CN111447269A - Deserializing method and deserializing device for high-concurrency scenes in block chain transaction - Google Patents
Deserializing method and deserializing device for high-concurrency scenes in block chain transaction Download PDFInfo
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- CN111447269A CN111447269A CN202010216962.6A CN202010216962A CN111447269A CN 111447269 A CN111447269 A CN 111447269A CN 202010216962 A CN202010216962 A CN 202010216962A CN 111447269 A CN111447269 A CN 111447269A
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Abstract
The invention provides a de-serialization method and a de-serialization device for high concurrency scenes in block chain transaction, wherein the de-serialization method and the de-serialization device comprise the following steps: acquiring to-be-processed transaction data from a block chain node; constructing a family spectrogram according to the transaction data to be processed, wherein the family spectrogram is a net-shaped relation graph formed by transaction data with a tandem relation in a transaction data active area, and the transaction data active area is a process from the beginning of processing the transaction to the completion of completely processing the transaction; splitting the transaction data to be processed according to the genealogy graph, and putting the transaction data to be processed in different genealogies into different data queues to be processed; carrying out multi-process concurrent processing on the transaction data to be processed of different data queues to be processed; and carrying out subsequent service processing on the processing result data. According to the scheme, the cluster map is constructed to split and queue transaction data to be processed, so that the complexity of processing a transaction sequence by a high concurrent process in block chain transaction can be reduced.
Description
Technical Field
The invention relates to the technical field of transaction data processing, in particular to a de-serialization method and a de-serialization device for high-concurrency scenes in block chain transactions.
Background
After the transaction amount of the blockchain is gradually increased, in the subsequent processing after the blockchain data is blocked, in order to improve the data processing performance, the problem needs to be solved by using multi-process concurrent processing. However, once the blockchain is blocked, it means that there is a strict precedence relationship between transaction sequences, and this sequence relationship cannot be destroyed no matter what the service is. In subsequent concurrent processing, there are several obstacles to maintaining this ordering relationship. For example, each process can be used to process a piece of data, and subsequent splicing can be performed, if the previous piece is not completed, the subsequent splicing and other processes can only wait, especially when a server where an intermediate process is located fails.
Disclosure of Invention
The embodiment of the invention provides a de-serialization method and a de-serialization device for high-concurrency scenes in block chain transaction, which solve the technical problem that in the prior art, due to the fact that a transaction sequence enables a block chain to have a sequence relation, multi-process concurrency of data has a fault.
The embodiment of the invention provides a de-serialization method for high-concurrency scenes in block chain transaction, which comprises the following steps:
acquiring to-be-processed transaction data from a block chain node;
constructing a data family spectrogram according to the transaction data to be processed, wherein the data family spectrogram is a network relation graph formed by transaction data with a tandem relation in a transaction data active area, and the transaction data active area is a process from the beginning of processing to the complete processing of the transaction;
splitting the transaction data to be processed according to the data family spectrogram, and putting the transaction data to be processed in different data family spectrums into different data queues to be processed;
carrying out multi-process concurrent processing on the transaction data to be processed of different data queues to be processed;
and carrying out subsequent service processing on the processing result data.
The embodiment of the invention also provides a de-serialization device for high concurrency scenes in block chain transaction, which comprises:
the data acquisition module is used for acquiring transaction data to be processed from the block chain node;
the family spectrogram constructing module is used for constructing a data family spectrogram according to the transaction data to be processed, the data family spectrogram is a network relation graph formed by transaction data with a tandem relation in a transaction data active area, and the transaction data active area is a process from transaction processing to transaction complete processing;
the data splitting processing module is used for splitting the transaction data to be processed according to the data family spectrogram and putting the transaction data to be processed in different data family spectrums into different data queues to be processed;
the multi-process concurrent processing module is used for performing multi-process concurrent processing on the transaction data to be processed of different data queues to be processed;
and the subsequent service processing module is used for performing subsequent service processing on the processing result data.
The embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the method when executing the computer program.
The embodiment of the invention also provides a computer readable storage medium, and the computer readable storage medium stores a computer program for executing the method.
