and improve the accuracy of subsequent retrieval prediction. In the initial stage, the cameras in the same area are configured, and the preset data storage paths are different as much as possible to reduce the influence of single-area failure.

[0080] According to the data retrieval prediction method provided in the embodiment of the present application, the target operation object experienced by the data object from the source end to the destination end is determined in the target query time period, the storage condition of the data object in the target query time period is predicted by analyzing whether the target operation object has storage influence, the data object itself does not need to be directly retrieved, the data storage condition is predicted by using the operation object experienced by the data object from the source end to the destination end to analyze the storage influence event, and the system service pressure caused by a large number of concurrent data retrievals is dispersed. In addition, the data storage condition is predicted by using the influence event configuration information of each node, level and module of the system, combining the data storage influence condition of each operation object in the whole storage path from the source end to the destination end, and using the bystander confirmation mechanism and the constantly updated influence event configuration information to make the prediction more accurate.

[0081] Figure 3 Figure 1 is a structural block diagram of a data retrieval prediction device provided in an embodiment of the present application. The technical solution of the embodiment can be applied to the case of querying the data storage condition in the data storage device due to data demand. The device can be realized in the form of software and / or hardware and integrated on any electronic device with network communication function. As shown in Figure 1, the data retrieval prediction device in the embodiment of the present application can include a storage path determination module 310, an operation object determination module 320 and a data storage prediction module 330. Wherein: Figure 3

[0082] The storage path determination module 310 is configured to determine the data storage path information used by the data object in the target query time period.

[0083] The operation object determination module 320 is configured to determine the target operation object experienced by the data object from the source end to the destination end from the data storage path information.

[0084] The image storage prediction module 330 is configured to predict the storage condition of the data object in the target query time period by analyzing the storage influence event of the target operation object.

[0085] On the basis of the above-mentioned embodiment, the data storage prediction module 330 can optionally include:

[0086] The target operation object experienced from the source end to the destination end is analyzed based on the pre-stored influence event configuration information;

[0087] The storage condition of the data object in the target query time period is predicted according to the analysis result of the storage influence event of the target operation object;

[0088] ​The storage impact event in the impact event configuration information includes an operation object identifier indicating the impact on data storage, an impact event description, and impact event start and end time.

[0089] Based on the above embodiment, optionally, based on the pre-stored impact event configuration information, the target operation object experienced from the source end to the destination end is analyzed for storage impact events, including:

[0090] If the target operation object exists in the impact event configuration information, the impact event start and end time period of the target operation object recorded in the storage impact event record of the impact event configuration information is determined.

[0091] If the impact event start and end time period of the target operation object overlaps with the target query time period, it is predicted that the data object has abnormal storage in the overlapping time period.

[0092] Based on the above embodiment, optionally, the operation object experienced from the source end to the destination end can include at least two of the following: front-end acquisition device, server, switch device, storage end device, storage end device grouping, disk, array, user start-stop storage operation, and alarm linkage start-stop storage operation.

[0093] Based on the above embodiment, optionally, the storage impact event includes at least one of the following: network disconnection, power failure, device offline restart, service offline restart, and user operation.

[0094] Based on the above embodiment, optionally, the device further includes:

[0095] The storage impact event record of the operation object with data storage impact in the impact event configuration information is updated and corrected by the observing device associated with the operation object with data storage impact.

[0096] The observing device and the operation object with data storage impact are not in the same data storage path, or they do not observe each other.

[0097] Based on the above embodiment, optionally, the device further includes:

[0098] In a non-high-concurrency time period predicted by data retrieval, a new operation object causing data storage impact is determined by data retrieval sampling, and a new storage impact event record is formed and added to the impact event configuration information.

[0099] The data retrieval prediction apparatus provided in the embodiments of the present application can execute the data retrieval prediction method provided in any of the embodiments of the present application, has the corresponding functions and advantages of executing the data retrieval prediction method, and the technical details not described in the embodiments are referable to the data retrieval prediction method provided in any of the embodiments of the present application.

