System capacity expansion method, device, equipment, medium and program product

Abstract

The invention provides a system capacity expansion method which can be applied to the technical field of computers. The system capacity expansion method comprises the following steps: circularly acquiring transaction data generated by a target system in each time interval according to a preset time interval; aiming at the ith time interval in the time intervals, under the condition that the ith transaction duration corresponding to the ith transaction data generated by the target system in the ith time interval meets a first preset condition, determining the ith transaction data as suspected transaction data, and determining an ith transaction processing score aiming at the ith time interval according to the system weight of the target system; updating a system capacity score of the target system according to the ith transaction processing score to obtain an updated system capacity score; and when the updated system capacity score is greater than or equal to a first threshold value, expanding the system capacity of the target system. The invention further provides a system capacity expansion device, equipment, a storage medium and a program product.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to a system expansion method, device, equipment, medium and program product. Background Art

[0002] System capacity refers to the number of services that the system can support and return normally. System capacity can be determined by the number of cluster nodes and the processing capacity of each node. In actual applications, system capacity can be configured according to the number of business requests in the historical records. After configuration, the system's processing resources are fixed, and thus the system capacity is also fixed. However, as the number of business requests increases, the system capacity is unable to efficiently handle a large number of business requests, resulting in the unavailability of the entire service link and causing large-scale failures.

[0003] In the related art, it is generally determined that the system needs to be expanded and the expansion process is performed by judging that the system capacity is less than the preset capacity threshold when the system is idle. However, this method does not combine the comprehensive analysis of business requests, and it is difficult to accurately determine the usage of system resources, which is prone to the insensitivity or oversensitivity of expansion and contraction reactions. Summary of the invention

[0004] In view of the above problems, the present disclosure provides a system expansion method, apparatus, device, medium and program product.

[0005] According to a first aspect of the present disclosure, a system expansion method is provided, comprising:

[0006] According to the preset time intervals, the transaction data generated by the target system in each time interval is cyclically acquired, wherein the transaction data includes the transaction duration;

[0007] For the i-th time interval in each time interval, if the i-th transaction duration corresponding to the i-th transaction data generated by the target system in the i-th time interval satisfies the first preset condition, the i-th transaction data is determined to be questionable transaction data, and the i-th transaction processing score for the i-th time interval is determined according to the system weight of the target system, where i is a positive integer;

[0008] updating the system capacity score of the target system according to the i-th transaction processing score to obtain an updated system capacity score, wherein the system capacity score is determined according to the transaction processing scores corresponding to each of i-1 time intervals before the start time of the i-th time interval, and the system capacity score represents the system capacity utilization rate of the target system; and

[0009] When the updated system capacity score is greater than or equal to the first threshold, the system capacity of the target system is expanded.

[0010] According to an embodiment of the present disclosure, the above-mentioned i-th transaction data includes multiple items;

[0011] The above method further includes:

[0012] Determine an i-th average transaction duration for the i-th time interval according to the i-th transaction durations of the plurality of i-th transaction data;

[0013] In the case where the i-th average transaction duration satisfies the first preset condition, the i-th transaction score for the i-th time interval is determined according to the system weight of the target system.

[0014] According to an embodiment of the present disclosure, the above method further includes:

[0015] Determine the historical average transaction duration based on the historical transaction data generated before the start time of the i-th time interval;

[0016] When it is determined that the ratio of the i-th average transaction duration to the historical average transaction duration is greater than the second threshold, it is determined that the i-th average transaction duration satisfies the first preset condition.

[0017] According to an embodiment of the present disclosure, the transaction data also includes transaction status;

[0018] Before determining that the i-th transaction data is questionable transaction data, the method further includes:

[0019] Determine the historical transaction success rate based on the historical transaction data generated before the start time of the i-th time interval;

[0020] determining an i-th transaction success rate for an i-th time interval according to an i-th transaction status of each of the plurality of i-th transaction data;

[0021] When it is determined that the ratio of the i-th transaction success rate to the historical transaction success rate is less than a third threshold, it is determined that the i-th transaction data is questionable transaction data.

[0022] According to an embodiment of the present disclosure, the target system includes a plurality of system nodes; wherein determining the i-th transaction score for the i-th time interval according to the system weight of the target system includes:

[0023] For a j-th system node among the plurality of system nodes, determining j-th transaction sub-data corresponding to the j-th system node from the i-th transaction data;

[0024] When it is determined that the jth transaction duration corresponding to the jth transaction sub-data satisfies the first preset condition, determining the jth node weight of the jth system node according to the historical transaction data for the jth system node generated before the start time of the i-th time interval;

[0025] The i-th transaction processing score is determined according to the node weights of the plurality of system nodes and the system weight of the target system.