In the embodiment of the invention, the cluster spectrogram is constructed to split and queue transaction data to be processed acquired from the block chain nodes, so that the complexity of processing a transaction sequence by using a high concurrent process of the block chain nodes can be reduced.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a deserialization method for a high concurrency scenario in a blockchain transaction according to an embodiment of the present invention;
FIG. 2 is a flowchart of a de-serialization method for a high concurrency scenario of block link point data according to an embodiment of the present invention;
fig. 3 is a block diagram of a deserializing apparatus for a high concurrency scenario in a blockchain transaction according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In an embodiment of the present invention, a method for deserializing a high concurrency scenario in a blockchain transaction is provided, as shown in fig. 1 and fig. 2, the method includes:
step 102: and acquiring to-be-processed transaction data from the blockchain node.
Step 104: and constructing a data family spectrogram according to the transaction data to be processed, wherein the data family spectrogram is a network relation graph formed by transaction data with a tandem relation in a transaction data active area, and the transaction data active area is a process from the beginning of processing the transaction to the complete processing of the transaction.
Step 106: splitting the transaction data to be processed according to the data family spectrogram, and putting the transaction data to be processed in different family spectrums into different data queues to be processed;
step 108: carrying out multi-process concurrent processing on the transaction data to be processed of different data queues to be processed;
step 110: and carrying out subsequent service processing on the processing result data.
Wherein the transaction data active region: the process from the starting point of transaction to the completion of transaction processing is an active area for transaction data processing, data which does not enter the active area does not enter a visible state of a processing process, and the processed data leaves the view of the processing process without paying attention and logic calculation.
Data family spectrogram: the high concurrency scene in the block chain transaction is deserialized to obtain the reticular relation graph transaction formed by the transaction of which the data family spectrum graph family spectrogram has the successive relation.
In the embodiment of the invention, the strong sequence relation of the data in the block link points is mainly caused by the context of the transaction, for example, a deposit transaction must not be in reverse order before a withdrawal transaction, otherwise, the situation that the balance of the withdrawal transaction is negative in the following withdrawal transaction is possibly caused, and the situation is not consistent with the actual situation in reality. Based on this, a data family spectrogram needs to be constructed according to the transaction data to be processed. Specifically, step 104 includes:
acquiring transaction data with a tandem relation from the transaction data to be processed;
and constructing a data family spectrogram according to the transaction data with the context relationship.
Each transaction data to be processed may have a plurality of successors, and the mesh structure formed by these successors is a data family spectrogram.
When transaction data are processed, a family spectrogram is firstly constructed, when each transaction data is obtained, successors of transactions are set to be null, and if the successors of the transactions are found according to the objects processed by the exchange, the successors of the transactions are set.
However, in practice, the correlation between transactions is not necessarily large, and even large area, the duration of the transaction is short, or the correlation between transactions in the period from the time of taking transaction data to the time of finishing processing transaction data may be very limited. That is, the data genealogy graph is not always continuous, otherwise, the multiprocess still cannot be realized, the genealogy graph only concerns the part in the data activity area, and if the genealogy graph is broken in the data activity area, that is, at the moment when all transaction data in the same queue are processed, all successors are not in the data activity area, the life cycle of the queue is temporarily ended.
In the embodiment of the present invention, it is,
in embodiments of the invention, all transactions within a data genealogy are placed in one queue and unrelated transactions are placed in different queues, which may form a pending transaction data pool. For the to-be-processed transaction data that cannot be put into the to-be-processed data queue (for example, for the transaction data subsequently obtained in the transaction data active area, the data in the to-be-processed data queue are both the successors of the transaction data, and if the successors are not processed, the transaction data cannot be put into the queue), only the corresponding to-be-processed transaction data can be put into the to-be-processed stack in the to-be-processed transaction data pool.
If the front of a certain transaction data relates to a plurality of queues, the queue starting from the transaction data is pushed, and the queue is processed in a pool after all front queues are processed.