[0100] Figure 4 is a structural schematic diagram of an electronic device provided in the embodiments of the present application. As shown in the structure, the electronic device provided in the embodiments of the present application comprises one or more processors 410 and a storage device 420; the processor 410 in the electronic device can be one or more, Figure 4 In the embodiments, the processor 410 is taken as an example; the storage device 420 is configured to store one or more programs; the one or more programs are executed by the one or more processors 410, so that the one or more processors 410 implement the data retrieval prediction method according to any of the embodiments of the present application. Figure 4

[0101] The electronic device can further comprise an input device 430 and an output device 440.

[0102] The processor 410, the storage device 420, the input device 430 and the output device 440 in the electronic device can be connected through a bus or other means, Figure 4 In the embodiments, the connection through the bus is taken as an example.

[0103] The storage device 420 in the electronic device can be used as a computer readable storage medium to store one or more programs, and the programs can be software programs, computer executable programs and modules, such as program instructions / modules corresponding to the data retrieval prediction method provided in the embodiments of the present application. The processor 410 executes the software programs, instructions and modules stored in the storage device 420, so as to execute various functional applications and data processing of the electronic device, that is, to implement the data retrieval prediction method in the above method embodiments.

[0104] The storage device 420 can comprise a program storage area and a data storage area, wherein the program storage area can store an operating system and at least one application program required by a function; the data storage area can store data created according to the use of the electronic device, etc. In addition, the storage device 420 can comprise a high-speed random access memory, and can further comprise a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device or other non-volatile solid-state storage device. In some examples, the storage device 420 can further comprise a memory remotely arranged relative to the processor 410, and the remote memory can be connected to the device through a network. Examples of the above network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network and a combination thereof. ​

[0105] The input device 430 can be used to receive inputted digital or character information, and to generate key signal input related to user settings and function control of the electronic device. The output device 440 can include a display device such as a display screen.

[0106] And when the one or more programs included in the above electronic device are executed by the one or more processors 410, the programs perform the following operations:

[0107] determining data storage path information used by the data object in the target query time period;

[0108] from the data storage path information, determining a target operation object experienced by the data object when writing from a source end to a destination end;

[0109] by performing storage impact event analysis on the target operation object, predicting the storage condition of the data object in the target query time period.

[0110] Of course, those skilled in the art can understand that when the one or more programs included in the above electronic device are executed by the one or more processors 410, the programs can also perform related operations in the data retrieval prediction method provided in any embodiment of the present application.

[0111] The present embodiment provides a computer readable storage medium, which stores a computer program, and the program is executed by a processor to perform a data retrieval prediction method, and the method comprises:

[0112] determining data storage path information used by the data object in the target query time period;

[0113] from the data storage path information, determining a target operation object experienced by the data object when writing from a source end to a destination end;

[0114] by performing storage impact event analysis on the target operation object, predicting the storage condition of the data object in the target query time period.

[0115] Optionally, the program is executed by the processor to perform the data retrieval prediction method provided in any embodiment of the present application.

[0116] The computer storage medium of the embodiments of the present application can adopt any combination of one or more computer readable media. The computer readable medium can be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium may, for example, be, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or apparatus, or any combination thereof. More specific examples (a non-exhaustive list) of the computer readable storage medium include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read only memory (ROM), an erasable programmable read only memory (EPROM), a flash memory, an optical fiber, a portable CD-ROM, an optical storage device, a magnetic storage device, or any suitable combination of the above. The computer readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus or device.

[0117] The computer readable signal medium can include a data signal propagated in baseband or propagated as a carrier wave in a propagated data signal, in which the computer readable program code is embodied. Such propagated data signal can take a variety of forms, including but not limited to electro-magnetic, optical or any suitable combination thereof. The computer readable signal medium can also be any computer readable medium that is not a storage medium and that can communicate, propagate or transport programming for use by or in connection with an instruction execution system, apparatus or device.

[0118] The program code embodied on the computer readable medium can be transmitted using any suitable medium, including but not limited to wireless, wire line, optical fiber cable, Radio Frequency (RF), or any suitable combination thereof.

[0119] Computer program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0120] In the description of the specification, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in one or more embodiments or examples.

[0121] Note that the above only describes the preferred embodiments of the present application and the applied technical principles. Those skilled in the art will understand that the present application is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of the present application. Therefore, although the present application has been described in more detail through the above embodiments, the present application is not limited to the above embodiments, and can include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the appended claims.

