HK1247300B - Data processing method and equipment based on blockchain - Google Patents

Description

A data processing method and device based on blockchain

Technical Field

The present application relates to the fields of Internet information processing technology and computer technology, and in particular to a data processing method and device based on blockchain.

Background Art

Blockchain technology, also known as distributed ledger technology, is a distributed internet database technology characterized by decentralization, transparency, immutability, and trustworthiness. A network built on blockchain technology is called a blockchain network. This network consists of network nodes (also referred to as blockchain nodes, hereinafter referred to as nodes). Each network node corresponds to at least one blockchain, and each blockchain contains at least one block.

Since a network node sends the data to be stored to other network nodes in the blockchain network by broadcasting when receiving the data to be stored, each network node in the blockchain network stores the full amount of data of the blockchain network, and the data stored on each network node is consistent.

Specifically, data storage in a blockchain network generally involves two phases: First, nodes in the blockchain network receive the data to be stored and broadcast it across the entire network. This allows all nodes in the blockchain network to receive the data and, at this point, write it into their cache. Second, nodes in the blockchain network that obtain storage rights for the data write it into a block upon obtaining the recording rights, and then add the block to the existing blockchain. This demonstrates that blockchain networks employ an asynchronous write strategy for data storage.

However, in real-world scenarios, asynchronous write strategies are used to store business data in blockchain networks. Typically, in the first phase, a data pool queue is maintained, and data to be stored is written to the data pool queue sequentially according to its timestamp. In the second phase, data in the data pool queue is written to the block according to the first-in, first-out principle.

Research has found that storing data in the blockchain network in the above manner has the following problems: for businesses with higher business priorities, the business data processing efficiency is relatively low, which in turn leads to relatively low processing efficiency of these businesses.

Summary of the Invention

In view of this, the embodiments of the present application provide a blockchain-based data processing method and device, which are used to solve the problem of low efficiency in processing business data with relatively high business priority in the prior art.

The present invention provides a data processing method based on blockchain, including:

A node in the blockchain receives at least one piece of business data generated within a set time period, wherein the business data includes tag information for representing a processing priority of the business data;

When a new block is generated, the node determines the processing volume corresponding to the label information according to the preset correspondence between the label information and the processing volume;

The node obtains, according to the processing volume, service data that meets the processing volume and contains the label information from the data processing center, and the data processing center stores the received service data;

The acquired business data is stored in the block.

The present application also provides a blockchain-based data processing device, including:

a receiving unit, configured to receive at least one piece of service data generated within a set time period, wherein the service data includes tag information for representing a processing priority of the service data;

a determining unit, which determines, when a new block is generated, a processing amount corresponding to the label information according to a preset correspondence between the label information and the processing amount;

an acquiring unit, configured to acquire, from a data processing center, business data that meets the processing volume and contains the tag information, based on the processing volume, and to store the received business data in the data processing center;

The processing unit stores the acquired business data in the block.

At least one of the above technical solutions adopted in the embodiments of the present application can achieve the following beneficial effects:

By determining the processing volume for business data with different processing priorities, business data with different processing priorities can be obtained when storing business data in the block, so that business data with different processing priorities can be processed. This breaks the provision in the prior art that business data is processed solely according to time factors, and avoids the problem of low processing efficiency of business with higher business priorities in the prior art. The solution provided in the embodiment of the present application not only ensures the processing efficiency of business data with high processing priority, but also ensures the processing efficiency of business data with low processing priority. When meeting the processing priority, it increases the flexibility of business data processing in the blockchain and also enhances the use value of the blockchain in the field of business applications.

BRIEF DESCRIPTION OF THE DRAWINGS

The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

FIG1 is a flow chart of a data processing method based on blockchain provided in an embodiment of the present application;

FIG2 is a schematic diagram of a data processing set corresponding to business data of different processing priorities provided by an embodiment of the present application;

FIG3 is a schematic diagram of a scenario of a blockchain-based data processing method provided in an embodiment of the present application;

FIG4 is a schematic diagram of the structure of a blockchain-based data processing device provided in an embodiment of the present application.

