CN115460222A - Block chain data flow calculating device - Google Patents
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Abstract
The present disclosure relates to a blockchain flow calculation apparatus and a blockchain flow calculation method. A method of blockchain data flow computation, comprising: receiving a get target blockchain request from a stream computing engine; determining a target block according to the request; acquiring target block chain data from a target block chain; generating a data stream of the universal block chain according to the universal block chain model and the acquired target block chain data; and performing stream calculation according to the data stream of the universal block chain.
Description
Technical Field
The present disclosure relates to the field of blockchain, and in particular, to a blockchain dataflow computation apparatus.
Background
With the popularization of the blockchain, the advantages of the blockchain in the aspects of promoting trust, promoting cross-organization cooperation and the like are more widely recognized, the blockchain is generally applied to the ground in many industries all over the world, and more large quantities of business data are deposited and accumulated on the chain.
On the other hand, the demands of these governments, enterprises and scientific research institutions for higher real-time business applications, such as real-time operation analysis, real-time business alarm, financial wind control, precise marketing, real-time reconciliation, etc., are also increasing.
From the perspective of a user, high-reliability and high-value business data on a block chain are docked into real-time business application in an efficient and reliable mode, the business value of the data can be timely mined and utilized, the business insights are improved, and a multi-play collaborative new business mode is developed.
From the perspective of a block chain manufacturer, the general capability of realizing real-time calculation of block chain data is beneficial to further exploiting potential application scenarios of the block chain in services with high real-time requirements or time sensitivity. Meanwhile, the method is also beneficial to creating a block chain downlink and richer value-added product service capability facing service data.
Disclosure of Invention
According to an aspect of the present disclosure, there is provided a block chain data stream calculation apparatus including:
a blockchain adaptation device configured to obtain target blockchain data from a target blockchain;
a general blockchain model storage configured to store a general blockchain model;
the data analysis device is configured to generate a data stream of the universal block chain according to the universal block chain model and the acquired target block chain data;
a blockchain data acquisition device configured to receive a data stream of the universal blockchain;
a stream computation engine configured to perform stream computations based on the data streams of the universal blockchain.
In some embodiments according to the present disclosure, the blockchain data retrieving means is further configured to instruct the blockchain adapting means to retrieve the target blockchain data from the target blockchain according to a request of the stream calculation engine.
In some embodiments according to the disclosure, the request includes the target blockchain and target blockchain data.
In some embodiments according to the disclosure, the target blockchain data comprises at least one of: a block of a predetermined block height range, a transaction of a predetermined range, and an event in a predetermined time period.
In some embodiments according to the disclosure, the block chain data flow calculation apparatus further comprises:
a message storage module configured to store the data stream of the universal block chain in a queue manner.
In some embodiments according to the present disclosure, the block chain data stream calculating apparatus further comprises:
a state management module configured to record the state of the data stream of the general blockchain received by the blockchain data acquisition device.
In some embodiments according to the present disclosure, the status comprises at least one of: a block height of the universal blockchain, a transaction in the universal blockchain, and a timestamp of an event in the universal blockchain.
According to another aspect of the present disclosure, there is provided a block chain data stream calculation apparatus including: a blockchain data gateway, a blockchain data connector and a stream computation engine,
wherein the blockchain data gateway comprises:
a blockchain adaptation device configured to obtain target blockchain data from a target blockchain;
a general blockchain model storage configured to store a general blockchain model; and
a data analysis device configured to generate a data stream of the universal blockchain according to the universal blockchain model and the acquired target blockchain data,
the blockchain data connector comprises:
a blockchain data acquisition device configured to receive a data stream of the universal blockchain,
the stream computation engine is configured to perform stream computations based on the data streams of the universal blockchain.
In some embodiments according to the present disclosure, the blockchain data retrieving means is further configured to instruct the blockchain adapting means to retrieve the target blockchain data from the target blockchain according to a request of the stream calculation engine.
In some embodiments according to the disclosure, the request includes the target blockchain and target blockchain data.
