CN114338360A - Live list service processing method and system, electronic device and storage medium - Google Patents
Live list service processing method and system, electronic device and storage medium Download PDFInfo
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Abstract
The embodiment of the application discloses a live list service processing method, a live list service processing system, electronic equipment and a storage medium. According to the technical scheme provided by the embodiment of the application, the list request processing success rate of the main service node is calculated by responding to the list request sent by the user side; comparing the processing success rate of the list request with a set threshold value to obtain a corresponding comparison result, wherein the set threshold value is used for evaluating the service performance of the current main service node; and sending the list request to the main service node or the standby service node according to the comparison result so as to pull the live broadcast list and return the live broadcast list to the user side. By adopting the technical means, the main service node and the standby service node are adaptively selected to process the list request according to the list request processing success rate of the main service node, so that the stability of live list service processing can be ensured, the condition that the list is refreshed slowly due to repeated switching of the processing nodes is avoided, the processing efficiency of list service is improved, and the use experience of a user is optimized.
Description
Technical Field
The embodiment of the application relates to the technical field of data processing, in particular to a live list service processing method and system, electronic equipment and a storage medium.
Background
Currently, when a user uses live broadcast software, a home page recommends a personalized live broadcast list according to the characteristics of the user. Live listings require constant iteration and frequent changes, so the quality of service of the listings directly impacts the user experience. At present, in order to ensure the stability of the listing service, when a main service node processing a live list request has abnormal conditions such as reply timeout, error codes and the like, the listing service node will smoothly transit the live list request to a standby service node for processing, so as to pull live list information from the standby service node and return the live list information to a corresponding user terminal, thereby providing a stable and reliable listing service.
However, in the existing live list service processing method, under the condition of network fluctuation, service nodes requested by a live list are frequently switched, the processing efficiency of the live list request and the continuity of the content of the live list are affected, the live list at a user terminal is slowly refreshed, and the use experience of a user is further affected.
Disclosure of Invention
The embodiment of the application provides a live list service processing method, a live list service processing system, electronic equipment and a storage medium, which can improve the stability and processing efficiency of live list service processing and solve the technical problem that the live list request processing is low in efficiency due to frequent switching of processing nodes in the existing live list service processing.
In a first aspect, an embodiment of the present application provides a live list service processing method, including:
responding to a list request sent by a user side, and calculating the list request processing success rate of a main service node;
comparing the processing success rate of the list request with a set threshold value to obtain a corresponding comparison result, wherein the set threshold value is used for evaluating the service performance of the current main service node;
and sending the list request to the main service node or the standby service node according to the comparison result so as to pull the live broadcast list and return the live broadcast list to the user side.
In a second aspect, an embodiment of the present application provides a live list service processing system, including:
the computing module is used for responding to the list request sent by the user side and computing the list request processing success rate of the main service node;
the comparison module is used for comparing the processing success rate of the list request with a set threshold value to obtain a corresponding comparison result, and the set threshold value is used for evaluating the service performance of the current main service node;
and the sending module is used for sending the list request to the main service node or the standby service node according to the comparison result so as to pull the live broadcast list and return the live broadcast list to the user side.
In a third aspect, an embodiment of the present application provides an electronic device, including:
a memory and one or more processors;
the memory for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement a live list service processing method as described in the first aspect.
In a fourth aspect, embodiments of the present application provide a storage medium containing computer-executable instructions for performing the live list service processing method according to the first aspect when executed by a computer processor.
The method and the device for processing the list request of the main service node calculate the list request processing success rate of the main service node by responding to the list request sent by the user side; comparing the processing success rate of the list request with a set threshold value to obtain a corresponding comparison result, wherein the set threshold value is used for evaluating the service performance of the current main service node; and sending the list request to the main service node or the standby service node according to the comparison result so as to pull the live broadcast list and return the live broadcast list to the user side. By adopting the technical means, the main service node and the standby service node are adaptively selected to process the list request according to the list request processing success rate of the main service node, so that the stability of live list service processing can be ensured, the condition that the list is refreshed slowly due to repeated switching of the processing nodes is avoided, the processing efficiency of list service is improved, and the use experience of a user is optimized.