[0026] According to an embodiment of the present disclosure, the above method further includes:

[0027] If the j-th transaction duration in the j-th transaction sub-data satisfies the first preset condition, marking the j-th transaction sub-data as abnormal transaction sub-data;

[0028] The determining of the jth node weight of the jth system node according to the historical transaction data for the jth system node generated before the start time of the i-th time interval includes:

[0029] In a case where it is determined that the historical transaction data for the j-th system node generated before the start time of the i-th time interval contains abnormal transaction sub-data, determining the j-th node weight of the j-th system node to be a first value;

[0030] When it is determined that the historical transaction data for the j-th system node generated before the start time of the i-th time interval does not contain abnormal transaction sub-data, the j-th node weight of the j-th system node is determined to be a second value.

[0031] According to an embodiment of the present disclosure, the above method further includes:

[0032] After expanding the system capacity of the target system, adjusting the system capacity score of the target system to zero; or;

[0033] According to the preset time period, the system capacity score of the target system is cyclically cleared to zero, so that the system capacity score of the target system corresponding to the end time of each preset time period is zero.

[0034] According to an embodiment of the present disclosure, when the updated system capacity score meets the first threshold, before expanding the system capacity of the target system, the method further includes:

[0035] A preset whitelist is obtained, and when it is determined that the preset whitelist does not include the target system, the system capacity of the target system is expanded.

[0036] A second aspect of the present disclosure provides a system expansion device, comprising:

[0037] A first acquisition module is used to cyclically acquire transaction data generated by the target system in each time interval according to a preset time interval, wherein the transaction data includes transaction duration;

[0038] a first determining module, configured to determine, for an i-th time interval in each time interval, if an i-th transaction duration corresponding to an i-th transaction data generated by the target system in the i-th time interval satisfies a first preset condition, determine that the i-th transaction data is questionable transaction data, and determine an i-th transaction processing score for the i-th time interval according to a system weight of the target system, where i is a positive integer;

[0039] an updating module, configured to update a system capacity score of the target system according to the i-th transaction processing score to obtain an updated system capacity score, wherein the system capacity score is determined according to transaction processing scores corresponding to each of i-1 time intervals before the start time of the i-th time interval, and the system capacity score represents a system capacity utilization rate of the target system; and

[0040] The capacity expansion module is used to expand the system capacity of the target system when the updated system capacity score is greater than or equal to the first threshold.

[0041] A third aspect of the present disclosure provides an electronic device, comprising: one or more processors; and a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the above method.

[0042] The fourth aspect of the present disclosure further provides a computer-readable storage medium having a computer program or instructions stored thereon, which implements the steps of the above method when the above computer program or instructions are executed by a processor.

[0043] The fifth aspect of the present disclosure further provides a computer program product, including a computer program or instructions, which implement the steps of the above method when the above computer program or instructions are executed by a processor.

[0044] According to the embodiment of the present disclosure, by adopting the preset time interval, the transaction data including the transaction duration generated by the target system in each time interval is cyclically obtained; then for the i-th time interval in each time interval, if the i-th transaction duration corresponding to the i-th transaction data generated by the target system in the i-th time interval meets the first preset condition, the i-th transaction data is determined to be questionable transaction data, and the i-th transaction processing score for the i-th time interval is determined according to the system weight of the target system; the system capacity score of the target system is updated according to the i-th transaction processing score to obtain the updated system capacity score; when the updated system capacity score is greater than or equal to the first threshold, the system capacity of the target system is expanded. Since the present disclosure determines whether the transaction duration in the time interval meets the preset condition according to the transaction duration, if not, the transaction data is determined to be questionable transaction data, the transaction processing score of the system corresponding to the questionable transaction data is calculated, and then the transaction processing score of each time interval is superimposed to obtain the system capacity score, and when the system capacity score reaches a certain threshold, the system is expanded, and the system resource usage can be more accurately known by fully combining the system's business request data for comprehensive analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The above contents and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0046] Figure 1 The application scenario diagram of the system expansion method, apparatus, device, medium and program product according to the embodiment of the present disclosure is schematically shown;

[0047] Figure 2 A flowchart of a system expansion method according to an embodiment of the present disclosure is schematically shown;

[0048] Figure 3 A schematic diagram schematically illustrates a method for determining an updated system capacity score according to an embodiment of the present disclosure;

[0049] Figure 4 A flowchart for determining questionable data according to an embodiment of the present disclosure is schematically shown;

[0050] Figure 5 A flowchart for determining a transaction processing score according to an embodiment of the present disclosure is schematically shown;

[0051] Figure 6 A structural block diagram of a system capacity expansion device according to an embodiment of the present disclosure is schematically shown; and

[0052] Figure 7 A block diagram of an electronic device suitable for implementing the above method according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0053] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0054] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0055] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0056] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0057] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0058] It should be noted that the system expansion method and device disclosed in the present invention can be used in the financial field, and can also be used in any field other than the financial field. The application field of the system expansion method and device disclosed in the present invention is not limited.

[0059] Figure 1 The application scenario diagram of the system expansion method, apparatus, device, medium and program product according to the embodiments of the present disclosure is schematically shown.