DETAILED DESCRIPTION

To make the purpose, technical solutions, and advantages of this application more clear, the technical solutions of this application will be clearly and completely described below in conjunction with the specific embodiments of this application and the corresponding drawings. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

The following describes in detail the technical solutions provided by various embodiments of the present application in conjunction with the accompanying drawings.

Figure 1 is a flow chart of a blockchain-based data processing method provided in an embodiment of the present application. The method may be as follows. The execution subject in the embodiment of the present application may be any business node in the blockchain (also referred to as a blockchain node, hereinafter referred to as a node), without specific limitation here. In the embodiment of the present application, the execution subject is taken as an example to be described in detail.

Step 101: A node in the blockchain receives at least one piece of business data generated within a set time period.

The service data includes label information for representing the processing priority of the service data.

In the embodiments of the present application, processing priorities can be set for service data generated by different services. When the service data is generated, tag information indicating the processing priority of the service data can be added to the service data. In this way, when the service data is received, the processing priority of the service data can be determined based on the tag information. The processing priority here can also be referred to as the processing level, which is not specifically defined here.

Furthermore, in the embodiments of the present application, the processing priority set for service data may be determined based on the service type or other factors, which are not specifically limited herein. For example, the processing priorities of different service data generated by the same service may be the same or different; and the processing priorities of different service data generated by different services may be the same or different.

For example, first, service priorities can be determined for different services. The service priority here corresponds to the processing priority of the service data. That is, the higher the service priority, the higher the service processing priority of the service data generated by that service. Secondly, a field, called tag information, can be added to the service data to indicate the processing priority of the service data.

Preferably, in the technical solution provided in the embodiment of the present application, the processing volume can be determined in advance for business data with different processing priorities, and a corresponding relationship can be established between the label information corresponding to the processing priority and the determined processing volume.

Specifically, determine the processing priority of business data of different businesses, and determine the mapping relationship between different processing priorities and label information; determine the processing volume corresponding to the processing priority based on the processing priority; establish a corresponding relationship between the label information corresponding to the processing priority and the processing volume.

It should be noted that the processing capacity here can be a processing ratio or a processing quantity, and there is no specific limitation here.

Table 1 is a table showing the correspondence between label information and processing volume.

Table 1

Processing priority Tag information Processing volume (here we take the processing ratio as an example) First priority 10000 30% Second priority 20000 20% Third priority 30,000 10%

As can be seen from Table 1, if the tag information contained in the business data is 10,000, indicating that the processing priority of the business data is first, then the processing capacity for the first priority is 30%; if the tag information contained in the business data is 20,000, indicating that the processing priority of the business data is second, then the processing capacity for the second priority is 20%; if the tag information contained in the business data is 30,000, indicating that the processing priority of the business data is third, then the processing capacity for the third priority is 10%. It should be noted that the processing ratios shown in Table 1 are based on the storage capacity of the blockchain block. Therefore, the amount of business data required to store a particular business in a block can be calculated based on the processing capacity and the storage capacity of the block.

Preferably, in the embodiment of the present application, the processing volume of the same type of business data in different time periods can be different. That is, multiple processing priorities can be set for the same type of business data, so that the processing volume of the business data in different time periods is different.

Here, we take business data A as an example. In this embodiment of the present application, assuming that business data A is the first priority business data, the processing capacity of business data A can be set to 30% of the storage capacity of the block at any time; in addition, the processing capacity of business data A can be dynamically adjusted.

For example: in the T1 time period, if business data A is set to be the business data with the second priority for processing, then the processing volume of the business data A can account for 30% of the storage capacity of the block; in the T2 time period, if business data A is set to be the business data with the first priority for processing, then the processing volume of the business data A can account for 50% of the storage capacity of the block; in the T3 time period, if business data A is set to be the business data with the third priority for processing, then the processing volume of the business data A can account for 10% of the storage capacity of the block. In this embodiment of the present application, the correspondence between the time period, label information and processing volume can also be pre-established. For example: when business data is generated, the time period corresponding to the generation time of the business data is determined, and the label information corresponding to the time period is included in the business data.

