CN113626524A - Data processing method and device and data checking system - Google Patents
Data processing method and device and data checking system Download PDFInfo
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Abstract
The embodiment of the specification provides a data processing method and device and a data checking system, wherein the data processing method is applied to data service of an access block chain node and comprises the following steps: analyzing the data uplink response synchronized by the processing platform to obtain a data storage type and a corresponding data query parameter; calling a data query interface to perform data query on a block chain based on the data storage type and the corresponding data query parameters, and acquiring chain data returned by the data query interface; and storing the on-chain data so as to perform checking processing of the on-chain data and the source data stored by the processing platform.
Description
Technical Field
The present disclosure relates to the field of data processing technologies, and in particular, to a data processing method and apparatus, and a data checking system.
Background
The block chain is a decentralized distributed account book which is stored by taking blocks as units, is in a chain structure formed by ending according to a time sequence and is capable of guaranteeing that the account book cannot be tampered, forged and data transmission access is safe through cryptography. The blockchain technology has the characteristics of decentralization, participation of each computing node in data recording and rapid data synchronization among the computing nodes, so that the blockchain technology is widely applied in a plurality of fields.
Disclosure of Invention
One or more embodiments of the present specification provide a data processing method, which is applied to a data service of an access blockchain node, and includes: and analyzing the data uplink response synchronized by the processing platform to obtain the data storage type and the corresponding data query parameters. And calling a data query interface to perform data query on the block chain based on the data storage type and the corresponding data query parameters, and acquiring the chain data returned by the data query interface. And storing the on-chain data so as to perform checking processing of the on-chain data and the source data stored by the processing platform.
One or more embodiments of the present specification provide a data processing apparatus including: and the data uplink response analysis module is configured to analyze the data uplink response synchronized by the processing platform to obtain the data storage type and the corresponding data query parameters. And the on-chain data query module is configured to call a data query interface to perform data query on the block chain based on the data storage type and the corresponding data query parameters, and acquire on-chain data returned by the data query interface. The on-chain data storage module is configured to store the on-chain data so as to perform checking processing of the on-chain data and the source data stored by the processing platform.
One or more embodiments of the present specification provide a data collation system including: the system comprises a processing platform and a data service of an access block chain node and a data checking platform. The processing platform is configured to submit source data to the block link point and synchronize a data uplink response of the source data to the data service. And the data service is used for analyzing the data uplink response, calling a data query interface to perform data query on the block chain based on the data storage type obtained by analysis and the corresponding data query parameter, and acquiring and storing the data on the chain returned by the data query interface. And the data checking platform is used for checking the data on the chain and the source data stored by the processing platform.
One or more embodiments of the present specification provide a data processing apparatus including: a processor; and a memory configured to store computer-executable instructions that, when executed, cause the processor to: and analyzing the data uplink response synchronized by the processing platform to obtain the data storage type and the corresponding data query parameters. And calling a data query interface to perform data query on the block chain based on the data storage type and the corresponding data query parameters, and acquiring the chain data returned by the data query interface. And storing the on-chain data so as to perform checking processing of the on-chain data and the source data stored by the processing platform.
One or more embodiments of the present specification provide a storage medium storing computer-executable instructions that, when executed, implement the following: and analyzing the data uplink response synchronized by the processing platform to obtain the data storage type and the corresponding data query parameters. And calling a data query interface to perform data query on the block chain based on the data storage type and the corresponding data query parameters, and acquiring the chain data returned by the data query interface. And storing the on-chain data so as to perform checking processing of the on-chain data and the source data stored by the processing platform.
Drawings
In order to more clearly illustrate one or more embodiments or technical solutions in the prior art in the present specification, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present specification, and for those skilled in the art, other drawings can be obtained according to the drawings without inventive exercise;
FIG. 1 is a flow diagram of a data processing method provided in one or more embodiments of the present disclosure;
FIG. 2 is a process flow diagram of a data processing method applied to a data reconciliation scenario in accordance with one or more embodiments of the present disclosure;
FIG. 3 is a schematic diagram of a data processing apparatus according to one or more embodiments of the present disclosure;
FIG. 4 is a schematic diagram of a data reconciliation system provided in one or more embodiments of the present description;
fig. 5 is a schematic structural diagram of a data processing apparatus according to one or more embodiments of the present disclosure.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in one or more embodiments of the present disclosure, the technical solutions in one or more embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in one or more embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all embodiments. All other embodiments that can be derived by a person skilled in the art from one or more of the embodiments described herein without making any inventive step shall fall within the scope of protection of this document.
