WO2021093462A1

WO2021093462A1 - Method and apparatus for storing operation record in database, and device

Info

Publication number: WO2021093462A1
Application number: PCT/CN2020/117005
Authority: WO
Inventors: 杨新颖
Original assignee: 蚂蚁区块链科技(上海)有限公司
Priority date: 2019-11-11
Filing date: 2020-09-23
Publication date: 2021-05-20
Also published as: CN111046052A; CN111046052B

Abstract

Disclosed are a method and apparatus for storing an operation record in a database, and a device. The method comprises: receiving an operation instruction, wherein the operation instruction includes a service attribute (S301); assessing the degree to which the operation instruction changes a data record including the service attribute, and determining an operation influence feature value, wherein the operation influence feature value is positively correlated with the degree to which the data record including the service attribute is changed (S303); if the operation influence feature value exceeds a threshold value, generating and storing an operation record including the operation instruction (S305); otherwise, determining a change state of the data record including the service attribute, and generating and storing an operation record including the change state (S307).

Description

Method, device and equipment for storing operation records in database

Technical field

The embodiments of this specification relate to the field of information technology, and in particular to a method, device, and equipment for storing operation records in a database.

Background technique

When the centralized database server provides external data services, it also needs to save the user's operations on the data record (including adding, clearing, hiding, querying, etc.) resulting in the change of the data record or the status change of a certain attribute in the data record , That is, the operation records need to be stored for retrospective or rollback. In a centralized scenario, the number of data records is often huge, and the number of operation records is also often very large.

Based on this, a flexible operation record storage method is needed.

Summary of the invention

The purpose of the embodiments of the present application is to provide a flexible operation record storage solution in a database.

In order to solve the above technical problems, the embodiments of the present application are implemented by the following methods.

Receive an operation instruction, the operation instruction contains a business attribute; evaluate the degree of change of the operation instruction to the data record containing the business attribute, and determine the operation influence characteristic value, wherein the operation influence characteristic value and the operation influence characteristic value include The degree of change of the data record of the business attribute is positively correlated; if the operation influence characteristic value exceeds the threshold, an operation record containing the operation instruction is generated and stored; otherwise, the data record containing the business attribute is determined The change state of, an operation record containing the change state is generated and stored.

Correspondingly, the embodiment of this specification also provides an operation record storage device in a block chain ledger, including: a receiving module, which receives an operation instruction, the operation instruction contains business attributes; an evaluation module, which evaluates that the operation instruction is effective The change degree of the data record containing the business attribute is determined to determine the operation influence characteristic value, wherein the operation influence characteristic value is positively correlated with the change degree of the data record containing the business attribute; the first storage module, if the If the operation influence characteristic value exceeds the threshold, generate an operation record containing the operation instruction, and store it; the second storage module, otherwise, determine the change state of the data record containing the business attribute, and generate the change state containing the change State operation records and storage.

Through the solution provided by the embodiment of this specification, before generating the operation record, first evaluate the degree of change that the operation instruction may have on the data record containing the business attribute. If the degree of change is large, record the operation instruction and generate the operation containing the operation instruction Record and store; if the degree of change is not large, record the changed data record or its related hash value, generate an operation record containing the aforementioned state change, and store it. By evaluating the possible impact of the operation instructions, the relevant operation records are dynamically generated to ensure that the data status can be accurately traced back, saving the system overhead when storing the operation records, and realizing a flexible operation record storage method.

It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the embodiments of this specification.

In addition, any one of the embodiments of the present specification does not need to achieve all the above-mentioned effects.

Description of the drawings

In order to more clearly describe the technical solutions in the embodiments of this specification or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only These are some of the embodiments described in the embodiments of this specification. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings.

Figure 1 is a schematic diagram of the system architecture involved in an embodiment of the specification;

Figure 2 is a schematic diagram of the data system architecture provided by an embodiment of this specification;

FIG. 3 is a schematic flowchart of a method for storing operation records in a block chain ledger provided by an embodiment of the specification; FIG.