Typically, the fields in business data include but are not limited to: hash value, version number, public key, signature, hash value of the block to which it belongs, timestamp (i.e., the time when the node accepts the business data), etc., and the fields included in the business data recorded in the embodiment of the present application include but are not limited to: as shown in Table 2. Table 2 describes the specific attributes of each field:

Table 2

Preferably, in an embodiment of the present application, data processing sets can also be configured for business data of different processing priorities based on the determined processing priority, so that when business data is received, it can be stored separately according to the tag information contained in the business data, that is, business data containing the same tag information is stored in the same data processing set.

It should be noted that since there is a time interval between two adjacent blocks generated in the blockchain, this time interval can be used as a reference condition for setting the time period in the embodiments of the present application, and is not specifically limited here.

Preferably, in the embodiment of the present application, when the node receives at least one service data generated within a set time period, the method further includes:

Determining, based on the tag information included in the business data, a data processing set corresponding to the tag information;

The business data is stored in the determined data processing center.

Figure 2 is a schematic diagram of data processing sets corresponding to business data of different processing priorities provided in an embodiment of the present application. As can be seen from Figure 2, two data processing sets are included: one data processing set corresponds to processing priority 1, that is, the business data corresponding to processing priority 1 is stored in this data processing set; the other data processing set corresponds to processing priority 2, that is, the business data corresponding to processing priority 2 is stored in this data processing set.

Step 102: When a new block is generated, the node determines the processing volume corresponding to the label information according to the preset correspondence between the label information and the processing volume.

In the embodiment of the present application, the correspondence between the preset tag information and the processing amount can be established in the following ways, including:

Determine the processing priority of business data for different businesses, and determine the mapping relationship between different processing priorities and tag information;

determining, according to the processing priority, a processing amount corresponding to the processing priority;

A corresponding relationship between the label information corresponding to the processing priority and the processing volume is established.

Specifically, a piece of label information is arbitrarily selected, and the processing amount corresponding to the selected label information is determined according to a preset correspondence relationship between the label information and the processing amount.

Here, the tag information can also be selected in the order of processing priority, from high to low. Then, the processing amount corresponding to different tag information is determined according to the above method.

Step 103: The node obtains the service data including the service identifier that meets the processing volume from the data processing set according to the processing volume.

In the embodiment of the present application, the amount of service data including the tag information to be acquired is determined based on the processing volume and the storage capacity of the block;

The quantity of service data including the service identifier is acquired from a data processing center, and the data processing center stores the received service data.

For example: for business data to be processed, the processing volume corresponding to the preset tag information can be determined based on the correspondence between the tag information and the processing volume. For example: the processing volume is p (in percentage form), then in an embodiment of the present application, the storage capacity of the new block is determined. For example: the storage capacity is x, then the amount of business data corresponding to the tag information that needs to be stored in the block is determined to be xp.

Preferably, when a new block is generated, if the received business data corresponds to at least two different processing priorities, the node determines the processing volume corresponding to the label information of different processing priorities respectively, and the sum of the processing volumes corresponding to the different label information is less than or equal to the storage capacity of the block.

For example: assuming that the business data to be processed corresponds to multiple processing priorities (for example, processing priority 1 and processing priority 2), then based on the correspondence between the preset tag information and the processing volume, the processing volume corresponding to the tag information is determined respectively. For example: the processing volume corresponding to the tag information of processing priority 1 is p (in percentage form), and the processing volume corresponding to the tag information of processing priority 2 is m (in percentage form).

Another example: assuming that the business data to be processed corresponds to multiple businesses (for example: business 1 and business 2, the processing priority corresponding to business 1 is processing priority 1, and the processing priority corresponding to business 2 is processing priority 2), then according to the correspondence between the preset tag information and the processing volume, the processing volume corresponding to the tag information is determined respectively, for example: the processing volume corresponding to the tag information of business 1 is p (in percentage form), and the processing volume corresponding to the tag information of business 2 is m (in percentage form).