In this embodiment of the present invention, step 108 specifically includes:
determining a data processing requirement according to the transaction data to be processed;
and according to the data processing requirement, randomly reading a data queue to be processed from the transaction data pool to be processed to perform multi-process concurrent processing. If processing of a queue has already begun, the queue is processed until the queue has been processed.
Specifically, the data duration of each queue does not have to be continuous, and after the data processing of one queue is completed, the queue leaves the data active area. The next time the queue is encountered, the process can be selected at will.
The logic for each process to select the next transaction is as follows:
1) if in the initial state, the currently processed transaction is set to null.
2) And if the transaction processing is completed and no data which can be processed exists in the family spectrogram, setting the current processing transaction to be null.
3) If the currently processed transaction is empty, a queue is randomly selected from the group pool to begin processing. Until the queue is processed.
In the embodiment of the present invention, after the data processing process is completed in step 110, the subsequent service processing module receives the processed data, and performs subsequent service processing.
Based on the same inventive concept, the embodiment of the present invention further provides a de-serialization apparatus for high concurrency scenarios in blockchain transactions, as described in the following embodiments. Because the principle of solving the problem of the de-serialization device for the high-concurrency scene in the blockchain transaction is similar to that of the de-serialization method for the high-concurrency scene in the blockchain transaction, the implementation of the de-serialization device for the high-concurrency scene in the blockchain transaction can be referred to the implementation of the de-serialization method for the high-concurrency scene in the blockchain transaction, and repeated parts are not described again. As used hereinafter, the term "unit" or "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.
Fig. 3 is a block diagram of a deserializing apparatus of a high concurrency scenario in a blockchain transaction according to an embodiment of the present invention, as shown in fig. 3, including:
the data acquisition module 02 is used for acquiring transaction data to be processed from the block chain node;
the family chart construction module 04 is configured to construct a data family chart according to the transaction data to be processed, where the data family chart is a network relation chart formed by transaction data having a tandem relation in a transaction data active area, and the transaction data active area is a process from the start of processing to the completion of completely processing the transaction;
the data splitting processing module 06 is configured to split the to-be-processed transaction data according to the data family spectrogram, and place the to-be-processed transaction data in different data family spectrums into different to-be-processed data queues;
a multi-process concurrent processing module 08, configured to perform multi-process concurrent processing on the to-be-processed transaction data of different to-be-processed data queues;
and the subsequent service processing module 10 is configured to push the processing result data to the corresponding block link point to perform subsequent service processing.
In an embodiment of the present invention, the genealogy map constructing module 04 is specifically configured to:
acquiring transaction data with a tandem relation from the transaction data to be processed;
and constructing a data family spectrogram according to the transaction data with the context relationship.
In this embodiment of the present invention, the data splitting processing module 06 is further configured to:
and for the to-be-processed transaction data which cannot be put into the to-be-processed data queue, putting the corresponding to-be-processed transaction data into a to-be-processed stack in the to-be-processed transaction data pool.
In this embodiment of the present invention, the multi-process concurrent processing module 08 is specifically configured to:
determining a data processing requirement according to the transaction data to be processed;
and according to the data processing requirement, randomly reading a data queue to be processed from the transaction data pool to be processed to perform multi-process concurrent processing.
The embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the method when executing the computer program.
The embodiment of the invention also provides a computer readable storage medium, and the computer readable storage medium stores a computer program for executing the method.
In summary, the de-serialization method and device for high concurrency scenes in block chain transaction provided by the invention have the following advantages:
1. local data can be processed by self without influencing blockchain transaction;
2. the complexity of the concurrent process for processing the transaction sequence can be reduced;
3. and the overall data processing performance is improved.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention 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 invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes may be made to the embodiment of the present invention by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A deserialization method of high concurrency scenes in blockchain transactions is characterized by comprising the following steps:
acquiring to-be-processed transaction data from a block chain node;
constructing a data family spectrogram according to the transaction data to be processed, wherein the data family spectrogram is a network relation graph formed by transaction data with a tandem relation in a transaction data active area, and the transaction data active area is a process from the beginning of processing to the complete processing of the transaction;
splitting the transaction data to be processed according to the data family spectrogram, and putting the transaction data to be processed in different data family spectrums into different data queues to be processed;
carrying out multi-process concurrent processing on the transaction data to be processed of different data queues to be processed;
and carrying out subsequent service processing on the processing result data.
