Resource delivery data checking method and device and computing equipment

Abstract

The invention discloses a resource release data checking method and device and computing equipment, and the method comprises the steps: carrying out delayed aggregation association processing on filtering record data of a resource funnel system, and writing account layer funnel data obtained through processing into a database; performing real-time aggregation association processing on the filtering record data of the resource funnel system, and writing the processed account layer funnel data into a cache; wherein the filtering record data is used for recording a resource filtering event of the resource funnel system; according to query conditions of a query party, respectively querying in a database and a cache; and calculating delivery index data according to the queried target account layer funnel data, and displaying the delivery index data to a query party. By means of the mode, the real-time performance, comprehensiveness and accuracy of the query result can be guaranteed, visual and accurate delivery index data can be provided for the query party, and therefore visual and accurate data support is provided for the query party.

Description

Technical Field

[0001] The present application relates to the field of Internet technology, and specifically to a resource placement data screening method, device, computing equipment, computer storage medium and computer program product. Background Art

[0002] The resource funnel is a process of filtering resources that do not meet the requirements. Strict filtering logic is embedded in the funnel system at all levels to ensure the quality and effect of resources. In the broad scope of business classification, the funnel model runs through every link of the delivery, from the initial indexing, basic filtering, rough sorting, fine sorting, to bidding and other key steps, all of which reflect the application of the funnel model. The model continuously optimizes and purifies resources, only to present the best resources to the target audience.

[0003] In actual business, relevant personnel (such as resource providers, operation personnel, product experts, etc.) need to know the effect of resource delivery, and need to analyze the filtered record data generated by the funnel model and provide analysis results. How to provide complete and reliable delivery effect data is an urgent problem to be solved. Summary of the invention

[0004] In view of the above problems, the present application is proposed to provide a resource allocation data screening method, apparatus, computing device, computer storage medium and computer program product that overcome the above problems or at least partially solve the above problems.

[0005] According to one aspect of the present application, a resource delivery data screening method is provided, comprising:

[0006] Perform delayed aggregation and association processing on the filtered record data of the resource funnel system, and write the processed account-level funnel data into the database;

[0007] Perform real-time aggregation and association processing on the filtered record data of the resource funnel system, and write the processed account-level funnel data into the cache;

[0008] Among them, the filtering record data is used to record the filtering events of resources by the resource funnel system;

[0009] According to the query conditions of the query party, query is performed in the database and cache respectively;

[0010] The delivery index data is calculated based on the queried target account layer funnel data, and the delivery index data is displayed to the querying party.

[0011] Optionally, performing real-time aggregation and association processing on the filtered record data of the resource funnel system further includes:

[0012] Through the real-time processing service, the filter record data sent by the resource funnel system is received, and the received filter record data is aggregated and associated.

[0013] Optionally, the resource funnel system sends the filtered record data to the real-time processing service by sending a real-time data stream.

[0014] Optionally, performing delayed aggregation association processing on the filtered record data of the resource funnel system further includes:

[0015] At every first preset time interval, aggregation and association processing is performed on the filtered record data uploaded to the log system by the resource funnel system.

[0016] Optionally, the aggregation association process includes the following steps:

[0017] Aggregate the filtered record data of the resource funnel system to obtain resource layer funnel data;

[0018] The resource layer funnel data is associated with the account index information to which the resource belongs to obtain the account layer funnel data.

[0019] Optionally, before associating the resource layer funnel data with the account index information to which the resource belongs, the method further includes:

[0020] The account index information is pulled from the index pool at every second preset time interval through the preset plug-in.

[0021] Optionally, the resource funnel system includes multiple levels of funnel subsystems, and the funnel subsystems at different levels use different filtering strategies to perform filtering processing. The filtering record data of the resource funnel system includes the filtering record data of the funnel subsystems at multiple levels.

[0022] According to another aspect of the present application, a resource delivery data checking device is provided, comprising:

[0023] The first processing module is used to perform delayed aggregation and association processing on the filtered record data of the resource funnel system, and write the processed account-level funnel data into the database;

[0024] The second processing module is used to perform real-time aggregation and association processing on the filtered record data of the resource funnel system, and write the processed account-level funnel data into the cache;

[0025] Among them, the filtering record data is used to record the filtering events of resources by the resource funnel system;

[0026] The query module is used to query the database and cache according to the query conditions of the query party;

[0027] The indicator processing module is used to calculate the delivery indicator data based on the queried target account layer funnel data and display the delivery indicator data to the querying party.