An embodiment of a data processing method provided in this specification:
referring to fig. 1, which shows a processing flow chart of a data processing method provided by the present embodiment, and referring to fig. 2, which shows a processing flow chart of a data processing method applied to a data collation scenario provided by the present embodiment.
Referring to fig. 1, the data processing method provided in this embodiment is applied to a data service of an access block link node, and specifically includes steps S102 to S106.
Step S102, analyzing the data uplink response synchronized by the processing platform to obtain the data storage type and the corresponding data query parameter.
In the data processing method provided by this embodiment, through cooperation of the data service and the processing platform, the data checking platform, and the accessed block chain node, after the block chain node completes uplink processing of the source data of the processing platform, the data service analyzes a data uplink response synchronized by the processing platform to obtain a corresponding data uplink parameter, and performs data query on the block chain by using the data uplink parameter obtained through analysis as a data query interface provided by a reference calling block chain, and stores the on-chain data returned by the data query interface into an off-line database, and finally, the data checking platform checks the on-chain data stored in the off-line database with the source data stored in the database of the processing platform, thereby realizing checking of the on-chain data with the off-line stored source data, and improving security and correctness of the on-chain data stored in the block chain, the data risk occurrence probability is reduced.
In a specific implementation, before synchronizing the data uplink response, the processing platform initiates data uplink to a block link point accessed in a block chain, specifically, in a data uplink process, the processing platform submits source data to be uplink to the block link point in a data uplink request manner, and after receiving the source data included in the data uplink request, the block link node performs uplink processing on the source data, where data stored on the block chain after performing uplink processing on the source data is referred to as uplink data. In addition, the processing platform stores the source data into the database for subsequent checking processing of the on-chain data obtained by the query on the block chain and the source data in the database.
Optionally, the block chain node accessed by the processing platform in the block chain is the same as the block chain node accessed by the data service in the block chain, and the uplink data in the chain is generated by the block chain node after performing uplink processing according to the data uplink request submitted by the processing platform and is stored in the block chain.
In this embodiment, the data uplink response refers to a processing response obtained after performing data uplink processing on source data, where the data uplink response includes a type identifier of a data storage type and a data query parameter. Optionally, the block link point performs uplink processing according to the data uplink request submitted by the processing platform, and then returns the uplink processing to the processing platform, and the processing platform synchronizes to the data service; or, the data uplink response is generated after the processing platform performs the data uplink query in cooperation with the block link point, and is synchronized to the data service.
The data storage type refers to a type of uplink storage of the source data during uplink processing of the source data or a processing type during uplink storage, for example, hash encryption is performed on the source data, and then hash fields obtained after encryption are stored in a block chain; and for example, calling an intelligent contract deployed by a blockchain node to process the source data, and then storing the processed data into the blockchain.
The data query parameter is a parameter for querying data on the chain of blocks or a parameter related to data query on the chain, such as a hash field for querying data on the chain of blocks.
Optionally, the data storage type includes at least one of the following: a deposit type and a contract type; the evidence storing type refers to a storage mode that source data are stored on a block chain after data encryption is carried out, and data query parameters corresponding to the evidence storing type comprise a hash field;
the contract type refers to that source data is subjected to uplink storage after being processed by calling an intelligent contract deployed on a block link point in the process of uplink storage, and the data query parameters corresponding to the contract type comprise an intelligent contract identifier, a method identifier of an intelligent contract calling method and/or method execution parameters.
In a specific implementation, the processing platform synchronizes the data uplink response to the data service, and after the data uplink response synchronized by the processing platform is obtained, the data uplink response is analyzed, specifically, in the analyzing process, a type identifier and a data query parameter of a data storage type included in the data uplink response are extracted, the obtained data storage type to which the type identifier belongs is the data storage type in the uplink storage process of the source data, and the obtained data query parameter is a data query parameter required for querying data of the data storage type on the block chain, that is, a data query parameter corresponding to the data storage type.
And step S104, calling a data query interface to perform data query on the block chain based on the data storage type and the corresponding data query parameters, and acquiring the chain data returned by the data query interface.