Drawings
Fig. 1 is a flowchart of a live list service processing method provided in an embodiment of the present application;
fig. 2 is a schematic diagram of a list service node connection provided in an embodiment of the present application;
FIG. 3 is a flowchart illustrating the calculation of the success rate of processing a list request in an embodiment of the present application;
FIG. 4 is a flow chart of the processing of a list request in an embodiment of the present application;
FIG. 5 is a flow chart of processing node selection for a list request in an embodiment of the present application;
fig. 6 is a schematic structural diagram of a live list service processing system according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, specific embodiments of the present application will be described in detail with reference to the accompanying drawings. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be further noted that, for the convenience of description, only some but not all of the relevant portions of the present application are shown in the drawings. Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations (or steps) as a sequential process, many of the operations can be performed in parallel, concurrently or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.
The live list processing method aims to adaptively select the processing node of the current list request by calculating the list request processing success rate of the main service node, improve the stability of live list service processing, improve the live list refreshing efficiency of a user side and optimize the user experience. Compared with the traditional list service processing mode, the method has the advantages that the list request is forwarded to the standby service node to request the live broadcast list under the condition that the live broadcast list is overtime to the main service node every time, so that the method is easily influenced by network fluctuation, and the standby service node and the main service node are frequently switched back and forth to send the service request under the condition that the network is unstable. When the main service node is completely abnormal, the list request processing logic still requests the main service node first, and the degradation logic is removed after the time is out, so that the live broadcast list is requested from the standby service node, system processing resources are wasted, the time consumption of list service is increased, and the list refreshing efficiency is influenced. On the other hand, the live broadcast list supports paging pulling and has personalized recommendation logic, so each list request needs to select a processing node according to the context information of the live broadcast list, and if the live broadcast list is directly requested from the main service node each time, the content sequence of the original live broadcast list is disturbed, and the personalized recommendation strategy is disturbed. Based on this, a live list service processing method in the embodiment of the application is provided to solve the technical problem that the processing of a live list request is low in efficiency due to frequent switching of processing nodes in the existing live list service processing.
Example (b):
fig. 1 is a flowchart of a live listing service processing method provided in an embodiment of the present application, where the live listing service processing method provided in this embodiment may be executed by a live listing service processing device, the live listing service processing device may be implemented in a software and/or hardware manner, and the live listing service processing device may be formed by two or more physical entities or may be formed by one physical entity. In general, the live listing service processing device may be a computing device such as a listing service node for distribution listing requests in a live listing service scenario.
The following description will be given by taking the list service node as an example of a main body for executing the live list service processing method. Referring to fig. 1, the live list service processing method specifically includes:
s110, responding to the list request sent by the user side, and calculating the list request processing success rate of the main service node.
When the list service is processed, the availability of the list service of the main service node is evaluated by determining the real-time list request processing success rate of the main service node. And then, according to the evaluation result, adaptively selecting a main service node or a standby service node to send a list request, pulling a live broadcast list and returning the live broadcast list to the user side. Whether service degradation logic is triggered is judged by evaluating service node list service availability, and a standby service node is selected to pull a live broadcast list so as to ensure timely processing of list requests and optimize use experience of users.
Specifically, referring to fig. 2, a connection diagram of a list service node according to an embodiment of the present application is provided. As shown in fig. 2, a list service cluster is provided to distributively process the list request distribution traffic of different user terminals. By adopting a distributed processing mode, the disaster tolerance capability of the list service and the list request processing efficiency can be improved. Each list service node 12 of the list service cluster is connected to the main service node 13 and the standby service node 14, respectively, and is configured to transmit a list request and receive corresponding loopback information. The list request generated by the user terminal 11 is uploaded to the corresponding list service node 12 (e.g., the list service node closest to the user terminal), and then the list service node 12 selects the main service node 13 or the standby service node 14 based on the live list service processing method of the embodiment of the present application to transmit the list request, so as to obtain the live list from the corresponding processing node and return the live list to the user terminal 11.
When a user side uses the live broadcast application and refreshes a page, a list request is sent to a corresponding list service node based on the page refreshing operation, after the list service node receives the list service request, the availability of the current list service of the main service node is judged, and the main service node or the standby service node is adaptively selected according to the judgment result to send the list request.
After the list service node receives the list request, the list service node firstly determines the list request processing success rate of the current main service node in response to the list request. And judging the service availability of the main service node according to the list request processing success rate by calculating the list request processing success rate of the main service node. Referring to fig. 3, the calculation flow of the list request processing success rate includes:
s1101, determining local success rate of pulling a live broadcast list from a main service node by the self and other list service nodes in the list service cluster in a specified time period;
s1102, a list request processing success rate is calculated based on the local success rate.
