CN118296083A - Distributed account book data three-level read-write expansion blockchain storage method - Google Patents
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Abstract
The invention discloses a three-level read-write expansion blockchain storage method for distributed account book data, which comprises the steps of establishing a blockchain storage expandable model to perform three-level read-write on the blockchain account book data, wherein the blockchain storage expandable model comprises three dimensions of separation of latest data and non-latest data, separation of cold data and non-cold data and data read-write separation, and the adoption of a memory and a KV database to store less latest data and hot account book data so as to realize the rapid read-write of primary data; storing non-latest data in a relational database, and inquiring associated data through SQL (structured query language) to realize reading and writing of secondary data; the cold data is transferred to a local file database for storage, and three-level data reading and writing are realized by indexing the storage position of the file query block. The invention adopts a proper storage mode aiming at different types of account book data so as to improve the data reading and writing performance and the expandability of the data when the data is continuously increased.
Description
Technical Field
The invention relates to the technical field of distributed account book storage and blockchain, in particular to a three-level read-write expansion blockchain storage method for distributed account book data.
Background
Blockchain storage includes the following two aspects:
(1) Blockchain storage expansion
The blockchain ledger data is stored in a distributed manner, and generally, each full node stores a complete data backup. The blockchain has the advantages of open transparency, high security, high availability of data and the like, but at the same time, brings about some new challenges: 1) The blockchain node running cost increases. The node needs larger disk space and higher I/O performance, and when a new node joins the blockchain, a large amount of account book data needs to be downloaded; 2) The degree of decentralization of the blockchain system is reduced. Nodes with limited storage space cannot be added into the blockchain network, so that the total nodes for storing all accounts in the network are reduced; 3) Blockchain security is compromised. The block chain is more easily attacked due to the fact that the total nodes in the block chain network are reduced; 4) The blockchain performance decreases. The block chain link points store a large amount of account book data, so that the read-write speed of the block chain account book data is reduced, and the confirmation delay time of the block and the transaction is further influenced and increased. Therefore, research into blockchain storage scalability is very important and necessary.
In order to solve the problem of blockchain storage scalability, many innovative schemes have been proposed. According to whether nodes store full account data, schemes can be divided into two main categories: 1) Data storage compression scheme. Namely, the local ledger data is compressed by adopting a data compression algorithm, or the ledger data is stored by adopting a database with better data compression effect. These schemes introduce additional computational load and increase the delay of the blockchain. 2) More storage extensions employ block link points to store partial ledger data. The node acquires the account book data which is not stored locally by the node through the blockchain network. The schemes break the integrity of the ledger, increase network overhead, reduce data reading speed, and reduce the security and the decentralization degree of the blockchain.
(2) Block chain storage method
The data layer is one of the important levels in the blockchain architecture, and different blockchain systems employ different data storage schemes. Early (2016 ago) blockchains typically employed KV (key-value) databases that did not support relational queries. With the demands of blockchain applications and extensibility, more and more blockchain systems employ relational databases to support relational queries.
KV databases are a NoSQL model whose data is organized, indexed, and stored in key-value pairs, often used to store large amounts of unstructured or semi-structured data. The method has high extensibility, a non-fixed data structure and high performance, but does not provide SQL query and does not support the query of complex data.
The relational database is widely used for a relational data management system (RDBMS), adopts SQL language to manage and maintain data, has the characteristics of a structured data model, a powerful SQL query function, strong expansibility and the like, but has poor flexibility, especially under the condition of dynamic change of a data structure.
In addition, both the bitcoin blockchain and super ledger employ a file database to store rarely used historical data. File databases allow custom storage of data structures and generally occupy less disk space.
Therefore, there is a need to provide a new method for storing the distributed ledger data blockchain to solve the above-mentioned problems.
Disclosure of Invention
The invention aims to solve the technical problem of providing a three-level read-write expansion blockchain storage method for distributed account book data, which can solve the problem that the blockchain account book data is continuously expanded and has larger requirement on the storage space of all nodes of a blockchain; meanwhile, a proper storage mode is adopted for different types of account book data so as to improve the data reading and writing performance and the expandability of the data when the data is continuously increased.