After the data uplink response is analyzed in the above step, and the data storage type and the corresponding data query parameter are obtained, in this step, the data storage type and the corresponding data query parameter obtained by the analysis are taken as parameters, the data query interface provided by the block chain is called to perform data query, and the on-chain data returned by the data query interface is obtained, where the on-chain data is the data stored on the block chain by performing uplink processing on the source data.
As described above, the data storage types in this embodiment include the storage type and the contract type, and the following takes these two data storage types as an example to specifically describe a process of performing data query on a blockchain by using the data query interface, and a query processing process performed by a blockchain node in response to a query call.
If the data storage type is the evidence storage type, optionally, the type identifier of the evidence storage type and the hash field are transmitted to the data query interface, and the chained data returned by the data query interface is received in the process of calling the data query interface to perform data query.
Correspondingly, the block link point in the block chain executes a query processing operation for the query call of the data service to the data query interface, optionally, the query processing operation is implemented in the following manner:
according to the type identification of the evidence storage type and the hash field, which are transmitted by the data query interface, querying initial state data corresponding to the hash field on the block chain as data on the chain;
and returning the data on the chain to the data service through the data query interface.
If the data storage type is the contract type, optionally, in the process of calling the data query interface to perform data query, transmitting the type identifier of the contract type, the intelligent contract identifier, the method identifier of the intelligent contract calling method and/or the method execution parameter into the data query interface, and receiving the data on the chain returned by the data query interface.
Correspondingly, the block link point in the block chain executes a query processing operation for the query call of the data service to the data query interface, optionally, the query processing operation is implemented in the following manner:
carrying out intelligent contract calling and execution according to the type identification of the contract type and the intelligent contract identification, the method identification and/or the method execution parameter transmitted by the data query interface;
and inquiring final state data stored on the block chain as the data on the chain based on an intelligent contract execution result, and returning to the data service through the data inquiry interface.
The initial state data includes encrypted data processed by an encryption means such as an encryption algorithm, and the data type or the data substance of the encrypted data is not changed from the unencrypted state to the encrypted state with respect to the source data. For example, the processing platform encrypts transaction data submitted to the blockchain link point by using a hash algorithm, and then uploads the encrypted data obtained by encryption to the blockchain for storage.
In addition, the initial state data includes the source data itself and data obtained by performing data processing by using other data processing means that do not substantially change the data, such as data obtained by using data processing means such as data compression and data encoding.
The final state data comprises data obtained after the block link point calls an intelligent contract to process according to source data submitted by a processing platform, and compared with the initial state data, the final state data not only changes the data form, but also changes the data substance after corresponding data processing is carried out in the uplink processing process of the block link point.
For example, the processing platform submits transaction type data to the block chain node, after receiving the transaction type data, the block chain node invokes a deployed intelligent contract to perform credit point calculation on the transaction type data, obtains credit points corresponding to the transaction type data, and uploads the credit points obtained through calculation to the block chain for storage, wherein the credit points are changed from the transaction related data to the transaction type data, and the data essence is changed from the transaction related data to the credit related data.
And step S106, storing the data on the chain so as to carry out check processing on the data on the chain and the source data stored by the processing platform.
And after the chain data returned by the data query interface is received, storing the chain data for checking the stored chain data with the source data stored by the processing platform. The storing of the on-chain data specifically includes storing the on-chain data in an off-line database, so that the checking processing of the on-chain data and the source data is realized in an off-line environment.
Specifically, in the process of the collation processing, optionally, the collation processing of the data on the chain and the source data is executed by a data collation platform; after the data checking platform detects that the on-chain data is stored in the off-line database, checking processing is carried out on the basis of the on-chain data stored in the off-line database and the source data stored in the database.
Optionally, if the check result obtained after the checking process is that the on-chain data is consistent with the source data, deleting the on-chain data stored in the offline database; and if the check result obtained after the check processing is that the data on the chain is inconsistent with the source data, generating an alarm notification.
In addition, the data service may perform a checking process of the on-chain data and the source data, specifically, after detecting that the on-chain data is stored in the offline database, perform a checking process based on the on-chain data stored in the offline database and the source data stored in the database.
In this embodiment, an optional implementation manner of batch data export and data check from the blockchain is further provided, so as to improve the data check efficiency, and meanwhile, the implementation manner of batch export and data check is complementary to the implementation manner of the data check provided above, so that the link data stored on the blockchain and the source data stored on the processing platform can be checked from the overall perspective, and thus, the integrity and accuracy of data check are further improved.