Specifically, when calculating the list request processing success rate, first, a local success rate of pulling the live broadcast list from each list service node in the list service cluster to the main service node is determined. And collecting local success rates of the current list service node processing the list request and other list service nodes in the cluster through the list service node processing the list request, and calculating the list request processing success rate.
Optionally, the local success rate is calculated according to the number of the list requests and the number of the request successes by obtaining the number of the list requests and the number of the request successes of each sub-period in the specified period. For each list service node in the embodiment of the application, a time sliding window with second-level precision is maintained, and the list request quantity and the request success quantity of each sub-period in a specified period are counted by using the time sliding window.
For example, to obtain the number of list requests and the number of request successes per second in the past minute, assuming that the number of list requests per second is St and the number of request successes is Ct, the local success rate R of the last minute is obtainedlI.e., the sum of the number of most recent sixty second request successes divided by the sum of the number of most recent sixty second list requests. The local success rate calculation formula is as follows:
further, according to local success rates of the self and other list service nodes, the average success rate of the list service cluster for pulling the live broadcast list to the main service node is determined; and calculating the list request processing success rate based on the local success rate and the average success rate of the list request processing success rate and the corresponding influence weight coefficient.
It can be understood that, in order to avoid the influence of single-node data contingency, the embodiment of the present application services the number n of nodes according to the list participating in the calculation and the local success rate R of each list service nodelAnd obtaining the average success rate R of the cluster by averagingaThe following were used:
based on the average success rate, the availability of the current main service node can be represented. The average success rate of the cluster is recorded according to different service states of the corresponding main service node, so that a corresponding set threshold value can be obtained, and the service availability of the current main service node can be determined by comparing the average success rate with the set threshold value.
Preferably, considering that the local success rate of the list service node currently processing the service request and the average success rate of the whole service cluster are associated with the service availability of the main service node, in order to accurately determine the list request processing success rate of the main service node, the present application synthesizes the local success rate of the current list service node and the average success rate of the cluster, introduces a weight coefficient α representing the influence of the average success rate of the cluster on the list request processing success rate of the main service node, and finally calculates the list request processing success rate Rt of the main service node at the current time as follows:
and substituting the local success rate of the current list service node and the average success rate of the cluster into the formula so as to obtain the list request processing success rate of the current list service node.
In practical application, the weight coefficient is adaptively set according to the cluster average success rate or the association condition of the local success rate of the current service node to the list request processing success rate Rt, so as to ensure that the finally determined list request processing success rate Rt can intuitively reflect the service availability of the current main service node.
And S120, comparing the list request processing success rate with a set threshold to obtain a corresponding comparison result, wherein the set threshold is used for evaluating the service performance of the current main service node.
And comparing the processing success rate with a set threshold value according to the list request processing success rate of the current main service node, and determining the service availability of the current main service node. And the comparison result is used for selecting the processing node of the subsequent list request. It can be understood that, in the embodiment of the present application, the list request processing success rate of the main service node in different service states is determined in advance according to an actual test, so as to construct a corresponding set threshold, that is, the set threshold can be used to determine the list service availability of the current main service node.
Optionally, the set threshold includes a first threshold and a second threshold, and the second threshold is greater than the first threshold. Wherein the first threshold value PMinA minimum value representing a list request processing success rate at which the main service node can normally process the list request, and a second threshold value PMaxAnd identifying the minimum value of the list request processing success rate when the service performance of the current main service node is excellent. And determining the service performance of the current main service node by judging the size relationship between the current list request processing success rate and the first threshold and the second threshold.
Wherein, if the current list request processing success rate Rt is less than the first threshold PMinIndicating that the current master service node is completely unavailable and cannot process the list request; if it is determined that the current list request processing success rate Rt is greater than or equal to the first threshold value PMinIs less than a second threshold value PMaxIndicating that the current primary service node is partially available, a list request handling exception may occur. If the current list request processing success rate Rt is determined to be greater than the second threshold value PMaxAnd determining that the service performance of the current main service node is better, and directly processing the list request by the main service node without executing service degradation logic.
And S130, sending the list request to the main service node or the standby service node according to the comparison result so as to pull the live broadcast list and return the live broadcast list to the user side.
According to the comparison result, the main service node is adaptively selected or the slave service node sends the list request, and then the live broadcast list is pulled, so that the processing efficiency of the list request is improved. When the list request is sent to the main service node or the standby service node according to the comparison result, the list request is sent to the standby service node according to the comparison result under the condition that the processing success rate of the list request is smaller than a first threshold value; when the processing success rate of the list request is greater than or equal to a first threshold value and smaller than a second threshold value, the list request is sent to a main service node, and when the main service node is determined to be abnormal, the list request is sent to a standby service node; and sending the list request to the main service node under the condition that the processing success rate of the list request is greater than or equal to a second threshold value.