[0028] Optionally, the second processing module is further used for:

[0029] Through the real-time processing service, the filter record data sent by the resource funnel system is received, and the received filter record data is aggregated and associated.

[0030] Optionally, the resource funnel system sends the filtered record data to the real-time processing service by sending a real-time data stream.

[0031] Optionally, the first processing module is further used for:

[0032] At every first preset time interval, aggregation and association processing is performed on the filtered record data uploaded to the log system by the resource funnel system.

[0033] Optionally, the first processing module and the second processing module are further used for:

[0034] Aggregate the filtered record data of the resource funnel system to obtain resource layer funnel data;

[0035] The resource layer funnel data is associated with the account index information to which the resource belongs to obtain the account layer funnel data.

[0036] Optionally, the device further comprises:

[0037] The pulling module is used to pull account index information from the index pool at intervals of a second preset time through a preset plug-in.

[0038] Optionally, the resource funnel system includes multiple levels of funnel subsystems, and the funnel subsystems at different levels use different filtering strategies to perform filtering processing. The filtering record data of the resource funnel system includes the filtering record data of the funnel subsystems at multiple levels.

[0039] According to another aspect of the present application, there is provided a computing device, comprising: a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus;

[0040] The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute operations corresponding to the above-mentioned resource allocation data screening method.

[0041] According to another aspect of the present application, a computer storage medium is provided, wherein the storage medium stores at least one executable instruction, and the executable instruction enables a processor to perform operations corresponding to the above-mentioned resource allocation data screening method.

[0042] According to another aspect of the present application, a computer program product is provided, comprising at least one executable instruction, wherein the executable instruction enables a processor to execute operations corresponding to the above-mentioned resource allocation data screening method.

[0043] According to the resource delivery data investigation method, device, computing equipment, computer storage medium and computer program product provided in the embodiment of the present application, the filtered record data of the resource funnel system is subjected to delayed aggregation and association processing, and the processed account-level funnel data is written into the database; the filtered record data of the resource funnel system is subjected to real-time aggregation and association processing, and the processed account-level funnel data is written into the cache; wherein the filtered record data is used to record the filtering events of the resource funnel system on the resources; according to the query conditions of the querying party, queries are respectively performed in the database and the cache; the delivery index data is calculated according to the queried target account-level funnel data, and the delivery index data is displayed to the querying party. Through the above-mentioned method, the real-time, comprehensive and accurate query results can be guaranteed, and intuitive and accurate delivery index data can also be provided to the querying party, thereby providing intuitive and accurate data support to the querying party.

[0044] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present application. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0046] Figure 1 A flow chart of a method for checking resource delivery data provided by an embodiment of the present application is shown;

[0047] Figure 2 A flow chart of a method for checking resource delivery data provided by another embodiment of the present application is shown;

[0048] Figure 3 A flowchart of real-time aggregation association processing provided by another embodiment of the present application is shown;

[0049] Figure 4 A functional structure diagram of a resource delivery data checking device provided in an embodiment of the present application is shown;

[0050] Figure 5A schematic diagram of the structure of a computing device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0051] The exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art.

[0052] First, the terms involved in one or more embodiments of the present application are explained.

[0053] Resources: Content that users put into the platform to be promoted, including advertisements, promotional content, etc.

[0054] Resource funnel system: used to filter resources that do not meet the requirements. The front end initiates a resource request at the resource position, and there are a large number of resources in the backend system for screening. The resource funnel system filters through layers and finally selects the resources to be displayed at the resource position.

[0055] Filtering records: The resource funnel system records the filtering of several resources entering the system.

[0056] Data platform: a platform that integrates data access, data processing, data storage, query retrieval, analysis and mining, application interface and other functions.

[0057] Database: The most basic definition is a collection of related information used to store and organize data to make it easier to manage and access.

[0058] Nebula: is an open source distributed graph database designed to handle large-scale graph data storage and efficient query.

[0059] Kafka: is a distributed stream processing platform designed to process real-time data streams. Its architecture is designed to support high throughput, persistent log storage, and powerful messaging capabilities.

[0060] Flink: is an open source stream processing framework designed to provide high-performance, scalable, and fault-tolerant data processing capabilities.