Specifically, after receiving a batch verification request of the processing platform, the data export service exports an on-chain data set corresponding to the batch verification request from the block chain through the data export service, and stores the on-chain data set to an off-line database; and the data checking platform checks the initial state data contained in the data set on the chain and the source data stored by the processing platform.
The following further describes the data processing method provided in this embodiment by taking an application of the data processing method provided in this embodiment in a dinner party scenario as an example, referring to fig. 2, the data processing method applied in a data verification scenario specifically includes steps S202 to S210.
Step S202 is to obtain a data uplink response synchronized after the processing platform and the accessed block link point perform uplink processing on the source data.
Step S204, the data uplink response is analyzed to obtain the data storage type and the corresponding data query parameters.
Step S206, if the data storage type is the evidence storage type, the type identification and the hash field of the evidence storage type are transmitted to the data query interface, and the linked data returned by the data query interface are received.
Correspondingly, after the block chain link point receives the query call of the data service for the data query interface, the initial state data corresponding to the hash field is queried on the block chain as the data on the chain according to the type identification of the transmitted evidence storage type and the hash field, and the initial state data is returned through the data service.
And S208, if the data storage type is a contract type, transmitting the type identifier of the contract type, the intelligent contract identifier, the method identifier of the intelligent contract calling method and/or the method execution parameter into the data query interface, and receiving the linked data returned by the data query interface.
Correspondingly, after receiving the query call of the data service to the data query interface, the block chain node performs intelligent contract call and execution according to the transmitted type identifier of the contract type and the intelligent contract identifier, the method identifier and/or the method execution parameter, queries the final state data stored on the block chain based on the intelligent contract execution result as the data on the chain, and returns the data through the data query interface.
Step S210, storing the on-chain data to an off-line database, so that the data checking platform performs checking processing based on the on-chain data stored in the off-line database and the source data stored in the database of the processing platform.
An embodiment of a data processing apparatus provided in this specification is as follows:
in the above embodiments, a data processing method is provided, and correspondingly, a data processing apparatus is also provided, which is described below with reference to the accompanying drawings.
Referring to fig. 3, a schematic diagram of a data processing apparatus provided in this embodiment is shown.
Since the device embodiments correspond to the method embodiments, the description is relatively simple, and the relevant portions may refer to the corresponding description of the method embodiments provided above. The device embodiments described below are merely illustrative.
The present embodiment provides a data processing apparatus, which operates in a data service of an access block chain node, and includes:
a data uplink response analysis module 302 configured to analyze a data uplink response synchronized by the processing platform to obtain a data storage type and a corresponding data query parameter;
the on-chain data query module 304 is configured to invoke a data query interface to perform data query on a block chain based on the data storage type and the corresponding data query parameter, and acquire on-chain data returned by the data query interface;
an on-chain data storage module 306 configured to store the on-chain data for reconciliation of the on-chain data with source data stored by the processing platform.
The embodiment of a data checking system provided by the specification is as follows:
referring to fig. 4, a schematic diagram of a data collation system provided in the present embodiment is shown.
The present embodiment provides a data collation system, including:
a processing platform 401 and a data service 402 of an access blockchain node, and a data collation platform 403;
wherein, the processing platform 401 is configured to submit source data to the block link point, and synchronize a data uplink response of the source data to the data service 402;
the data service 402 is configured to analyze the data uplink response, and based on the data storage type obtained through analysis and the corresponding data query parameter, invoke a data query interface to perform data query on a block chain, and obtain and store data on the chain returned by the data query interface;
the data checking platform 403 is configured to perform checking processing on the on-chain data and the source data stored in the processing platform 401.
It should be noted that, before the processing platform 401 synchronizes the data uplink response, data uplink is initiated to a block link point accessed in a block chain, specifically, in the data uplink process, the processing platform 401 submits source data to be uplink to the block link point in a data uplink request manner, and after receiving the source data included in the data uplink request, the block link node performs uplink processing on the source data, where data stored in the block chain after performing uplink processing on the source data is referred to as uplink data. In addition, the processing platform 401 stores the source data in the database for subsequent checking processing of the on-chain data obtained by the query on the block chain with the source data in the database.
