Data processing method and device, equipment and storage medium

Abstract

The invention discloses a data processing method and device, equipment and a storage medium, and relates to the technical field of computers, and the method comprises the steps: obtaining a bearing index of a target system and traffic data in a storage layer; according to a service value, dividing the traffic data to obtain target traffic data with a low service value; and if the traffic data is greater than a preset traffic threshold or the bearing index is greater than a preset index threshold, closing the target traffic data. According to the invention, when the data volume of the system is too large, the target data flow with the data type of low business value in the storage layer is automatically closed, so that the pressure of the system can be quickly reduced, the service jitter of the system is prevented, and the service stability of the system is effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular, to a data processing method, apparatus, device, and storage medium. Background Art

[0002] When a software system encounters a resource bottleneck, common solutions include adding machines (e.g., adding more servers to share the load), adding nodes (e.g., adding more storage nodes in a distributed storage system), or upgrading configurations (e.g., increasing CPU, memory, or disk capacity). However, when the bottleneck occurs at the storage layer, the situation becomes complicated. Specifically, when the data volume is very large (e.g., greater than 1TB), adding storage nodes requires synchronizing all data. And the synchronization of all data is a time-consuming process, especially when the data volume is very large. It is impossible to complete the synchronization of all data in a short time, resulting in the inability to quickly relieve the storage bottleneck by adding nodes. When the bottleneck of the storage system is I / O performance, increasing disk capacity can only increase storage space but cannot improve I / O performance. For example, adding more mechanical hard disks (HDDs) may increase storage space, but the I / O performance is still limited by the physical characteristics of the disks. Summary of the Invention

[0003] Based on this, it is necessary to provide a data processing method, apparatus, device, and storage medium for the above technical problems to solve at least one of the problems existing in the above technical problems.

[0004] The present invention provides a data processing method, including:

[0005] Obtaining the bearing index of the target system and the traffic data in the storage layer;

[0006] Dividing the traffic data according to business value to obtain target traffic data with low business value;

[0007] If the traffic data is greater than a preset traffic threshold or the bearing index is greater than a preset index threshold, closing the target traffic data.

[0008] Optionally, according to a data processing method provided by the present invention, after the traffic data is greater than a preset traffic threshold or the bearing index is greater than a preset index threshold, it further includes:

[0009] Monitoring the response time corresponding to each service access request of the target system;

[0010] Counting the proportion of the number of requests corresponding to the response time greater than a preset time threshold;

[0011] Based on the proportion of the request quantity, determine a target fusing strategy, and perform fusing processing on the target system according to the target fusing strategy.

[0012] Optionally, according to a data processing method provided by the present invention, the determining a target fusing strategy based on the proportion of the request quantity includes:

[0013] Compare the proportion of the request quantity with a preset quantity threshold;

[0014] Determine a response level according to the comparison result;

[0015] Use the fusing strategy corresponding to the response level as the target fusing strategy.

[0016] Optionally, according to a data processing method provided by the present invention, after the traffic data is greater than a preset traffic threshold or the bearing index is greater than a preset index threshold, it further includes:

[0017] Obtain a newly added target processing node;

[0018] Perform preheating processing on the target processing node, and use the preheated target processing node to perform capacity expansion processing on the target system.

[0019] Optionally, according to a data processing method provided by the present invention, the performing preheating processing on the target processing node includes:

[0020] Obtain a traffic processing strategy for time slice shunting;

[0021] Based on the traffic processing strategy, shunt a preset quantity of traffic data to the target processing node.

[0022] Optionally, according to a data processing method provided by the present invention, after using the preheated target processing node to perform capacity expansion processing on the target system, it further includes:

[0023] Obtain a target bearing index of the target system within a preset time period;

[0024] If the target bearing index is less than the preset index threshold, after the target processing node completes the data processing process, perform disconnection processing on the target processing node.

[0025] Optionally, according to a data processing method provided by the present invention, after performing closing processing on the target traffic data, it further includes:

[0026] Judge whether the target system is in a stable state;

[0027] If so, restore the target data traffic.