In this embodiment of the present application, the storage capacity of a new block is determined. For example, if the storage capacity is x, the amount of business data corresponding to the tag information of processing priority 1 that needs to be stored in the block is xp, and the amount of business data corresponding to the tag information of processing priority 2 that needs to be stored in the block is xm. It should be noted that the sum of (xm + xp) is less than or equal to x.

There is also a situation where some business data has a low processing priority and the system does not configure tag information for it, or configures tag information but does not determine the processing volume for it. In this case, you can handle it in the following ways, but not limited to:

When the service data does not contain tag information, according to the free capacity of the block, obtain service data that does not contain tag information and meets the free capacity from the data processing set; or

When the processing volume corresponding to the tag information is Null, business data containing the tag information that meets the idle capacity is acquired from the data processing set according to the idle capacity of the block.

For example: the received business data corresponds to multiple businesses (for example: business 1, business 2 and business 3) or multiple processing priorities, then according to the correspondence between the preset label information and the processing volume, the processing volume corresponding to the label information is determined respectively. For example: the processing volume corresponding to the label information of business 1 is p (in percentage form), the processing volume corresponding to the label information of business 2 is m (in percentage form), and the processing volume corresponding to the label information of business 3 is empty.

Then, in an embodiment of the present application, the storage capacity of a new block is determined. For example, if the storage capacity is x, the amount of business data corresponding to the tag information of business 1 that needs to be stored in the block is xp, the amount of business data corresponding to the tag information of business 2 that needs to be stored in the block is xm, and the amount of business data corresponding to the tag information of business 3 that needs to be stored in the block is (1-p-m)x.

In the embodiment of the present application, there is another situation where the amount of the business data stored in the data processing set corresponding to the tag information is less than the processing capacity, which means that the business data stored in the data processing set cannot meet the processing capacity requirement. In order to achieve reasonable use of resources, in this case, the business data is obtained from the data processing set according to the amount of business data stored in the data processing set. That is, all the business data stored in the data processing set is read out.

In an embodiment of the present application, based on the processing volume and the timestamp of the business data, business data that meets the processing volume is obtained from the data processing set corresponding to the tag information.

Specifically, according to the order of the acceptance times corresponding to the business data, business data that meets the processing volume is acquired from the data processing set corresponding to the tag information.

Step 104: The node stores the acquired business data in the block.

In the embodiment of the present application, the acquired business data are stored in the blocks in sequence according to the order of the acceptance times corresponding to the business data.

Through the technical solution provided in the embodiment of the present application, the processing volume is determined for business data of different processing priorities. When storing business data in the block, business data of different processing priorities can be obtained to ensure that business data of different processing priorities can be processed. This breaks the provision in the prior art that business data is processed solely according to time factors, and avoids the problem of low processing efficiency of businesses with higher business priorities in the prior art. The solution provided in the embodiment of the present application ensures both the processing efficiency of business data with high processing priority and the processing efficiency of business data with low processing priority. When the processing priority is met, the flexibility of business data processing in the blockchain is increased, and the use value of the blockchain in the field of business applications is also enhanced.

FIG3 is a schematic diagram of a scenario of a data processing method based on blockchain provided in an embodiment of the present application. As can be seen from FIG3, when a node in the blockchain receives business data, it determines the business identifier of the business data. When a new block is generated, the processing quantity of the business data can be determined based on the processing priority of the business data, and the business data that meets the processing quantity is obtained from the cache and stored in the block (i.e., implemented in the manner of steps 102 to 103 in the above embodiment).