Optionally, the block link point accessed by the processing platform 401 in the block chain is the same block chain node as the block chain node accessed by the data service 402 in the block chain, and the uplink data in the chain is generated by the block link point after performing uplink processing according to the data uplink request submitted by the processing platform 401 and is stored in the block chain.
In this embodiment, the data uplink response refers to a processing response obtained after performing data uplink processing on source data, where the data uplink response includes a type identifier of a data storage type and a data query parameter. Optionally, the block link node performs uplink processing according to the data uplink request submitted by the processing platform 401, and then returns the uplink processing to the processing platform 401, and the processing platform 401 synchronizes to the data service 402; alternatively, the data uplink response is generated after the processing platform 401 performs the data uplink query in cooperation with the block link point, and is synchronized to the data service 402.
The data storage type refers to a type of uplink storage of the source data during uplink processing of the source data or a processing type during uplink storage, for example, hash encryption is performed on the source data, and then hash fields obtained after encryption are stored in a block chain; and for example, calling an intelligent contract deployed by a blockchain node to process the source data, and then storing the processed data into the blockchain. The data query parameter is a parameter for querying data on the chain of blocks or a parameter related to data query on the chain, such as a hash field for querying data on the chain of blocks.
Optionally, the data storage type includes at least one of the following: a deposit type and a contract type; the evidence storing type refers to a storage mode that source data are stored on a block chain after data encryption is carried out, and data query parameters corresponding to the evidence storing type comprise a hash field; the contract type refers to that source data is subjected to uplink storage after being processed by calling an intelligent contract deployed on a block link point in the process of uplink storage, and the data query parameters corresponding to the contract type comprise an intelligent contract identifier, a method identifier of an intelligent contract calling method and/or method execution parameters.
In the system operation process, the processing platform 401 synchronizes the data uplink response to the data service 402, and after the data uplink response synchronized by the processing platform 401 is obtained, the data uplink response is analyzed, specifically, in the analysis process, a type identifier and a data query parameter of a data storage type included in the data uplink response are extracted, the obtained data storage type to which the type identifier belongs is the data storage type in the uplink storage process of the source data, and the obtained data query parameter is a data query parameter required for querying data of the data storage type on the block chain, that is, a data query parameter corresponding to the data storage type.
As described above, the data storage types in this embodiment include the storage type and the contract type, and the following takes these two data storage types as an example to specifically describe a process of performing data query on a blockchain by using the data query interface, and a query processing process performed by a blockchain node in response to a query call.
If the data storage type is the evidence storage type, optionally, the type identifier of the evidence storage type and the hash field are transmitted to the data query interface, and the chained data returned by the data query interface is received in the process of calling the data query interface to perform data query. Correspondingly, the block link point in the block chain executes a query processing operation for the query call of the data service 402 for the data query interface, and optionally, the query processing operation is implemented as follows: according to the type identification of the evidence storage type and the hash field, which are transmitted by the data query interface, querying initial state data corresponding to the hash field on the block chain as data on the chain; the on-chain data is returned to the data service 402 through the data query interface.
If the data storage type is the contract type, optionally, in the process of calling the data query interface to perform data query, transmitting the type identifier of the contract type, the intelligent contract identifier, the method identifier of the intelligent contract calling method and/or the method execution parameter into the data query interface, and receiving the data on the chain returned by the data query interface. Correspondingly, the block link point in the block chain executes a query processing operation for the query call of the data service 402 for the data query interface, and optionally, the query processing operation is implemented as follows: carrying out intelligent contract calling and execution according to the type identification of the contract type and the intelligent contract identification, the method identification and/or the method execution parameter transmitted by the data query interface; and inquiring final state data stored on the block chain as the data on the chain based on the intelligent contract execution result, and returning to the data service 402 through the data inquiry interface.
The initial state data includes encrypted data processed by an encryption means such as an encryption algorithm, and the data type or the data substance of the encrypted data is not changed from the unencrypted state to the encrypted state with respect to the source data. For example, the processing platform 401 sends transaction data to a block link point, and after the block link point encrypts the transaction data by using a hash algorithm, the encrypted data obtained by encryption is uploaded to the block link for storage. In addition, the initial state data includes the source data itself and data obtained by performing data processing by using other data processing means that do not substantially change the data, such as data obtained by using data processing means such as data compression and data encoding.