[0061] Figure 1 FIG. 1 is a flow chart showing a method for checking resource delivery data provided by an embodiment of the present application. Figure 1 As shown, the method comprises the following steps:

[0062] Step S110, performing delayed aggregation association processing on the filtered record data of the resource funnel system, and writing the processed account-level funnel data into the database.

[0063] Among them, the resource funnel system filters and selects resources according to the filtering strategy, and finally determines the resources displayed to the user. In one scenario, when the user enters the resource recommendation page, a resource request is automatically triggered. In response to the resource request, the resource funnel system screens all resources in the resource pool, selects several resources suitable for the user, and displays the selected resources on the resource recommendation page. If the resource is retained after being filtered by the resource funnel system, it is considered that the resource has passed the filtering of the resource funnel system; if the resource is not retained after being filtered by the resource funnel system, it is considered that the resource has not passed the filtering of the resource funnel system.

[0064] The filtering record data is used to record the filtering events of resources by the resource funnel system, specifically to record which resources failed to pass the filtering, which resources passed the filtering and were retained, the reasons why the resources failed to pass the filtering, the number of resources that failed to pass the filtering and passed the filtering, the total number of resources entering the resource funnel system, the resource position of this resource request, etc. Account-level funnel data refers to the funnel data that contains the association between account index information and resources. Through account-level funnel data, it is easy to produce more dimensional indicator data, providing a data basis for subsequent intelligent analysis.

[0065] Step S120 , performing real-time aggregation and association processing on the filtered record data of the resource funnel system, and writing the processed account-level funnel data into a cache.

[0066] In the method of the embodiment of the present application, the filtered record data of the resource funnel system is processed through two different calculation paths, including delayed aggregation association processing and real-time summary association processing. The specific implementation methods of the two processes are consistent, thereby ensuring the accuracy and consistency of the data.

[0067] Among them, delayed aggregation and association processing refers to periodic aggregation and association processing of filtered record data. The volume of filtered record data that needs to be processed in one aggregation and association processing is very large, and it takes a long time to complete the aggregation and association processing. Therefore, the account-level funnel data that falls into the database is delayed. Real-time aggregation and association processing is to process the filtered record data of the resource funnel system in real time. The volume of filtered record data processed in real time is relatively small, the cache is updated quickly, and the capacity is smaller than the database. Therefore, a small amount of account-level funnel data calculated in real time is stored in the cache.

[0068] In an optional manner, the resource funnel system includes multiple levels of successive funnel subsystems, and the funnel subsystems at different levels use different filtering strategies for filtering. For two adjacent levels of funnel subsystems, the remaining resources after filtering by the previous level of funnel subsystem enter the next level of funnel subsystem for further filtering. Correspondingly, the filtering record data of the resource funnel system includes the filtering record data of multiple levels of funnel subsystems, and the filtering record data of each level of funnel subsystem are subjected to delayed and real-time aggregation and association processing.

[0069] For example, a resource funnel system includes multiple funnel subsystems such as indexing subsystem, targeting subsystem, recall subsystem, coarse ranking subsystem, fine ranking subsystem, and bidding subsystem. Each funnel subsystem uses different filtering strategies to filter resources. The filtering strategies are refined step by step, and the resources entering the funnel subsystems at each level are reduced step by step.

[0070] Step S130: query the database and cache respectively according to the query conditions of the querying party.

[0071] For example, the querying party is the delivery user to which the resource belongs. The delivery user provides the resource ID, account ID and / or time range as query conditions to query the target account level funnel data corresponding to the specified resource, the target account level funnel data under the account, and / or the target account level funnel data within the specified time range.

[0072] After receiving the query conditions from the inquirer, queries are performed in the database and cache respectively. The account-level funnel data queried in the database is used as the basic data, and the account-level funnel data queried in the cache is used as the supplementary data to supplement the data that has not yet fallen into the database due to delayed processing.

[0073] At the same time, the data queried in the database is delayed, while the data queried in the cache is real-time. Specifically, assuming that the delayed aggregation association processing takes 4 hours, the latest account-level funnel data that falls into the database is obtained based on the filtered record data 4 hours ago, and lacks data within the last 4 hours. In the cache, the account-level funnel data obtained based on the filtered record data within the last 4 hours can be queried. By summarizing the database query results and the cache query results, comprehensive and accurate data can be obtained.

[0074] In an optional method, the query is performed in the order of database first and then cache. After matching account-level funnel data is found in the database, the time range of the missing data is determined, and then matching account-level funnel data is queried in the cache based on the time range of the missing data and the query conditions.

