Technical system and method for obtaining required automobile information in advance through one key

Abstract

The invention belongs to the technical field of data transmission, and discloses a technical system and method for obtaining required automobile information in advance through one key, and the system comprises an App, a service module and a cache module. The service module is composed of online service and offline scheduling; and the cache module is composed of a Redis unit, an Apoll unit and a Memory unit. According to the method, through an intelligent search prefetching strategy, the search main flow is kept not to be increased in the peak period, and system overload is effectively prevented; meanwhile, the prefetch flow is remarkably increased in the low peak period, the search rendering speed of the client is remarkably improved, the peak clipping and valley leveling effect is achieved, and the user experience is improved; according to the method, the fusing signal is set based on the health state of the searched main path service, abnormal conditions are sensed and dealt with in time, flow pressure possibly caused by offline data calculation errors is effectively prevented, the avalanche effect of upstream and downstream services is avoided, and stable operation of the system is guaranteed.

Description

Technical Field

[0001] The present invention belongs to the technical field of data transmission, and specifically relates to a system and method for pre-acquiring required automobile information technology with one click. Background Art

[0002] Currently, in the field of automobile information search, especially for platforms like "Zhijia" that focus on vertical search, the search pre-fetching function is still imperfect or missing. This means that before the user searches, the system fails to prepare possible high-frequency search results in advance, resulting in the user having to wait for the server to process after initiating the search request, which increases the search response time; the search traffic has obvious peak and trough characteristics, that is, the search volume will vary significantly in different time periods. Usually, during specific peak periods, the search volume will increase dramatically, resulting in increased server load and longer search response time; during off-peak periods, the search volume is relatively small and server resources are relatively idle; based on the above user behavior analysis, the present invention proposes a method for optimizing search performance through a pre-fetching strategy. Summary of the invention

[0003] The purpose of the present invention is to provide a system and method for pre-acquiring required automotive information technology with one click, so as to solve the problems raised in the above-mentioned background technology.

[0004] In order to achieve the above-mentioned purpose, the present invention provides the following technical solutions: a system and method for pre-acquiring required automotive information technology with one click, including an App, a service module and a cache module;

[0005] The service module is composed of online service and offline scheduling;

[0006] The cache module is composed of a Redis unit, an Apollo unit and a Memory unit.

[0007] Preferably, the online service controls whether to perform search pre-fetching through a gateway service, and determines whether to start the pre-fetching process according to the state of the pre-fetching switch configured in apollo.

[0008] Preferably, the online service ensures that the main search traffic does not increase during peak hours, and effectively utilizes resources for pre-fetching during off-peak hours by configuring parameters such as the comprehensive search peak qps of a single container, the comprehensive search pre-fetching upper limit per second, and using a token bucket algorithm.

[0009] Preferably, the online service sets an automatic fuse mechanism to prevent traffic pressure caused by offline data calculation errors; when an abnormal situation is detected, the fuse signal will be written to redis through the offline script, and the gateway service will turn off the pre-fetch function after sensing the fuse signal.

[0010] Preferably, the offline scheduling configures the search main path service that needs to be monitored through the monitoring service, sets the fuse thresholds of CPU usage, memory usage, and storage usage, and the offline scheduling sets a fuse signal according to the monitoring results when the service exceeds the preset threshold.

[0011] Preferably, the offline scheduling obtains a list of all pods under different services and monitors their resource usage, and determines whether the offline scheduling is in an abnormal situation according to the monitored resource usage.

[0012] Preferably, the abnormal situation of the offline scheduling will alarm through email, SMS, etc., and the fuse signal will be automatically closed after the service returns to a healthy state.

[0013] Preferably, the technical method comprises the following steps:

[0014] S1. Gateway service control: First, the system determines whether to perform a search pre-fetch operation through the gateway service.

[0015] S2. Pre-fetch switch check: The gateway service checks the status of the pre-fetch switch (the switch is configured in the Apollo system and is named presearch_switch) to determine whether search pre-fetching is allowed.

[0016] S3. Resource flow limiting and fuse checking: The system will then perform a resource flow limiting check, using the Apollo-configured single container search peak QPS (limit_qps), the upper limit of comprehensive search pre-fetching per second, and other parameters, as well as the automatic fuse signal in Redis (presearch_qps_threshold) to determine whether the current situation is suitable for pre-fetching operations. If the flow limiting threshold is reached or the fuse signal is triggered, no pre-fetching will be performed; at the same time, the system will also monitor the health status of the main search channel service, including CPU usage, memory usage, storage usage, etc. If it exceeds the preset fuse threshold, the fuse signal will be automatically triggered to prevent system overload.