[0060] like Figure 1As shown, the application scenario 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 is used to provide a medium for a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or optical fiber cables, etc.

[0061] The user can use the first terminal device 101, the second terminal device 102, and the third terminal device 103 to interact with the server 105 through the network 104 to receive or send messages, etc. Various communication client applications can be installed on the first terminal device 101, the second terminal device 102, and the third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only for example).

[0062] The first terminal device 101, the second terminal device 102, and the third terminal device 103 may be various electronic devices having display screens and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, and the like.

[0063] The server 105 may be a server that provides various services, such as a background management server (only as an example) that provides support for websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103. The background management server may analyze and process the received data such as user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

[0064] It should be noted that the system expansion method provided in the embodiment of the present disclosure can generally be executed by the server 105. Accordingly, the system expansion device provided in the embodiment of the present disclosure can generally be set in the server 105. The system expansion method provided in the embodiment of the present disclosure can also be executed by a server or server cluster that is different from the server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105. Accordingly, the system expansion device provided in the embodiment of the present disclosure can also be set in a server or server cluster that is different from the server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105.

[0065] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0066] The following will be based on Figure 1 The scene described by Figure 2~Figure 5 The system expansion method of the disclosed embodiment is described in detail.

[0067] Figure 2 The flowchart of the system expansion method according to the embodiment of the present disclosure is schematically shown.

[0068] like Figure 2 As shown, the system expansion method of this embodiment includes operations S210 to S240, and the system expansion method can be executed by the server.

[0069] In operation S210, transaction data generated by the target system in each time interval is cyclically acquired according to a preset time interval, wherein the transaction data includes transaction duration.

[0070] According to the embodiments of the present disclosure, a scheduled task may be set to periodically obtain transaction data generated by the target system from the message data of the transaction log.

[0071] The preset time interval can be 1 hour, 10 hours, 24 hours, 48 ​​hours, etc.

[0072] Transaction data may include system information, node information, transaction response and transaction duration, and transaction status, such as transaction success or transaction failure.

[0073] The acquired transaction data can be spliced ​​into SQL statements and stored in the database for persistence.

[0074] In operation S220, for the i-th time interval in each time interval, when it is determined that the i-th transaction duration corresponding to the i-th transaction data generated by the target system in the i-th time interval satisfies the first preset condition, the i-th transaction data is determined to be questionable transaction data, and the i-th transaction processing score for the i-th time interval is determined according to the system weight of the target system, where i is a positive integer.

[0075] According to an embodiment of the present disclosure, the first preset condition may be that the ratio of the average transaction duration of the i-th transaction data to the historical transaction duration is greater than a second threshold, and the second threshold may be, for example, 1.5; it may also be that the average transaction duration of the i-th transaction data is greater than the preset transaction duration.

[0076] According to an embodiment of the present disclosure, determining the i-th transaction processing score for the i-th time interval according to the system weight of the target system may include: determining the system weight of the target system as the i-th transaction processing score.

[0077] The system weight of the target system can be pre-configured according to the type of the target system and the level of the target system. The system weights corresponding to different target systems can be the same or different.

[0078] It should be noted that, in the process of determining the transaction processing score corresponding to each time interval, the transaction processing score corresponding to each time interval is determined in chronological order.

[0079] For example, first determine the transaction processing score corresponding to the first time interval, then determine the transaction processing score corresponding to the second time interval, and so on, determine the transaction processing score corresponding to the i-th time interval.

[0080] According to an embodiment of the present disclosure, when it is determined that the i-th transaction duration corresponding to the i-th transaction data generated by the target system within the i-th time interval does not meet the first preset condition, the i-th transaction processing score corresponding to the i-th time interval can be determined to be a preset value, for example, it can be zero.

[0081] In operation S230, the system capacity score of the target system is updated according to the i-th transaction processing score to obtain an updated system capacity score, wherein the system capacity score is determined according to the transaction processing scores corresponding to each of the i-1 time intervals before the start time of the i-th time interval, and the system capacity score represents the system capacity utilization rate of the target system.

[0082] According to an embodiment of the present disclosure, updating the system capacity score of the target system according to the i-th transaction processing score may include: adding the system capacity scores of the target systems updated by the i-th transaction processing score to obtain an updated system capacity score.

[0083] In operation S240 , if the updated system capacity score is greater than or equal to the first threshold, the system capacity of the target system is expanded.

[0084] According to an implementation of the present disclosure, the first threshold may be preconfigured.

[0085] According to the embodiments of the present disclosure, expanding the system capacity of the target system may include node expansion and service expansion. When performing node expansion, the system will use the latest node snapshot to add node instances, and automatically start the corresponding service process after the node is started; when performing service expansion, the system will deploy a new service instance directory after self-increment based on the instance number of the current service, and start the corresponding service process after completion; after the above services are started, they will automatically join the scheduling pool, and the scheduling pool will realize cluster load and high availability.

