WO2022134830A1

WO2022134830A1 - Method and apparatus for processing block node data, computer device, and storage medium

Info

Publication number: WO2022134830A1
Application number: PCT/CN2021/126083
Authority: WO
Inventors: 王强
Original assignee: 深圳壹账通智能科技有限公司
Priority date: 2020-12-23
Filing date: 2021-10-25
Publication date: 2022-06-30
Also published as: CN112732775A

Abstract

A method and apparatus for processing block node data, a computer device, and a storage medium. The method comprises: in response to a query condition carried in a query request of a user, determining a target block node for storage of target data on each block node (S302); analyzing performance of the target block node by using a distributed exploration routing analysis method to obtain a performance analysis result (S304); and performing, according to the performance analysis result and the query condition, query processing on stored data which is uploaded to a distributed cloud storage server and at least comprises the target data, so as to obtain target data meeting the query condition (S306). Therefore, since the target block node for storage of target data can be determined in each block node row according to the query condition carried in the query request, the target data meeting the query request of the user can be quickly and accurately queried, thereby effectively improving the processing efficiency of the data stored on the block node, and improving the user experience.

Description

Method, device, computer equipment and storage medium for processing block node data

This application claims the priority of the Chinese patent application filed on December 23, 2020 with the application number 202011537841.8 and the title of the invention is "block node data processing method, device, computer equipment and storage medium", all of which The contents are incorporated herein by reference.

technical field

The present application relates to the technical field of block storage, and in particular, to a method, apparatus, computer equipment and storage medium for processing block node data.

Background technique

The inventor found that the current blockchain technology cannot query and preview the data stored on each block node in the blockchain in advance. The downloaded data is viewed on the device. In this way, the downloaded data may take a lot of time for the user and is not the data required by the user, which not only wastes precious memory resources, but also consumes the user's precious time, resulting in poor user experience.

In view of the problem that the existing processing methods of data stored on block nodes are too lagging, how to improve the processing efficiency of data stored on block nodes and quickly and accurately query the data required by users is to be solved technical issues.

technical problem

Based on this, it is necessary to provide a method, device, computer equipment and storage medium for processing block node data in order to solve the problem of low processing efficiency of the data stored on each block on the blockchain.

technical solutions

In a first aspect, an embodiment of the present application provides a method for processing block node data, the method includes: in response to a query condition carried in a user's query request, determining a target area for storing target data on each block node The block node, the query request is used to query the target data; the performance of the target block node is analyzed by using a distributed probe route analysis method, and a performance analysis result is obtained; according to the performance analysis result and the query condition, the The stored data including at least the target data uploaded to the distributed cloud storage server is subjected to query processing to obtain the target data that meets the query conditions, and the target data includes target summary data that meets the query conditions. and the target full-text data that matches the query conditions.

In a second aspect, an embodiment of the present application provides an apparatus for processing block node data, the apparatus comprising: a determination unit configured to determine a target on each block node in response to a query condition carried in a user's query request The target block node of the data storage, the query request is used to query the target data; the performance analysis unit is used to analyze the performance of the target block node determined by the determination unit by using a distributed probe route analysis method, and obtain A performance analysis result; a processing unit configured to query the stored data uploaded to the distributed cloud storage server including at least the target data according to the performance analysis result and the query condition analyzed by the performance analysis unit processing to obtain the target data that meets the query condition, and the target data includes target abstract data that matches the query condition and target full-text data that matches the query condition.

In a third aspect, an embodiment of the present application provides a computer device, including a memory and a processor, where computer-readable instructions are stored in the memory, and when the computer-readable instructions are executed by the processor, the processor causes the processor to Execute the above-mentioned processing method of block node data, the method includes: in response to the query condition carried in the user's query request, determining the target block node of the target data storage on each block node, and the query request is used for querying the target data; analyze the performance of the target block node by using a distributed probe route analysis method, and obtain a performance analysis result; Perform query processing on the stored data including the target data to obtain the target data that meets the query conditions, and the target data includes target summary data that meets the query conditions and targets that meet the query conditions. Full text data.