[0028] The present invention also provides a data processing device, including:

[0029] An acquisition module, configured to acquire the bearing index of the target system and the traffic data in the storage layer;

[0030] A division module, configured to divide the traffic data according to the business value to obtain target traffic data with low business value;

[0031] A processing module, configured to perform a shutdown process on the target traffic data if the traffic data is greater than a preset traffic threshold or the bearing index is greater than a preset index threshold.

[0032] The present invention also provides a computer device, including a memory, a processor, and computer-readable instructions stored in the memory and executable on the processor. When the processor executes the computer-readable instructions, the above data processing method is implemented.

[0033] The present invention also provides one or more readable storage media storing computer-readable instructions. When the computer-readable instructions are executed by a processor, the above data processing method is implemented.

[0034] The present invention also provides a computer program product, including computer-readable instructions. When the computer-readable instruction program is executed by a processor, the data processing method described in any one of the above is implemented.

[0035] The above data processing method, device, equipment, and storage medium include: acquiring the bearing index of the target system and the traffic data in the storage layer; dividing the traffic data according to the business value to obtain target traffic data with low business value; and performing a shutdown process on the target traffic data if the traffic data is greater than a preset traffic threshold or the bearing index is greater than a preset index threshold. When the system data volume is too large, the present invention automatically shuts down the target data traffic with low business value in the storage layer, which can quickly reduce the system pressure and prevent service jitter of the system, thereby effectively improving the service stability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0037] Figure 1 is a flowchart of a data processing method in an embodiment of the present invention;

[0038] Figure 2 It is a schematic structural diagram of a data processing device in an embodiment of the present invention;

[0039] Figure 3 It is a schematic diagram of a computer device in an embodiment of the present invention. Specific embodiments

[0040] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0041] The terms used in one or more embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit one or more embodiments of the present invention. The singular forms "a", "the", and "said" used in one or more embodiments of the present invention are also intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in one or more embodiments of the present invention refers to and includes any or all possible combinations of one or more of the associated listed items.

[0042] It should be understood that although the terms first, second, etc. may be used in one or more embodiments of the present invention to describe various information, such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of one or more embodiments of the present invention, the first may also be referred to as the second, and similarly, the second may also be referred to as the first. Depending on the context, the word "if" as used herein may be interpreted as "when" or "while".

[0043] In one embodiment, specifically, as Figure 1 shown, Figure 1 It is a schematic flowchart of a data processing method in an embodiment of the present invention. The embodiment of the present invention provides a data processing method, including the following steps:

[0044] Step S11, obtaining the load indicators of the target system and the traffic data in the storage layer;

[0045] Specifically, collect the load indicators of the target system and the traffic data in the storage layer. Among them, there is no specific limitation on the selection of the load indicators. For example, the load indicators include one or more of the central processor usage rate, disk usage rate, memory usage rate, system queries per second, request latency, etc.

[0046] Step S12: Divide the traffic data according to the business value to obtain target traffic data with low business value.

[0047] Specifically, the business value scores of each business data are generated in advance according to the actual usage value corresponding to different business data, and a business value threshold is set. If the business value score corresponding to the current business data is greater than the business value threshold, the business value of this data is set to high; if the business value score of the data is less than or equal to the business value threshold, the business value of this data is set to low. Among them, the value of the above-mentioned business value threshold is not specifically limited. Thus, according to the business value, the traffic data is divided and processed to correspondingly divide the data into data with high business value and target traffic data with low business value.

[0048] Step S13: If the traffic data is greater than the preset traffic threshold or the load index is greater than the preset index threshold, close the target traffic data.

[0049] It should be noted that the value of the above-mentioned traffic threshold is not specifically limited, and the value of the above-mentioned preset index threshold is not specifically limited.