[0075] Step S140, calculating delivery index data according to the queried target account layer funnel data, and displaying the delivery index data to the querying party.

[0076] Based on the queried target account-level funnel data (including database query results and cache query results), multiple dimensions of delivery indicator data are calculated, such as the account's resource pass rate, the resource pass rate of the industry to which the account belongs, etc., thereby providing the inquirer with more reliable and efficient information support and facilitating the inquirer to make more scientific decisions.

[0077] To summarize, according to the resource delivery data investigation method provided in this embodiment, a delayed calculation path and a real-time calculation path are used to respectively perform aggregation and association processing on the filtered record data of the resource funnel system. The account-level funnel data obtained by the delayed processing falls into the database, and the account-level funnel data obtained by the real-time processing is written into the cache. When the inquirer performs a query, the cached query results are used as a supplement to the database query results, which can ensure the real-time, comprehensiveness and accuracy of the query results, and can also provide the inquirer with intuitive and accurate delivery indicator data, thereby providing the inquirer with intuitive and accurate data support.

[0078] Figure 2 A flow chart of a resource delivery data checking method provided by another embodiment of the present application is shown. Figure 2 As shown, the method comprises the following steps:

[0079] Step S210 , at intervals of a first preset time, aggregate and associate the filtered record data uploaded from the resource funnel system to the log system, and write the processed account-level funnel data into a database.

[0080] The processing method of this step is the delayed processing method. In this method, the filtering record data is specifically the log data of the resource funnel system, indicating the filtering events of the resource funnel system on each resource, including the results of the filtering events, filtering strategies, etc. The resource funnel system uploads the log data to the log system, and periodically aggregates and associates the log data in the log system through a scheduled task, and stores the account-level funnel data obtained by the aggregation and association processing into the database.

[0081] Scheduled tasks can be hourly tasks, with aggregation and association processing performed every hour. Since the resource funnel system generates a large amount of log data, each aggregation and association processing takes a long time.

[0082] The aggregation and association processing specifically includes two stages of processing. The first is the aggregation processing, which is used to obtain the funnel data of each resource, and the second is the association processing, which is used to match the resource layer funnel data with the account layer information. The aggregation and association processing specifically includes the following steps: aggregate the filtered record data of the resource funnel system to obtain the resource layer funnel data; associate the resource layer funnel data with the account index information to which the resource belongs to obtain the account layer funnel data. Specifically, the account index information is used to record the association relationship between accounts, resources and industries. The account specifically refers to the account of the user who is the publisher.

[0083] Resource-layer funnel data refers to resource filtering event record data. The filtering record data of the resource funnel system is aggregated according to the resource dimension to obtain filtering event record data of each resource (including which funnel the filtering event occurred in, which resource request the filtering event belongs to, the number of times the filtering event occurred, etc.). Account-layer funnel data refers to funnel data that contains the relationship between account-layer information and resources. According to the account index information, the account and industry are matched with the resource-layer funnel data to obtain account-related resource funnel data and industry-related resource funnel data, collectively referred to as account-layer funnel data.

[0084] In an optional manner, account index information is pulled from the index pool at every second preset time interval through a preset plug-in, wherein the index pool contains valid account index information, and the account index information in the index pool is dynamically updated. Based on this, account index information is pulled from the index pool at every second preset time interval through a preset plug-in to ensure that complete and accurate account index information is obtained.

[0085] Step S220, receiving the filtering record data sent by the resource funnel system through the real-time processing service, performing aggregation and association processing on the received filtering record data, and writing the processed account-level funnel data into the cache.

[0086] The processing method of this step is real-time processing. In addition to sending log data to the log system, the resource funnel system also sends the filtered record data to the real-time processing service by sending real-time data streams. The real-time processing service aggregates and associates the real-time data streams, and synchronizes the output account-level funnel data to the cache every third preset time interval to ensure the timeliness of the data.

[0087] Optionally, each funnel subsystem in the resource funnel system has a corresponding real-time processing service for receiving the real-time data stream sent by the funnel subsystem and performing real-time aggregation and association processing on the real-time data stream. Further optionally, the real-time processing service is a service built based on Kafka, and the real-time data stream is a Kafka data stream. In this method, the Kafka cluster is used to realize the real-time processing of the filtered record data, relying on Kafka's superior processing ability for high-concurrency scenarios to ensure smooth data consumption.