In a fourth aspect, an embodiment of the present application provides a storage medium storing computer-readable instructions. When the computer-readable instructions are executed by one or more processors, the one or more processors execute the above-mentioned block node A data processing method, the method comprising: in response to a query condition carried in a user's query request, determining a target block node for storing target data on each block node, and the query request is used to query the target data; using The distributed probe route analysis method analyzes the performance of the target block node, and obtains a performance analysis result; The stored data is subjected to query processing to obtain the target data that meets the query conditions, and the target data includes target abstract data that meets the query conditions and target full-text data that meets the query conditions.

beneficial effect

By adopting the embodiment of the present application, since the target block node for storing the target data can be determined in each block node row according to the query conditions carried in the query request, the target data that meets the user's query request can be quickly and accurately queried, Thus, the processing efficiency of the data stored on the block nodes is effectively improved, and the user experience is improved.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not limiting of the present application.

Description of drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description serve to explain the principles of the application.

FIG. 1 is an implementation environment diagram of a method for processing block node data provided in an embodiment.

FIG. 2 is a block diagram of the internal structure of a computer device in one embodiment.

FIG. 3 is a schematic flowchart of a method for processing block node data provided by an embodiment of the present disclosure.

FIG. 4 is a schematic structural diagram of an apparatus for processing block node data according to an embodiment of the present disclosure.

Embodiments of the present invention

The following description and drawings sufficiently illustrate specific embodiments of the application to enable those skilled in the art to practice them.

It should be clear that the described embodiments are only a part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

This application may relate to the field of artificial intelligence technology, for example, relevant data may be acquired and processed based on artificial intelligence technology. Optionally, the technical solutions of the present application can be applied to various data processing scenarios, such as data processing scenarios for medical data in digital medicine, and data processing scenarios for financial data in financial technology. For example, the medical data, financial data, etc. can be stored in the blockchain. Optionally, the medical data may include one or more of personal health records, prescriptions, examination reports, and medical insurance business data.

The optional embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.

FIG. 1 is an implementation environment diagram of a method for processing block node data provided in an embodiment. As shown in FIG. 1 , the implementation environment includes a computer device 110 and a terminal 120 .

It should be noted that the terminal 120 and the computer device 110 may be a smart phone, a tablet computer, a notebook computer, a desktop computer, etc., but are not limited thereto. The computer device 110 and the terminal 110 may be connected through Bluetooth, USB (Universal Serial Bus, Universal Serial Bus) or other communication connection methods, which are not limited in this application.

FIG. 2 is a schematic diagram of the internal structure of a computer device in one embodiment. As shown in FIG. 2, the computer device includes a processor, a non-volatile storage medium, a memory, and a network interface connected through a system bus. Wherein, the non-volatile storage medium of the computer device stores an operating system, a database and computer-readable instructions, and the database may store a sequence of control information. When the computer-readable instructions are executed by the processor, the processor can realize a A method for processing block node data. The processor of the computer device is used to provide computing and control capabilities and support the operation of the entire computer device. Computer-readable instructions may be stored in the memory of the computer device, and when the computer-readable instructions are executed by the processor, the processor may execute a method for processing block node data. The network interface of the computer equipment is used for communication with the terminal connection. Those skilled in the art can understand that the structure shown in FIG. 2 is only a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer equipment to which the solution of the present application is applied. Include more or fewer components than shown in the figures, or combine certain components, or have a different arrangement of components.

As shown in FIG. 3 , an embodiment of the present disclosure provides a method for processing block node data. The method for processing block node data is applied to a server, and specifically includes the following method steps.

S302: In response to the query condition carried in the query request of the user, determine the target block node of the target data storage on each block node, and the query request is used to query the target data.

In this embodiment of the present application, query conditions matching the user's query request may be configured according to the needs of different users. The query conditions include at least one target keyword for querying target data and a valid time period of the data. The target data includes not only the target abstract data conforming to the query conditions, but also the target full-text data conforming to the query conditions.

In a possible implementation manner, the method for processing block node data provided by an embodiment of the present disclosure further includes the following steps: in a blockchain network, discovering block nodes.

In the embodiment of the present application, the discovery of block nodes can be divided into the discovery of initial block nodes and the discovery of block nodes after startup. The discovery of the initial block node means that the block node has just been downloaded, and when it is run for the first time, there is no block node data in the block node. The discovery of block nodes after startup indicates that the running wallet has been able to dynamically maintain available block nodes following the network.

Specifically, the discovery process of the initial block node is as follows.

In the blockchain network, the discovery of the initial block node is realized in the following two ways: the first is DNS seed, also known as the DNS seed block node. DNS is a centralized domain name query service. The second is some addresses hardcoded in the code, and these addresses are called hardcoded seed block nodes. When the DNS seed block nodes all fail, the full block nodes will try to connect to the hardcoded seed block nodes.