Fig. 4 is a schematic diagram of a process for generating a block chain ledger provided by an embodiment of the specification;

5 is a schematic diagram of a block header of a data block provided by an embodiment of this specification;

6 is a schematic structural diagram of an operation record storage device in a database provided by an embodiment of this specification;

Fig. 7 is a schematic structural diagram of a device for configuring the method of the embodiment of this specification.

Detailed ways

In order to enable those skilled in the art to better understand the technical solutions in the embodiments of this specification, the technical solutions in the embodiments of this specification will be described in detail below in conjunction with the drawings in the embodiments of this specification. Obviously, the described implementation The examples are only a part of the embodiments in this specification, not all the embodiments. Based on the embodiments in this specification, all other embodiments obtained by those of ordinary skill in the art should fall within the scope of protection.

Centralized database server often provides services to various institutions, and each institution can record the data generated between them and third-party users (including other institutions or individuals) in the database server for storage. As shown in FIG. 1, FIG. 1 is a schematic diagram of a system architecture involved in an embodiment of the specification. In this schematic diagram, an enterprise organization can face multiple users, and each user can query the database service provider through its corresponding enterprise organization.

For example, the organization connected to the database server is a financial product company, and the data records can be individual users’ financial management records in the financial product company; or, the connected organization can be a government department, where the data records are what the government department has for the department. Expense details of the managed public project; or, the database server is connected to a hospital, and the data record is the patient’s medical record; or the database server is connected to a third-party payment agency, and the data record can be an individual user Payment records through the agency, and so on.

The way the database provides services can be a conventional relational/non-relational data structure, or a block-chain data structure. As shown in FIG. 2, FIG. 2 is a schematic diagram of the data system architecture provided by the embodiment of the present specification. The user's data is stored in the main body of the ledger shown in Figure 2 (it can be a relational table, a blockchain ledger, etc.). The index can be defined as needed. For example, for a blockchain ledger, the index can include an inverted index with the business attribute of the data record as the main key, and the block height and offset sequence number as the value; the metadata part can be Perform statistics on the main body, index and other information of the ledger to obtain relevant information. For example, the metadata part can include: the total number of data records in the ledger, the total number of data blocks in the ledger, the total number of business attributes in the ledger, and the quantity The number of data records of the top business attributes, the number of data blocks where a business attribute is located in the ledger, and so on. In some business scenarios, metadata can also perform state calculations for certain business attributes. For example, in financial-related scenarios, the data record is about the user's expenditure/income record, or the user's purchase/sale of securities Records and so on. In this way, the metadata can also include world state values for certain business attributes (for example, the user's amount of money).

After the user's data record is written into the data block, the user can also perform various operations on the data record in the ledger, for example, including updating UPDATA, adding APPEND, clearing PURGE, verifying VERIFY, querying SELECT, hiding OCCULT, and so on. In this process, corresponding operation records will be generated, and the operation records can be stored in the log part or the main part of the ledger in the storage. Based on this, the embodiment of this specification also provides a method for storing operation records in a block chain ledger, as shown in FIG. 3, which is the flow of the method for storing operation records in a block chain ledger provided by the embodiment of this specification. Schematic diagram, including the following steps.

S301: Receive an operation instruction, where the operation instruction includes a business attribute.

As mentioned above, in conventional databases, operation instructions can use common structured query language (SQL), including such as UPDATA, APPEND, PURGE, VERIFY, SELECT, OCCULT, and so on.

For example, SELECT (balance, FULL), to query all data records with "balance" as the business attribute in the ledger; for example, UPDATA (key1, v1, v2), the ledger will contain data records with the business attribute "key1" Replace v1 in v2 with v2 and so on. The operating instructions can come from the database server, the docking organization, or the users of the docking organization, and so on.

In some unconventional databases, operating instructions can also be user-defined statements with certain functions, such as clear PURGE (used to clear data blocks before the specified block height) in the block chain ledger. Hidden OCCULT (used to hide the plaintext of a specified data record) and so on.