[0050] Specifically, compare the traffic data with the preset traffic threshold, and compare the load index with the preset index threshold. If the traffic data is not greater than the preset traffic threshold and the load index is not greater than the preset index threshold, it proves that the data volume of the system is small, and it is determined that the system is in a stable state of normal operation. If the traffic data is greater than the preset traffic threshold or the load index is greater than the preset index threshold, close the target traffic data. In one embodiment, determine the data identifier of the target traffic data with low business value, and directly close each target traffic data corresponding to the data identifier.

[0051] The embodiment of the present invention adopts the above scheme, including: obtaining the load index of the target system and the traffic data in the storage layer; dividing the traffic data according to the business value to obtain target traffic data with low business value; if the traffic data is greater than the preset traffic threshold or the load index is greater than the preset index threshold, close the target traffic data. When the data volume of the system is too large, the present invention automatically closes the target data traffic with low business value in the storage layer, which can quickly reduce the system pressure and prevent service jitter of the system, thereby effectively improving the service stability of the system.

[0052] In one embodiment of the present invention, after the traffic data is greater than the preset traffic threshold or the load index is greater than the preset index threshold, it further includes:

[0053] Monitor the response time corresponding to each service access request of the target system; count the proportion of the number of requests corresponding to the response time greater than the preset time threshold; determine a target fusing policy based on the proportion of the number of requests, so as to perform fusing processing on the target system according to the target fusing policy.

[0054] It should be noted that the proportion of the number of requests refers to the proportional value of the service access requests that have timed out and cannot be processed on time among all the service access requests received by the target system.

[0055] Specifically, monitor the response time corresponding to each service access request of the target system, and then compare the response time with the preset time threshold. The preset time threshold is set according to the actual situation. For example, the get query in the system is set to 10 ms, and the mget query is set to 20 ms. If the response time is greater than the preset time threshold, it proves that the service access request is a request that cannot be processed on time. Further, count the proportion of the number of requests corresponding to the service access requests with a response time greater than the preset time threshold. Then compare the proportion of the number of requests with the preset number threshold. If the proportion of the number of requests is greater than the preset number threshold, perform fusing processing on the target system using the target fusing policy set by the system. For example, when 20% of the service access requests time out, automatically fuse for 10 s to prevent service jitter in the system and effectively improve the service stability of the system.

[0056] The embodiment of the present invention adopts the above solution, including: monitoring the response time corresponding to each service access request of the target system; counting the proportion of the number of requests corresponding to the response time greater than the preset time threshold; determining a target fusing policy based on the proportion of the number of requests, so as to perform fusing processing on the target system according to the target fusing policy. It realizes determining the fusing policy according to the proportion of access requests with request timeouts, and performing fusing processing on the target system according to the fusing policy, which can effectively reduce the system pressure of the target system, reduce the service jitter of the target system, and improve the service stability of the target system.

[0057] In an embodiment of the present invention, determining a target fusing policy based on the proportion of the number of requests includes:

[0058] Compare the proportion of the number of requests with the preset number threshold; determine the response level according to the comparison result; use the fusing policy corresponding to the response level as the target fusing policy.

[0059] In one embodiment, multiple preset quantity thresholds may be set. The proportion of the request quantity is compared with the multiple preset quantity thresholds. According to the comparison result, the response level is determined. Among them, the circuit-breaking strategies corresponding to different response levels are different. Furthermore, the circuit-breaking strategy associated with the current response level is used as the target circuit-breaking strategy. The circuit-breaking process is performed on the target system according to the target circuit-breaking strategy. For example, the response level corresponding to the request quantity proportion of 10%-20% is the first-level response, the response level corresponding to the request quantity proportion of 20%-40% is the second-level response, and the response level corresponding to the request quantity proportion of 40%-60% is the third-level response. Among them, the specific content of the circuit-breaking strategy can be set according to the actual circuit-breaking service. Exemplarily, the circuit-breaking strategy corresponding to the first-level response is that the system automatically breaks for 10s, the circuit-breaking strategy corresponding to the second-level response is that the system automatically breaks for 30s, and the circuit-breaking strategy corresponding to the third-level response is that the system automatically breaks for 60s.