Figure 4 is a schematic diagram of the structure of a blockchain-based data processing device provided in an embodiment of the present application. The data processing device includes: a receiving unit 401, a determining unit 402, an acquiring unit 403, and a processing unit 404, wherein:

The receiving unit 401 receives at least one piece of service data generated within a set time period, wherein the service data includes tag information for representing a processing priority of the service data;

The determining unit 402 determines the processing amount corresponding to the tag information according to the preset correspondence between the tag information and the processing amount when a new block is generated;

The acquiring unit 403 acquires, according to the processing volume, business data that meets the processing volume and contains the tag information from the data processing center, and the data processing center stores the received business data;

The processing unit 404 stores the acquired business data in the block.

In another embodiment of the present application, the data processing device further includes: an establishing unit 405, wherein:

The establishing unit 405 establishes a correspondence between preset tag information and processing volume, including:

Determine the processing priority of business data for different businesses, and determine the mapping relationship between different processing priorities and tag information;

determining, according to the processing priority, a processing amount corresponding to the processing priority;

A corresponding relationship between the label information corresponding to the processing priority and the processing volume is established.

In another embodiment of the present application, the processing volume of the same type of business data is different in different time periods.

In another embodiment of the present application, the acquiring unit 403 acquires, from the data processing set according to the processing volume, the business data containing the tag information that satisfies the processing volume, including:

Determining the amount of service data containing the tag information to be acquired based on the processing volume and the storage capacity of the block;

Acquire the quantity of business data containing the tag information from the data processing set.

In another embodiment of the present application, the acquiring unit 403 acquires, from the data processing set according to the processing volume, the business data containing the tag information that satisfies the processing volume, including:

When the service data does not contain tag information, according to the free capacity of the block, obtain service data that does not contain tag information and meets the free capacity from the data processing set; or

When the processing volume corresponding to the tag information is Null, business data containing the tag information that meets the idle capacity is acquired from the data processing set according to the idle capacity of the block.

In another embodiment of the present application, the data device further includes: a storage unit 406, wherein:

When the node receives at least one piece of service data generated within a set time period, the storage unit 406 determines a data processing set corresponding to the label information according to the label information included in the service data;

The business data is stored in the determined data processing center.

In another embodiment of the present application, the acquiring unit 403 acquires, from the data processing set according to the processing volume, the business data containing the tag information that satisfies the processing volume, including:

According to the processing volume and the timestamp of the business data, business data that meets the processing volume is acquired from the data processing set corresponding to the tag information.

In another embodiment of the present application, the acquiring unit 403 acquires, from the data processing set according to the processing volume, the business data containing the tag information that satisfies the processing volume, including:

When the amount of the business data stored in the data processing set corresponding to the tag information is less than the processing volume, the business data is obtained from the data processing set according to the amount of the business data stored in the data processing set.

In another embodiment of the present application, when a new block is generated, the determining unit 402 determines the processing amount corresponding to the tag information according to a preset correspondence between the tag information and the processing amount, including:

When a new block is generated, if the received business data corresponds to at least two different processing priorities, the processing volume corresponding to the tag information of different processing priorities is determined respectively, and the sum of the processing volumes corresponding to different tag information is less than or equal to the storage capacity of the block.

It should be noted that the data processing device provided in the embodiment of the present application can be implemented by software or hardware, and is not specifically limited here. The data processing device recorded in the embodiment of the present application determines the processing capacity for business data of different processing priorities. When storing business data in the block, business data of different processing priorities can be obtained to enable business data of different processing priorities to be processed, breaking the provisions of the prior art that only process business data according to time factors, and avoiding the problem of low processing efficiency of business with higher business priority in the prior art. The solution provided in the embodiment of the present application not only ensures the processing efficiency of business data with high processing priority, but also ensures the processing efficiency of business data with low processing priority. When the processing priority is met, the flexibility of business data processing in the blockchain is increased, and the use value of the blockchain in the field of business applications is also enhanced.