[0088] Step S230: query the database and cache respectively according to the query conditions of the querying party.

[0089] The query party is specifically a user with permission, and people of different roles can participate in the investigation through authorization. After receiving the query conditions from the query party, the query scope is first determined according to the query party's permissions, and then the data within the query scope is queried in the database and cache.

[0090] For example, if the querying party is a user who delivers resources on the delivery platform, the query scope of the delivery user is the relevant funnel data under his own account; if the querying party is an internal user of the delivery platform (such as operations personnel, product personnel, R&D personnel, testers, sales personnel, etc.), the query scope of the querying party is all data, that is, internal users of the delivery platform can query all funnel data in the system.

[0091] In an optional approach, different data platforms are built for delivery users and internal users of the delivery platform. Delivery users use the data platform to check the relevant funnel data under their own accounts, and internal users use the data platform to check the funnel data of the entire platform. This implements a troubleshooting system covering multiple roles, ensuring that problems can be quickly discovered from different angles and effectively resolved.

[0092] Step S240, calculating delivery index data according to the queried target account layer funnel data, and displaying the delivery index data to the querying party.

[0093] Based on the queried target account layer funnel data, delivery indicator data of multiple dimensions are calculated and displayed to the querying party through the query result page.

[0094] The delivery index data is equivalent to the index data obtained based on the filtering records of the resources under the account, which may include: the overall account resource pass rate, the account resource position pass rate, the account resource pass rate details, the account overall resource pass rate change trend, the industry resource pass rate, the industry resource pass rate change trend and / or the industry resource strategy pass rate. Among them, the overall account resource pass rate can be the ratio of the total number of times the resources under the same account pass the filtering process of the resource funnel system to the total number of resource requests; the account resource position pass rate can be the ratio of the total number of times the resources under the same account at a specified resource position pass the filtering process of the resource funnel system to the total number of resource requests at that resource position; the account resource pass rate details are for specific resources under the account, which may include: the global pass rate, the funnel subsystem pass rate, the strategy pass rate, the resource pass rate change trend, the global pass rate can be the ratio of the total number of times the resources pass the filtering process of the resource funnel system to the total number of resource requests, the funnel subsystem pass rate can be the ratio of the total number of times the resources pass the filtering process of the funnel subsystem to the total number of resource requests The ratio of times, the strategy pass rate can be the ratio of the total number of times that resources are filtered through the specified filtering strategy to the total number of resource requests, and the resource pass rate change trend can be the month-on-month change of the resource pass rate; the account overall resource pass rate change trend can be the month-on-month change of the account overall resource pass rate; the industry-related delivery indicator data is obtained by comprehensive analysis of the account-level funnel data in the same industry, the industry resource pass rate can be the ratio of the total number of times that resources under the industry are filtered through the resource funnel system to the total number of resource requests, the industry resource pass rate change rate can be the month-on-month change of the industry resource pass rate, and the industry resource strategy pass rate can be the ratio of the total number of times that resources in the same industry are filtered through the specified filtering strategy to the total number of resource requests. It should be noted that the delivery indicator data includes but is not limited to the various indicator data listed above. In actual applications, more dimensional indicator data can be configured according to actual business needs to provide multi-dimensional indicator data to the query party.

[0095] In addition to providing powerful data support, the method of the embodiment of the present application also provides an intelligent analysis function of indicators, which can provide all-round data insights for the users, so that the users can understand the resource delivery situation and optimize the delivery strategy, thereby improving their own competitiveness and delivery effect, and meeting the diverse delivery needs of the users. For the internal users of the delivery platform, it can provide intuitive and accurate data support, so that the internal users can make more informed decisions.

[0096] In summary, according to the resource delivery data investigation method provided by the present embodiment, on the one hand, the resource funnel system uploads the filtered record data to the log system by uploading logs, and periodically aggregates and associates the filtered record data in the log system through a scheduled task, and writes the processed account-level funnel data into the database, thereby realizing persistent storage of a large amount of account-level funnel data to ensure data integrity; on the other hand, the resource funnel system sends a real-time data stream of the filtered record data to the real-time processing service, and writes the account-level funnel data obtained by real-time processing into the cache, thereby storing a small amount of real-time account-level funnel data in the cache; thereafter, when the querying party queries according to the query conditions, queries are performed in the database and the cache respectively, so as to obtain the data in the data. Based on the delayed data queried from the database, supplemented by the real-time data queried from the cache, complete and timely data can be queried; the query party can complete the query by providing simple query conditions, which simplifies the query party's operation process, reduces the difficulty of use, and enables the query party to easily obtain and use data; further, based on the queried target account layer funnel data, multiple dimensions of delivery indicators are calculated and provided to the query party, which can provide the query party with powerful and intelligent analysis functions, thereby providing the query party with more reliable and efficient information support, and facilitating the query party to make more reasonable decisions; further, indicator data of the same industry is also provided for comparison, which is convenient for delivery users to understand their own position in the market and adjust the delivery strategy in time.

