CN115334003B - Data stream processing method and system based on convergence and distribution equipment - Google Patents
Data stream processing method and system based on convergence and distribution equipment Download PDFInfo
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Abstract
The invention relates to the technical field of data stream processing, in particular to a data stream processing method and system based on convergence and distribution equipment. The data stream processing method based on the convergence and distribution equipment comprises the following steps: in the state of acquiring the data stream, acquiring characteristic data and address data of the current data stream according to the data stream; performing feature code matching on the feature data to form a feature code matching rule set, and performing numbering processing on each feature code rule in the feature code matching rule set to form a feature rule number; and carrying out matching processing on the data stream according to the characteristic rule number and the address data to form a matching rule output.
Description
Technical Field
The invention relates to the technical field of data stream processing, in particular to a data stream processing method and system based on convergence and distribution equipment.
Background
With the rapid increase of network traffic, it has been difficult for a single network device to process the traffic of the entire network, and a service processing system is usually formed by using multiple network devices to provide services to the outside. The network convergence and distribution device is responsible for distributing the converged network messages to different devices of the service system. The convergence and distribution equipment should support the analysis of the link layer address and the load protocol information in the message, and determine the message output port after taking the module, so that the messages belonging to the same data flow can be finally distributed to the same processing end point, and the homologous and the same destination of the messages are realized. The message distribution mode of the current convergence and distribution equipment is simple and easy to realize, but the message distribution mode also has inherent defects. For example, in the process of data aggregation and/or splitting, after the data stream enters, the data stream needs to be subjected to matching processing, in the matching processing, the data stream needs to be subjected to processing according to a preset compounding rule, for example, an IP matching and a feature code matching are adopted as source data matched by one compounding rule, the IP matching is performed by an independent IP matching module to form an IP matching result, the feature code matching is performed by a feature code matching module to form a feature code matching result, then the IP matching processing result and the feature code matching processing result are transmitted to the compounding rule module to be subjected to processing to form a final matching result, and the data stream is discarded due to the fact that the feature code matching and the IP matching are matched with different compounding rules, namely, the data stream is lost.
Disclosure of Invention
Aiming at the defects of the prior art, a data stream processing method and a system based on convergence and distribution equipment. In particular, the method comprises the steps of,
in one aspect, the present application provides a data stream processing method based on a convergence and splitting device, where the method includes:
in the state of acquiring the data stream, acquiring characteristic data and address data of the current data stream according to the data stream;
performing feature code matching on the feature data to form a feature code matching rule set, and performing numbering processing on each feature code rule in the feature code matching rule set to form a feature rule number;
and carrying out matching processing on the data stream according to the characteristic rule number and the address data to form a matching rule output.
Preferably, in the above data stream processing method based on convergence and splitting device, performing feature code matching on the feature data to form a feature code matching rule set, and performing numbering processing on rules in the feature code matching rule set to form feature rule numbers specifically includes:
inquiring and acquiring each feature code rule matched with the feature code in a TCAM storage unit;
and reading the priority of each feature code rule, and performing sequencing processing on each feature code rule according to the priority to form the feature rule number.
Preferably, the method for processing a data stream based on a convergence and splitting device further includes the step of executing an action corresponding to the matching rule by the data stream.
In another aspect, the application further provides a data stream processing system based on the convergence and diversion device, which comprises,
the first processing unit is connected with an external input port and is used for acquiring acquisition data and preprocessing the acquisition data to form a data stream;
the second processing unit is connected with the first processing unit and is used for receiving the data stream and splitting the data stream to form output data, wherein the splitting processing method is a data stream processing method based on convergence splitting equipment.
Preferably, the data stream processing system based on the convergence and splitting device, wherein the second processing unit includes:
the reading module is used for acquiring characteristic data and address data of the current data stream according to the data stream in the state of acquiring the data stream;
the first matching module is used for carrying out feature code matching on the feature data to form a feature code matching rule set, and carrying out numbering processing on each feature code rule in the feature code matching rule set to form a feature rule number;
and the second matching module performs matching processing on the data stream according to the characteristic rule number and the address data to form a matching rule output.
Preferably, the data stream processing system based on the convergence and splitting device, wherein the first matching module includes:
the inquirer inquires and acquires each feature code rule matched with the feature code in the TCAM storage unit;
and the numbering device reads the priority of each feature code rule, and performs sorting processing on each feature code rule according to the priority to form the feature rule number.