Business attributes can be fields related to the user's business data, for example, user ID, mobile phone number, item name, etc. There are no restrictions here; business attributes can also be related to the main body of the ledger, index, and metadata that store user data Fields, such as the name of the ledger, the name of the index, the number of rows and columns in the index, and so on.

S303: Evaluate the degree of change of the operation instruction to the data record containing the business attribute, and determine the operation influence characteristic value.

When the user operates the data record by operating instructions, the corresponding data record will be affected. The degree of impact change here mainly includes "changes to the data record itself", "changes to the index related to the data record", and "changes to the metadata" and so on.

Specifically, it can be comprehensively evaluated from multiple aspects. Two aspects are listed below.

First, evaluate based on the type of operation instruction.

As mentioned earlier, there are many types of operating instructions, and different types of operating instructions have different effects on data recording. For example, a query command may not change any data records or metadata, while a hidden command OCCULT may affect a data record, and an UPDATA may affect all data records containing specified business attributes, and for Both indexing and metadata may have a corresponding impact.

Therefore, according to actual experience, the corresponding command influence coefficient K can be assigned to each operation command, and the command influence coefficient is used to evaluate the operation influence characteristic value of the operation command. For example, K1=0 for query instructions, K2=1 for hidden instructions, and so on.

Second, it is evaluated based on the number of data records containing business attributes.

As mentioned earlier, in a conventional database or a block-chain database, metadata related to the main body of the ledger can be included. For example, the total number of data records in the ledger, the total number of business attributes in the ledger, and the number of business attribute data records in the top several rankings (for example, the top 20).

Therefore, for an operation instruction containing a specified business attribute, how many data records it may affect can be intuitively reflected from the metadata.

For example, suppose that in the metadata, the number of the top 100 data records containing a certain business attribute is recorded in sequence, the business attribute "key1" is in the table, and the number of data records containing the business attribute "key1" is in the table. If the number is "N1", it can be known that the operation instruction may affect the "N1" data records.

For another example, assuming that the business attribute "key2" is not in the table in the metadata, you can know that the number of business attributes "key2" is not particularly large, and it can be inferred that the business attributes that are not in the top 100 correspond to the data records The number of data records is uniformly distributed. Therefore, the number N2 that contains the business attribute "key2" can be calculated as N2 = (N total-N top 100)/(Total number of data records-100).

In this case, you can evaluate the number of data records that may be affected by the operation instruction "N", and get the data quantity influence coefficient "M". Obviously, M and the number of data records that may be affected "N" It is positively correlated, such as "M=N" or "M=LnN".

The evaluation of the operation influence characteristic value T can be carried out comprehensively according to the command influence coefficient K and/or the data quantity influence coefficient "M", for example, T=K*M. And, in practical applications, other related factors can also be integrated, for example, the time complexity or space complexity of the operation instruction itself. In short, the greater the degree of change of the data record that may be affected by the operation instruction, the greater the characteristic value T of the operation influence.

S305: If the operation influence characteristic value exceeds a threshold, an operation record containing the operation instruction is generated and stored.

If the operation influence characteristic value exceeds the threshold, it indicates that the operation instruction may have affected multiple data records and metadata. If the change status of each data record is recorded in the operation instruction, considerable resources may be required.

For example, suppose that a UPDATA command uniformly updates the value corresponding to a certain business attribute, and there are 1000 data records containing the business attribute. Then, if the change status of each data record is recorded, it needs to be in an operation record Record 1000 data records before and after changes. This obviously requires considerable resources.

At this time, if the method of recording the operation instruction is adopted, then obviously only the operation instruction needs to be included in the operation record at this time. Specifically, the generated operation record may also include the receiving time of the operation instruction, the user ID of the specific sending instruction, etc., and the operation instruction is stored in plain text.

The generated operation record can be stored in the corresponding log file. In the block chain ledger, the generated operation record can also be written into the data block in the ledger.

S307: Otherwise, determine the change state of the data record containing the business attribute, generate an operation record containing the change state, and store it.