The final state data includes data obtained after the block link node calls an intelligent contract to process according to source data submitted by the processing platform 401, and with respect to the initial state data, after the final state data performs corresponding data processing in the process of performing uplink processing on the block link node, not only the data form changes, but also the data substance changes. For example, the processing platform 401 submits transaction data to a block link point, and after receiving the transaction data, the block link point invokes a deployed intelligent contract to perform credit point calculation on the transaction data, to obtain credit points corresponding to the transaction data, and then uploads the credit points obtained through calculation to the block link for storage.
Specifically, in the process of performing the collation processing by the data collation platform 403, after the data collation platform 403 detects that the on-chain data is stored in the off-line database, the collation processing is performed based on the on-chain data stored in the off-line database and the source data stored in the database. Optionally, if the check result obtained after the checking process is that the on-chain data is consistent with the source data, deleting the on-chain data stored in the offline database; and if the check result obtained after the check processing is that the data on the chain is inconsistent with the source data, generating an alarm notification.
In addition, the embodiment also provides a data export service for exporting data from the blockchain in batches, and by taking the implementation mode of batch export and data verification as a supplement to the implementation of the data verification, the on-chain data stored on the blockchain and the source data stored by the processing platform 401 can be verified from the overall perspective, so that the data verification efficiency is further improved. Specifically, after receiving the batch verification request of the processing platform 401, the data export service exports an on-chain data set corresponding to the batch verification request from the block chain through the data export service, and stores the on-chain data set in an offline database; and the data checking platform 403 performs checking processing on the initial state data included in the data set on the chain and the source data stored by the processing platform 401.
An embodiment of a data processing apparatus provided in this specification is as follows:
corresponding to the data processing method described above, based on the same technical concept, one or more embodiments of the present specification further provide a data processing apparatus for executing the data processing method provided above, and fig. 5 is a schematic structural diagram of the data processing apparatus provided in one or more embodiments of the present specification.
The data processing device provided by the embodiment comprises:
as shown in fig. 5, the data processing apparatus may have a relatively large difference due to different configurations or performances, and may include one or more processors 501 and a memory 502, where the memory 502 may store one or more stored applications or data. Memory 502 may be, among other things, transient or persistent storage. The application programs stored in memory 502 may include one or more modules (not shown), each of which may include a series of computer-executable instructions in a data processing device. Still further, the processor 501 may be arranged in communication with the memory 502 to execute a series of computer executable instructions in the memory 502 on the data processing device. The data processing apparatus may also include one or more power supplies 503, one or more wired or wireless network interfaces 504, one or more input/output interfaces 505, one or more keyboards 506, etc.
In one particular embodiment, a data processing apparatus comprises a memory, and one or more programs, wherein the one or more programs are stored in the memory, and the one or more programs may comprise one or more modules, and each module may comprise a series of computer-executable instructions for the data processing apparatus, and the one or more programs configured for execution by the one or more processors comprise computer-executable instructions for:
analyzing the data uplink response synchronized by the processing platform to obtain a data storage type and a corresponding data query parameter;
calling a data query interface to perform data query on a block chain based on the data storage type and the corresponding data query parameters, and acquiring chain data returned by the data query interface;
and storing the on-chain data so as to perform checking processing of the on-chain data and the source data stored by the processing platform.
An embodiment of a storage medium provided in this specification is as follows:
in correspondence to the above-described data processing method, based on the same technical concept, one or more embodiments of the present specification further provide a storage medium.
The storage medium provided in this embodiment is used to store computer-executable instructions, and when executed, the computer-executable instructions implement the following processes:
analyzing the data uplink response synchronized by the processing platform to obtain a data storage type and a corresponding data query parameter;
calling a data query interface to perform data query on a block chain based on the data storage type and the corresponding data query parameters, and acquiring chain data returned by the data query interface;
and storing the on-chain data so as to perform checking processing of the on-chain data and the source data stored by the processing platform.
It should be noted that the embodiment related to the storage medium in this specification and the embodiment related to the data processing method in this specification are based on the same inventive concept, and therefore, specific implementation of this embodiment may refer to implementation of the foregoing corresponding method, and repeated details are not described here.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
In the 30 s of the 20 th century, improvements in a technology could clearly be distinguished between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an Integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Hardware Description Language), traffic, pl (core universal Programming Language), HDCal (jhdware Description Language), lang, Lola, HDL, laspam, hardward Description Language (vhr Description Language), vhal (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.