Preferably, the data flow processing system based on the convergence and splitting device further comprises an execution unit, and the data flow executes actions corresponding to the matching rules.
In yet another aspect, the present application further provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements a data stream processing method based on a convergence and splitting device according to any one of the above when executing the computer program.
Finally, the present application further provides a computer program product, which comprises a computer readable code or a readable storage medium carrying computer readable code, wherein the computer readable code when executed in a processor of an electronic device performs a data stream processing method based on a convergence splitting device as described in any of the above.
In the method, address matching and feature code matching are combined, namely the address matching and the feature matching are updated from original mutually independent matching to mutually combined matching to form a matching rule, so that the situation that the address matching is matched with one rule, the feature code matching is formed into the other rule is avoided, and the address matching rule is inconsistent with the feature code matching rule to cause missed matching.
Drawings
Fig. 1 is a flow schematic diagram of a data flow processing method based on a convergence and distribution device according to an embodiment of the present invention;
fig. 2 is a flow schematic diagram of a data flow processing method based on a convergence and splitting device according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In the prior art, data stream miss-matching or data stream loss occurs because: high priority matching rules will override low priority matching rules, which typically include IP matching and feature code matching. The IP matching processing mode generally adopts a ternary content addressable memory as a data storage unit, and data stored in the ternary content addressable memory includes KEY data and MASK data, for example, the current data flow IP is: DATA 1.1.1.1.2.2.2.2; matching according to a first rule: KEY data 1.1.1.1-, MASK data 1.1.1.0.0.0; according to a second matching rule: KEY data —2.2.2.2: MASK data 0.0.0.0.2.2.2.2; the DATA matches both the first rule and the second rule, the matching result of the first rule being 1.1.1.0.0.0.0; the matching result of the second rule is 0.0.0.0.2.2.2.2; and because the first rule and the second rule can be matched, determining a final matching result according to the priority of the first rule and the priority of the second rule. And after the IP matching processing is completed, performing feature code matching. For example, the current data stream DATE data is 1.1.1.1.2.2.2.2+ "abc"; the first compounding rule is 1.1.1.0.0.0.0+ "abc"; the second compounding rule is 0.0.0.2.2.2.2+ "abd"; the method comprises the steps that IP matching '1.1.1.0.0.0.0' in a first compound rule and IP matching '0.0.0.0.2.2.2' in a second compound rule are stored in a TCAM and executed by an IP matching module, feature codes 'abc' in the first compound rule and feature codes 'abd' in the second compound rule are stored in a HYSCAN and executed by a feature code matching module, wherein the priority of the first compound rule is 100, and the priority of the second compound rule is 101; in the IP matching, the DATE data can be successfully matched with the IP matching in the first compound rule I and the IP matching in the second compound rule, and the current data flow is matched with the second compound rule because the priority of the IP matching of the second compound rule is higher than that of the first compound rule. But the result of the feature code matching is a first compound rule; since the two-part matching compound rule results are not identical, the data stream can only be discarded, but in practice, the data stream should match the first compound rule according to the rules that are intended to be set.
The above specific technical problems were found after the study by the applicant. In practical applications, only data stream losses and data stream losses are found. However, no specific cause of this phenomenon was found.
Aiming at the technical defects, the technical scheme provided by the application is as follows:
as shown in FIG. 1, a data stream processing method based on convergence and distribution equipment is characterized by comprising the following steps of
Step S110, in the state of acquiring the data stream, acquiring characteristic data and address data of the current data stream according to the data stream;
step S120, performing feature code matching on the feature data to form a feature code matching rule set, and performing numbering processing on rules in the feature code matching rule set to form feature rule numbers;
specifically, a further preferred scheme is:
as shown in fig. 2, step S1201, query and acquire each feature code rule matched with the feature code in the TCAM storage unit;
step S1202, reading the priority of each feature code rule, and performing sorting processing on each feature code rule according to the priority to form the feature rule number.
And step 130, performing matching processing on the data stream according to the characteristic rule number and the address data to form a matching rule output. For example, the matching rule may be a feature rule number + address data match.
It should be noted that, because the feature rule number matching is adopted in the present application, once the data stream is matched with the corresponding matching rule, the subsequent matching is not continued, for example, when the compound rule with the feature rule number 1 is matched with the current data stream, the matching rule of the current data is the compound rule with the number 1, and at this time, the compound rule with the subsequent number is not continuously matched.