[0060] The embodiment of the present invention adopts the above solution, including: comparing the proportion of the request quantity with the preset quantity threshold; determining the response level according to the comparison result; using the circuit-breaking strategy corresponding to the response level as the target circuit-breaking strategy. Different circuit-breaking strategies are preset for different response levels. Using the circuit-breaking strategy associated with the current response level to perform the circuit-breaking process on the target system can effectively reduce the system pressure of the target system, reduce the service jitter of the target system, and improve the service stability of the target system.

[0061] In one embodiment of the present invention, after the traffic data is greater than the preset traffic threshold or the bearing index is greater than the preset index threshold, it further includes:

[0062] Obtain the newly added target processing node; perform a warm-up process on the target processing node to use the warm-up processed target processing node to perform an expansion process on the target system.

[0063] It should be noted that the target processing node is a data node with traffic processing function pre-built. Among them, the number of target processing nodes can be set according to the actual service expansion requirement, without specific limitation.

[0064] It should be noted that when the existing nodes in the target system cannot support the current business traffic volume, new target processing nodes can be added for traffic diversion to disperse the system pressure. Specifically, obtain the traffic processing strategy for time slice diversion; then, based on the traffic processing strategy, divert a preset number of traffic data to the target processing nodes. It can be understood that after the full amount of data of the new node is ready, small traffic preheating is first performed. For example, in the way of time slice diversion, 1% of the traffic is first diverted to evenly preheat the data of the new processing node to prevent the response time of data processing from being too high when the traffic hits the new processing node without the read cache of the disk. In addition, the processing flow of preheating the processing nodes based on the processing strategy may include: first cut small traffic to evenly preheat the newly added processing nodes, then gradually increase the traffic, and finally release the full amount. Using the processing strategy of time slice diversion to preheat the nodes can quickly and accurately obtain the target processing nodes required for expanding the system, improving the construction efficiency of the target processing nodes.

[0065] Furthermore, expand the preheated target processing nodes to the storage layer of the target system to complete the expansion processing of the target system, so that the target system can use the target processing nodes to perform internal traffic processing.

[0066] The embodiment of the present invention adopts the above scheme, including: obtaining newly added target processing nodes; performing preheating processing on the target processing nodes to use the preheated target processing nodes to expand the target system. By using the newly added target processing nodes to perform internal traffic processing of the target system, the system pressure of the target system can be effectively reduced, the service jitter of the target system can be reduced, and the service stability of the target system can be improved.

[0067] In an embodiment of the present invention, after using the preheated target processing nodes to expand the target system, it further includes:

[0068] Obtain the target bearing index of the target system within a preset time period; if the target bearing index is less than the preset index threshold, after the target processing node completes the data processing process, perform a disconnection processing on the target processing node.

[0069] Specifically, monitor the target bearing indicators of the target system within a preset time period after capacity expansion, where the target bearing indicators include one or more of the central processing unit usage rate, disk usage rate, memory usage rate, system queries per second, request latency, etc. Compare the target bearing indicators with the indicator thresholds, and then determine whether the specified bearing indicator is less than the indicator threshold according to the result of the numerical comparison. If so, after the target processing node completes the data processing process, perform a disconnection process on the target processing node.

[0070] The embodiment of the present invention through the above solution includes: obtaining the target bearing indicators of the target system within a preset time period; if the target bearing indicators are less than the preset indicator thresholds, then after the target processing node completes the data processing process, perform a disconnection process on the target processing node. When the target bearing indicators are less than the preset indicator thresholds, the target processing node will be intelligently disconnected after the data processing process is completed, so as to complete the capacity reduction process of the production management system under the condition of stable system operation, effectively reducing the power consumption brought by the target processing node and ensuring the load balance of the processing nodes of the system.

[0071] In an embodiment of the present invention, after performing a shutdown process on the target traffic data, it further includes:

[0072] Determine whether the target system is in a stable state; if so, restore the target data traffic.