If the operation influence characteristic value does not exceed the threshold, it can indicate that the operation record may only affect a small number of data records. For example, for an operation instruction APPEND (key1, V), only a data record containing the business attribute "key1" is added to the database. In the metadata, the possible change is the data record corresponding to "key1" The number of items is +1, or the possible change is that the world state corresponding to "key1" is changed from the current value to the current value plus the corresponding value in "V".

Even if the amount of data corresponding to the business attribute "key1" is small (for example, it is not in the top 100 table), there will be no change to the metadata.

Then, you can determine which data records or metadata have changed at this time, and write the corresponding state changes into the operation records.

Specifically, for the change of the operation record, the change of the data record itself may be directly recorded. That is, it is determined that in the data record containing the business attribute that has changed, the initial value and the change value of the business attribute are determined, and the operation record containing the initial value and the change value of the business attribute is generated.

For example, suppose an operation instruction only changes the corresponding value of "key1" in a data record from "0" to "1", which does not change the metadata. At this time, the operation record only needs to record the location of the data record where the data record has changed, the business attribute key1, and the initial value (the value before the change) "0" and the change value (that is, the value after the change) " 1" is fine.

In one embodiment, for some specific implementation scenarios, if the cumulative value of the business attribute has a specific meaning to the user (for example, the account balance caused by the change in user account expenditure and income, the user’s buying or selling Profit value, etc.). At this time, for the operation instruction, the cumulative status value of the business attribute in the data record containing the business attribute can also be determined, and an operation record including the cumulative status value can be generated. In this embodiment, it is obvious that one operation instruction will only affect one change of the accumulated state value.

When there are not many data records that are affected, by recording the initial value, change value, and change of the cumulative status value of a small amount of data records, too much resources are not required to be consumed.

In one embodiment, when recording the state value of the data record, it is also possible to record the before and after changes of the data record completely, and record the first data hash value of the data record before the change and the data record after the change. The second data hash value of the data record generates an operation record containing the first data hash value and the second data hash value.

In this way, both the hash value before the data record change and the original text before the data record change are recorded. When the data is rolled back, it can also be verified according to the first data hash value of the data record: That is, after the rollback, the rollback hash value of the data record is recalculated and compared with the first data hash value. If it is consistent, the rollback is correct and the correctness of the data rollback is ensured. The second data hash value is used when the data state changes next time, and is used to trace back according to the first data hash value and the second data hash value in the operation record.

Through the solution provided by the embodiment of this specification, before generating the operation record, first evaluate the degree of change that the operation instruction may have on the data record containing the business attribute. If the degree of change is large, record the operation instruction and generate the operation containing the operation instruction Record and store; if the degree of change is not large, record the changed data record or its related hash value, generate an operation record containing the aforementioned state change, and store it. By evaluating the possible impact of the operation instructions, the relevant operation records are dynamically generated, while ensuring that the data status can be accurately traced back, the system overhead when storing the operation records is saved, and a flexible operation record storage method is realized.

In an implementation manner, the database involved in the embodiment of this specification may be a centralized database that provides services to external parties with a blockchain ledger. The blockchain ledger here can be either a blockchain ledger or a centralized blockchain-like ledger.

At the centralized database service provider, the block chain ledger is generated in the following manner, as shown in Figure 4. Figure 4 is a schematic diagram of the process of generating a block chain ledger provided by the embodiment of this specification, including:

S401: Receive a data record to be stored, and determine a hash value of each data record, where the data record contains business attributes.

As mentioned earlier, the data records to be stored here can be various consumption records of individual users on the client side, or they can be business results, intermediate states, and operations generated when the application server executes business logic based on user instructions. Records and so on. Specific business scenarios can include consumption records, audit logs, supply chains, government supervision records, medical records, and so on.

In the embodiment of this specification, the data record contains business attributes. In each organization that connects with the database server, the business attribute is generally the only one in the docking organization, and the business attributes are based on different The business scenarios of, can include user name, user ID number, driver’s license number, mobile phone number, project unique number, etc.

For example, for a third-party payment institution, the data record is the user's consumption record, and the business attribute at this time is the user ID (including mobile phone number, ID number, user name, etc.), or the user ID is hashed The hash value obtained by the algorithm; or, for government agencies, the data record is the overhead flow of multiple public projects, then the business attribute at this time can be a unique number for each project.