In order to solve the technical problems, the first technical scheme adopted by the invention is as follows: the three-level read-write expansion blockchain storage method for the distributed account data is provided, and three-level read-write is carried out on the blockchain account data by establishing a blockchain storage expandable model, wherein the blockchain storage expandable model comprises three dimensions of latest data and non-latest data separation, cold data and non-cold data separation and data read-write separation:
(1) The latest data is separated from the non-latest data: the m latest block data generated on the block chain are the latest data, the block data before the m latest blocks are the non-latest data, and the memory and KV database are used for storing less latest data and hot account book data, so that the quick reading and writing of the primary data are realized;
(2) Cold data is separated from non-cold data: along with the continuous generation of new data blocks, the previous latest data become non-latest data, the non-latest data are stored in a relational database, and related data query is carried out through SQL, so that the reading and writing of secondary data are realized; the data which is not read or is rarely read is cold data, the cold data is transferred to a local file database for storage, and the storage position of a block is queried through an index file, so that the reading and writing of three-level data are realized;
(3) Data read-write separation: the data writing is mainly completed in the KV database, and the data reading is realized through three-level reading from the memory, the relational database and the file database.
In a preferred embodiment of the present invention, the first level data writing is to cache the latest data and hot account book data into the memory to realize quick data reading, and to permanently store the latest data and hot account book data into the KV database to realize quick data writing.
In a preferred embodiment of the present invention, when the number of blocks in the first stage reaches a set upper limit, the current block is transferred to the second stage as non-cold data, and the process is performed once when the number of blocks to be circulated reaches a certain threshold.
In a preferred embodiment of the present invention, hot ledger data that is rarely read in the first level read-write will be converted into non-cold data in the second level read-write, and non-cold data that is frequently read in the second level read-write will be converted into hot ledger data in the first level read-write.
In a preferred embodiment of the present invention, the frequently read second level non-cold data will be converted into third level read-write cold data, and the frequently read third level cold data will be converted into second level read-write non-cold data.
In a preferred embodiment of the invention, the transaction details and the transaction response pieces are stored in a relational database in the same data table, and the transaction details and response pieces are queried according to the block hash or the height query field block in the data table and the transaction hash.
In a preferred embodiment of the present invention, the third level data writing process is automatically performed once when the number of non-latest blocks reaches the set value.
In order to solve the technical problems, a second technical scheme adopted by the invention is as follows: providing an electronic device comprising at least one processor and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the distributed ledger wall data three-level read-write extended blockchain storage method of any of the above.
In order to solve the technical problems, a third technical scheme adopted by the invention is as follows: there is provided a non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the distributed ledger data three-level read-write extended blockchain storage method according to any of the above.
In order to solve the technical problems, a fourth technical scheme adopted by the invention is as follows: a computer program product is provided, comprising a computer program; the computer program, when executed by a processor, implements the distributed ledger-data three-level read-write extended blockchain storage method of any of the above.
The beneficial effects of the invention are as follows:
(1) The invention provides a block chain storage extensible model, which is designed from different dimensionalities of latest/non-latest data separation, cold/non-cold data separation and data read-write separation so as to improve the expandability of block chain account book data storage;
(2) The three-level read-write block chain data storage system framework improves the block chain data management efficiency. The method adopts the memory and the KV database to store less latest and hot account book data, thereby realizing the quick reading and writing of the primary data. In the second level, more non-up-to-date ledger data is stored in a relational database that supports complex associative data queries through SQL. The third stage adopts a file database to store most account book data so as to reduce the consumption of storage space;
(3) The invention reduces the storage space consumption of the nodes, improves the data reading efficiency, realizes the inquiry of complex relation data, does not introduce too much extra load, and does not influence the consistency, the safety, the decentralization degree and the writing speed of the data. All data transmission processes are performed at the node client, and data transmission through a network is not required. Therefore, the method does not bring extra network overhead. In addition, the three-level storage solution significantly reduces disk storage overhead.
Drawings
FIG. 1 is a schematic diagram of the architecture of the blockchain storage extensible model;
FIG. 2 is a schematic diagram of the three-level read-write flow of the blockchain;
FIG. 3 is a flow diagram of the blockchain data.
Detailed Description
The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings so that the advantages and features of the present invention can be more easily understood by those skilled in the art, thereby making clear and defining the scope of the present invention.