[0097] Figure 3 A flowchart of real-time aggregation association processing provided by another embodiment of the present application is shown, wherein real-time data stream 330, real-time data stream 340, real-time data stream 350 and real-time data stream 360 are respectively filtered record data streams of different funnel subsystems, specifically Kafka real-time data streams. In actual applications, there will be a large number of funnel subsystems in a resource funnel system. The embodiment of the present application only takes 4 funnel subsystems as an example for illustration.

[0098] Step S310 specifically includes: performing aggregation processing on the filtered record data of the resource funnel system, analyzing and obtaining the relevant funnel data of each resource, that is, obtaining the resource layer funnel data;

[0099] Step S320 specifically includes: associating the resource layer funnel data with the account index information to obtain the account layer funnel data, thereby realizing the splicing of the account index information with the resource funnel data.

[0100] Each real-time data stream is processed in step S310 to obtain resource layer funnel data, which is delivered to the corresponding message queue 331, message queue 341, message queue 351 and message queue 361. The message queue specifically uses the kafka message queue to aggregate the data of each message queue to obtain aggregate data 370. The aggregate data 370 and the account index information 380 are processed in step S320 to obtain the account layer funnel data, which is written into the cache 390, wherein the account index information is pulled based on the Nebula framework.

[0101] Figure 3 The real-time data streams shown in the figure are: the filtering record data stream of the directional subsystem, the filtering record data stream of the coarse sorting subsystem, the filtering record data stream of the fine sorting subsystem, and the filtering record data stream of the recall subsystem.

[0102] For the filtered record data stream of the coarse sorting subsystem, the coarse sorting information is finely processed in the Flink system to generate resource layer funnel data in the coarse sorting stage, thereby ensuring the integrity and accuracy of the data.

[0103] For the filtered record data stream of the fine sorting subsystem, since the resources processed by the fine sorting subsystem are smaller in volume than those processed by the coarse sorting subsystem, they can be processed directly by the computing program without the need for preprocessing with the help of the Flink system, thereby greatly improving the speed and efficiency of data processing.

[0104] For the filtered record data stream of the recall subsystem: by processing the filtered record data stream of the recall subsystem, the resource layer funnel data of the recall level is produced, and by associating the account index information, the funnel data of the three dimensions of resources, accounts and industries at the recall level can be obtained.

[0105] For the filtering record data flow of the targeting subsystem, the targeting subsystem specifically filters resources by matching the targeting of each dimension with the requesting user. The targeting dimensions include: age, gender, region, etc. If the information of the requesting user does not match the targeting information of the resource, the resource cannot pass the filtering of the targeting subsystem.

[0106] Figure 4 The functional structure diagram of the resource delivery data checking device provided in the embodiment of the present application is shown. Figure 4 As shown, the device comprises:

[0107] The first processing module 41 is used to perform delayed aggregation and association processing on the filtered record data of the resource funnel system, and write the processed account-level funnel data into the database;

[0108] The second processing module 42 is used to perform real-time aggregation and association processing on the filtered record data of the resource funnel system, and write the processed account-level funnel data into the cache;

[0109] Among them, the filtering record data is used to record the filtering events of resources by the resource funnel system;

[0110] A query module 43, used to query the database and cache respectively according to the query conditions of the query party;

[0111] The indicator processing module 44 is used to calculate the delivery indicator data according to the queried target account layer funnel data, and display the delivery indicator data to the querying party.

[0112] In an optional manner, the second processing module 42 is further configured to:

[0113] Through the real-time processing service, the filter record data sent by the resource funnel system is received, and the received filter record data is aggregated and associated.

[0114] In an optional manner, the resource funnel system sends the filtered record data to the real-time processing service by sending a real-time data stream.