In the embodiment of the application, after a list request of a user side reaches a list service node each time, a sliding window of a request number and a failure number is maintained in a local memory, so that when a main service node repacks, a numerical value corresponding to the sliding window is updated according to repackaging information (such as a live broadcast list or overtime and error code information) returned by the main service node, and a local success rate Rl of a certain period of time (such as the latest minute) is calculated. And then requests a calculation mode of the processing success rate with reference to the list. When the next list request reaches the list service node, the success rate Rt and the first threshold value P are processed according to the list requestMinAnd a second threshold value PMaxAnd determining the processing node of the current list request.
Wherein when Rt is<PMinAnd then, the representative policy main service is completely unavailable, and the list request is sent to the standby service node at the moment so as to ensure the normal processing of the list request and enable the user side to refresh the list normally. And meanwhile, carrying out asynchronous detection on the main service node to determine the service state of the main service node. Updating the service state of a primary service node in real time by enabling processing logic that asynchronously probes the primary service node to facilitateWhen the service of the main service node is determined to be available, switching back to the main service node to process the list request in time; when in usePMin≤Rt<PMaxWhen the representative main service node part is available, the list request is firstly distributed to the main service node for processing, and if the main service node has abnormal conditions such as packet return overtime, error code reporting and the like, the live broadcast list is requested from the standby service node; when Rt ≧ PMaxAnd meanwhile, the availability of the representative main service node is good, and the list request is directly sent to the main service node for processing without the need of performing the degradation logic of the list service.
When the processing success rate of the list request is the first threshold value, the list request is directly sent to the standby service node, so that invalid list requests and processing time consumption can be reduced, and the processing efficiency of the list requests is improved. Meanwhile, the asynchronous detection is carried out on the main service node, so that the service state recovery condition of the main service node can be sensed quickly, and the self-healing management effect of the service is realized.
Illustratively, referring to fig. 4, in a scenario where the user side uses live application software, when the live list is refreshed by operating on the live list interface, the user side generates a list request 1 and sends it to a corresponding list service node of the list service cluster. At this time, the list service node determines the list request processing success rate of the current main service node, determines that the list request processing success rate is greater than a preset first threshold value, indicates that the current main service node is available, and sends the list request to the main service node for processing. If the processing success rate of the list request is smaller than the second threshold value, it indicates that the main service node is in a partially available state, and if the return packet of the main service node is overtime or has an error code, it needs to execute the degradation logic of the current live list service. After receiving the back packet of the main service node, the back packet is forwarded to the user side so as to load the live broadcast list 1 at the user side. Further, when the user refreshes the page again, list request 2 is uploaded to the list service node. At this time, the list service node determines the list request processing success rate of the current main service node, determines that the current main service node is unavailable if the list request processing success rate is smaller than a first threshold value, forwards the list request to a standby service node for processing, receives a return packet of the standby service node, and loads a live broadcast list 2 to a user side.
The main service node or the standby service node is dynamically and smoothly adjusted and accessed by calculating the list request processing success rate and strategy main and standby service nodes, so that the problem of frequent switching of processing nodes caused by network fluctuation is solved.
In one embodiment, referring to fig. 5, the list service node further selects a processing node for the current list request by determining a processing node for processing the user side list request last time, so as to ensure the continuity of the contents of the live list. Determining a processing node for processing a list request on a user terminal as a standby service node; and judging whether the current list request is a first request for refreshing the live page list, and if not, sending the current list request to the standby service node.
It can be understood that, because the live list has a paging logic, if the context content of the list is ignored, the live list is pulled only according to the availability of the current main service node and standby service node, and there may be problems of duplication, disorder of sequence, etc. for the content displayed on the user side. Especially in the case of network jitter, if the pulled list content is switched back and forth, the user experience is greatly affected. Therefore, the processing node of the current list request needs to be selected according to the processing node of the last list request of the user terminal.