In some embodiments according to the disclosure, the target blockchain data comprises at least one of: a block of a predetermined range, a transaction of a predetermined range, and an event in a predetermined time period.
In some embodiments according to the present disclosure, the block chain data stream calculating apparatus further comprises:
a message storage module configured to store the data stream of the universal block chain in a queue manner.
In some embodiments according to the present disclosure, the block chain data stream calculating apparatus further comprises:
a state management module configured to record the state of the data stream of the general blockchain received by the blockchain data acquisition device.
In some embodiments according to the present disclosure, the status comprises at least one of: a height of the universal blockchain, a transaction in the universal blockchain, and a timestamp of an event in the universal blockchain.
According to yet another aspect of the present disclosure, there is provided a block chain data stream calculation method including:
receiving a get target blockchain request from a stream computing engine;
determining a target block according to the request;
acquiring target block chain data from a target block chain;
generating a data stream of the universal block chain according to the universal block chain model and the acquired target block chain data;
and performing stream calculation according to the data stream of the universal block chain.
In some embodiments according to the disclosure, the request includes the target blockchain and target blockchain data.
In some embodiments according to the disclosure, the target blockchain data comprises at least one of: a block of a predetermined range, a transaction of a predetermined range, and an event in a predetermined time period.
In some embodiments according to the disclosure, the method of block chain data flow calculation further comprises:
and storing the data stream of the universal block chain according to a queue mode.
In some embodiments according to the present disclosure, the method of calculating a blockchain data stream further comprises:
and recording the state of the received data stream of the universal block chain.
In some embodiments according to the present disclosure, the status comprises at least one of: a height of the universal blockchain, a transaction in the universal blockchain, and a timestamp of an event in the universal blockchain.
According to yet another aspect of the present disclosure, there is provided a computer apparatus comprising a memory and a processor, the memory having stored thereon a computer program executable by the processor, the processor executing the computer program to perform the block chain data flow calculation method as described above.
Other features of the present disclosure and advantages thereof will become more apparent from the following detailed description of exemplary embodiments thereof, which proceeds with reference to the accompanying drawings.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description, serve to explain the principles of the disclosure.
The present disclosure may be more clearly understood from the following detailed description, taken with reference to the accompanying drawings, in which:
fig. 1 shows a schematic diagram of a blockchain flow computing device according to one or more exemplary embodiments of the present disclosure.
Fig. 2 shows a schematic diagram of a blockchain flow computing device according to one or more exemplary embodiments of the present disclosure.
Fig. 3 shows a schematic diagram of a blockchain flow computing device according to one or more exemplary embodiments of the present disclosure.
Fig. 4 shows a schematic diagram of a blockchain flow computing device according to one or more exemplary embodiments of the present disclosure.
Fig. 5 shows a flowchart of a blockchain flow calculation method performed by a blockchain flow calculation apparatus according to one or more exemplary embodiments of the present disclosure.
Fig. 6 shows a flowchart of a blockchain flow calculation method performed by a blockchain flow calculation apparatus according to one or more exemplary embodiments of the present disclosure.
Fig. 7 shows a schematic diagram of a different type of blockchain.
FIG. 8 shows a block diagram of a computing device, according to an example embodiment of the present disclosure.
Note that in the embodiments described below, the same reference numerals are used in common between different drawings to denote the same portions or portions having the same functions, and a repetitive description thereof will be omitted. In some cases, similar reference numbers and letters are used to denote similar items, and thus, once an item is defined in one figure, it need not be discussed further in subsequent figures.
For convenience of understanding, the positions, sizes, ranges, and the like of the respective structures shown in the drawings and the like do not sometimes indicate actual positions, sizes, ranges, and the like. Therefore, the present disclosure is not limited to the positions, sizes, ranges, and the like disclosed in the drawings and the like.
Detailed Description
Various exemplary embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. It should be noted that: the relative arrangement of parts and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present disclosure unless specifically stated otherwise.