[0086] It should be noted that the target system can be expanded using existing expansion methods, which will not be described in detail in this disclosure.

[0087] According to the embodiment of the present disclosure, by adopting the preset time interval, the transaction data including the transaction duration generated by the target system in each time interval is cyclically obtained; then for the i-th time interval in each time interval, if the i-th transaction duration corresponding to the i-th transaction data generated by the target system in the i-th time interval meets the first preset condition, the i-th transaction data is determined to be questionable transaction data, and the i-th transaction processing score for the i-th time interval is determined according to the system weight of the target system; the system capacity score of the target system is updated according to the i-th transaction processing score to obtain the updated system capacity score; when the updated system capacity score is greater than or equal to the first threshold, the system capacity of the target system is expanded. Since the present disclosure determines whether the transaction duration in the time interval meets the preset condition according to the transaction duration, if not, the transaction data is determined to be questionable transaction data, the transaction processing score of the system corresponding to the questionable transaction data is calculated, and then the transaction processing score of each time interval is superimposed to obtain the system capacity score, and when the system capacity score reaches a certain threshold, the system is expanded, and the system resource usage can be more accurately known by fully combining the system's business request data for comprehensive analysis.

[0088] According to an embodiment of the present disclosure, the above method further includes: after expanding the system capacity of the target system, adjusting the system capacity score of the target system to zero.

[0089] According to an embodiment of the present disclosure, the method may further include: cyclically clearing the system capacity score of the target system according to preset time periods, so that the system capacity score of the target system corresponding to the end time of each preset time period is zero.

[0090] For example, the system capacity score of the target system is adjusted to zero every other month, so that the system capacity score of the target system is accumulated again from zero.

[0091] According to an embodiment of the present disclosure, by adjusting the system capacity score of the target system to zero, it is avoided that the system capacity score of the target system is inconsistent with the actual situation due to the long-term accumulation of transaction processing scores.

[0092] Figure 3 A schematic diagram of determining an updated system capacity score according to an embodiment of the present disclosure is schematically shown.

[0093] like Figure 3As shown, in this embodiment, i is 2. It should be noted that the first time interval refers to the first time interval after the initial system capacity score of the target system is adjusted to zero. First, the first transaction data 311 generated by the target system in the first time interval 310 is obtained; then 312 is executed to determine whether the first transaction data 311 is questionable transaction data according to the first preset condition; if the first transaction data 311 is questionable transaction data, the first transaction processing score 314 is determined according to the system weight of the target system; then the initial system capacity score 315 is updated according to the first transaction processing score 314, for example, to zero, to obtain the updated system capacity score, i.e., the first system capacity score 316; if the first transaction data 311 is not questionable transaction data, the preset value 313 is directly obtained, and the preset value can be zero; then the initial system capacity score 315 is updated according to the preset value 313, to obtain the updated system capacity score, i.e., the first system capacity score 316. Then, the second transaction data 321 generated by the target system in the second time interval 320 is obtained; then 322 is executed to determine whether the second transaction data 321 is questionable transaction data according to the first preset condition; if the second transaction data 321 is questionable transaction data, the second transaction processing score 323 is determined according to the system weight of the target system; then the system capacity score of the target system, i.e. the first system capacity score 316, is updated according to the second transaction processing score 323 to obtain an updated system capacity score, i.e. the second system capacity score 325; if the second transaction data 321 is not questionable transaction data, the preset value 324 is directly obtained, and the preset value can be zero; then the system capacity score of the target system, i.e. the first system capacity score 316, is updated according to the preset value 324 to obtain an updated system capacity score, i.e. the second system capacity score 325.

[0094] According to an embodiment of the present disclosure, the i-th transaction data includes multiple items; the above method also includes: determining the i-th average transaction duration for the i-th time interval based on the i-th transaction durations of each of the multiple i-th transaction data; when the i-th average transaction duration satisfies the first preset condition, determining the i-th transaction score for the i-th time interval based on the system weight of the target system.

[0095] According to an embodiment of the present disclosure, the first preset condition may be that the ratio of the average transaction duration of the i-th transaction data to the historical transaction duration is greater than a second threshold.

[0096] According to an embodiment of the present disclosure, the i-th average transaction duration may be obtained by adding the i-th transaction durations of a plurality of i-th transaction data and dividing the sum by the number of first transaction data.

[0097] According to an embodiment of the present disclosure, the above method also includes: determining the historical average transaction duration based on historical transaction data generated before the starting moment of the i-th time interval; when it is determined that the ratio of the i-th average transaction duration to the historical average transaction duration is greater than a second threshold, determining that the i-th average transaction duration meets the first preset condition.

[0098] According to an embodiment of the present disclosure, when the starting time of the i-th time interval is t, the historical transaction data generated before the starting time of the i-th time interval may be the historical transaction data generated before time t.

[0099] According to an embodiment of the present disclosure, the historical transaction data generated before the start time of the i-th time interval may be the historical transaction data generated within a preset time period before the start time of the i-th time interval. For example, the historical transaction data generated within one month before the start time of the i-th time interval is obtained.