The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: the ARC625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functions of the units may be implemented in the same software and/or hardware or in multiple software and/or hardware when implementing the embodiments of the present description.
One skilled in the art will recognize that one or more embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, one or more embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The description has been presented with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the description. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, 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, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
One or more embodiments of the present description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. One or more embodiments of the specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The above description is only an example of this document and is not intended to limit this document. Various modifications and changes may occur to those skilled in the art from this document. Any modifications, equivalents, improvements, etc. which come within the spirit and principle of the disclosure are intended to be included within the scope of the claims of this document.
Claims (25)
1. A data processing method is applied to data service of an access block chain node, and comprises the following steps:
analyzing the data uplink response synchronized by the processing platform to obtain a data storage type and a corresponding data query parameter;
calling a data query interface to perform data query on a block chain based on the data storage type and the corresponding data query parameters, and acquiring chain data returned by the data query interface;
and storing the on-chain data so as to perform checking processing of the on-chain data and the source data stored by the processing platform.
2. The data processing method of claim 1, the data storage type comprising at least one of: a deposit type and a contract type;
the data query parameter corresponding to the certificate storage type comprises a hash field;
the data query parameters corresponding to the contract type comprise an intelligent contract identifier, a method identifier of an intelligent contract calling method and/or method execution parameters.
3. The data processing method according to claim 2, wherein the invoking a data query interface to perform data query on a blockchain and obtain chain data returned by the data query interface based on the data storage type and the corresponding data query parameter comprises:
and if the data storage type is the evidence storage type, transmitting the type identification of the evidence storage type and the hash field into the data query interface, and receiving the data on the link returned by the data query interface.
4. The data processing method of claim 3, wherein the block link node receives a query call of the data service to the data query interface, and performs the following operations:
according to the type identification of the evidence storage type and the hash field, which are transmitted by the data query interface, querying initial state data corresponding to the hash field on the block chain as data on the chain;
and returning the data on the chain to the data service through the data query interface.
5. The data processing method according to claim 2, wherein the invoking a data query interface to perform data query on a blockchain and obtain chain data returned by the data query interface based on the data storage type and the corresponding data query parameter comprises:
and if the data storage type is the contract type, transmitting the type identifier of the contract type, the intelligent contract identifier, the method identifier of the intelligent contract calling method and/or the method execution parameter into the data query interface, and receiving the chain data returned by the data query interface.
6. The data processing method of claim 5, wherein the block link node receives a query call of the data service to the data query interface, and performs the following operations:
carrying out intelligent contract calling and execution according to the type identification of the contract type and the intelligent contract identification, the method identification and/or the method execution parameter transmitted by the data query interface;
and inquiring final state data stored on the block chain as the data on the chain based on an intelligent contract execution result, and returning to the data service through the data inquiry interface.
7. The data processing method of claim 1, wherein the processing platform accesses the block chain node, and the uplink data is generated by the block chain node after uplink processing according to a data uplink request submitted by the processing platform and is stored in the block chain.
8. The data processing method of claim 7, wherein the data uplink response is returned to the processing platform by the block-chaining point after uplink processing according to the data uplink request submitted by the processing platform, and is synchronized to the data service by the processing platform.
9. The data processing method of claim 7, wherein the data uplink response is generated after the processing platform performs data uplink inquiry in conjunction with the block node and is synchronized to the data service.
10. The data processing method of claim 1, the source data being stored in a database of the processing platform;
the storing the on-chain data comprises: and storing the on-chain data to an off-line database.
11. The data processing method of claim 10, wherein the collation process of the on-chain data with the source data is performed by a data collation platform;
after the data checking platform detects that the on-chain data is stored in the off-line database, checking processing is carried out on the basis of the on-chain data stored in the off-line database and the source data stored in the database.
12. The data processing method according to claim 11, wherein if the check result obtained after the check processing is that the on-chain data is consistent with the source data, the on-chain data stored in the off-line database is deleted;
and if the check result obtained after the check processing is that the data on the chain is inconsistent with the source data, generating an alarm notification.
13. The data processing method according to claim 1, after receiving a batch verification request of the processing platform, exporting an on-chain data set corresponding to the batch verification request from the block chain through a data export service, and storing the on-chain data set to an off-line database;
and the data checking platform checks the initial state data contained in the data set on the chain and the source data stored by the processing platform.