Referring to fig. 1 and 2, an embodiment of the present invention includes:
A three-level read-write expansion blockchain storage method for distributed account data is disclosed, wherein a blockchain storage expandable model is established to carry out three-level read-write on the blockchain account data, and the blockchain storage expandable model comprises three dimensions of latest data and non-latest data separation, cold data and non-cold data separation and data read-write separation:
(1) The latest data is separated from the non-latest data: the m latest block data generated on the block chain are the latest data, the block data before the m latest blocks are classified as non-latest data, and the latest data need to be quickly written into the database and read frequently. Therefore, the memory is used for caching the latest data, and the KV database is used for storing the latest data permanently;
(2) Cold data is separated from non-cold data: along with the continuous generation of new data blocks, the previous latest data becomes non-latest data, and the non-latest data is stored in a relational database so as to meet the requirement of data reading; the data that is not or rarely read is cold data, which is transferred to a local file database for storage in order to further reduce data storage space. In contrast, frequently read data, known as hot data, is also loaded into memory to improve read efficiency and is permanently stored in the KV database. All data except cold data and hot data are non-cold data;
(3) Data read-write separation: data writing is mainly completed in a KV database because of relatively high writing efficiency. Data reading is achieved by three levels of reading from memory, relational databases and file databases.
As shown in fig. 1, the data blocks B n-1 and B n are the latest data, and can be quickly written into the memory and KV database. Non-current data in blocks B 0、B1 and B 2 is transferred to the relational database for efficient reading. Some rarely read cold data is transferred to the file database to reduce the storage space consumption of the node. Blocks B 0、B1、 B2、Bn-1 and B n are shown as examples only.
The method adopts the memory and the KV database to store less latest and hot account book data, thereby realizing the quick reading and writing of the primary data. In the second level data read-write, more non-up-to-date ledger data is stored in a relational database that supports complex associative data queries through SQL. And the third-level data reading and writing adopts a file database to store most account book data so as to reduce the consumption of storage space. The third level of data reading is the slowest, it is read from the file database by data indexing, but the data is rarely read.
In connection with fig. 2, data writing involves three hierarchical processes: the first level of data writing is a process of caching data into memory to achieve fast data reading and persisting the data into KV database to achieve fast data writing (steps ①, including 1.1 and 1.2). The latest data and hot data remain synchronized in real time in the memory and KV databases (steps ④ and ⑤). The non-up-to-date data is transferred to the relational database for complex data association queries, completed in the second level data write (step ②). To reduce data storage space, the third level data write transfers cold data to the file database (step ③).
Likewise, the data read (step ⑥) also includes three stages: the most recent hot data is read from memory, which is the first level of data read (step 6.1). The secondary data reading is to read data from the relational database, so that a complex data association query can be performed (step 6.2). The rarely queried cold data is retrieved from the file database, which is implemented in a three-level data read (step 6.3).
Specifically, the first level data reads and writes: the object of the first level read-write is the latest data and hot data, and these data are stored in memory and KV database. The first level reading can quickly retrieve the data in the memory. The latest data refers to the data of the latest m blocks, and the hot data also refers to the x block data most commonly used by the current node client. The amount and size of these data are fixed and therefore take up little memory and are deterministic. In order to realize quick reading and writing of data, the data in the memory is preferentially written and read. When new block data is written into the node memory, the new block data is simultaneously persisted into the KV database. When the node is restarted, the latest data and the hot data are read from the KV database and loaded into the memory. That is, the latest data and hot data in the memory are consistent with the data in the KV database.
Second level data read/write: with the continued generation of the latest block, the previous non-latest block data is transferred to the secondary storage and stored in the relational database. In the relational database, the transaction details and the transaction receipt are stored in the same data table, which helps to reduce the repeated storage of some field data, such as transaction basic information of transaction hash, block hash and the like. On the other hand, from the data table, the block can be queried according to the block hash or the height, and transaction details and receipts can be queried according to the transaction hash, so that the requirement of a user on complex association query between the transaction and the block is met.
Third-stage data reading and writing: to further reduce the memory space of blockchain data, tertiary data writes may transfer some rarely used cold data into the local file database. The necessary index file is used to increase the efficiency of data queries. When the number of non-latest blocks reaches a set value, the three-level data writing process is automatically performed once. In the data blocks with longer reading time, the data with set proportion (the proportion of the data is set in the block chain configuration item) is reserved in the relational database, and other data is written into the file database according to the height sequence of the data blocks. The index file records the storage position of each block in the file database, so that a user can conveniently and quickly position the storage position to acquire the required block data.
In general, the data of a blockchain is fixed after storage. In this approach, however, data needs to be transferred between the primary, secondary, and tertiary stages, which introduces additional overhead to the blockchain system. Data flow as shown in fig. 3, there are several cases of data flow: (1) When the number of the latest blocks of the first stage reaches a set upper limit, the latest blocks are transmitted to the second stage to become non-cold data. To reduce the frequency of this process, it is performed only once when the number of blocks that need to be streamed reaches a certain threshold. (2) The hot data that is rarely read in the primary will be converted to non-cold data in the secondary, while the non-cold data that is often read in the secondary will be converted to hot data in the primary, both of which are done together periodically. (3) The frequently read second stage non-cold data will be converted to third stage cold data, and the frequently read third stage cold data will be converted to second stage non-cold data, both of which are also often performed together. Thus, the data transfer is not a high frequency event, and may introduce some additional I/O overhead to the node clients, but not significantly.