[0017] S4. Search prefetching: If the prefetching switch is turned on and the fuse signal is not triggered, the system will cache the search results of these sug words in the client's network library in advance based on the high-frequency sug words in the user's search behavior and the high-scoring sug words selected by model scoring; when the user's actual search hits these prefetched sug words, the system directly returns the cached search results to the client for rendering, omitting the network time for requesting the server and the server search time, thereby significantly improving the search performance.

[0018] S5. Automated monitoring and alarm: The system also has an automated monitoring function that can monitor the status of the search main channel service in real time and send an alarm via email, SMS, etc. when an abnormal situation occurs or exceeds the threshold. This helps to discover and solve problems in a timely manner and ensure the stable operation of the system.

[0019] S6. Cache strategy configuration: The system allows you to configure the cache time of the network library according to actual needs to optimize the utilization efficiency of cache resources and user experience. By flexibly configuring the cache strategy, you can further improve the performance and response speed of the system.

[0020] The beneficial effects of the present invention are as follows:

[0021] 1. The present invention uses an intelligent search pre-fetching strategy to keep the main search traffic from growing during peak hours, effectively preventing system overload; at the same time, it significantly increases the pre-fetching traffic during off-peak hours, significantly improves the search rendering speed of the client, achieves the effect of peak shaving and valley flattening, and improves the user experience.

[0022] 2. The present invention sets a fuse signal based on the health status of the search main channel service, timely perceives and responds to abnormal situations, effectively prevents the traffic pressure that may be caused by offline data calculation errors, avoids the avalanche effect of upstream and downstream services, and ensures the stable operation of the system.

[0023] 3. The present invention calculates the scores of sug words through a model, and the system can accurately select high-scoring sug words for pre-fetching and discard low-scoring sug words, thereby maximizing search efficiency within limited resources and optimizing resource utilization.

[0024] 4. The present invention flexibly configures cache time and rules in the network library through the system to ensure that the pre-fetch requests normally returned by the server can be efficiently cached and directly rendered when the user searches, greatly shortening the search response time and improving the overall performance of the system and user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 This is a flow chart for implementing the technology of the present invention. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] like Figure 1As shown, the embodiment of the present invention provides a system and method for pre-acquiring required automotive information technology with one click, including an App, a service module and a cache module;

[0028] The service module consists of online services and offline scheduling;

[0029] The cache module consists of Redis unit, Apollo unit and Memory unit.

[0030] The system first analyzes the user's historical search behavior, especially the frequency and pattern of the user's use of search suggestions (sug words). Through statistics, it is found that the proportion of user searches for sug words is quite high, which provides a data basis for pre-fetching.

[0031] The sug words are scored based on the model, and the sug words with high scores are selected as pre-fetch objects; the system caches these high-scoring sug words and their corresponding search results in the client's network library in advance.

[0032] In order to control the pre-fetch traffic, the system implements a series of traffic management strategies through online services, including using the gateway service to control the pre-fetch switch, managing pre-fetch related parameters (such as the number of pods, search peak qps, etc.) through the apollo configuration platform, and using the token bucket algorithm to limit the pre-fetch request flow.

[0033] The system also has offline scheduling tasks to monitor the health status of the main search channel service; once a service abnormality is detected (such as CPU, memory, and storage usage exceeding the threshold), the system will automatically trigger the fuse mechanism and shut down the pre-fetch function to avoid additional pressure on the main search channel.

[0034] When a user initiates a search request, if the search term matches the pre-fetched sug term, the system directly obtains the search results from the client's network library cache and renders them for the user. This process saves the network delay of the request server and the server processing time, significantly improving the search performance.

[0035] By pre-fetching and caching search results for high-scoring sug words, the system can respond quickly when users search, significantly reducing search time and improving search performance.

[0036] like Figure 1 As shown, the online service controls whether to perform search pre-fetching through the gateway service, and decides whether to start the pre-fetching process according to the state of the pre-fetching switch configured in apollo.