The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the disclosure, its application, or uses. That is, the structures and methods herein are shown by way of example to illustrate different embodiments of the structures and methods of the present disclosure. Those skilled in the art will understand, however, that they are merely illustrative of exemplary ways in which the disclosure may be practiced and not exhaustive. Furthermore, the figures are not necessarily to scale, some features may be exaggerated to show details of particular components.
Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.
In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values.
The block chain is a distributed and multi-party shared account book technology. The transaction data and the history records can not be tampered by a mathematical method, and the common confirmation and the account book records of all the participants on the transaction are realized by a consensus algorithm and an intelligent contract. The execution of basic operations such as transfer and evidence storage of the block chain by the user or the calling of the intelligent contract and the data thereof form the transaction of the block chain, and the transaction is stored in the block in a certain sequence. While a change in state of the blockchain or execution of a contract may trigger the generation of a system-standard or user-defined event, which may be received and processed by the application of the blockchain.
Stream computing is a streaming data-oriented computing technique that receives upstream real-time, continuous data stream inputs, performs efficient computations within a stream computation engine according to predefined stream computation logic, and then outputs in real-time to downstream multiple types of data storage. Stream computing is widely applied to big data business application scenarios with high real-time requirements or time sensitivity, such as e-commerce recommendation systems, financial real-time wind control, website user analysis, ioT data analysis, and the like.
Fig. 1 shows a schematic diagram of a blockchain flow computing device according to an embodiment of the present disclosure. As shown in fig. 1, the blockchain stream computing device 100 may include a general blockchain model storage device 111, a data parsing device 112, a blockchain adapting device 113, a blockchain data obtaining device 121, a stream computing engine interface calling module 122, a stream computing engine 130, a business data model storage 133, and a module generator 132.
Wherein, the blockchain adapting device 113 can obtain data on the blockchain from various blockchains. For example, the block chain adapting device 113 may obtain data of the block chain 101 from the block chain 101 or obtain data of the block chain 102 from the block chain 102 as needed.
The data acquired from the blockchain by the blockchain adapting device 113 may be a block, a transaction or an event, depending on the type of blockchain. For example, according to the instruction from the blockchain data obtaining device 121, the blockchain adapting device 113 may determine a predetermined range of blocks of a predetermined blockchain height range, a transaction of a predetermined range in the blocks of the predetermined blockchain height, or an event of a predetermined timestamp range (i.e., a time period).
The general blockchain model storage means 111 may store therein a general blockchain model. For example, the generic blockchain model may be a variety of known blockchain models and formats such as JSON String, and may also be any custom blockchain model and format.
The data parsing means 112 may convert the blockchain data obtained by the blockchain adapting means 113 into general blockchain data. For example, the data parsing device 112 may convert the data of the blockchain 101 acquired by the blockchain adapting device 113 from the data model and format specific to the blockchain 101 into the data model and format of the general blockchain according to the general blockchain model stored in the general blockchain model storage device and the type of the blockchain 101.
For example, in some embodiments according to the present disclosure, a known interface of the blockchain 101 may be directly called in the data parsing apparatus 112, various data required for generating the universal blockchain are obtained from the data of the blockchain 101, and then the blocks, transactions and/or events of the universal blockchain are generated according to the universal blockchain model.
In addition, in some embodiments according to the present disclosure, the general blockchain model storage device 111 may also store various known transformation relationship models between blockchains and general blockchains in advance. The data parsing means 112 may convert the data of the blockchain 101 into the data of the general blockchain according to the conversion relation model according to the type of the blockchain 101 provided by the blockchain adapting means 113.
Further, after obtaining the data of the general blockchain, the data analysis device 112 may send the data of the general blockchain to the blockchain data acquisition device 121 as a service data stream.
The blockchain data obtaining device 121 may forward the received service data stream to the stream calculation engine 130. For example, the blockchain data obtaining device 121 may call the stream calculation engine interface by using a stream calculation engine interface calling module, and send the service data stream to the stream calculation engine 130 through the stream calculation engine interface.
The stream computation engine 130 includes stream computation logic 131. The flow computation logic 131 may execute the computation task based on the description and arrangement of the computation task by the flow computation engine (including the invocation of basic operators, the extension of the custom computation logic, and the like) by using the service data stream provided by the blockchain data obtaining device 121 as an input source.