In the 1990s, technological improvements could be clearly distinguished as either hardware improvements (for example, improvements to circuit structures such as diodes, transistors, and switches) or software improvements (improvements to process flows). However, with the advancement of technology, many process flow improvements today can now be considered direct improvements to hardware circuit structures. Designers almost always create the corresponding hardware circuit structure by programming the improved process flow into the hardware circuit. Therefore, it cannot be said that a process flow improvement cannot be implemented using hardware modules. For example, a programmable logic device (PLD), such as a field programmable gate array (FPGA), is an integrated circuit whose logical function is determined by user programming. Designers can "integrate" a digital system on a PLD by programming it themselves, without having to hire a chip manufacturer to design and produce a dedicated integrated circuit chip. Moreover, nowadays, instead of manually fabricating integrated circuit chips, this programming is mostly done using "logic compiler" software. This is similar to the software compiler used when developing programs. Before compilation, the original code must also be written in a specific programming language, called a hardware description language (HDL). There is not just one HDL, but many, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art will also understand that by simply programming the method flow in one of these hardware description languages and then programming it into an integrated circuit, a hardware circuit that implements the logic method flow can be easily obtained.

The controller can be implemented in any suitable manner. For example, the controller can take the form of 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, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. The memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also know that in addition to implementing the controller in a purely computer-readable program code format, the controller can be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, such a controller can be considered a hardware component, and the devices included therein for implementing various functions can also be considered as structures within the hardware component. Or even, the devices for implementing various functions can be considered as both software modules that implement the method and structures within the hardware component.

The systems, devices, modules, or units described in the above embodiments may be implemented by computer chips or entities, or by products having certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, 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 the convenience of description, the above devices are described as being divided into various units according to their functions. Of course, when implementing this application, the functions of each unit can be implemented in the same or multiple software and/or hardware.

It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

The present invention is described with reference to the flowcharts and/or block diagrams of the methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and/or box in the flowchart and/or block diagram, as well as the combination of processes and/or boxes in the flowchart and/or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device that implements the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.

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

Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and/or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. 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, compact disc read-only memory (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 that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

The present application may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communications network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

The various embodiments in this specification are described in a progressive manner. Similar parts between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the system embodiments are generally similar to the method embodiments, so the description is relatively simple. For relevant parts, refer to the description of the method embodiments.

The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims (18)