[0037] When the system load is high or encounters other potential risks, turning off the prefetch switch can avoid the additional occupation of system resources by the prefetch process, thereby ensuring the stability and performance of the main process of the system.

[0038] like Figure 1 As shown in the figure, the online service ensures that the main search traffic does not increase during peak hours and effectively utilizes resources for prefetching during off-peak hours by configuring parameters such as the comprehensive search peak qps of a single container and the upper limit of comprehensive search prefetching per second, as well as using the token bucket algorithm.

[0039] By accurately configuring the comprehensive search peak qps and the comprehensive search prefetching upper limit per second for a single container, the system can effectively manage traffic during peak and off-peak periods. During peak periods, the system limits the prefetching amount to ensure that the main search traffic does not increase, avoiding server overload and performance degradation. During off-peak periods, the system makes full use of the remaining resources for prefetching operations to improve resource utilization.

[0040] like Figure 1 As shown in the figure, in order to prevent traffic pressure caused by offline data calculation errors, the online service sets up an automatic circuit breaker mechanism; when an abnormal situation is detected, the circuit breaker signal will be written to redis through the offline script, and the gateway service will turn off the pre-fetch function after sensing the circuit breaker signal.

[0041] Through the automatic circuit breaker mechanism, the system can respond quickly when offline data calculation errors or abnormal situations are detected, avoiding traffic surges caused by erroneous data, thereby protecting the system from unnecessary pressure and enhancing the overall stability of the system.

[0042] like Figure 1 As shown, offline scheduling configures the search main channel service that needs to be monitored through the monitoring service, sets the fuse thresholds of CPU usage, memory usage, and storage usage. Offline scheduling sets a fuse signal based on the monitoring results when the service exceeds the preset threshold.

[0043] By monitoring the CPU usage, memory usage, and storage usage of the main search channel service and setting reasonable fuse thresholds, abnormal usage of system resources can be discovered in a timely manner. Once resource usage exceeds the preset threshold, the system can automatically trigger the fuse mechanism to prevent system crashes or service unavailability caused by resource overload, thereby improving the stability and reliability of the entire system.

[0044] like Figure 1 As shown in the figure, offline scheduling obtains a list of all pods under different services and monitors their resource usage, and determines whether offline scheduling is abnormal based on the monitored resource usage.

[0045] By obtaining a list of all pods under different services and monitoring their key resource indicators such as CPU usage, memory usage, storage usage, etc., abnormal conditions and potential bottlenecks in service operation can be discovered in a timely manner. This helps ensure the stability and reliability of the main search channel service and prevents damage to user experience due to service failures or performance degradation.

[0046] like Figure 1 As shown in the figure, abnormal situations of offline scheduling will be reported through emails, text messages, etc., and the fuse signal will be automatically closed after the service returns to a healthy state.

[0047] When offline dispatching monitors abnormal service conditions, it can quickly send an alarm to relevant personnel via email, SMS, etc. to ensure that the problem can be discovered in time. This timely response mechanism helps to reduce service interruption time and improve system stability and availability.

[0048] Working principle and usage process:

[0049] S1. Gateway service control: First, the system determines whether to perform a search pre-fetch operation through the gateway service.

[0050] S2. Pre-fetch switch check: The gateway service checks the status of the pre-fetch switch (the switch is configured in the Apollo system and is named presearch_switch) to determine whether search pre-fetching is allowed.

[0051] S3. Resource flow limiting and fuse checking: The system will then perform a resource flow limiting check, using the Apollo-configured single container search peak QPS (limit_qps), the upper limit of comprehensive search pre-fetching per second, and other parameters, as well as the automatic fuse signal in Redis (presearch_qps_threshold) to determine whether the current situation is suitable for pre-fetching operations. If the flow limiting threshold is reached or the fuse signal is triggered, no pre-fetching will be performed; at the same time, the system will also monitor the health status of the main search channel service, including CPU usage, memory usage, storage usage, etc. If it exceeds the preset fuse threshold, the fuse signal will be automatically triggered to prevent system overload.

[0052] S4. Search prefetching: If the prefetching switch is turned on and the fuse signal is not triggered, the system will cache the search results of these sug words in the client's network library in advance based on the high-frequency sug words in the user's search behavior and the high-scoring sug words selected by model scoring; when the user's actual search hits these prefetched sug words, the system directly returns the cached search results to the client for rendering, omitting the network time for requesting the server and the server search time, thereby significantly improving the search performance.