Business data model storage 133 can store business data models. And. Template generator 132 may generate business model tables and data tables from the business data models and provide them to stream computation engine 130 for parsing and processing of the blockchain business data stream.
The stream computation engine 130 may output the computation result data stream to a designated data store 140.
In the present disclosure, the stream computation engine 130 may be implemented based on existing stream computation techniques in the industry, such as Apache Flink, and the like. Accordingly, the present disclosure will not be described in detail with respect to the stream computation engine 130.
It should be understood that the above description of the embodiment of the present disclosure takes the blockchain 101 as an example, but the same processing procedure is also applied to the blockchain 102, and thus the description is omitted here.
With the blockchain data stream calculation device according to the above embodiment of the present disclosure, stream calculations can be performed on various different types of blockchains using the same stream calculation engine.
Fig. 2 shows a schematic diagram of a blockchain flow computing device according to an embodiment of the present disclosure. As shown in fig. 2, the blockchain stream computing device 200 includes a general blockchain model storage device 111, a data parsing device 112, a blockchain adapting device 113, a blockchain data obtaining device 121, a stream computing engine interface calling module 122, a stream computing engine 130, a business data model storage 133, and a module generator 132.
Compared with the blockchain flow calculation apparatus 100 of fig. 1, the difference is that in the blockchain flow calculation apparatus 200, a blockchain data gateway 210 and a blockchain data connector 220 are provided. The blockchain data gateway 210 and the blockchain data connector 220 are two devices that are independent of each other. The blockchain data gateway 210 may include a general blockchain model storage device 111, a data analysis device 112, and a blockchain adaptation device 113. The blockchain data connector 220 may include a blockchain data obtaining device 121 and a stream calculation engine interface calling module 122.
Using the system architecture of the blockchain flow computing device 200, the blockchain data connector 220 may implement a uniform, efficient architecture that focuses on reliability management and maintenance of blockchain flow data acquisition. The blockchain data gateway 210 not only can serve blockchain data flow calculation, but also has good expandability, and can be used as a basic service for independent blockchain data pulling for business application and other blockchain middleware.
For example, fig. 3 shows a schematic diagram of a blockchain flow computing device according to an embodiment of the present disclosure. Compared to the blockchain flow computing device 200 shown in fig. 2, the difference is that the blockchain data gateway 310 of the blockchain flow computing device 300 further includes an application API 314, a message queue 315, and a task manager 316.
Through the application API 314, one can obtain the data of the general blockchain generated by the data analysis device 112, and also obtain the data of the blockchain 101 or 102 received by the blockchain adaptation device 113.
The message queue (i.e., message storage module) 315 may receive the traffic data stream generated by the data parsing device 112 and implement the buffering and subsequent reliable output or pushing of data in the scenario where the downstream consumer is temporarily unavailable, e.g., in the form of an asynchronous queue.
Fig. 4 shows a schematic diagram of a block chain flow calculation apparatus 400 according to an embodiment of the present disclosure. Compared to the blockchain flow calculation apparatus 300 of fig. 3, the difference is that the blockchain data connector 420 of the blockchain flow calculation apparatus 400 further includes a status management module 423.
State management module 423 may record the state of the data flow of blockchain 101 acquired by blockchain data gateway 310. For example, status management module 423 may record the most recently acquired tile height of the blockchain 101, a transaction sequence number, and/or a timestamp of an event.
Fig. 7 shows a schematic diagram of a data flow of a common block chain. Wherein, for the block chain data stream (block stream) of the block type, the transmission and transmission can be performed in units of blocks. The data stream of block types is in order of block height, with smaller blocks being older records (earlier generated blocks) and larger blocks being newer records (later generated). For a data stream of a block type, the status management module 423 may record the block height of the newly acquired block.
