WO2018196650A1 - Procédé et dispositif d'acquisition de données de caractéristiques d'utilisateur, serveur et support - Google Patents

Procédé et dispositif d'acquisition de données de caractéristiques d'utilisateur, serveur et support Download PDF

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Publication number
WO2018196650A1
WO2018196650A1 PCT/CN2018/083298 CN2018083298W WO2018196650A1 WO 2018196650 A1 WO2018196650 A1 WO 2018196650A1 CN 2018083298 W CN2018083298 W CN 2018083298W WO 2018196650 A1 WO2018196650 A1 WO 2018196650A1
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Prior art keywords
data
user
access request
data access
database
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PCT/CN2018/083298
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English (en)
Chinese (zh)
Inventor
王海平
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平安科技（深圳）有限公司
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Publication of WO2018196650A1 publication Critical patent/WO2018196650A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/25—Integrating or interfacing systems involving database management systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/10—File systems; File servers
    • G06F16/17—Details of further file system functions
    • G06F16/178—Techniques for file synchronisation in file systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/10—File systems; File servers
    • G06F16/18—File system types
    • G06F16/182—Distributed file systems

Definitions

  • the present application belongs to the field of Internet technologies, and in particular, to a method, an apparatus, a server, and a medium for acquiring user feature data.
  • business systems For example, financial and insurance companies have various types of business systems, such as life insurance insurance systems, property insurance insurance systems, and customer personal information systems. Each business system has its own independent database, which stores the operational data of the enterprise in this business.
  • the embodiment of the present application provides a method, an apparatus, a server, and a medium for acquiring user feature data, so as to solve the problem that in the prior art, when multi-service database is distributed, it is difficult to quickly acquire multi-dimensional user feature data. problem.
  • a first aspect of the embodiment of the present application provides a method for acquiring user feature data, including:
  • the calculation engine is used to analyze and summarize the synchronized user basic data, and the feature data corresponding to each user is obtained;
  • a second aspect of the embodiments of the present application provides a device for acquiring user feature data, where the device for acquiring user feature data includes a module for performing a method for acquiring user feature data according to the above first aspect.
  • a third aspect of an embodiment of the present application provides a server including a memory and a processor, the memory storing computer readable instructions executable on the processor, the processor executing the computer readable The steps of the method for acquiring user feature data as described in the first aspect are implemented when instructed.
  • a fourth aspect of the embodiments of the present application provides a computer readable storage medium storing computer readable instructions, the computer readable instructions being executed by a processor to implement the first aspect as described in the first aspect The steps of the method of obtaining user characteristic data.
  • the multi-service database in the case that the multi-service database is separated, by constructing a user attribute library that summarizes the basic data of each user, the feature data corresponding to each user can be quickly parsed based on the calculation engine, and the user feature data is realized. Comprehensive assessment. Moreover, since the analysis and aggregation process is performed in the user attribute library, it does not affect the operation of the existing business system. In addition, by receiving the data access request by using the interface, each service system can conveniently obtain the feature data of the user, and can provide accurate functions for personalized service customization and service recommendation according to different feature data corresponding to different users. data support. At the same time, since the business system needs to perform conversion processing on the user basic data in other service databases by itself, the efficiency of the user system for obtaining the user characteristic data is improved.
  • FIG. 1 is a flowchart of an implementation of a method for acquiring user feature data provided by an embodiment of the present application
  • FIG. 2 is a flowchart of an implementation of a method for acquiring user feature data according to another embodiment of the present application
  • FIG. 3 is a specific implementation flowchart of a method S4 for acquiring user feature data according to an embodiment of the present application
  • FIG. 4 is a flowchart of another specific implementation of the method S4 for acquiring user feature data provided by the embodiment of the present application;
  • FIG. 5 is a schematic diagram of an application scenario applicable to a method for acquiring user feature data according to an embodiment of the present disclosure
  • FIG. 6 is a structural block diagram of an apparatus for acquiring user feature data according to an embodiment of the present application.