[0053] S5. Automated monitoring and alarm: The system also has an automated monitoring function that can monitor the status of the search main channel service in real time and send an alarm via email, SMS, etc. when an abnormal situation occurs or exceeds the threshold. This helps to discover and solve problems in a timely manner and ensure the stable operation of the system.

[0054] S6. Cache strategy configuration: The system allows you to configure the cache time of the network library according to actual needs to optimize the utilization efficiency of cache resources and user experience. By flexibly configuring the cache strategy, you can further improve the performance and response speed of the system.

[0055] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0056] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. One-click pre-acquisition of required automotive information technology systems, characterized by: The technical system includes: App, service module and cache module; The service module is composed of online service and offline scheduling; The cache module is composed of a Redis unit, an Apollo unit and a Memory unit.

2. The one-click pre-acquisition required automotive information technology system according to claim 1, characterized in that: The online service controls whether to perform search pre-fetching through the gateway service, and determines whether to start the pre-fetching process according to the state of the pre-fetching switch configured in apollo.

3. The one-click pre-acquisition required automotive information technology system according to claim 1, characterized in that: The online service also includes configuring the comprehensive search peak qps of a single container, the comprehensive search pre-fetch upper limit parameters per second, and using a token bucket algorithm to ensure that the main search traffic does not increase during peak periods, while effectively utilizing resources for pre-fetching during off-peak periods.

4. The one-click pre-acquisition required automotive information technology system according to claim 1, characterized in that: In order to prevent traffic pressure caused by offline data calculation errors, the online service sets up an automatic fuse mechanism; when an abnormal situation is detected, the fuse signal will be written to redis through the offline script, and the gateway service will turn off the pre-fetch function after sensing the fuse signal.

5. The one-click pre-acquisition required automotive information technology system according to claim 1, characterized in that: The offline scheduling configures the search main path service that needs to be monitored through the monitoring service, sets the fuse thresholds of CPU usage, memory usage, and storage usage. The offline scheduling sets a fuse signal according to the monitoring results when the service exceeds the preset threshold.

6. The one-click pre-acquisition required automotive information technology system according to claim 1, characterized in that: The offline scheduling also includes obtaining a list of all pods under different services and monitoring their resource usage, and determining whether the offline scheduling is in an abnormal situation according to the monitored resource usage.

7. The one-click pre-acquisition required automotive information technology system according to claim 1, characterized in that: The abnormal situation of offline scheduling will be reported via email or SMS, and the fuse signal will be automatically closed after the service returns to a healthy state.

8. A method for pre-acquiring required automobile information technology with one click, characterized in that: The technical method comprises the following steps: S1. Gateway service control: First, the system determines whether to perform a search prefetch operation through the gateway service; S2, pre-fetch switch check: The gateway service checks the status of the pre-fetch switch to determine whether search pre-fetching is allowed; S3. Resource current limiting and circuit breaker check: The system will then perform a resource current limiting check to determine whether the current time is suitable for prefetching operations based on the peak QPS of a single container search configured by Apollo, the upper limit parameter of comprehensive search prefetching per second, and the automatic circuit breaker signal in Redis. If the current limiting threshold is reached or the fuse signal is triggered, no pre-fetching will be performed; at the same time, the system will also monitor the health status of the main search channel service, including CPU usage, memory usage, and storage usage. If it exceeds the preset fuse threshold, the fuse signal will be automatically triggered to prevent system overload; S4, search prefetch: If the prefetch switch is turned on and the fuse signal is not triggered, the system will cache the search results of these sug words in the client's network library in advance based on the high-frequency sug words in the user's search behavior and the high-scoring sug words selected by model scoring; When users actually search and hit these pre-fetched sug words, the system directly returns the cached search results to the client for rendering, omitting the network time for requesting the server and the server search time, thus significantly improving the search performance; S5. Automated monitoring and alarm: Automated monitoring is used to monitor the status of the main channel service in real time, and alarms are sent via email or SMS when abnormal conditions or thresholds are exceeded; this helps to identify and resolve problems in a timely manner, ensuring the stable operation of the system; S6. Cache strategy configuration: Configure the cache time of the network library according to actual needs to optimize the utilization efficiency of cache resources and user experience; further improve the performance and response speed of the system by flexibly configuring the cache strategy.

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