For a blockchain data stream of transaction types (transaction stream), each transaction is identified by the height of the block and the relative order of the transactions in the block. In the case where a plurality of transactions are contained within one block, the relative order between the transactions is fixed. For transaction type data flow, the state management module 423 may record the tile height of the tile where the newly obtained transaction is located and the relative order of the transaction in the tile.
The time-type blockchain data stream (event stream) determines the sequence according to the sequence of the time stamps generated on the blockchain by the blockchain events. The state management module 423 may record a timestamp of the most recently retrieved blockchain event.
In an embodiment according to the present disclosure, a reliability guarantee or fault tolerance mechanism of the stream computation engine may also be provided in the stream computation engine interface calling module. The state management module 423 may store the state of the data stream of the universal blockchain according to a reliability assurance or fault tolerance mechanism of the stream computation engine. In this way, data and computational tasks may be recovered more quickly in the event of a failure or anomaly.
Fig. 5 shows a flowchart of a blockchain flow calculation method performed by the blockchain flow calculation apparatus 400 according to an embodiment of the present disclosure.
First, the stream computation engine sends a request to the blockchain data connector 420 for reading the data stream of blockchain 101 as needed for stream computation. In this request, in addition to specifying the name of the block chain 101, the range of data in the block chain 101 to be read can be specified. Depending on the type of blockchain, a range of block heights to be read, a transaction range, or a range of event timestamps may be specified, for example.
The blockchain data acquisition device 121 of the blockchain data connector 420 may forward the request from the stream computing device 130 to the blockchain data gateway 310.
The blockchain adaptation device 113 of the blockchain data gateway 310 may read corresponding ranges of blockchain data from the blockchain 101 according to the request from the stream calculation engine 130 forwarded by the blockchain data obtaining device 121, such as blocks specifying a range of block heights, transactions specifying a range, or events specifying a range of timestamps, etc. In some embodiments, the request from stream computation engine 130 may specify only blockchain 101 without specifying a data range, in which case blockchain adaptation device 113 may retrieve all data of blockchain 101.
After the data of the blockchain 101 is acquired by the blockchain adapting device 113, the data analyzing device 112 of the blockchain data gateway 310 may analyze the data of the blockchain 101. For example, the data analysis device 112 may generate a data stream of the general blockchain according to the data of the blockchain 101 and the blockchain model stored in the general blockchain model storage device 111.
The generated data stream of the general blockchain may be stored into the message queue module 315 and the data stream in the message queue module 315 may be provided to the blockchain data connector 420 in a queue manner. As described above, the message queue module 315 can implement the staging and subsequent reliable output or pushing of data in a scenario where a downstream consumer (e.g., blockchain data connector, etc.) is temporarily unavailable, e.g., in an asynchronous queue.
The data stream from the blockchain data gateway 310 is received by the blockchain data acquisition device 121 of the blockchain data connector 420. Before providing the data stream to the stream calculation engine 130, the blockchain data acquisition means 121 may save the state of the data stream of the newly acquired blockchain 101 in the state management module 423. As described above, the state management module 423 may store the state of the data stream according to the reliability assurance or fault tolerance mechanism of the stream computation engine provided by the stream computation engine interface call module 122. For example, the state management module 423 may record at least one of: the block height of the newly acquired block, the block height of the block where the newly acquired transaction is located, the relative order of the transaction in the block, the timestamp of the newly acquired blockchain event, and the like.
After saving the state of the data stream, the blockchain data connector 420 may call the stream calculation engine call interface module 122 to forward the data stream to the stream calculation engine 130.
Stream computation engine 130, upon receiving the data stream for the universal blockchain, may perform a stream computation function or operator using stream computation logic 131.
Fig. 6 illustrates a blockchain data stream calculation method performed by a blockchain data stream calculation apparatus according to an embodiment of the present disclosure.