[0100] The historical average transaction time can be determined by dividing the total transaction time of all historical transaction data by the number of historical transaction data.

[0101] According to an embodiment of the present disclosure, the transaction data also includes a transaction status; before determining that the i-th transaction data is questionable transaction data, it also includes: determining a historical transaction success rate based on historical transaction data generated before the starting moment of the i-th time interval; determining an i-th transaction success rate for the i-th time interval based on the i-th transaction status of each of multiple i-th transaction data; and determining that the i-th transaction data is questionable transaction data when it is determined that the ratio of the i-th transaction success rate to the historical transaction success rate is less than a third threshold.

[0102] According to an embodiment of the present disclosure, the third threshold may be 0.8, for example.

[0103] According to an embodiment of the present disclosure, the transaction status may include transaction success or transaction failure.

[0104] According to an embodiment of the present disclosure, determining the historical transaction success rate may be based on the ratio of the number of historical transaction data with a transaction status of successful transaction in the historical transaction data to the number of all historical transaction data.

[0105] According to an embodiment of the present disclosure, the i-th transaction success rate may be the ratio of the i-th transaction data with a transaction status of successful transaction among multiple i-th transaction data to the total number of i-th transaction data. For example, if the i-th transaction data includes M pieces, then among the M pieces of i-th transaction data, the number of i-th transaction data with a transaction status of successful transaction is m, where m≤M, and the i-th transaction success rate is m / M.

[0106] Figure 4 The flowchart of determining questionable data according to an embodiment of the present disclosure is schematically shown.

[0107] like Figure 4 As shown, this embodiment includes operations S410 to S480.

[0108] In operation S410, an i-th average transaction duration for an i-th time interval is determined according to i-th transaction durations of respective pieces of i-th transaction data.

[0109] In operation S420, a historical average transaction duration is determined based on historical transaction data generated before the start time of the i-th time interval.

[0110] In operation S430, it is determined whether the ratio of the i-th average transaction duration to the historical average transaction duration is greater than a second threshold; if so, operation S440 is executed; if not, operation S480 is executed.

[0111] In operation S440, a historical transaction success rate is determined based on the historical transaction data generated before the start time of the i-th time interval.

[0112] In operation S450, an i-th transaction success rate for an i-th time interval is determined according to i-th transaction states of respective pieces of i-th transaction data.

[0113] In operation S460, it is determined whether the ratio of the i-th transaction success rate to the historical transaction success rate is less than a third threshold value. If so, operation S470 is performed; if not, operation S480 is performed.

[0114] In operation S470, it is determined that the i-th transaction data is questionable transaction data.

[0115] In operation S480, it is determined that the i-th transaction data is normal transaction data.

[0116] According to the embodiments of the present disclosure, by comprehensively judging whether the data is questionable based on the average transaction duration and the transaction success rate, it helps to improve the accuracy of the judgment.

[0117] According to an embodiment of the present disclosure, the target system includes a plurality of system nodes.

[0118] Figure 5 The flowchart of determining a transaction processing score according to an embodiment of the present disclosure is schematically shown.

[0119] like Figure 5 As shown, this embodiment includes operations S510 to S530.

[0120] In operation S510, for a j-th system node among a plurality of system nodes, j-th transaction sub-data corresponding to the j-th system node is determined from the i-th transaction data.

[0121] In operation S520, when it is determined that the jth transaction duration corresponding to the jth transaction sub-data satisfies the first preset condition, the jth node weight of the jth system node is determined according to the historical transaction data for the jth system node generated before the start time of the i-th time interval.

[0122] According to an embodiment of the present disclosure, the above method also includes: when the j-th transaction duration in the j-th transaction sub-data meets the first preset condition, marking the j-th transaction sub-data as abnormal transaction sub-data; determining the j-th node weight of the j-th system node based on the historical transaction data for the j-th system node generated before the starting moment of the i-th time interval includes: when the historical transaction data for the j-th system node generated before the starting moment of the i-th time interval contains abnormal transaction sub-data, determining the j-th node weight of the j-th system node as a first value; when the historical transaction data for the j-th system node generated before the starting moment of the i-th time interval does not contain abnormal transaction sub-data, determining the j-th node weight of the j-th system node as a second value.

[0123] In operation S530, an i-th transaction processing score is determined according to the node weights of the respective system nodes and the system weight of the target system.

[0124] For example, when it is determined that the i-th transaction data is questionable transaction data, the database flag field is set from 0 to 1, and then the weight score, i.e., the transaction processing score, is calculated based on the system level to which the questionable data belongs and the number of times the corresponding node has been marked in history. The system can be divided into three levels: A, B, and C, and the weight scores can be 4, 2, and 1 respectively. The weight scores of the nodes can be 1 (historically marked) and 0 (historically not marked). For example, if the system to which the questionable data belongs is level A and the corresponding node has been marked in history, then the weight score of the questionable data is 4+1=5, i.e., the transaction processing score.