  • FIG. 7 is a schematic diagram of a server provided by an embodiment of the present application.
  • the method for acquiring user feature data may be executed on a server on which a distributed file system is installed.
  • the distributed file system can be a Hadoop distributed file system (HDFS file system), which can be adapted to run on common hardware (commodity) Hardware) provides high throughput data access.
  • HDFS file system Hadoop distributed file system
  • FIG. 1 is a flowchart showing an implementation process of a method for acquiring user feature data provided by an embodiment of the present application, which is described in detail as follows:
  • S1 Synchronize user-based data in each business database to a distributed file system to build a user attribute library.
  • the service database is used to manage and store data resources generated by the service system, and the data resources include user basic data.
  • the user refers to the customer directly facing the business, that is, the user basic data is the business data or basic information related to the customer.
  • the user-based data generated by the life insurance system is the personal basic data of the policy customer.
  • User-based data generated by different business systems can be stored in different business databases.
  • the HDFS file system of the user-based data constitutes a user attribute library, which is also a database.
  • the synchronization method can meet the construction requirements of the user attribute library.
  • the calculation engine is used to analyze and summarize the synchronized user basic data, and the feature data corresponding to each user is obtained.
  • SPARK refers to Apache Spark, which is a fast and universal computing engine designed for large-scale data processing.
  • the SPARK Compute Engine enables memory-distributed datasets to optimize iterative workloads in addition to providing interactive queries.
  • the user attribute library uses the SPARK calculation engine and the ETL (Extraction, Transformation, Loading) tool to perform conversion and filtering analysis on the collected large amount of user basic data, and finally loads the processing result into the data warehouse according to the predefined data warehouse model.
  • the processing result is the summarized user characteristic data.
  • the user characteristic data stored in the user attribute database is summary information for the usage, usage habits, and attention service of the user in each business system, and is summary statistics for each user.
  • a Hadoop distributed file system can be composed of multiple servers.
  • the user base data is synchronized to the HDFS file system
  • the user base data from different service databases can also be synchronized to different servers, and each server uses the SPARK calculation engine and the ETL tool to synchronize the users on the server.
  • the basic data is analyzed and summarized, and then the analysis results of each server are summarized.
  • the user attribute library uses multiple servers in parallel to implement analysis and summary of user basic data, the data processing efficiency of the system is improved.
  • S3 Obtain a data access request sent by the service system based on the interface of the user attribute library.
  • the interface is a shared boundary between the user attribute library and other external components for information exchange. It is developed by using the java servlet, and is composed of a preset expression program structure and data provided by a preset SQL language.
  • the user's feature data is published externally by the interface of the user attribute library. If other business systems within the enterprise need to obtain or invoke the feature data of a certain user, the interface provided by the user attribute library is invoked by the post method to issue a data access request.
  • the user attribute library interacts with the business system through the http protocol.
  • step S1 specifically includes:
  • the method for acquiring the user feature data further includes:
  • the JOB is a function provided by the database to periodically execute a certain stored procedure or a package body.
  • the data synchronization is implemented by the SQL JOB timing job at the database level.
  • the implementation principle includes: creating a data synchronization task by using the JOB method, and in the execution condition corresponding to the data synchronization task, Set the task execution time and the task execution interval. When the current time reaches the preset task execution time, or when the difference between the current time and the task execution time is a multiple of the task execution interval, the HDFS file system is created to establish a database connection for each service.
  • the database is connected.
  • the SQL statement preset to the HDFS file system is executed, and according to the syntax analysis result of the SQL statement, if the table parameter corresponding to the SQL statement exists in the service database, the HDFS file system is preset from the service database by the identity authority.
  • the user base data is read and the read user base data update is inserted into the HDFS file system.