Claims

1. A data retrieval and prediction method, characterized in that, The method includes: Determine the data storage path information used by the data objects within the target query time period; From the data storage path information, the target operation object that the data object goes through from the source end to the destination end is determined. The target operation object is an operation object that meets the preset influence conditions. The preset influence conditions are used to avoid wasting analysis resources on event analysis of invalid operation objects in data storage. By performing storage impact event analysis on the target operation object, the storage status of the data object during the target query time period is predicted and determined. This prediction and determination includes: based on pre-stored impact event configuration information, performing storage impact event analysis on the target operation object as it is written from the source to the destination; and based on the results of the storage impact event analysis on the target operation object, predicting and determining the storage status of the data object during the target query time period. The impact event configuration information includes records of storage impact events that affect the data storage of the data object as it is written from the source to the destination. By using a bystander device associated with the operation object affected by data storage, the storage impact event records of the operation object affected by data storage in the impact event configuration information are updated and corrected; wherein, the bystander device and the operation object affected by data storage are not on the same data storage path, and / or the two do not observe each other; if the bystander's determination of the operation object of the storage impact event record matches the result recorded in the impact event configuration information within the start time of the impact event of the storage impact event record, it is considered that no video recording was stored during this time period; if it is contrary to the determination result obtained, a real data query is initiated, and the query result is taken as the final result.

2. The method according to claim 1, characterized in that, The storage of impact event records includes the identifier of the operation object affecting data storage, the description of the impact event, and the start and end times of the impact event.

3. The method according to claim 2, characterized in that, Based on pre-stored impact event configuration information, storage impact event analysis is performed on the target operation object that is written from the source to the destination, including: If the target operation object exists in the impact event configuration information, then determine the start and end time period of the impact event of the target operation object recorded in the storage impact event record of the impact event configuration information; If the start and end time periods of the impact event on the target operation object overlap with the target query time period, it is predicted that the data object in the overlapping time period has abnormal storage.

4. The method according to claim 1, characterized in that, The operations involved in writing from the source to the destination include at least two of the following: front-end acquisition devices, servers, switching devices, storage devices, storage device groups, disks, arrays, user start / stop storage operations, and alarm-linked start / stop storage operations.

5. The method according to claim 1, characterized in that, The storage-impacting events include at least one of the following: network outage, power outage, device offline and restart, service offline and restart, and user operations.

6. The method according to claim 1, characterized in that, The method further includes: During the non-high-concurrency period predicted by data retrieval, new operation objects that cause data storage impact are identified through data retrieval sampling, and a new storage impact event record is created and added to the impact event configuration information.

7. A data retrieval and prediction device, characterized in that, The device includes: The storage path determination module is used to determine the data storage path information used by the data object during the target query time period; The operation object determination module is used to determine the target operation object that the data object goes through from the source end to the destination end from the data storage path information. The target operation object is an operation object that meets the preset influence conditions. The preset influence conditions are used to avoid wasting analysis resources on event analysis of invalid operation objects in data storage. The data storage prediction module is used to predict and determine the storage status of data objects during a target query time period by performing storage impact event analysis on the target operation objects. This prediction and determination includes: performing storage impact event analysis on the target operation objects as they are written from the source to the destination based on pre-stored impact event configuration information; and predicting and determining the storage status of data objects during the target query time period based on the results of the storage impact event analysis. The impact event configuration information includes records of storage impact events that affect the data storage of data objects as they are written from the source to the destination. By using a bystander device associated with the operation object affected by data storage, the storage impact event records of the operation object affected by data storage in the impact event configuration information are updated and corrected; wherein, the bystander device and the operation object affected by data storage are not on the same data storage path, and / or the two do not observe each other; if the bystander's determination of the operation object of the storage impact event record matches the result recorded in the impact event configuration information within the start time of the impact event of the storage impact event record, it is considered that no video recording was stored during this time period; if it is contrary to the determination result obtained, a real data query is initiated, and the query result is taken as the final result.

8. An electronic device, characterized in that, include: One or more processing devices; Storage device for storing one or more programs; When the one or more programs are executed by the one or more processing devices, the one or more processing devices implement the data retrieval and prediction method according to any one of claims 1-6.

9. A computer-readable medium having a computer program stored thereon, characterized in that, When executed by the processing device, the program implements the data retrieval and prediction method according to any one of claims 1-6.

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