The business attribute can be stored in a designated field in the data record (for example, the head or tail of the data record), so that the database server and the user can easily obtain the business attribute of the data record from it.

It should be noted that multiple data records can be included in the same ledger. The business attributes of these data records are likely to be different. For example, when a ledger is open to multiple users, the data records may come from different users. If the business attribute is a user ID, it is easy to understand that different data records often contain different user IDs.

S403: When a preset block forming condition is reached, determine each data record to be written in the data block, and generate an Nth data block including the hash value of the data block and the data record.

The preset blocking conditions include: the number of data records to be stored reaches the number threshold, for example, every time one thousand data records are received, a new data block is generated and one thousand data records are written into the block; or , The time interval from the last block formation time reaches the time threshold, for example, every 5 minutes, a new data block is generated, and the data records received within these 5 minutes are written into the block.

Here, N refers to the serial number of the data block. In other words, in the embodiment of this specification, the data block is in the form of a block chain, which is arranged sequentially based on the order of the block time, and has strong timing characteristics. Among them, the block height of the data block increases monotonically based on the sequence of the block time. The block height can be a sequence number, at this time the block height of the Nth data block is N; the block height can also be generated in other ways.

When N=1, that is, the data block at this time is the initial data block. The hash value and block height of the initial data block are given based on a preset method. For example, if the initial data block does not contain data records, the hash value is any given hash value, and the block height blknum=0; for another example, the generation trigger condition of the initial data block is consistent with the trigger conditions of other data blocks. However, the hash value of the initial data block is determined by hashing all the contents in the initial data block.

When N>1, since the content and hash value of the previous data block have been determined, at this time, the current data block (the first data block) can be generated based on the hash value of the previous data block (that is, the N-1th data block). For example, a feasible way is to determine the hash value of each data record to be written in the Nth block, and generate a Merck according to the order in the block. In the Er tree, the root hash value of the Merkel tree and the hash value of the previous data block are spliced together, and the hash algorithm is used again to generate the hash value of the current block. For another example, it is also possible to splice according to the order of the data records in the block and obtain the hash value of the entire data record by hashing, splicing the hash value of the previous data block and the hash value of the entire data record, and combining the result The string is hashed to generate the hash value of the data block.

After the user uploads the data successfully, the hash value of the corresponding data record and the hash value of the data block can be obtained and saved, and integrity verification can be initiated based on the hash value. The specific verification method includes recalculating the hash value of the data record itself and the hash value of the data block in which it is located, and comparing it with the locally stored hash value.

The data block generated in the above manner may include two parts: a block header and a block body. The block body can be used to store the plaintext of the spliced data, or the hash value of the spliced data, etc.; the block header can be used to store metadata about the data block, for example, the version number of the ledger, the hash of the previous data block Value, the root hash value of the Merkel tree composed of the spliced data in the own data block, the hash value of the own data block, the state array used to record the operated state of the spliced data, and so on. As shown in FIG. 5, FIG. 5 is a schematic diagram of a block header of a data block provided by an embodiment of this specification.

Through the foregoing method, the user's data record is stored in the blockchain ledger, and integrity verification can be initiated at any time, thereby ensuring that the user's data will not be tampered with. At the same time, it should be noted that in the embodiments of this specification, the blockchain ledger is a broadly defined ledger, which not only includes the part of the structure that stores the user's data record, but also includes the storage of metadata and operations related to the data record. Logs, indexes, and so on.

In this implementation scenario, data records are stored in a non-tamperable block chain ledger, but the database server can also check the "status data" of a certain business attribute (including accumulated value, whether it has been operated, the time it has been operated, etc.) Etc.) to calculate. For example, for a certain business attribute, the status data related to the business attribute is recorded in a designated area block in the index table or metadata.

At this time, if the user performs a corresponding operation for a certain business attribute, some values in the area will change. At this time, the database server can determine the changed designated area block containing the business attribute according to the business attribute, and then determine the first block hash value of the designated area block before the change and the changed Specify the second block of the hash value of the area block, and generate an operation record containing the first block of the hash value and the second block of the hash value.