The discovery process of block nodes after startup is as follows: In a blockchain network, a block node can send the list of peer block nodes it maintains to neighboring block nodes, and after the initial block node is discovered , the current block node will ask the other party for the block node list, that is, make a copy of the other party's block node list. Therefore, every time a protocol message needs to be sent, it will spend a fixed time trying to establish a connection with the block nodes in the existing block node list. As long as any block node can be connected before the timeout, there is no need to pass DNS seed block node gets the address.

In practical application scenarios, if the number of full-block nodes is very large, the possibility of connection timeout of all the block nodes in the existing list is very small.

S304: Analyze the performance of the target block node by using a distributed probe route analysis method, and obtain a performance analysis result.

In the embodiment of the present application, the performance analysis result includes the block hash value of the target block node and the target storage amount of the target data stored by the target block node.

The above lists the contents of common performance analysis results. In addition to the block hash value of the target block node and the target storage amount of the target data stored by the target block node listed above, it can also be used according to different application scenarios. requirements, introduce other parameters, which will not be repeated here.

In a possible implementation manner, the method for processing block node data provided by the embodiment of the present disclosure further includes the following steps: using a distributed probe route analysis method to analyze the nodes stored on each block node of the blockchain data.

In the blockchain network, the above block node list is obtained, and the block node list adopts a mature algorithm in the P2P network protocol, the KAD network. The KAD network uses DHT to locate resources, which is a distributed hash table. The KAD network will maintain a routing table for quickly locating the target block node. The KAD network is based on the UDP protocol. In the blockchain network, the block node discovery is based on the UDP protocol. After the block node is found, the data interaction will switch to the TCP protocol.

In the process of using the distributed probe route analysis method to analyze the node data on each block node of the storage blockchain, the interaction protocol between each block node will be involved.

The interaction protocol process between each block node is as follows: Once the block node establishes a connection, the interaction between each block node will follow some specific commands, which are written in the header of the message and in the body of the message. Write the message content.

There are two types of commands: one is a request command, and the other is a data interaction command.

The first thing to do after the block node is connected is the handshake operation. Through the above handshake operation, get some brief information, for example, first exchange the version number to see if it is compatible.

After the handshake is completed, a long connection needs to be maintained. In order to maintain the heartbeat of the long connection between the block nodes, two types of messages, PING/PONG, are used.

Commands are generally divided into control commands and data transmission commands. For example, the getaddr command is used to obtain the list of available block nodes of the other party, and the inv command provides data transmission. The message body will contain a data vector.

In order to realize data sharing between each block node, block synchronization is adopted. There are two methods of block synchronization. The first method is called HeaderFirst. This method will synchronize the block header first, and then obtain the block body from other block nodes after the synchronization is completed. This provides a better interactive process. This reduces the burden on the blockchain network; the second is called BlockFirst, which requires the blocks obtained from other block nodes to be complete.

S306: Perform query processing on the stored data uploaded to the distributed cloud storage server including at least the target data according to the performance analysis result and the query conditions, to obtain the target data that meets the query conditions, and the target data includes the target abstracts that meet the query conditions. Data and target full-text data that match the query conditions.

In this embodiment of the present application, the query conditions include at least one target keyword for querying the target data and a valid time period of the data, and the query processing of the stored data uploaded to the distributed cloud storage server including at least the target data includes the following: Step: According to the at least one target keyword, select data matching the at least one target keyword from the stored data as candidate data.

In a possible implementation manner, according to the at least one target keyword, selecting data matching the at least one target keyword from the stored data as candidate data includes the following steps: according to the at least one target keyword and the target abstract data, from the storage data The data that matches at least one target keyword is selected from the abstract data of the data as candidate data.

In the embodiment of the present application, in order to save resources, when querying the target data in the stored data, only part of the data of the stored data is often queried. For example, part of the data may be the hash value of the block, and part of the data may also be the stored data. The summary data of the stored data may be a summary and summary of the full-text data corresponding to the stored data. In this way, the user can judge in advance whether the data stored in the current block has the target data required by the user by previewing the summary data. If it is judged from the summary data that the data stored in the current block includes the target data required by the user, the address information of the block node is pushed to the user's terminal device, so that according to the address information of the block node, the distributed The cloud storage server accurately locates the target block node where the target data that meets the query conditions of the user is stored, and queries the target abstract data corresponding to the target data and the target full-text data corresponding to the target data on the target block node.