According to the above steps, in the application, the address matching and the feature code matching are combined, that is, the address matching and the feature matching are updated from original mutually independent matching to mutually combined matching so as to form a matching rule, so that the situation that one rule is matched by the address matching is avoided, and the other rule is formed by the feature code matching, because the address matching rule is inconsistent with the feature code matching rule, the matching is missed.
In this application, address matching may not be performed first, and then feature code matching may be performed. In the configuration rule applied in the application, the address matching rule is usually accurate matching, so that the feature code matching operation cannot be performed after the address matching.
Based on the above technical solution, as a further preferred embodiment, the method further includes: step S140, the data flow executes an action corresponding to the matching rule. Such as performing a copy action, forwarding action, etc. of the data stream.
Example two
In another aspect, the application further provides a data stream processing system based on the convergence and diversion device, which comprises,
the first processing unit is connected with an external input port and is used for acquiring acquisition data and preprocessing the acquisition data to form a data stream; the preprocessing at least comprises message identification and basic message rule matching.
The second processing unit is connected with the first processing unit and is used for receiving the data stream and splitting the data stream to form output data, wherein the splitting processing method is a data stream processing method based on convergence splitting equipment.
Preferably, the data stream processing system based on the convergence and splitting device, wherein the second processing unit includes:
the reading module is used for acquiring characteristic data and address data of the current data stream according to the data stream in the state of acquiring the data stream;
the first matching module is used for carrying out feature code matching on the feature data to form a feature code matching rule set, and carrying out numbering processing on each feature code rule in the feature code matching rule set to form a feature rule number;
and the second matching module performs matching processing on the data stream according to the characteristic rule number and the address data to form a matching rule output.
Preferably, the data stream processing system based on the convergence and splitting device, wherein the first matching module includes:
the inquirer inquires and acquires each feature code rule matched with the feature code in the TCAM storage unit;
and the numbering device reads the priority of each feature code rule, and performs sorting processing on each feature code rule according to the priority to form the feature rule number.
As a further preferred embodiment, the data stream processing system based on the convergence and splitting device further includes an execution unit, where the data stream executes an action corresponding to the matching rule.
The working principle of the data stream processing system based on the convergence and distribution equipment is the same as that of the data stream processing method based on the convergence and distribution equipment, and the obtained technical effects are also completely the same, and are not described in detail herein.
Example III
The embodiment of the application provides electronic equipment, and the electronic equipment can integrate the data stream processing method based on the convergence and distribution equipment. Fig. 3 is a schematic structural diagram of an electronic device according to a third embodiment of the present application. As shown in fig. 3, the present embodiment provides an electronic device 400, which includes: one or more processors 420; storage 410 for storing one or more programs that, when executed by the one or more processors 420, cause the one or more processors 420 to implement:
in the state of acquiring the data stream, acquiring characteristic data and address data of the current data stream according to the data stream;
performing feature code matching on the feature data to form a feature code matching rule set, and performing numbering processing on each feature code rule in the feature code matching rule set to form a feature rule number;
and carrying out matching processing on the data stream according to the characteristic rule number and the address data to form a matching rule output.
As shown in fig. 3, the electronic device 400 includes a processor 420, a storage device 410, an input device 430, and an output device 440; the number of processors 420 in the electronic device may be one or more, one processor 420 being taken as an example in fig. 3; the processor 420, the storage device 410, the input device 430, and the output device 440 in the electronic device may be connected by a bus or other means, which is illustrated in fig. 2 as being connected by a bus 450.
The storage device 410 is used as a computer readable storage medium, and can be used to store a software program, a computer executable program, and a module unit, such as program instructions corresponding to the NPC performance method based on the environmental attribute in the embodiment of the present application.
The storage device 410 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, at least one application program required for functions; the storage data area may store data created according to the use of the terminal, etc. In addition, the storage 410 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage device. In some examples, storage device 410 may further include memory located remotely from processor 420, which may be connected via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 430 may be used to receive input numeric, character information, or voice information, and to generate key signal inputs related to user settings and function control of the electronic device. The output device 440 may include a display screen, speakers, etc.
Example IV
In some embodiments, the methods described above may be implemented as a computer program product. The computer program product may include a computer readable storage medium having computer readable program instructions embodied thereon for performing aspects of the present disclosure. Specifically:
in the state of acquiring the data stream, acquiring characteristic data and address data of the current data stream according to the data stream;
performing feature code matching on the feature data to form a feature code matching rule set, and performing numbering processing on each feature code rule in the feature code matching rule set to form a feature rule number;
and carrying out matching processing on the data stream according to the characteristic rule number and the address data to form a matching rule output.