As shown in fig. 6, in order to perform stream computation, the stream computation engine needs to fetch data from the blockchain 101 and the blockchain 102, respectively. The stream calculation engine may sequentially obtain the data of the blockchain 101 and the blockchain 102 according to the process shown in fig. 6 (i.e., after obtaining the data stream of the blockchain 101, a request for reading the data of the blockchain 102 is issued), and since the process of specifically obtaining the blockchain data stream is similar to that shown in fig. 5, the description of the present disclosure is not repeated. However, the present disclosure is not limited thereto. For example, the stream computation engine may simultaneously forward to both blockchain 101 and blockchain 102. That is, the process of acquiring data from blockchain 101 and blockchain 102 may be performed simultaneously, in case the processing capacity of the blockchain data gateway and blockchain data connector is sufficient.
Fig. 8 shows a block diagram of a computing device, which is one example of a hardware device applicable to aspects of the present disclosure, according to an example embodiment of the present disclosure.
With reference to fig. 8, a computing device 700, which is one example of a hardware device that may be applied to aspects of the present disclosure, will now be described. Computing device 700 may be any machine configured to implement processing and/or computing, and may be, but is not limited to, a workstation, a server, a desktop computer, a laptop computer, a tablet computer, a personal digital assistant, a smart phone, an in-vehicle computer, or any combination thereof. The various aforementioned apparatus/servers/client devices may be implemented in whole or at least in part by computing device 700 or similar devices or systems.
The bus 702 may include, but is not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MCA) bus, an Enhanced ISA (EISA) bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus. In particular, for an in-vehicle device, the bus 702 may also include a Controller Area Network (CAN) bus or other structure designed for applications in an automobile.
Software components may be located in the working memory 714, including, but not limited to, an operating system 716, one or more application programs 718, drivers, and/or other data and code. Instructions for implementing the above-described methods and steps may be included in the one or more application programs 718, and the aforementioned modules/units/components of the various apparatus/server/client devices may be implemented by the processor 704 reading and executing the instructions of the one or more application programs 718.
It should also be appreciated that variations may be made in accordance with specific needs. For example, customized hardware might also be used and/or particular components might be implemented in hardware, software, firmware, middleware, microcode, hardware description languages, or any combination thereof. In addition, connections to other computing devices, such as network input/output devices and the like, may be employed. For example, some or all of the disclosed methods and apparatus may be implemented with logic and algorithms according to the present disclosure through programming hardware (e.g., programmable logic circuitry including Field Programmable Gate Arrays (FPGAs) and/or Programmable Logic Arrays (PLAs)) having assembly language or hardware programming languages (e.g., VERILOG, VHDL, C + +).
As used herein, the word "exemplary" means "serving as an example, instance, or illustration," and not as a "model" that is to be replicated accurately. Any implementation exemplarily described herein is not necessarily to be construed as preferred or advantageous over other implementations. Furthermore, there is no intention to be bound by any expressed or implied theory presented in the preceding technical field, background, brief summary or the detailed description.
In addition, "first," "second," and like terms may also be used herein for reference purposes only, and thus are not intended to be limiting. For example, the terms "first," "second," and other such numerical terms referring to structures or elements do not imply a sequence or order unless clearly indicated by the context.
It will be further understood that the terms "comprises/comprising," "includes" and/or "including," when used herein, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
Those skilled in the art will appreciate that the boundaries between the above described operations merely illustrative. Multiple operations may be combined into a single operation, single operations may be distributed in additional operations, and operations may be performed at least partially overlapping in time. Moreover, alternative embodiments may include multiple instances of a particular operation, and the order of operations may be altered in various other embodiments. However, other modifications, variations, and alternatives are also possible. The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense.
Although some specific embodiments of the present disclosure have been described in detail by way of example, it should be understood by those skilled in the art that the foregoing examples are for purposes of illustration only and are not intended to limit the scope of the present disclosure. The various embodiments disclosed herein may be combined in any combination without departing from the spirit and scope of the present disclosure. It will also be appreciated by those skilled in the art that various modifications may be made to the embodiments without departing from the scope and spirit of the disclosure. The scope of the present disclosure is defined by the appended claims.