In the embodiment of the present application, in order to improve the security of blockchain data query and download, the user can also be asked to provide the hash value of the target block node storing the target data, only the hash value of the target block node provided by the user Only when the desired value is correct, the user is allowed to view or download the target abstract data and target full-text data corresponding to some data.

In a possible implementation manner, according to the at least one target keyword, selecting data matching the at least one target keyword from the stored data as candidate data further includes the following steps: according to the at least one target keyword and the target full-text data, from The data matching at least one target keyword is selected from the full-text data of the stored data as candidate data.

According to the valid time period of the data, the data within the valid time period of the data is selected from the candidate data as the target data.

In a possible implementation manner, the method for processing block node data provided by the embodiment of the present disclosure further includes the following steps: converting the target abstract data, the target full-text data, the block hash value of the target block node and the target block The target storage amount of the target data stored by the node is synchronized to the target block node.

In the embodiment of the present application, the storage of the blockchain is based on a distributed database, and the database is the data carrier of the blockchain.

In a blockchain, each block has the hash of the previous block, which is called the parent block of the current block.

The transaction data is a single hash value and is stored in the block header. Through the hash value, the security of the data is improved. For the same message, the same hash value is generated. The hash value can help to see if the data has been tampered with.

In this embodiment of the present application, to check whether the data has been tampered with, the data can be run through a hash value algorithm, and the hash value of the data and the hash value of the received data can be compared. If the above two hash values are the same, the data is not changed. If the above two hashes do not match, the data is changed before it is received.

In the embodiment of the present application, after it is determined that the hash value of the block has not been tampered with, the hash value can be automatically synchronized to the block node.

In a possible implementation manner, after it is determined that the block hash value of the target block node has not been tampered with, the block hash value of the target block node can be automatically synchronized to the target block node.

In addition to automatically synchronizing the hash value to the block node, digest data or storage data can also be automatically synchronized to the block node.

In a possible implementation manner, in addition to automatically synchronizing the block hash value of the target block node to the target block node, the target abstract data or the target full-text data can also be automatically synchronized to the target block node.

In a possible implementation manner, the method for processing block node data provided by the embodiment of the present disclosure further includes the following steps: downloading the target digest data to the user's terminal device; The processing efficiency of the data on the node is to further filter the target data according to the target summary data by downloading the target summary data to the user's terminal device, so that the target data can be accurately determined.

In a possible implementation manner, the method for processing block node data provided by the embodiment of the present disclosure further includes the following steps: downloading the target full-text data to the user's terminal device; in this way, directly downloading the target full-text data to the user's terminal On the device, the user can quickly and accurately obtain the target data that meets the user's query conditions, which improves the processing efficiency of the data stored in each block node, and ultimately improves the user experience.

In a possible implementation manner, the method for processing block node data provided by the embodiment of the present disclosure further includes the following steps: downloading the target abstract data to the user's terminal device, and downloading the target full-text data to the user's terminal device In this way, it is convenient for the user to review the target data according to the target summary data, and when the target full-text data needs to be viewed, the target full-text data that has been downloaded to the user's terminal device can be directly viewed.

In the embodiment of the present application, in order to further improve the security of the data stored in the block node, the user who has the ability to view the target full-text data can also be configured to have the first authority, and the user who has the ability to download the target full-text data can be configured as Has a second authority, wherein the second authority is higher than the first authority.

In an actual application scenario, after multiple users have provided the block hash value of the target block node, it is preliminarily determined that the multiple users have the first authority to view the target full-text data.

In a possible implementation manner, the method for processing block node data provided by the embodiment of the present disclosure further includes the following steps: acquiring historical behavior data of multiple users, if the historical behavior data of multiple users shows that a certain user The target associated data related to the target full-text data is also shared, and the target associated data is uploaded to the target block node, then it is determined that the user who shares the target associated data not only has the first authority to view the target full-text data, but also has The second permission to download the target full-text data. In this way, a reward mechanism is introduced, which is beneficial for more users to upload the target-related data related to the target full-text data to the target block node, so as to achieve the purpose of data sharing. .