  • the HDFS file system creates a database connection that includes creating a dblink for the remote database. Based on the dblink method, the HDFS file system can quickly acquire the user base data of the remote service database as fast as accessing the local database, thereby improving synchronization efficiency.
  • the data to be synchronized preset in the data synchronization task of the JOB mode is the user basic data generated by the service system within a preset time period
  • the HDFS file system when the data synchronization task is executed, only puts the service system in the pre-predetermined time.
  • the preset time period is from the first day of the month to the day before. That is, the HDFS file system only synchronizes the user-based data generated by the business system from the 1st of the month to the day.
  • the user base data in the service database is still in the real-time update state because the day has not passed. Therefore, in order to prevent the HDFS file system from being synchronized, the user base data in the service database is updated again. As a result, the HDFS file system and the service database are not substantially synchronized.
  • the HDFS file system performs the data synchronization task, only the user basic data generated by the business system before the day is synchronized.
  • the effective time of the user's business is calculated on a monthly basis, and the 31st of each month is the expiration date, for example, the user is insured for 5 on October 2
  • the monthly life insurance policy the March 31 of the second year is the expiration date of the policy.
  • the HDFS file system only synchronizes monthly. User-based data generated by the business system from the 1st to the day.
  • the user basic data is divided into a common level and an important level according to the user level.
  • the user property library is pre-configured with two JOB tasks for setting the analysis summary action execution time of the user base data of the common level and the important level.
  • the user attribute library performs an analysis and summary operation on the user-level data of the synchronized important level according to the rules preset by the JOB task, and performs the analysis summary operation on the weekly basis for the user-level data of the common level.
  • the user attribute library performs an analysis summary operation on the user base data only during the non-access busy period.
  • the business system usually concentrates on accessing the user characteristic data in the user attribute database during the time period from 09:00 to 18:00, and the JOB task analyzes and summarizes the user basic data that has been synchronized to the local.
  • the task execution time can be set to 0:00 in the morning.
  • the execution time of the analysis and summary action of the user attribute database is limited, so that when the service system issues a data access request, the user attribute database can respond in time, and does not occupy too much due to the analysis and summary operation.
  • System resources improve the response efficiency of the user property library.
  • S4 Verify the validity of the data access request, and if the data access request is legal, return the feature data of the user that matches the data access request to the service system.
  • the user attribute database When the user attribute database receives the data access request based on the user feature data sent by any service system from the interface, it does not immediately return the user's feature data to the service system, but first determines whether the data access request is legal, including: Whether the source of the data access request satisfies the preset data acquisition authority and determines whether the data content of the data access request is abnormal. Only when the data access request is legal, the user property library queries and returns the user feature data requested by the business system. The user feature data requested by the service system is the feature data that matches the user number carried in the data access request. The user attribute library performs a query from the stored data according to the user number, and converts the feature data obtained by the query into data in an xml format and returns.
  • FIG. 3 shows a specific implementation process of the foregoing step S4, which is described in detail as follows:
  • S411 Determine whether the IP address carried by the data access request and the access key are both present in a configuration file of the user attribute database.
  • the user attribute library parses the received data access request, and reads the first attribute value corresponding to the source IP field and the second attribute value corresponding to the access key field from the data report of the data access request, then the first An attribute value is an IP address carried by the data access request, and represents an IP address currently used by the service system that issues the data access request, and the second attribute value is an access key, which is input by the operator of the service system. Account key.
  • the user property library loads the settings of the environment and the collection of files that it needs, which is the configuration file.
  • the source IP address and the access key that are allowed to acquire the user feature data are pre-stored in the configuration file.
  • the legal IP address saved in the configuration file includes the exact IP address, IP address segment, or IP address in the form of a wildcard. As long as the user attribute database detects that the IP address carried by the data access request is the same as the IP address in the configuration file or belongs to any IP address segment in the configuration file, it may be determined that the IP address carried by the data access request exists. In the configuration file of the user property library.