[0125] According to an embodiment of the present disclosure, determining the i-th transaction processing score based on the node weights of each of the multiple system nodes and the system weight of the target system may include: adding the node weights of each of the multiple system nodes and the system weight of the target system to obtain the i-th transaction processing score.

[0126] According to an embodiment of the present disclosure, the above method may further include: after each collection cycle, the system capacity score is sorted in reverse order, and the results are recorded in the memory for further analysis. If doubtful situations occur compared with the time of each historical day, the system is marked as a whitelist.

[0127] According to an embodiment of the present disclosure, when the updated system capacity score meets the first threshold, before expanding the system capacity of the target system, the method further includes:

[0128] A preset whitelist is obtained, and when it is determined that the preset whitelist does not include the target system, the system capacity of the target system is expanded.

[0129] According to an embodiment of the present disclosure, by setting a whitelist, it is possible to avoid the situation where the system capacity score is higher than the first threshold due to special reasons.

[0130] Based on the above system expansion method, the present disclosure also provides a system expansion device. Figure 6 The device is described in detail.

[0131] Figure 6 The structural block diagram of the system expansion device according to an embodiment of the present disclosure is schematically shown.

[0132] like Figure 6 As shown, the system expansion device 600 of this embodiment includes a first acquisition module 610 , a first determination module 620 , an update module 630 and an expansion module 640 .

[0133] The first acquisition module 610 is used to cyclically acquire transaction data generated by the target system in each time interval according to a preset time interval, wherein the transaction data includes transaction duration. In one embodiment, the first acquisition module 610 can be used to perform the operation S210 described above, which will not be described in detail here.

[0134] The first determination module 620 is used to determine, for the i-th time interval in each time interval, if the i-th transaction duration corresponding to the i-th transaction data generated by the target system in the i-th time interval meets the first preset condition, determine the i-th transaction data as questionable transaction data, and determine the i-th transaction processing score for the i-th time interval according to the system weight of the target system, where i is a positive integer. In one embodiment, the first determination module 620 can be used to perform the operation S220 described above, which will not be repeated here.

[0135] The updating module 630 is used to update the system capacity score of the target system according to the i-th transaction processing score to obtain an updated system capacity score, wherein the system capacity score is determined according to the transaction processing scores corresponding to the i-1 time intervals before the start time of the i-th time interval, and the system capacity score represents the system capacity utilization rate of the target system. In one embodiment, the updating module 630 can be used to perform the operation S230 described above, which will not be described in detail here.

[0136] The expansion module 640 is used to expand the system capacity of the target system when the updated system capacity score is greater than or equal to the first threshold. In one embodiment, the expansion module 640 can be used to perform the operation S240 described above, which will not be described in detail here.

[0137] According to an embodiment of the present disclosure, the i-th transaction data includes multiple items.

[0138] According to an embodiment of the present disclosure, the above-mentioned device further includes: a second determination module and a third determination module.

[0139] The second determining module is used to determine the i-th average transaction duration for the i-th time interval according to the i-th transaction durations of each of the plurality of i-th transaction data.

[0140] The third determination module is used to determine the i-th transaction score for the i-th time interval according to the system weight of the target system when the i-th average transaction duration meets the first preset condition.

[0141] According to an embodiment of the present disclosure, the above-mentioned device further includes: a fourth determination module and a fifth determination module.

[0142] The fourth determination module is used to determine the historical average transaction duration based on the historical transaction data generated before the start time of the i-th time interval.

[0143] The fifth determination module is used to determine that the i-th average transaction duration meets the first preset condition when it is determined that the ratio of the i-th average transaction duration to the historical average transaction duration is greater than the second threshold.

[0144] According to an embodiment of the present disclosure, the transaction data also includes a transaction status.

[0145] According to an embodiment of the present disclosure, the above-mentioned device further includes: a sixth determination module, a seventh determination module and an eighth determination module.

[0146] The sixth determination module is used to determine the historical transaction success rate based on the historical transaction data generated before the start time of the i-th time interval.

[0147] The seventh determination module is used to determine the i-th transaction success rate for the i-th time interval according to the i-th transaction status of each of the plurality of i-th transaction data.

[0148] The eighth determination module is used to determine that the i-th transaction data is questionable transaction data when it is determined that the ratio of the i-th transaction success rate to the historical transaction success rate is less than a third threshold.

[0149] According to an embodiment of the present disclosure, the target system includes a plurality of system nodes.

[0150] According to an embodiment of the present disclosure, the first determination module includes: a first determination submodule, a second determination submodule, a third determination submodule and a fourth determination submodule.

[0151] The first determining submodule is used to determine, for a j-th system node among the multiple system nodes, a j-th transaction sub-data corresponding to the j-th system node from the i-th transaction data.