All data transmission processes are performed at the node client, and data transmission through a network is not required. Therefore, the method does not bring extra network overhead. In addition, the three-level storage solution significantly reduces disk storage overhead.
The invention provides a block chain storage extensible model which is designed from different dimensionalities of latest/non-latest data separation, cold/non-cold data separation and data read-write separation so as to improve the expandability of block chain account book data storage. The three-level read-write block chain data storage system framework also improves the block chain data management efficiency.
The embodiment of the invention also provides electronic equipment, which comprises at least one processor and a memory which is in communication connection with the at least one processor; the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the distributed ledger-book data three-level read-write extended blockchain storage method.
The embodiment of the invention also provides a non-transitory computer readable storage medium storing computer instructions, wherein the computer instructions are used for enabling the computer to execute the distributed ledger-book data three-level read-write extended blockchain storage method.
The embodiment of the invention also provides a computer program product, which comprises a computer program; the computer program, when executed by the processor, implements the distributed ledger-book data three-level read-write extended blockchain storage method described above.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical aspects of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the above embodiments, it should be understood by those of ordinary skill in the art that: modifications and equivalents may be made to the specific embodiments of the invention without departing from the spirit and scope of the invention, which is intended to be covered by the claims.
Claims (10)
1. The three-level read-write expansion blockchain storage method for the distributed account book data is characterized in that a blockchain storage expandable model is established to carry out three-level read-write on the blockchain account book data, and the blockchain storage expandable model comprises three dimensions of separation of latest data and non-latest data, separation of cold data and non-cold data and data read-write separation:
(1) The latest data is separated from the non-latest data: the m latest block data generated on the block chain are the latest data, the block data before the m latest blocks are the non-latest data, and the memory and KV database are used for storing less latest data and hot account book data, so that the quick reading and writing of the primary data are realized;
(2) Cold data is separated from non-cold data: along with the continuous generation of new data blocks, the previous latest data become non-latest data, the non-latest data are stored in a relational database, and related data query is carried out through SQL, so that the reading and writing of secondary data are realized; the data which is not read or is rarely read is cold data, the cold data is transferred to a local file database for storage, and the storage position of a block is queried through an index file, so that the reading and writing of three-level data are realized;
(3) Data read-write separation: the data writing is mainly completed in the KV database, and the data reading is realized through three-level reading from the memory, the relational database and the file database.
2. The distributed ledger-paper data three-level read-write extended blockchain storage method of claim 1, wherein the first level data writing is to cache the latest data and hot ledger data into a memory to realize quick data reading, and to permanently store the latest data and hot ledger data into a KV database to realize quick data writing.
3. The method of claim 1, wherein when the number of blocks in the first stage reaches a set upper limit, the data is transferred to the second stage as non-cold data, and the process is performed once when the number of blocks to be circulated reaches a certain threshold.
4. The distributed ledger-data three-level read-write extended blockchain storage method of claim 1, wherein hot ledger data rarely read in the first level read-write is to be converted into non-cold data in the second level read-write, and non-cold data frequently read in the second level read-write is to be converted into hot ledger data in the first level read-write.
5. The distributed ledger-book data three-level read-write extended blockchain storage method of claim 1, wherein frequently read second-level non-cold data is converted into third-level read-write cold data, and frequently read third-level cold data is converted into second-level read-write non-cold data.
6. The distributed ledger-book data three-level read-write extended blockchain storage method of claim 1, wherein in the relational database, the transaction details and the transaction receipts are stored in the same data table, and the transaction details and the receipts are queried according to a block hash or a height query block in the data table and according to the transaction hash.
7. The distributed ledger-book data three-level read-write extended blockchain storage method of claim 1, wherein the third-level data writing process is automatically performed once when the number of non-latest blocks reaches a set value.
8. An electronic device comprising at least one processor and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the distributed ledger wall data three-level read-write extended blockchain storage method of any of claims 1-7.
9. A non-transitory computer readable storage medium storing computer instructions, wherein the computer instructions are for causing the computer to perform the distributed ledger data three-level read-write extended blockchain storage method of any of claims 1-7.
10. A computer program product comprising a computer program; the computer program, when executed by a processor, implements the distributed ledger data three-level read-write extended blockchain storage method according to any of claims 1-7.
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