[0073] Specifically, collect the current data traffic and the current bearing indicators in the storage layer of the target system. If the current data traffic is less than the preset traffic threshold and the current bearing indicators are less than the preset indicator thresholds, it is determined that the system is in a stable state of normal operation. Then perform a restoration process on the target data traffic corresponding to the target service data, that is, restore the normal processing process for the target data traffic.

[0074] The embodiment of the present invention through the above solution effectively improves the intelligence and processing integrity of the data traffic in the storage layer of the system by performing a restoration process on the target data traffic when it is detected that the system has returned to a stable state.

[0075] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The order of execution of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0076] In one embodiment, a data processing device is provided, and this data processing device corresponds one-to-one with the data processing method in the above embodiment. As Figure 2 shown, Figure 2It is a schematic structural diagram of a data processing device in an embodiment of the present invention. The data processing device includes:

[0077] An acquisition module 21, configured to acquire the bearing index of the target system and the traffic data in the storage layer;

[0078] A division module 22, configured to divide the traffic data according to the business value to obtain target traffic data with low business value;

[0079] A processing module 23, configured to perform a closing process on the target traffic data if the traffic data is greater than a preset traffic threshold or the bearing index is greater than a preset index threshold.

[0080] The data processing device further includes:

[0081] Monitoring the response time corresponding to each service access request of the target system;

[0082] Counting the proportion of the number of requests whose response time is greater than a preset time threshold;

[0083] Based on the proportion of the number of requests, determining a target fusing policy to perform a fusing process on the target system according to the target fusing policy.

[0084] The data processing device further includes:

[0085] Comparing the proportion of the number of requests with a preset number threshold;

[0086] Determining a response level according to the comparison result;

[0087] Taking the fusing policy corresponding to the response level as the target fusing policy.

[0088] The data processing device further includes:

[0089] Acquiring a newly added target processing node;

[0090] Performing a preheating process on the target processing node to use the preheated target processing node to perform an expansion process on the target system.

[0091] The data processing device further includes:

[0092] Acquiring a traffic processing policy for time slice shunting;

[0093] Based on the traffic processing policy, shunting a preset amount of traffic data to the target processing node.

[0094] The data processing device further includes:

[0095] Acquiring the target bearing index of the target system within a preset time period;

[0096] If the target load index is less than the preset index threshold, after the data processing process is completed at the target processing node, a disconnection process is performed on the target processing node.

[0097] The data processing device further includes:

[0098] Determine whether the target system is in a stable state;

[0099] If so, restore the target data traffic.

[0100] For the specific limitations of the data processing device, reference can be made to the limitations on the data processing method in the foregoing text, which will not be elaborated here. Each module in the above data processing device can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or stored in the memory in the computer device in the form of software, so as to facilitate the processor to call and execute the operations corresponding to the above modules.

[0101] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as Figure 3 shown Figure 3 is a schematic diagram of a computer device in an embodiment of the present invention. The computer device includes a processor, a memory, a network interface, and a database connected through a device bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a readable storage medium and an internal memory. The readable storage medium stores an operating device, computer-readable instructions, and a database. The internal memory provides an environment for the operation of the operating device and computer-readable instructions in the readable storage medium. The database of the computer device is used to store the data involved in the data processing method. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer-readable instructions are executed by the processor, a data processing method is implemented. The readable storage medium provided in this embodiment includes a non-volatile readable storage medium and a volatile readable storage medium.

[0102] In one embodiment, a computer device is provided. The computer device may be a terminal device, and its internal structure diagram may be as Figure 3As shown in the figure. The computer device includes a processor, a memory, and a network interface connected through a device bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a readable storage medium. The readable storage medium stores computer-readable instructions. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer-readable instructions are executed by the processor, a data processing method is implemented. The readable storage medium provided in this embodiment includes a non-volatile readable storage medium and a volatile readable storage medium.