[0152] The second determination submodule is used to determine the jth node weight of the jth system node based on the historical transaction data for the jth system node generated before the starting time of the i-th time interval when it is determined that the j-th transaction duration corresponding to the j-th transaction sub-data satisfies the first preset condition.

[0153] The third determination submodule is used to determine the i-th transaction processing score based on the node weights of the multiple system nodes and the system weight of the target system.

[0154] According to an embodiment of the present disclosure, the above-mentioned device also includes: a marking module.

[0155] The marking module is used to mark the jth transaction sub-data as abnormal transaction sub-data when the jth transaction duration in the jth transaction sub-data meets the first preset condition.

[0156] According to an embodiment of the present disclosure, the second determining submodule includes: a first determining unit and a second determining unit.

[0157] The first determining unit is used to determine that the jth node weight of the jth system node is a first value when the historical transaction data for the jth system node generated before the start time of the i-th time interval contains abnormal transaction sub-data.

[0158] The second determining unit is used to determine that the jth node weight of the jth system node is a second value when the historical transaction data for the jth system node generated before the start time of the i-th time interval does not contain abnormal transaction sub-data.

[0159] According to an embodiment of the present disclosure, the above-mentioned device further includes: an adjustment module and a zeroing processing module.

[0160] The adjustment module is used to adjust the system capacity score of the target system to zero after the system capacity of the target system is expanded.

[0161] The clearing processing module is used to cyclically clear the system capacity score of the target system according to the preset time period, so that the system capacity score of the target system corresponding to the end time of each preset time period is zero.

[0162] According to an embodiment of the present disclosure, the above-mentioned device also includes: a second acquisition module.

[0163] The second acquisition module is used to acquire a preset white list, and expand the system capacity of the target system when it is determined that the preset white list does not include the target system.

[0164] According to an embodiment of the present disclosure, any multiple modules of the first acquisition module 610, the first determination module 620, the update module 630, and the expansion module 640 can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the first acquisition module 610, the first determination module 620, the update module 630, and the expansion module 640 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware, and firmware, or in any appropriate combination of any of them. Alternatively, at least one of the first acquisition module 610, the first determination module 620, the update module 630 and the expansion module 640 may be at least partially implemented as a computer program module, and when the computer program module is executed, a corresponding function may be executed.

[0165] Figure 7 A block diagram of an electronic device suitable for implementing the above method according to an embodiment of the present disclosure is schematically shown.

[0166] like Figure 7 As shown, the electronic device 700 according to an embodiment of the present disclosure includes a processor 701, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 702 or a program loaded from a storage part 708 to a random access memory (RAM) 703. The processor 701 may include, for example, a general-purpose microprocessor (such as a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (for example, an application-specific integrated circuit (ASIC)), etc. The processor 701 may also include an onboard memory for caching purposes. The processor 701 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0167] In RAM 703, various programs and data required for the operation of electronic device 700 are stored. Processor 701, ROM 702 and RAM 703 are connected to each other via bus 704. Processor 701 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 702 and / or RAM 703. It should be noted that the program can also be stored in one or more memories other than ROM 702 and RAM 703. Processor 701 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in the one or more memories.

[0168] According to an embodiment of the present disclosure, the electronic device 700 may further include an input / output (I / O) interface 705, which is also connected to the bus 704. The electronic device 700 may further include one or more of the following components connected to the input / output (I / O) interface 705: an input portion 706 including a keyboard, a mouse, etc.; an output portion 707 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 708 including a hard disk, etc.; and a communication portion 709 including a network interface card such as a LAN card, a modem, etc. The communication portion 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the input / output (I / O) interface 705 as needed. A removable medium 711, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 710 as needed, so that a computer program read therefrom is installed into the storage portion 708 as needed.

[0169] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0170] According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, it may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus or a device. For example, according to an embodiment of the present disclosure, the computer-readable storage medium may include the ROM 702 and / or RAM 703 described above and / or one or more memories other than ROM 702 and RAM 703.

[0171] The embodiment of the present disclosure also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the method provided by the embodiment of the present disclosure.

[0172] The above functions defined in the system / device of the embodiment of the present disclosure are performed when the computer program is executed by the processor 701. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0173] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 709, and / or installed from the removable medium 711. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0174] In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 709, and / or installed from the removable medium 711. When the computer program is executed by the processor 701, the above functions defined in the system of the embodiment of the present disclosure are performed. According to the embodiment of the present disclosure, the system, device, means, module, unit, etc. described above can be implemented by a computer program module.