The source information of the last list request can be carried in the user list request and the return packet, so that the list service node can determine the processing node of the last list request of the last user end according to the source mark. If the processing node of the last list request is the main service node, the list request is processed by referring to the list service processing method described above with reference to fig. 1. If the processing node of the last list request is the standby node, further judging whether the current list request is a first request for refreshing the live page list, if the user side is determined to be the first page refresh, the problem of continuity of context content of the list does not need to be considered, and at this time, referring to the list service processing method described in the figure 1 to process the list request, and selecting corresponding main and standby service nodes to process the current list request. When the user side is determined not to refresh the page for the first time, because the processing node processing the user side list request for the last time is the standby service node, in order to guarantee the continuity of the list contents and avoid interfering with the personalized recommendation logic, the list request is still sent to the standby service node to obtain the context-associated list contents and returns the context-associated list contents to the user side for refreshing. Therefore, the list request carries the source mark of the processing node which processes the user side list request last time, the processing node which processes the user side list request last time is a standby service node, and when the user side does not refresh the page for the first time, the current list request is selected to be sent to the standby service node, so that the paging logic and content continuity of the live broadcast list can be guaranteed, the recommendation strategy of the live broadcast list is not interfered, and the use experience of a user is optimized.
Calculating the list request processing success rate of the main service node by responding to the list request sent by the user side; comparing the processing success rate of the list request with a set threshold value to obtain a corresponding comparison result, wherein the set threshold value is used for evaluating the service performance of the current main service node; and sending the list request to the main service node or the standby service node according to the comparison result so as to pull the live broadcast list and return the live broadcast list to the user side. By adopting the technical means, the main service node and the standby service node are adaptively selected to process the list request according to the list request processing success rate of the main service node, so that the stability of live list service processing can be ensured, the condition that the list is refreshed slowly due to repeated switching of the processing nodes is avoided, the processing efficiency of list service is improved, and the use experience of a user is optimized.
Based on the foregoing embodiment, fig. 6 is a schematic structural diagram of a live list service processing system provided in the present application. Referring to fig. 6, the live list service processing system provided in this embodiment specifically includes: a calculation module 31, a comparison module 32 and a sending module 33.
The calculation module 31 is configured to calculate a list request processing success rate of the main service node in response to a list request sent by a user side;
the comparison module 32 is configured to compare the list request processing success rate with a set threshold to obtain a corresponding comparison result, where the set threshold is used to evaluate the service performance of the current main service node;
the sending module 33 is configured to send the list request to the main service node or the standby service node according to the comparison result, so as to pull the live broadcast list and return the live broadcast list to the user side.
The calculation module 31 is specifically configured to determine a local success rate of pulling the live broadcast list from the main service node to the self and other list service nodes in the list service cluster within a specified time period; the list request processing success rate is calculated based on the local success rate.
Optionally, the local success rate is calculated according to the number of the list requests and the number of the request successes by obtaining the number of the list requests and the number of the request successes of each sub-period in the specified period.
Determining the average success rate of the list service cluster for pulling the live broadcast list to the main service node according to the local success rates of the list service cluster and other list service nodes; and calculating the list request processing success rate based on the local success rate and the average success rate of the list request processing success rate and the corresponding influence weight coefficient.
Specifically, the set threshold includes a first threshold and a second threshold, and the second threshold is greater than the first threshold; the sending module 33 is configured to send the list request to the standby service node when the processing success rate of the list request is smaller than the first threshold; carrying out asynchronous detection on the main service node to determine the service state of the main service node; when the processing success rate of the list request is greater than or equal to a first threshold value and smaller than a second threshold value, the list request is sent to a main service node, and when the main service node is determined to be abnormal, the list request is sent to a standby service node; and sending the list request to the main service node under the condition that the processing success rate of the list request is greater than or equal to a second threshold value.
Specifically, the live list service processing system is further configured to determine that a processing node that processes a list request on the user side is a standby service node; and judging whether the current list request is a first request for refreshing the live page list, and if not, sending the current list request to the standby service node.
Calculating the list request processing success rate of the main service node by responding to the list request sent by the user side; comparing the processing success rate of the list request with a set threshold value to obtain a corresponding comparison result, wherein the set threshold value is used for evaluating the service performance of the current main service node; and sending the list request to the main service node or the standby service node according to the comparison result so as to pull the live broadcast list and return the live broadcast list to the user side. By adopting the technical means, the main service node and the standby service node are adaptively selected to process the list request according to the list request processing success rate of the main service node, so that the stability of live list service processing can be ensured, the condition that the list is refreshed slowly due to repeated switching of the processing nodes is avoided, the processing efficiency of list service is improved, and the use experience of a user is optimized.
The live list service processing system provided by the embodiment of the application can be used for executing the live list service processing method provided by the embodiment, and has corresponding functions and beneficial effects.