2. The method for deserializing high concurrency scenarios in blockchain transactions according to claim 1, wherein constructing a data family spectrogram according to the transaction data to be processed comprises:
acquiring transaction data with a tandem relation from the transaction data to be processed;
and constructing a data family spectrogram according to the transaction data with the context relationship.
3. The method of claim 1, wherein different queues of pending data form a pending transaction data pool;
the method for performing multi-process concurrent processing on the to-be-processed transaction data of different to-be-processed data queues specifically comprises the following steps:
determining a data processing requirement according to the transaction data to be processed;
and according to the data processing requirement, randomly reading a data queue to be processed from the transaction data pool to be processed to perform multi-process concurrent processing.
4. The method of claim 3, further comprising:
and for the to-be-processed transaction data which cannot be put into the to-be-processed data queue, putting the corresponding to-be-processed transaction data into a to-be-processed stack in the to-be-processed transaction data pool.
5. A deserializing apparatus for high concurrency scenarios in blockchain transactions, comprising:
the data acquisition module is used for acquiring transaction data to be processed from the block chain node;
the family spectrogram constructing module is used for constructing a data family spectrogram according to the transaction data to be processed, the data family spectrogram is a network relation graph formed by transaction data with a tandem relation in a transaction data active area, and the transaction data active area is a process from transaction processing to transaction complete processing;
the data splitting processing module is used for splitting the transaction data to be processed according to the data family spectrogram and putting the transaction data to be processed in different data family spectrums into different data queues to be processed;
the multi-process concurrent processing module is used for performing multi-process concurrent processing on the transaction data to be processed of different data queues to be processed;
and the subsequent service processing module is used for performing subsequent service processing on the processing result data.
6. The apparatus of claim 5, wherein the genealogy graph constructing module is configured to:
acquiring transaction data with a tandem relation from the transaction data to be processed;
and constructing a data family spectrogram according to the transaction data with the context relationship.
7. The apparatus for deserializing high concurrency scenarios in blockchain transactions according to claim 5, wherein different queues of pending data form a pending transaction data pool;
the multi-process concurrent processing module is specifically configured to:
determining a data processing requirement according to the transaction data to be processed;
and according to the data processing requirement, randomly reading a data queue to be processed from the transaction data pool to be processed to perform multi-process concurrent processing.
8. The apparatus for deserializing high concurrency scenarios in blockchain transactions of claim 7, wherein the data splitting processing module is further configured to:
and for the to-be-processed transaction data which cannot be put into the to-be-processed data queue, putting the corresponding to-be-processed transaction data into a to-be-processed stack in the to-be-processed transaction data pool.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of any of claims 1 to 4 when executing the computer program.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program for executing the method of any one of claims 1 to 4.
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| CN108537543A (en) * | 2018-03-30 | 2018-09-14 | 百度在线网络技术（北京）有限公司 | Method for parallel processing, device, equipment and the storage medium of block chain data |
| CN108595157A (en) * | 2018-04-28 | 2018-09-28 | 百度在线网络技术（北京）有限公司 | Processing method, device, equipment and the storage medium of block chain data |
| CN109636384A (en) * | 2018-10-26 | 2019-04-16 | 阿里巴巴集团控股有限公司 | A kind of parallelization executes the method, apparatus and system of block chain transaction |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108537543A (en) * | 2018-03-30 | 2018-09-14 | 百度在线网络技术（北京）有限公司 | Method for parallel processing, device, equipment and the storage medium of block chain data |
| CN108595157A (en) * | 2018-04-28 | 2018-09-28 | 百度在线网络技术（北京）有限公司 | Processing method, device, equipment and the storage medium of block chain data |
| CN109636384A (en) * | 2018-10-26 | 2019-04-16 | 阿里巴巴集团控股有限公司 | A kind of parallelization executes the method, apparatus and system of block chain transaction |
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