[0115] In an optional manner, the first processing module 41 is further used for:

[0116] At every first preset time interval, aggregation and association processing is performed on the filtered record data uploaded to the log system by the resource funnel system.

[0117] In an optional manner, the first processing module 41 and the second processing module 42 are further used for:

[0118] Aggregate the filtered record data of the resource funnel system to obtain resource layer funnel data;

[0119] The resource layer funnel data is associated with the account index information to which the resource belongs to obtain the account layer funnel data.

[0120] In an optional manner, the device further includes:

[0121] The pulling module is used to pull account index information from the index pool at intervals of a second preset time through a preset plug-in.

[0122] In an optional manner, the resource funnel system includes multiple levels of funnel subsystems, and the funnel subsystems at different levels use different filtering strategies to perform filtering processing. The filtering record data of the resource funnel system includes the filtering record data of the funnel subsystems at multiple levels.

[0123] To summarize, according to the resource delivery data investigation device provided by this embodiment, a delayed calculation path and a real-time calculation path are used to respectively perform aggregation and association processing on the filtered record data of the resource funnel system. The account-level funnel data obtained by the delayed processing falls into the database, and the account-level funnel data obtained by the real-time processing is written into the cache. When the inquirer performs a query, the cached query results are used as a supplement to the database query results, which can ensure the real-time, comprehensiveness and accuracy of the query results, and can also provide the inquirer with intuitive and accurate delivery indicator data, thereby providing the inquirer with intuitive and accurate data support.

[0124] An embodiment of the present application provides a non-volatile computer storage medium, which stores at least one executable instruction or computer program, and the executable instruction or computer program can enable a processor to perform operations corresponding to the resource allocation data screening method in any of the above method embodiments.

[0125] An embodiment of the present application provides a computer program product, which includes at least one executable instruction or computer program, and the executable instruction or computer program can enable a processor to perform operations corresponding to the resource allocation data screening method in any of the above method embodiments.

[0126] Figure 5 A schematic diagram of the structure of a computing device provided in an embodiment of the present application is shown. The specific embodiment of the present application does not limit the specific implementation of the computing device.

[0127] like Figure 5 As shown, the computing device may include: a processor (processor) 502 , a communications interface (Communications Interface) 504 , a memory (memory) 506 , and a communication bus 508 .

[0128] The processor 502, the communication interface 504, and the memory 506 communicate with each other via the communication bus 508. The communication interface 504 is used to communicate with other devices such as a client or other server network elements. The processor 502 is used to execute the program 510, which can specifically execute the relevant steps in the above-mentioned resource placement data screening method embodiment for a computing device.

[0129] Specifically, the program 510 may include program codes, which include computer operation instructions.

[0130] The processor 502 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application. The one or more processors included in the computing device may be processors of the same type, such as one or more CPUs; or may be processors of different types, such as one or more CPUs and one or more ASICs.

[0131] The memory 506 is used to store the program 510. The memory 506 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0132] The program 510 can be specifically used to enable the processor 502 to execute the resource placement data screening method in any of the above method embodiments. The specific implementation of each step in the program 510 can refer to the corresponding description in the corresponding steps and units in the resource placement data screening embodiment, which will not be repeated here. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process of the above-described devices and modules can refer to the corresponding process description in the aforementioned method embodiment, which will not be repeated here.

[0133] The algorithm or display provided here are not inherently related to any specific computer, virtual system or other equipment. Various general systems can also be used together with the teaching based on this. According to the above description, it is obvious to construct the structure required for this type of system. In addition, the present application embodiment is not directed to any specific programming language yet. It should be understood that various programming languages ​​can be utilized to realize the content of the present application described here, and the above description of specific languages ​​is to disclose the best mode of implementation of the present application.

[0134] In the description provided herein, a large number of specific details are described. However, it is understood that the embodiments of the present application can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0135] Similarly, it should be understood that in order to streamline the present application and aid in understanding one or more of the various inventive aspects, in the above description of the exemplary embodiments of the present application, the various features of the embodiments of the present application are sometimes grouped together into a single embodiment, figure, or description thereof. However, the disclosed method should not be interpreted as reflecting the following intention: the claimed application requires more features than the features explicitly recited in each claim. More specifically, as reflected in the claims, the inventive aspects lie in less than all the features of the single embodiment disclosed above. Therefore, the claims that follow the specific embodiment are hereby expressly incorporated into the specific embodiment, with each claim itself serving as a separate embodiment of the present application.