[0103] In one embodiment, a computer device is provided, including a memory, a processor, and computer-readable instructions stored in the memory and executable on the processor. When the processor executes the computer-readable instructions, the steps of the data processing method as described above are implemented. The method includes: obtaining the bearing index of the target system and the traffic data in the storage layer; dividing the traffic data according to the business value to obtain the target traffic data with low business value; if the traffic data is greater than a preset traffic threshold or the bearing index is greater than a preset index threshold, closing the target traffic data.

[0104] In one embodiment, a readable storage medium is provided. The readable storage medium stores computer-readable instructions. When the computer-readable instructions are executed by the processor, the steps of the data processing method as described above are implemented. Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through computer-readable instructions. The computer-readable instructions can be stored in a non-volatile readable storage medium or a volatile readable storage medium. When the computer-readable instructions are executed, they can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided in this application can include non-volatile and / or volatile memories. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or an external cache. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0105] In one embodiment, a computer program product is provided. The computer program product includes computer-readable instructions that can be stored in a non-volatile readable storage medium or a volatile readable storage medium. When the computer-readable instructions are executed by a processor, the computer can perform the data processing methods provided by the above-mentioned various methods. The method includes: obtaining the bearing index of the target system and the traffic data in the storage layer; dividing the traffic data according to the business value to obtain the target traffic data with low business value; if the traffic data is greater than a preset traffic threshold or the bearing index is greater than a preset index threshold, then perform a shutdown process on the target traffic data.

[0106] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the above-mentioned division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above.

[0107] The above-described embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A data processing method, characterized in that: include: Obtain the target system's load indicators and traffic data in the storage layer; According to the business value, the traffic data is divided to obtain target traffic data with low business value; If the traffic data is greater than a preset traffic threshold or the carrying index is greater than a preset index threshold, the target traffic data is closed.

2. The data processing method according to claim 1, characterized in that: If the flow data is greater than a preset flow threshold or the carrying index is greater than a preset index threshold, the method further includes: Monitoring the response time of each service access request of the target system; Count the proportion of requests whose response time is greater than a preset time threshold; Based on the proportion of the number of requests, a target fusing strategy is determined to perform fusing processing on the target system according to the target fusing strategy.

3. The data processing method according to claim 2, characterized in that: The determining of a target fuse strategy based on the proportion of the number of requests includes: Compare the request quantity ratio with a preset quantity threshold; Determine the response level based on the comparison results; The fuse policy corresponding to the response level is used as the target fuse policy.

4. The data processing method according to claim 1, characterized in that: If the flow data is greater than a preset flow threshold or the carrying index is greater than a preset index threshold, the method further includes: Get the newly added target processing node; The target processing node is preheated to expand the target system using the preheated target processing node.

5. The data processing method according to claim 4, characterized in that: The preheating process of the target processing node includes: Obtain the traffic processing strategy for time slice diversion; Based on the traffic processing strategy, a preset amount of traffic data is diverted to the target processing node.

6. The data processing method according to claim 4, characterized in that: After the target processing node after the preheating process is used to expand the target system, the method further includes: Obtaining a target load indicator of the target system within a preset time period; If the target carrying index is less than a preset index threshold, after the target processing node completes the data processing flow, a disconnection process is performed on the target processing node.

7. The data processing method according to claim 1, characterized in that: After the target traffic data is closed, the method further includes: Determining whether the target system is in a stable state; If so, the target data flow is restored.

8. A data processing device, characterized in that: include: The acquisition module is used to obtain the load indicators of the target system and the traffic data in the storage layer; A division module, used for dividing the traffic data according to the business value to obtain target traffic data with low business value; The processing module is used to close the target traffic data if the traffic data is greater than a preset traffic threshold or the carrying index is greater than a preset index threshold.

9. A computer device comprising a memory, a processor, and computer-readable instructions stored in the memory and executed on the processor, characterized in that: When the processor executes the computer-readable instructions, the data processing method according to any one of claims 1 to 7 is implemented.

10. A readable storage medium having computer readable instructions stored thereon, characterized in that: When the computer-readable instructions are executed by a processor, the data processing method according to any one of claims 1 to 7 is implemented.

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