1. A data processing method based on blockchain, comprising: A node in the blockchain receives at least one piece of business data generated within a set time period, wherein the business data includes tag information for representing a processing priority of the business data; When a new block is generated, the node determines the processing volume corresponding to the label information according to the preset correspondence between the label information and the processing volume; The node obtains, according to the processing volume, service data that meets the processing volume and contains the label information from the data processing center, and the data processing center stores the received service data; The acquired business data that meets the processing volume and contains the tag information is stored in the new block. 2. The data processing method according to claim 1, wherein establishing a correspondence between preset tag information and processing volume comprises: Determine the processing priority of business data for different businesses, and determine the mapping relationship between different processing priorities and tag information; determining, according to the processing priority, a processing amount corresponding to the processing priority; A corresponding relationship between the label information corresponding to the processing priority and the processing volume is established. 3. The data processing method according to claim 2 is characterized in that the processing volume of the same business data in different time periods is different. 4. The data processing method according to claim 1, wherein, based on the processing volume, obtaining business data containing the tag information that meets the processing volume from the data processing set comprises: Determining the amount of service data containing the tag information to be acquired based on the processing volume and the storage capacity of the block; Acquire the quantity of business data containing the tag information from the data processing set. 5. The data processing method according to any one of claims 1 to 4, characterized in that, according to the processing volume, obtaining business data containing the tag information that meets the processing volume from the data processing set comprises: When the service data does not contain tag information, according to the free capacity of the block, obtain service data that does not contain tag information and meets the free capacity from the data processing set; or When the processing volume corresponding to the tag information is Null, business data containing the tag information that meets the idle capacity is acquired from the data processing set according to the idle capacity of the block. 6. The data processing method according to claim 1, wherein when the node receives at least one service data generated within a set time period, the method further comprises: Determining, based on the tag information included in the business data, a data processing set corresponding to the tag information; The business data is stored in the determined data processing center. 7. The data processing method according to claim 6, wherein, based on the processing volume, obtaining business data containing the tag information that meets the processing volume from the data processing set comprises: According to the processing volume and the timestamp of the business data, business data that meets the processing volume is acquired from the data processing set corresponding to the tag information. 8. The data processing method according to claim 6, wherein, based on the processing volume, obtaining business data containing the tag information that meets the processing volume from the data processing set comprises: When the amount of the business data stored in the data processing set corresponding to the tag information is less than the processing volume, the business data is obtained from the data processing set according to the amount of the business data stored in the data processing set. 9. The data processing method according to claim 1, wherein when a new block is generated, the node determines the processing volume corresponding to the tag information based on a preset correspondence between the tag information and the processing volume, comprising: When a new block is generated, if the received business data corresponds to at least two different processing priorities, the processing volume corresponding to the tag information of different processing priorities is determined respectively, and the sum of the processing volumes corresponding to different tag information is less than or equal to the storage capacity of the block. 10. A data processing device based on blockchain, comprising: a receiving unit, configured to receive at least one piece of service data generated within a set time period, wherein the service data includes tag information for representing a processing priority of the service data; a determining unit, which determines, when a new block is generated, a processing amount corresponding to the label information according to a preset correspondence between the label information and the processing amount; an acquiring unit, configured to acquire, from a data processing center, business data that meets the processing volume and contains the tag information, based on the processing volume, and to store the received business data in the data processing center; The processing unit stores the acquired business data that meets the processing volume and contains the tag information in the new block. 11. The data processing device according to claim 10, characterized in that the data processing device comprises: an establishment unit, wherein: The establishing unit establishes a correspondence between preset tag information and processing volume, including: Determine the processing priority of business data for different businesses, and determine the mapping relationship between different processing priorities and tag information; determining, according to the processing priority, a processing amount corresponding to the processing priority; A corresponding relationship between the label information corresponding to the processing priority and the processing volume is established. 12. The data processing device according to claim 11, wherein the processing volume of the same business data is different in different time periods. 13. The data processing device according to claim 10, wherein the acquiring unit acquires the business data containing the tag information that meets the processing volume from the data processing set according to the processing volume, comprising: Determining the amount of service data containing the tag information to be acquired based on the processing volume and the storage capacity of the block; Acquire the quantity of business data containing the tag information from the data processing set. 14. The data processing device according to any one of claims 10 to 13, wherein the acquiring unit acquires the business data containing the tag information that meets the processing volume from the data processing set according to the processing volume, comprising: When the service data does not contain tag information, according to the free capacity of the block, obtain service data that does not contain tag information and meets the free capacity from the data processing set; or When the processing volume corresponding to the tag information is Null, business data containing the tag information that meets the idle capacity is acquired from the data processing set according to the idle capacity of the block. 15. The data processing device according to claim 10, wherein when the receiving unit receives at least one piece of service data generated within a set time period, the receiving unit further comprises: Determining, based on the tag information included in the business data, a data processing set corresponding to the tag information; The business data is stored in the determined data processing center. 16. The data processing device according to claim 15, wherein the acquiring unit acquires the business data containing the tag information that meets the processing volume from the data processing set according to the processing volume, comprising: According to the processing volume and the timestamp of the business data, business data that meets the processing volume is acquired from the data processing set corresponding to the tag information. 17. The data processing device according to claim 15, wherein the acquiring unit acquires the business data containing the tag information that meets the processing volume from the data processing set according to the processing volume, comprising: When the amount of the business data stored in the data processing set corresponding to the tag information is less than the processing volume, the business data is obtained from the data processing set according to the amount of the business data stored in the data processing set. 18. The data processing device according to claim 10, wherein when a new block is generated, the determining unit determines the processing amount corresponding to the tag information according to a preset correspondence between the tag information and the processing amount, comprising: When a new block is generated, if the received business data corresponds to at least two different processing priorities, the processing volume corresponding to the tag information of different processing priorities is determined respectively, and the sum of the processing volumes corresponding to different tag information is less than or equal to the storage capacity of the block.