[0136] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and in addition they may be divided into a plurality of submodules or subunits or subcomponents. Except that at least some of such features and / or processes or units are mutually exclusive, all features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device disclosed in this manner may be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature providing the same, equivalent or similar purpose.

[0137] In addition, those skilled in the art will appreciate that, although some embodiments herein include certain features included in other embodiments but not other features, the combination of features of different embodiments is meant to be within the scope of the present application and form different embodiments. For example, in the claims, any one of the claimed embodiments may be used in any combination.

[0138] The various component embodiments of the present application can be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It should be understood by those skilled in the art that a microprocessor or digital signal processor (DSP) can be used in practice to implement some or all functions of some or all components according to the embodiments of the present application. The application can also be implemented as a device or apparatus program (e.g., computer program and computer program product) for executing a part or all of the methods described herein. Such a program implementing the present application can be stored on a computer-readable medium, or can have the form of one or more signals. Such a signal can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0139] It should be noted that the above embodiments illustrate the present application rather than limit the present application, and that those skilled in the art may design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference symbol between brackets shall not be constructed as a limitation on the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "one" or "an" preceding an element does not exclude the presence of multiple such elements. The present application may be implemented by means of hardware including several different elements and by means of a suitably programmed computer. In a unit claim that lists several devices, several of these devices may be embodied by the same hardware item. The use of the words first, second, and third, etc. does not indicate any order. These words may be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be understood as limitations on the order of execution.

Claims

1. A resource delivery data investigation method, comprising: Perform delayed aggregation and association processing on the filtered record data of the resource funnel system, and write the processed account-level funnel data into the database; Perform real-time aggregation and association processing on the filtered record data of the resource funnel system, and write the processed account-level funnel data into the cache; Wherein, the filtering record data is used to record the filtering events of resources by the resource funnel system; According to the query conditions of the querying party, query is performed in the database and the cache respectively; The delivery index data is calculated according to the queried target account layer funnel data, and the delivery index data is displayed to the querying party.

2. The method according to claim 1, wherein: The real-time aggregation and association processing of the filtered record data of the resource funnel system further includes: The filtering record data sent by the resource funnel system is received through the real-time processing service, and the received filtering record data is aggregated and associated.

3. The method according to claim 2, wherein: The resource funnel system sends the filtered record data to the real-time processing service by sending a real-time data stream.

4. The method according to claim 1, wherein: The delayed aggregation and association processing of the filtered record data of the resource funnel system further includes: At every first preset time interval, aggregation and association processing is performed on the filtered record data uploaded to the log system by the resource funnel system.

5. The method according to any one of claims 1 to 4, wherein: The aggregation association process comprises the following steps: Aggregate the filtered record data of the resource funnel system to obtain resource layer funnel data; The resource layer funnel data is associated with the account index information to which the resource belongs to obtain the account layer funnel data.

6. The method according to claim 5, wherein: Before associating the resource layer funnel data with the account index information to which the resources belong, the method further includes: The account index information is pulled from the index pool at every second preset time interval through the preset plug-in.

7. The method according to any one of claims 1 to 6, wherein: The resource funnel system includes multiple levels of funnel subsystems, and the funnel subsystems at different levels use different filtering strategies to perform filtering processing. The filtering record data of the resource funnel system includes the filtering record data of the multiple levels of funnel subsystems.

8. A resource placement data checking device, comprising: The first processing module is used to perform delayed aggregation and association processing on the filtered record data of the resource funnel system, and write the processed account-level funnel data into the database; The second processing module is used to perform real-time aggregation and association processing on the filtered record data of the resource funnel system, and write the processed account-level funnel data into the cache; Wherein, the filtering record data is used to record the filtering events of resources by the resource funnel system; A query module, used to query the database and the cache respectively according to the query conditions of the query party; The indicator processing module is used to calculate the delivery indicator data according to the queried target account layer funnel data, and display the delivery indicator data to the querying party.

9. A computing device comprising: A processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute an operation corresponding to the resource delivery data screening method according to any one of claims 1-7.

10. A computer storage medium, wherein at least one executable instruction is stored in the storage medium, and the executable instruction enables a processor to execute operations corresponding to the resource delivery data screening method according to any one of claims 1 to 7.

11. A computer program product, comprising at least one executable instruction, wherein the executable instruction enables a processor to execute operations corresponding to the resource allocation data screening method according to any one of claims 1 to 7.

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