The computer readable storage medium described above can be a tangible device that can hold and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: portable computer disks, hard disks, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static Random Access Memory (SRAM), portable compact disk read-only memory (CD-ROM), digital Versatile Disks (DVD), memory sticks, floppy disks, mechanical coding devices, punch cards or in-groove structures such as punch cards or grooves having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media, as used herein, are not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., optical pulses through fiber optic cables), or electrical signals transmitted through wires.
The computer readable program instructions described herein may be downloaded from a computer readable storage medium to a respective computing/processing device or to an external computer or external storage device over a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmissions, wireless transmissions, routers, firewalls, switches, gateway computers and/or edge servers. The network interface card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium in the respective computing/processing device.
The computer program instructions for performing the operations of the present disclosure can be assembly instructions, instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object-oriented programming language and conventional procedural programming languages. The computer readable program instructions may be executed entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, aspects of the present disclosure are implemented by personalizing electronic circuitry, such as programmable logic circuitry, field Programmable Gate Arrays (FPGAs), or Programmable Logic Arrays (PLAs), with state information of computer readable program instructions, which can execute the computer readable program instructions.
These computer readable program instructions may be provided to a processing unit of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processing unit of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable medium having the instructions stored therein includes an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of devices, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The foregoing description of the embodiments of the present disclosure has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the various embodiments described. The terminology used herein was chosen in order to best explain the principles of the embodiments, the practical application, or the technical improvement of the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (7)
1. The data stream processing method based on the convergence and distribution equipment is characterized by comprising the following steps of:
in the state of acquiring the data stream, acquiring characteristic data and address data of the current data stream according to the data stream;
performing feature code matching on the feature data to form a feature code matching rule set, and performing numbering processing on each feature code rule in the feature code matching rule set to form a feature rule number;
performing matching processing on the data stream according to the characteristic rule number and the address data to form a matching rule output;
the step of performing feature code matching on the feature data to form a feature code matching rule set, and the step of performing numbering processing on rules in the feature code matching rule set to form feature rule numbers specifically includes: inquiring and acquiring each feature code rule matched with the feature code in a TCAM storage unit; reading the priority of each feature code rule, and performing sequencing treatment on each feature code rule according to the priority to form the feature rule number;
the matching rule is as follows: matching rules formed by combining feature rule numbers and address data matching.
2. The method of claim 1, further comprising performing an action by the data stream corresponding to the matching rule.
3. A data stream processing system based on convergence and distribution equipment, which is characterized in that: comprising the steps of (a) a step of,
the first processing unit is connected with an external input port and is used for acquiring acquisition data, preprocessing the acquisition data and performing first matching processing on the acquisition data to form a data stream;
the second processing unit is connected to the first processing unit, and is configured to receive the data stream and split the data stream to form output data, where the splitting method is a data stream processing method based on the convergence splitting device as set forth in claim 1.
4. A data stream processing system based on a convergence and splitting device as set forth in claim 3, wherein: the second processing unit includes:
the reading module is used for acquiring characteristic data and address data of the current data stream according to the data stream in the state of acquiring the data stream;
the first matching module is used for carrying out feature code matching on the feature data to form a feature code matching rule set, and carrying out numbering processing on each feature code rule in the feature code matching rule set to form a feature rule number;
the second matching module is used for carrying out matching processing on the data stream according to the characteristic rule number and the address data so as to form a matching rule output;
the first matching module includes:
the inquirer inquires and acquires each feature code rule matched with the feature code in the TCAM storage unit;
the numbering device reads the priority of each feature code rule, and performs sorting processing on each feature code rule according to the priority to form the feature rule number;
the matching rule is as follows: matching rules formed by combining feature rule numbers and address data matching.
5. A data stream processing system based on a convergence splitting device as set forth in claim 3, further comprising an execution unit, wherein the data stream performs an action corresponding to the matching rule.
6. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements a data stream processing method based on a convergence splitting device as claimed in any one of claims 1-2 when executing the computer program.
7. A computer readable storage medium comprising computer readable code which, when run in a processor of an electronic device, performs a method for implementing a data stream processing based on a convergence splitting device as claimed in any one of claims 1 to 2.
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