In the embodiment of the present disclosure, in response to the query condition carried in the query request of the user, the target block node of the target data storage is determined on each block node; the performance of the target block node is analyzed by using the distributed probe route analysis method, Obtain a performance analysis result; according to the performance analysis result and query conditions, perform query processing on the stored data uploaded to the distributed cloud storage server including at least target data, and obtain target data that meets the query conditions. Therefore, according to the embodiment of the present application, the target block node of the target data storage can be determined in each block node row according to the query conditions carried in the query request, so that the target that meets the user's query request can be quickly and accurately queried. data, thereby effectively improving the processing efficiency of the data stored on the block nodes and improving the user experience.

The following is an embodiment of an apparatus for processing block node data of the present application, which can be used to execute an embodiment of a method for processing block node data of the present application. For details not disclosed in the embodiments of the apparatus for processing block node data of the present application, please refer to the embodiments of the method for processing block node data of the present application.

Please refer to FIG. 4 , which shows a schematic structural diagram of an apparatus for processing block node data provided by an exemplary embodiment of the present application. The block node data processing device can be implemented as all or a part of the terminal through software, hardware or a combination of the two. The block node data processing apparatus includes a determination unit 402 , a performance analysis unit 404 and a processing unit 406 .

Specifically, the determining unit 402 is configured to, in response to the query condition carried in the query request of the user, determine the target block node of the target data storage on each block node, and the query request is used to query the target data.

The performance analysis unit 404 is configured to analyze the performance of the target block node determined by the determination unit 402 by adopting a distributed probe route analysis method to obtain a performance analysis result.

The processing unit 406 is configured to perform query processing on the stored data uploaded to the distributed cloud storage server including at least the target data according to the performance analysis results and query conditions analyzed by the performance analysis unit 404, to obtain target data that meets the query conditions, The target data includes target abstract data conforming to the query condition and target full-text data conforming to the query condition.

Optionally, the query conditions include at least one target keyword for querying the target data and a valid time period of the data, and the processing unit 406 is configured to: filter the stored data according to the at least one target keyword that matches the at least one target keyword. The data is used as candidate data; according to the valid time period of the data, the data within the valid time period of the data is selected from the candidate data as the target data.

Optionally, the processing unit 406 is specifically configured to: filter data matching the at least one target keyword from the abstract data of the stored data as candidate data according to the at least one target keyword and the target abstract data.

Optionally, the processing unit 406 is further configured to: filter data matching the at least one target keyword from the full-text data of the stored data as candidate data according to the at least one target keyword and the target full-text data.

Optionally, the performance analysis result includes the block hash value of the target block node and the target storage amount of the target data stored by the target block node.

Optionally, the device further includes: a synchronization unit (not shown in FIG. 4 ) for storing the target abstract data, the target full-text data, the block hash value of the target block node and the target block node The target storage amount of data is synchronized to the target block node.

Optionally, the apparatus further includes: a downloading unit (not shown in FIG. 4 ), configured to download the target summary data to the terminal device of the user after the processing unit obtains the target data that meets the query condition, or, Download the target full-text data to the user's terminal device.

The downloading unit (not shown in FIG. 4 ) is further configured to download the target abstract data to the user’s terminal device and download the target full-text data to the user’s terminal device after the processing unit obtains the target data that meets the query condition .

It should be noted that, when the apparatus for processing block node data provided by the above embodiments executes the method for processing block node data, only the division of the above-mentioned functional modules is used as an example. The function distribution is completed by different function modules, that is, the internal structure of the device is divided into different function modules to complete all or part of the functions described above. In addition, the apparatus for processing block node data provided by the above embodiments and the embodiment of the method for processing block node data belong to the same concept, and the implementation process of the embodiment is detailed in the embodiment of the method for processing block node data, which will not be repeated here.

In the embodiment of the present disclosure, the determining unit is used to determine the target block node of the target data storage on each block node in response to the query condition carried in the user's query request; the performance analysis unit is used to analyze the route by distributed exploration The method analyzes the performance of the target block node determined by the determination unit, and obtains a performance analysis result; and the processing unit is used for, according to the performance analysis result and query condition analyzed by the performance analysis unit, to upload to the distributed cloud storage server at least the target block. The stored data of the data is subjected to query processing to obtain target data that meets the query conditions. Therefore, according to the embodiment of the present application, the target block node of the target data storage can be determined in each block node row according to the query conditions carried in the query request, so that the target that meets the user's query request can be quickly and accurately queried. data, thereby effectively improving the processing efficiency of the data stored on the block nodes and improving the user experience.