14. A data processing apparatus operable on a data service of an access blockchain node, comprising:
the data uplink response analysis module is configured to analyze the data uplink response synchronized by the processing platform to obtain a data storage type and corresponding data query parameters;
the on-chain data query module is configured to call a data query interface to perform data query on a block chain based on the data storage type and the corresponding data query parameter, and acquire on-chain data returned by the data query interface;
the on-chain data storage module is configured to store the on-chain data so as to perform checking processing of the on-chain data and the source data stored by the processing platform.
15. A data collation system comprising:
accessing a processing platform and a data service of a block chain node, and a data checking platform;
wherein, the processing platform is configured to submit source data to the block link point and synchronize a data uplink response of the source data to the data service;
the data service is used for analyzing the data uplink response, calling a data query interface to perform data query on the block chain based on the data storage type obtained by analysis and the corresponding data query parameter, and acquiring and storing the data on the chain returned by the data query interface;
and the data checking platform is used for checking the data on the chain and the source data stored by the processing platform.
16. The data collation system according to claim 15, said data storage type including at least one of: a deposit type and a contract type;
the data query parameter corresponding to the certificate storage type comprises a hash field;
the data query parameters corresponding to the contract type comprise an intelligent contract identifier, a method identifier of an intelligent contract calling method and/or method execution parameters.
17. The data collation system according to claim 16, wherein the step of calling a data query interface to perform data query on the blockchain based on the data storage type obtained by the parsing and the corresponding data query parameter comprises:
and if the data storage type is the evidence storage type, transmitting the type identification of the evidence storage type and the hash field into the data query interface.
18. A data collation system according to claim 17, wherein, after the block link node receives a query call by the data service to the data query interface, the following is performed:
according to the type identification of the evidence storage type and the hash field, which are transmitted by the data query interface, querying initial state data corresponding to the hash field on the block chain as data on the chain;
and returning the data on the chain to the data service through the data query interface.
19. The data collation system according to claim 16, wherein the step of calling a data query interface to perform data query on the blockchain based on the data storage type obtained by the parsing and the corresponding data query parameter comprises:
and if the data storage type is the contract type, transmitting the type identifier of the contract type, the intelligent contract identifier, the method identifier of the intelligent contract calling method and/or the method execution parameter into the data query interface, and receiving the chain data returned by the data query interface.
20. A data collation system according to claim 19, wherein, after the block link node receives a query call by the data service to the data query interface, the following is performed:
carrying out intelligent contract calling and execution according to the type identification of the contract type and the intelligent contract identification, the method identification and/or the method execution parameter transmitted by the data query interface;
and inquiring final state data stored on the block chain as the data on the chain based on an intelligent contract execution result, and returning to the data service through the data inquiry interface.
21. The data collation system according to claim 19, said source data being stored in a database of said processing platform;
the on-chain data is stored to an off-line database.
22. The data collation system according to claim 21, wherein if the collation result obtained after the collation process is that the on-chain data is identical to the source data, the on-chain data stored in the off-line database is deleted;
and if the check result obtained after the check processing is that the data on the chain is inconsistent with the source data, generating an alarm notification.
23. The data reconciliation system of claim 15 further comprising:
the data export service is used for exporting the on-chain data set corresponding to the batch checking request from the block chain according to the batch checking request of the processing platform and storing the on-chain data set to an off-line database; and the data checking platform checks the initial state data contained in the data set on the chain and the source data stored by the processing platform.
24. A data processing apparatus comprising:
a processor; and a memory configured to store computer-executable instructions that, when executed, cause the processor to:
analyzing the data uplink response synchronized by the processing platform to obtain a data storage type and a corresponding data query parameter;
calling a data query interface to perform data query on a block chain based on the data storage type and the corresponding data query parameters, and acquiring chain data returned by the data query interface;
and storing the on-chain data so as to perform checking processing of the on-chain data and the source data stored by the processing platform.
25. A storage medium storing computer-executable instructions that when executed implement the following:
analyzing the data uplink response synchronized by the processing platform to obtain a data storage type and a corresponding data query parameter;
calling a data query interface to perform data query on a block chain based on the data storage type and the corresponding data query parameters, and acquiring chain data returned by the data query interface;
and storing the on-chain data so as to perform checking processing of the on-chain data and the source data stored by the processing platform.
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