Claims (21)
1. A blockchain data stream computing apparatus, comprising:
a blockchain adaptation device configured to obtain target blockchain data from a target blockchain;
a general blockchain model storage configured to store a general blockchain model;
the data analysis device is configured to generate a data stream of the universal blockchain according to the universal blockchain model and the acquired target blockchain data;
a blockchain data acquisition device configured to receive a data stream of the universal blockchain;
a stream computation engine configured to perform stream computations based on the data streams of the universal blockchain.
2. The blockchain data stream computation device of claim 1, wherein the blockchain data fetching device is further configured to instruct the blockchain adaptation device to fetch the target blockchain data from the target blockchain according to a request of the stream computation engine.
3. The blockchain data stream computing device of claim 2, wherein the request includes the destination blockchain and destination blockchain data.
4. The blockchain data stream computing device of claim 3, wherein the target blockchain data includes at least one of: a block of a predetermined block height range, a transaction of a predetermined range, and an event in a predetermined time period.
5. The blockchain data stream computing device of claim 1, further comprising:
a message storage module configured to store the data stream of the universal block chain in a queue manner.
6. The blockchain data stream computing device of claim 1, further comprising:
a state management module configured to record the state of the data stream of the general blockchain received by the blockchain data acquisition device.
7. The blockchain data stream computing device of claim 6, wherein the state includes at least one of: a block height of the universal blockchain, a transaction in the universal blockchain, and a timestamp of an event in the universal blockchain.
8. A blockchain data stream computing apparatus, comprising: a blockchain data gateway, a blockchain data connector and a stream computation engine,
wherein the blockchain data gateway comprises:
a blockchain adaptation device configured to obtain target blockchain data from a target blockchain;
a general blockchain model storage configured to store a general blockchain model; and
a data analysis device configured to generate a data stream of the universal blockchain according to the universal blockchain model and the acquired target blockchain data,
the blockchain data connector comprises:
a blockchain data acquisition device configured to receive the data stream of the general blockchain, the stream computation engine configured to perform stream computation according to the data stream of the general blockchain.
9. The blockchain data stream computing device of claim 8, wherein the blockchain data fetching device is further configured to instruct the blockchain adapting device to fetch the target blockchain data from the target blockchain upon request of the stream computing engine.
10. The blockchain data stream computing device of claim 9, wherein the request includes the destination blockchain and destination blockchain data.
11. The blockchain data stream computing device of claim 10, wherein the target blockchain data includes at least one of: a block of a predetermined range, a transaction of a predetermined range, and an event in a predetermined time period.
12. The blockchain data stream computing device of claim 8, further comprising:
a message storage module configured to store the data stream of the universal block chain in a queue manner.
13. The blockchain data stream computing device of claim 8, further comprising:
a state management module configured to record the state of the data stream of the general blockchain received by the blockchain data acquisition device.
14. The blockchain data stream computing device of claim 13, wherein the state includes at least one of: a height of the universal blockchain, a transaction in the universal blockchain, and a timestamp of an event in the universal blockchain.
15. A method of blockchain data flow computation, comprising:
receiving a get target blockchain request from a stream computing engine;
determining a target block according to the request;
acquiring target block chain data from a target block chain;
generating a data stream of the universal block chain according to the universal block chain model and the acquired target block chain data;
and performing stream calculation according to the data stream of the universal block chain.
16. The blockchain data stream computing method of claim 15, wherein the request includes the target blockchain and target blockchain data.
17. The blockchain data stream computing method of claim 16, wherein the target blockchain data includes at least one of: a block of a predetermined range, a transaction of a predetermined range, and an event in a predetermined time period.
18. The blockchain data stream computing method of claim 15, further comprising:
and storing the data stream of the universal block chain according to a queue mode.
19. The blockchain data stream computing method of claim 15, further comprising:
and recording the state of the received data stream of the universal block chain.
20. The blockchain data stream computing method of claim 19, wherein the state includes at least one of: a height of the universal blockchain, a transaction in the universal blockchain, and a timestamp of an event in the universal blockchain.
21. A computer apparatus comprising a memory and a processor, the memory having stored thereon a computer program executable by the processor, the processor when executing the computer program performing the method of block chain data flow computation of any of claims 15-20.
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