[0175] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0176] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0177] It will be appreciated by those skilled in the art that the features described in the various embodiments of the present disclosure may be combined and / or combined in a variety of ways, even if such combinations or combinations are not explicitly described in the present disclosure. In particular, without departing from the spirit and teachings of the present disclosure, the features described in the various embodiments of the present disclosure may be combined and / or combined in a variety of ways. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0178] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A system expansion method, comprising: According to the preset time intervals, cyclically obtain the transaction data generated by the target system in each time interval, wherein the transaction data includes the transaction duration; For an i-th time interval in each time interval, if an i-th transaction duration corresponding to an i-th transaction data generated by the target system in the i-th time interval satisfies a first preset condition, the i-th transaction data is determined to be questionable transaction data, and an i-th transaction processing score for the i-th time interval is determined according to the system weight of the target system, where i is a positive integer; updating the system capacity score of the target system according to the i-th transaction processing score to obtain an updated system capacity score, wherein the system capacity score is determined according to the transaction processing scores corresponding to each of i-1 time intervals before the start time of the i-th time interval, and the system capacity score represents the system capacity utilization rate of the target system; and When the updated system capacity score is greater than or equal to the first threshold, the system capacity of the target system is expanded.

2. The method according to claim 1, wherein: The i-th transaction data includes a plurality of items; The method further comprises: Determine, according to the i-th transaction durations of the plurality of i-th transaction data, the i-th average transaction duration for the i-th time interval; When the i-th average transaction duration satisfies the first preset condition, an i-th transaction score for the i-th time interval is determined according to the system weight of the target system.

3. The method according to claim 2, further comprising: Determine the historical average transaction duration based on the historical transaction data generated before the start time of the i-th time interval; When it is determined that the ratio of the i-th average transaction duration to the historical average transaction duration is greater than a second threshold, it is determined that the i-th average transaction duration satisfies the first preset condition.

4. The method according to claim 2, wherein: The transaction data also includes transaction status; Before determining that the i-th transaction data is questionable transaction data, the method further includes: Determining a historical transaction success rate based on historical transaction data generated before the start time of the i-th time interval; determining an i-th transaction success rate for an i-th time interval according to an i-th transaction status of each of the plurality of i-th transaction data; When it is determined that the ratio of the i-th transaction success rate to the historical transaction success rate is less than a third threshold, it is determined that the i-th transaction data is questionable transaction data.

5. The method according to claim 1, wherein: The target system includes a plurality of system nodes; wherein determining the i-th transaction score for the i-th time interval according to the system weight of the target system includes: For a j-th system node among the plurality of system nodes, determining j-th transaction sub-data corresponding to the j-th system node from the i-th transaction data; When it is determined that the jth transaction duration corresponding to the jth transaction sub-data satisfies the first preset condition, determining a jth node weight of the jth system node according to historical transaction data for the jth system node generated before the start time of the i-th time interval; The i-th transaction processing score is determined according to the node weights of each of the plurality of system nodes and the system weight of the target system.

6. The method according to claim 5, further comprising: When the j-th transaction duration in the j-th transaction sub-data satisfies the first preset condition, marking the j-th transaction sub-data as abnormal transaction sub-data; Determining the jth node weight of the jth system node according to the historical transaction data for the jth system node generated before the start time of the i-th time interval includes: In a case where it is determined that the historical transaction data for the j-th system node generated before the start time of the i-th time interval contains abnormal transaction sub-data, determining the j-th node weight of the j-th system node to be a first value; When it is determined that the historical transaction data for the j-th system node generated before the start time of the i-th time interval does not include abnormal transaction sub-data, the j-th node weight of the j-th system node is determined to be a second value.

7. The method according to claim 1, further comprising: After expanding the system capacity of the target system, adjusting the system capacity score of the target system to zero; or; According to the preset time period, the system capacity score of the target system is cyclically cleared to zero, so that the system capacity score of the target system corresponding to the end time of each preset time period is zero.

8. The method according to claim 1, wherein: When the updated system capacity score meets the first threshold, before expanding the system capacity of the target system, the method further includes: A preset whitelist is obtained, and when it is determined that the preset whitelist does not include the target system, the system capacity of the target system is expanded.

9. A system expansion device, comprising: A first acquisition module, configured to cyclically acquire transaction data generated by the target system in each time interval according to a preset time interval, wherein the transaction data includes transaction duration; a first determining module, configured to determine, for an i-th time interval in each time interval, if an i-th transaction duration corresponding to an i-th transaction data generated by the target system in the i-th time interval satisfies a first preset condition, determine that the i-th transaction data is questionable transaction data, and determine an i-th transaction processing score for the i-th time interval according to a system weight of the target system, where i is a positive integer; an updating module, configured to update a system capacity score of the target system according to the i-th transaction processing score to obtain an updated system capacity score, wherein the system capacity score is determined according to transaction processing scores corresponding to each of i-1 time intervals before the start time of the i-th time interval, and the system capacity score represents a system capacity utilization rate of the target system; and The capacity expansion module is used to expand the system capacity of the target system when the updated system capacity score is greater than or equal to a first threshold.

10. An electronic device, comprising: one or more processors; a memory for storing one or more computer programs, It is characterized in that the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1 to 8.

11. A computer-readable storage medium having a computer program or instruction stored thereon, characterized in that: When the computer program or instruction is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

12. A computer program product comprising a computer program or instructions, characterized in that When the computer program or instruction is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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