The first block of hash value and the second block of hash value have similar functions to the aforementioned first data hash value and second data hash value, and are used for the rollback and traceability of the specified area block. Ensure the accuracy of data rollback.

Obviously, the generated operation record may also include the position mark of the designated table block and the business attribute for traceability and rollback.

Correspondingly, an embodiment of this specification also provides an operation record storage device in a database, as shown in FIG. 6, which is a schematic structural diagram of an operation record storage device in a database provided by an embodiment of this specification, including the following modules .

The receiving module 601 receives an operation instruction, and the operation instruction includes a business attribute.

The evaluation module 603 evaluates the degree of change of the operation instruction to the data record containing the business attribute, and determines the operation influence characteristic value, wherein the operation influence characteristic value and the degree of change of the data record containing the business attribute Positive correlation.

The first storage module 605, if the operation influence characteristic value exceeds a threshold, generates an operation record containing the operation instruction, and stores it.

The second storage module 607, otherwise, determines the change state of the data record containing the business attribute, generates an operation record containing the change state, and stores it.

Further, in the device, the evaluation module 603 evaluates the degree of change of the operation instruction to the data record containing the business attribute according to the type of the operation instruction.

Further, in the device, the evaluation module 603 determines the number of data records containing the business attribute, and evaluates the degree of change of the operation instruction to the data records containing the business attribute according to the number .

Further, in the device, the second storage module 607 determines that in the changed data record containing the business attribute, the initial value and the changed value of the business attribute are generated to contain the business attribute Or, determine the cumulative status value of the business attribute in the data record containing the business attribute, and generate the operation record containing the cumulative status value.

Further, in the device, the second storage module 607 determines that among the changed data records containing the business attributes, the first data hash value of the data record before the change and the data record after the change The second data hash value of the data record generates an operation record containing the first data hash value and the second data hash value.

Further, in the device, when the data record is stored in the block-chain ledger, the second storage module 607 determines the designated area block containing the business attribute that has changed; and determines that before the change occurs The first block hash value of the designated area block and the second block hash value of the designated area block after the change occurs, and an operation record containing the first block hash value and the second block hash value is generated .

Further, the device further includes a data block generation module 609, which receives the data records to be stored and determines the hash value of each data record. The data record contains the business attribute; when the preset block condition is reached, it is determined For each data record in the data block to be written, the Nth data block containing the hash value of the data block and the data record is generated, which specifically includes: when N=1, the hash value and block height of the initial data block are based on the preset value. The setting method is given; when N>1, the hash value of the Nth data block is determined according to the data records in the data block to be written and the hash value of the N-1th data block, and the Nth data block is generated. The hash value of the data block and the Nth data block of each data record, wherein the block height of the data block increases monotonically based on the sequence of the block time.

Further, in the device, the preset blocking condition includes: the number of data records to be stored reaches the number threshold; or, the time interval from the last blocking time reaches the time threshold.

The embodiments of this specification also provide a computer device, which includes at least a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the operations shown in FIG. 3 when the program is executed. Record storage prevention and control methods.

FIG. 7 shows a more specific hardware structure diagram of a computing device provided by an embodiment of this specification. The device may include a processor 1010, a memory 1020, an input/output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, the memory 1020, the input/output interface 1030, and the communication interface 1040 realize the communication connection between each other in the device through the bus 1050.

The processor 1010 may be implemented by a general-purpose CPU (Central Processing Unit, central processing unit), microprocessor, application specific integrated circuit (Application Specific Integrated Circuit, ASIC), or one or more integrated circuits for execution related Program to realize the technical solutions provided in the embodiments of this specification.

The memory 1020 may be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 may store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, related program codes are stored in the memory 1020 and called and executed by the processor 1010.

The input/output interface 1030 is used to connect an input/output module to realize information input and output. The input/output/module can be configured in the device as a component (not shown in the figure), or it can be connected to the device to provide corresponding functions. The input device may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and an output device may include a display, a speaker, a vibrator, an indicator light, and the like.