On the basis of the above practical example, an embodiment of the present application further provides an electronic device, with reference to fig. 7, the electronic device includes: a processor 31, a memory 32, a communication module 33, an input device 34, and an output device 35. The memory 32 is a computer-readable storage medium, and can be used to store software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the live listing service processing method described in any embodiment of the present application (for example, a computing module, an comparing module, and a sending module in a live listing service processing system). The communication module 33 is used for data transmission. The processor executes various functional applications and data processing of the device by running software programs, instructions and modules stored in the memory, that is, the live list service processing method is realized. The input device 34 may be used to receive entered numeric or character information and to generate key signal inputs relating to user settings and function controls of the apparatus. The output device 35 may include a display device such as a display screen. The electronic equipment provided by the embodiment can be used for executing the live list service processing method provided by the embodiment, and has corresponding functions and beneficial effects.
On the basis of the above embodiments, the present application also provides a storage medium containing computer executable instructions for performing a live listing service processing method when executed by a computer processor, and the storage medium may be any of various types of memory devices or storage devices. Of course, the storage medium containing the computer-executable instructions provided in the embodiments of the present application is not limited to the live list service processing method described above, and may also perform related operations in the live list service processing method provided in any embodiments of the present application.
The foregoing is considered as illustrative of the preferred embodiments of the invention and the technical principles employed. The present application is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present application has been described in more detail with reference to the above embodiments, the present application is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present application, and the scope of the present application is determined by the scope of the claims.
Claims (10)
1. A live list service processing method is characterized by comprising the following steps:
responding to a list request sent by a user side, and calculating the list request processing success rate of a main service node;
comparing the list request processing success rate with a set threshold value to obtain a corresponding comparison result, wherein the set threshold value is used for evaluating the service performance of the current main service node;
and sending the list request to the main service node or the standby service node according to the comparison result so as to pull a live broadcast list and return the live broadcast list to the user side.
2. The live list service processing method according to claim 1, wherein the set threshold includes a first threshold and a second threshold, and the second threshold is greater than the first threshold;
correspondingly, the sending the list request to the main service node or the standby service node according to the comparison result includes:
sending the list request to the standby service node when the processing success rate of the list request is smaller than the first threshold;
when the processing success rate of the list request is greater than or equal to the first threshold and smaller than the second threshold, sending the list request to the main service node, and when the main service node is determined to be abnormal, sending the list request to the standby service node;
and sending the list request to the main service node when the list request processing success rate is greater than or equal to the second threshold.
3. The live listing service processing method of claim 2, further comprising, after sending the listing request to the standby service node:
and carrying out asynchronous detection on the main service node, and determining the service state of the main service node.
4. The live listing service processing method according to claim 1, further comprising:
determining a processing node for processing one list request on the user terminal as a standby service node;
and judging whether the current list request is a first request for refreshing a page live broadcast list, and if not, sending the current list request to the standby service node.
5. The live list service processing method of claim 1, wherein the calculating a list request processing success rate of the master service node comprises:
determining local success rate of pulling a live broadcast list from the main service node by the self and other list service nodes in the list service cluster in a specified time period;
and calculating the list request processing success rate based on the local success rate.
6. The live list service processing method according to claim 5, wherein the calculating of the local success rate includes:
and acquiring the list request quantity and the request success quantity of each sub-period in the specified period, and calculating the local success rate according to the list request quantity and the request success quantity.
7. The live listing service processing method of claim 5, wherein said calculating said listing request processing success rate based on said local success rate comprises:
determining the average success rate of the list service cluster for pulling the live broadcast list to the main service node according to the local success rates of the list service cluster and the other list service nodes;
and calculating the list request processing success rate based on the local success rate, the average success rate and the corresponding influence weight coefficient.
8. A live listing service processing system, comprising:
the computing module is used for responding to the list request sent by the user side and computing the list request processing success rate of the main service node;
the comparison module is used for comparing the list request processing success rate with a set threshold value to obtain a corresponding comparison result, wherein the set threshold value is used for evaluating the service performance of the current main service node;
and the sending module is used for sending the list request to the main service node or the standby service node according to the comparison result so as to pull a live broadcast list and return the live broadcast list to the user side.
9. An electronic device, comprising:
a memory and one or more processors;
the memory for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement a live listing service processing method as recited in any of claims 1-7.
10. A storage medium containing computer-executable instructions, which when executed by a computer processor, are operable to perform a live listing service processing method as claimed in any one of claims 1 to 7.
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