In one embodiment, a computer device is proposed. The computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented: in response to a user's The query conditions carried in the query request are used to determine the target block node of the target data storage on each block node, and the query request is used to query the target data; the performance of the target block node is analyzed by the distributed probe routing analysis method, and the performance analysis is obtained. Result: According to the performance analysis results and query conditions, perform query processing on the stored data uploaded to the distributed cloud storage server including at least the target data, and obtain the target data that meets the query conditions, and the target data includes the target abstracts that meet the query conditions. Data and target full-text data that match the query conditions.

In one embodiment, a storage medium is provided that stores computer-readable instructions that, when executed by one or more processors, cause the one or more processors to perform the following steps: in response to a user's The query conditions carried in the query request determine the target block node of the target data storage on each block node, and the query request is used to query the target data; the performance of the target block node is analyzed by using the distributed probe routing analysis method, and the performance analysis is obtained. Result: According to the performance analysis result and the query conditions, query the stored data uploaded to the distributed cloud storage server including at least the target data, and obtain the target data that meets the query conditions, and the target data includes the target abstract that meets the query conditions. Data and target full-text data matching the query conditions.

Optionally, the storage medium involved in this application may be non-volatile or volatile.

Those of ordinary skill in the art can understand that the realization of all or part of the processes in the methods of the above embodiments can be accomplished by instructing relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and the program is During execution, it may include the processes of the embodiments of the above-mentioned methods. The aforementioned storage medium may be a non-volatile storage medium such as a magnetic disk, an optical disk, a read-only memory (Read-Only Memory, ROM), or a random storage memory (Random Access Memory, RAM), etc.

The technical features of the above embodiments can be combined arbitrarily. In order to make the description simple, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features It is considered to be the range described in this specification.

The above-mentioned embodiments only represent several embodiments of the present application, and the descriptions thereof are relatively specific and detailed, but should not be construed as a limitation on the scope of the patent of the present application. It should be pointed out that for those skilled in the art, without departing from the concept of the present application, several modifications and improvements can be made, which all belong to the protection scope of the present application. Therefore, the scope of protection of the patent of the present application shall be subject to the appended claims.

Claims

A method for processing block node data, wherein the method comprises:

In response to the query condition carried in the query request of the user, determine the target block node of the target data storage on each block node, and the query request is used to query the target data;

Analyze the performance of the target block node by using a distributed probe route analysis method to obtain a performance analysis result;

According to the performance analysis results and the query conditions, query processing is performed on the stored data uploaded to the distributed cloud storage server including at least the target data, to obtain the target data that meets the query conditions. The data includes target abstract data conforming to the query condition and target full-text data conforming to the query condition.
The method according to claim 1, wherein the query condition includes at least one target keyword for querying the target data and a valid time period of the data, and the pair of data uploaded to the distributed cloud storage server at least includes The query processing of the stored data of the target data includes:

According to at least one target keyword, filter data matching at least one target keyword from the stored data as candidate data;

According to the valid time period of the data, the data within the valid time period of the data is selected from the candidate data as the target data.
The method according to claim 2, wherein, according to the at least one target keyword, filtering the data matching the at least one target keyword from the stored data as the candidate data comprises:

According to the at least one target keyword and the target abstract data, the data matching the at least one target keyword is selected from the abstract data of the stored data as the candidate data.
The method according to claim 2, wherein, according to the at least one target keyword, filtering data matching at least one target keyword from the stored data as candidate data further comprises:

According to the at least one target keyword and the target full-text data, the data matching the at least one target keyword is selected from the full-text data of the stored data as the candidate data.
The method of claim 1, wherein,

The performance analysis result includes the block hash value of the target block node and the target storage amount of the target data stored by the target block node.
The method of claim 5, wherein the method further comprises:

Synchronize the target abstract data, the target full-text data, the block hash value of the target block node and the target storage amount of the target block node to store the target data to the target area on the block node.
The method according to claim 1, wherein after obtaining the target data that meets the query condition, the method further comprises:

downloading the target summary data to the user's terminal device, and/or,

Downloading the target full-text data to the user's terminal device.
An apparatus for processing block node data, wherein the apparatus comprises:

a determining unit, configured to determine a target block node for storing target data on each block node in response to the query condition carried in the user's query request, and the query request is used to query the target data;