The communication interface 1040 is used to connect a communication module (not shown in the figure) to realize the communication interaction between the device and other devices. The communication module can realize communication through wired means (such as USB, network cable, etc.), or through wireless means (such as mobile network, WIFI, Bluetooth, etc.).

The bus 1050 includes a path to transmit information between various components of the device (for example, the processor 1010, the memory 1020, the input/output interface 1030, and the communication interface 1040).

It should be noted that although the above device only shows the processor 1010, the memory 1020, the input/output interface 1030, the communication interface 1040, and the bus 1050, in the specific implementation process, the device may also include the equipment necessary for normal operation. Other components. In addition, those skilled in the art can understand that the above-mentioned device may also include only the components necessary to implement the solutions of the embodiments of the present specification, and not necessarily include all the components shown in the figures.

The embodiment of this specification also provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the operation record storage method shown in FIG. 3 is implemented.

Computer-readable media include permanent and non-permanent, removable and non-removable media, and information storage can be realized by any method or technology. The information can be computer-readable instructions, data structures, program modules, 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 technology, CD-ROM, digital versatile disc (DVD) or other optical storage, Magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media can be used to store information that can be accessed by computing devices. According to the definition in this article, computer-readable media does not include transitory media, such as modulated data signals and carrier waves.

From the description of the foregoing implementation manners, it can be understood that those skilled in the art can clearly understand that the embodiments of this specification can be implemented by means of software plus a necessary general hardware platform. Based on this understanding, the technical solutions of the embodiments of this specification can be embodied in the form of software products, which can be stored in storage media, such as ROM/RAM, A magnetic disk, an optical disk, etc., include several instructions to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute the methods described in the various embodiments or some parts of the embodiments of this specification.

The systems, methods, modules, or units explained in the above embodiments may be implemented by computer chips or entities, or implemented by products with certain functions. A typical implementation device is a computer. The specific form of the computer can be a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email receiving and sending device, and a game control A console, a tablet computer, a wearable device, or a combination of any of these devices.

The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, as for the method embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and for related parts, please refer to the part of the description of the method embodiment. The method embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separated. When implementing the solutions of the embodiments of this specification, the functions of the modules may be in the same Or multiple software and/or hardware implementations. It is also possible to select some or all of the modules according to actual needs to achieve the objectives of the solutions of the embodiments. Those of ordinary skill in the art can understand and implement it without creative work.

The above are only specific implementations of the embodiments of this specification. It should be pointed out that for those of ordinary skill in the art, without departing from the principle of the embodiments of this specification, several improvements and modifications can be made. These Improvement and retouching should also be regarded as the protection scope of the embodiments of this specification.

Claims

A method for storing operation records in a database, including:

Receiving an operation instruction, where the operation instruction includes a business attribute;

Evaluating the degree of change of the operation instruction to the data record containing the business attribute, and determining the operation influence characteristic value, wherein the operation influence characteristic value is positively correlated with the degree of change of the data record containing the business attribute;

If the operation influence characteristic value exceeds the threshold, an operation record containing the operation instruction is generated and stored;

Otherwise, the change state of the data record containing the business attribute is determined, and the operation record containing the change state is generated and stored.
The method of claim 1, evaluating the degree of change of the operation instruction to the data record containing the business attribute, comprising:

According to the type of the operation instruction, the degree of change of the operation instruction to the data record containing the business attribute is evaluated.
The method of claim 1, evaluating the degree of change of the operation instruction to the data record containing the business attribute, comprising:

The number of data records containing the business attribute is determined, and the degree of change of the operation instruction to the data records containing the business attribute is evaluated according to the number.
The method of claim 1, determining the change state of the data record containing the business attribute, and generating the operation record containing the change state, comprising:

Determine the initial value and the change value of the business attribute in the changed data record containing the business attribute, and generate an operation record that includes the initial value and the change value of the business attribute;

Alternatively, the cumulative status value of the business attribute in the data record containing the business attribute is determined, and an operation record including the cumulative status value is generated.
The method of claim 1, determining the change state of the data record containing the business attribute, and generating the operation record containing the change state, comprising:

Determine the changed data record containing the business attribute, the first data hash value of the data record before the change and the second data hash value of the data record after the change, and generate the data record containing the first Operation record of the hash value of the data and the hash value of the second data.
The method of claim 1, when the data record is stored in a blockchain ledger, determining the change state of the data record containing the business attribute, and generating an operation record containing the change state, include:

Determine the changed designated area block containing the business attribute;

Determine the first block hash value of the designated area block before the change and the second block hash value of the designated area block after the change, and generate the first block hash value and the second block hash value Operation record of the value.
The method according to claim 6, wherein the block chain ledger is pre-generated in the following manner:

Receive the data records to be stored and determine the hash value of each data record, where the data record contains business attributes;

When the preset blocking condition is reached, each data record to be written in the data block is determined, and the Nth data block containing the hash value of the data block and the data record is generated, which specifically includes:

When N=1, the hash value and block height of the initial data block are given based on a preset method;

When N>1, determine the hash value of the Nth data block according to the data records in the data block to be written and the hash value of the N-1th data block, and generate a hash containing the Nth data block The value and the Nth data block of each data record, where the block height of the data block increases monotonically based on the sequence of the block time.
8. The method of claim 7, wherein the preset blocking condition comprises:

The number of data records to be stored reaches the number threshold; or, the time interval from the last block time reaches the time threshold.
An operation record storage device in a database, including:

The receiving module receives an operation instruction, and the operation instruction contains business attributes;

The evaluation module evaluates the degree of change of the operation instruction to the data record containing the business attribute, and determines the operation influence characteristic value, wherein the degree of change of the operation influence characteristic value and the data record containing the business attribute is positive Related

The first storage module, if the operation influence characteristic value exceeds a threshold value, generate an operation record containing the operation instruction, and store it;

The second storage module, otherwise, determines the change state of the data record containing the business attribute, generates and stores the operation record containing the change state.
9. The device according to claim 9, wherein the evaluation module evaluates the degree of change of the operation instruction to the data record containing the business attribute according to the type of the operation instruction.
9. The apparatus according to claim 9, wherein the evaluation module determines the number of data records containing the business attribute, and evaluates the degree of change of the operation instruction to the data records containing the business attribute according to the number.
9. The device according to claim 9, wherein the second storage module determines the initial value and the changed value of the business attribute in the changed data record containing the business attribute, and generates a data record containing the business attribute Operation records of the initial value and the change value; or, determining the cumulative status value of the business attribute in the data record containing the business attribute, and generating the operation record containing the cumulative status value.
The device according to claim 9, wherein the second storage module determines that among the changed data records containing the business attributes, the first data hash value of the data record before the change and the data after the change The recorded second data hash value generates an operation record containing the first data hash value and the second data hash value.
9. The device according to claim 9, when the data record is stored in a block chain ledger, the second storage module determines the designated area block containing the business attribute that has changed; and determines the data before the change The hash value of the first block of the designated area block and the hash value of the second block of the designated area block after the change are generated, and an operation record containing the hash value of the first block and the hash value of the second block is generated.
The device according to claim 9, further comprising a data block generating module, which receives the data records to be stored and determines the hash value of each data record, wherein the data record contains the business attribute; when the preset block condition is reached , Determine each data record in the data block to be written, and generate the Nth data block containing the hash value of the data block and the data record, which specifically includes:

When N=1, the hash value and block height of the initial data block are given based on a preset method;

When N>1, determine the hash value of the Nth data block according to each data record to be written in the data block and the hash value of the N-1th data block, and generate a hash containing the Nth data block The value and the Nth data block of each data record, where the block height of the data block increases monotonically based on the sequence of the block time.
9. The device according to claim 9, wherein the preset blocking condition comprises: the number of data records to be stored reaches the number threshold; or, the time interval from the last blocking time reaches the time threshold.
A computer device, comprising a memory, a processor, and a computer program stored on the memory and running on the processor, wherein the processor executes the program as described in any one of claims 1 to 8 method.