A performance analysis unit, configured to analyze the performance of the target block node determined by the determination unit by using a distributed probe route analysis method to obtain a performance analysis result;

The processing unit is configured to perform query processing on the stored data uploaded to the distributed cloud storage server including at least the target data according to the performance analysis result and the query condition analyzed by the performance analysis unit, and obtain a The target data of the query condition, the target data includes target abstract data that conforms to the query condition and target full-text data that conforms to the query condition.
A computer device, comprising a memory and a processor, the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, causes the processor to perform the following method:

In response to the query condition carried in the query request of the user, determine the target block node of the target data storage on each block node, and the query request is used to query the target data;

Analyze the performance of the target block node by using a distributed probe route analysis method to obtain a performance analysis result;

According to the performance analysis result and the query conditions, query processing is performed on the stored data uploaded to the distributed cloud storage server including at least the target data, to obtain the target data that meets the query conditions. The data includes target abstract data conforming to the query condition and target full-text data conforming to the query condition.
The computer device according to claim 9, wherein the query condition includes at least one target keyword for querying the target data and a valid time period of the data, and executing the uploading to the distributed cloud storage server Performing query processing on the stored data including at least the target data includes:

According to at least one target keyword, screening data matching at least one target keyword from the stored data as candidate data;

According to the valid time period of the data, the data within the valid time period of the data is selected from the candidate data as the target data.
The computer device according to claim 10, wherein performing the screening of data matching the at least one target keyword from the stored data as candidate data according to the at least one target keyword comprises:

According to the at least one target keyword and the target abstract data, the data matching the at least one target keyword is selected from the abstract data of the stored data as the candidate data.
The computer device according to claim 10, wherein performing the screening of data matching the at least one target keyword from the stored data as candidate data according to the at least one target keyword further comprises:

According to the at least one target keyword and the target full-text data, the data matching the at least one target keyword is selected from the full-text data of the stored data as the candidate data.
The computer device according to claim 9, wherein the performance analysis result comprises a block hash value of the target block node and a target storage amount of the target data stored by the target block node; the processing The device also executes:

Synchronizing the target abstract data, the target full-text data, the block hash value of the target block node and the target storage amount of the target block node to store the target data to the target area on the block node.
The computer device according to claim 9, wherein after obtaining the target data that meets the query condition, the processor further executes:

downloading the target summary data to the user's terminal device, and/or,

The target full-text data is downloaded to the user's terminal device.
A storage medium storing computer-readable instructions that, when executed by one or more processors, cause the one or more processors to perform the following methods:

In response to the query condition carried in the query request of the user, determine the target block node of the target data storage on each block node, and the query request is used to query the target data;

Analyze the performance of the target block node by using a distributed probe route analysis method to obtain a performance analysis result;

According to the performance analysis result and the query conditions, query processing is performed on the stored data uploaded to the distributed cloud storage server including at least the target data, to obtain the target data that meets the query conditions. The data includes target abstract data conforming to the query condition and target full-text data conforming to the query condition.
The storage medium according to claim 15, wherein the query condition includes at least one target keyword for querying the target data and a valid time period of the data, and executing the uploading to the distributed cloud storage server Performing query processing on the stored data including at least the target data includes:

According to at least one target keyword, screening data matching at least one target keyword from the stored data as candidate data;

According to the valid time period of the data, the data within the valid time period of the data is selected from the candidate data as the target data.
The storage medium according to claim 16, wherein performing the screening of data matching the at least one target keyword from the stored data as candidate data according to the at least one target keyword comprises:

According to the at least one target keyword and the target abstract data, the data matching the at least one target keyword is selected from the abstract data of the stored data as the candidate data.
The storage medium according to claim 16, wherein performing the screening of data matching the at least one target keyword from the stored data as candidate data according to the at least one target keyword further comprises:

According to the at least one target keyword and the target full-text data, the data matching the at least one target keyword is selected from the full-text data of the stored data as the candidate data.
The storage medium according to claim 15, wherein the performance analysis result includes a block hash value of the target block node and a target storage amount of the target data stored by the target block node; the processing The device also executes:

Synchronizing the target abstract data, the target full-text data, the block hash value of the target block node and the target storage amount of the target block node to store the target data to the target area on the block node.
The storage medium according to claim 15, wherein after obtaining the target data that meets the query condition, the processor further executes:

downloading the target summary data to the user's terminal device, and/or,

The target full-text data is downloaded to the user's terminal device.