  • IP address and the access key carried in the data access request are both in the configuration file of the user attribute database, acquire attribute information in the data access request, where the attribute information includes a data request parameter. And an encrypted visitor signature.
  • the visitor signature is key data attached to the data access request or a transformation of the key data.
  • the user attribute library decrypts the received visitor signature by using a pre-agreed decryption key, thereby determining whether the source of the data access request is a real authorized user, and confirming the message integrity of the data access request, thereby receiving the illegality
  • the user attribute library can also recognize and respond to the data access request, thereby improving the transmission security of the user characteristic data.
  • the user attribute library does not respond to the data access request.
  • S413 Perform decryption processing on the visitor signature, determine whether the decrypted signature of the visitor is the same as the signature in the configuration file, and determine whether the data request parameter satisfies a preset condition.
  • the preset condition is the grammatical structure rule, including the character type attribute and the range of the value range. Only when each data request parameter in the data access request satisfies a preset grammatical structure rule, the user attribute database determines that the data access request is legal and responds to the data access request, that is, according to the characteristic data of the required user. After querying the feature data corresponding to the user from the user attribute library, return to the business system that issued the data access request.
  • the user attribute database If the decrypted visitor signature is different from the signature in the configuration file, and any data request parameter in the data access request does not satisfy the preset syntax structure rule, the user attribute database generates an error prompt information, and based on the error prompt information. Respond to the data access request.
  • the IP address and the access key carried in the data access request exist in the configuration file of the user attribute database and the signature of the visitor is legal
  • the content of the data access request message is "select" Name from persons”
  • the parameter type after "from” should be the table name, and the user attribute library does not have the "persons" table, therefore, the user attribute library determines that the data request parameter is not satisfied.
  • the default syntax structure rules, and the generated error message packet is returned through the interface to the business system that issues the data access request.
  • the user attribute library when receiving the data access request, the user attribute library first determines whether the number of data access requests received in the first time period reaches a preset threshold.
  • the first time period is a time interval from when the data access request is received to when the data access request is received, and the length of the first time period is a preset duration. If the number of data access requests received in the first time period has reached a preset threshold, the data access request received at the current time does not respond, and the above steps S411 to S414 are not performed.
  • the user attribute library determines the number of data access requests within the preset duration, and can not make any response when the number exceeds the threshold, thereby preventing the user attribute library from continuously processing a large number of data access requests, and controlling The processing frequency of the data access request ensures the normal operation of the user attribute library.
  • the view is performed in a view manner.
  • the service system directly invokes the view provided by the user attribute library through the foregoing interface, and can directly request the user feature data corresponding to the view. Therefore, when the storage data is adjusted within the user attribute library, since the view and the interface are not changed, the service system that invokes the user attribute data of the user attribute library through the interface and the view will not be affected, and the adjustment process is performed on the service. The system is invisible.
  • the interface can still pass through the interface.
  • the user view data obtained by the embodiment of the present application ensures the normal operation of the service system and improves the reliability of the service system.
  • FIG. 4 shows another specific implementation flow of the foregoing step S4, which is described in detail as follows:
  • S421 Acquire an IP address of the data access request.
  • S422 Acquire a total number of historical data access requests based on the IP address within a preset duration.
  • the user attribute database determines that the source IP of the data access request received in the preset time period is the same as the IP address in S421.
  • the preset time period is a time interval from a moment before the data access request is received to when the data access request is received, and the length of the preset time period is a preset duration.
  • the detailed message of the above log file includes information such as the source time of each data access request, the request parameter, the source IP, the processing duration of the user attribute database for each data access request, and the processing result.
  • the data access request is cached. If the duration of the data access request cached in the pre-created cache area has reached the preset duration, the user attribute database performs legality verification on the data access request.
  • the data access request is not responded.
  • the resource occupancy of the malicious data request to the user attribute database can be alleviated in the case of a malicious request, and the user attribute is guaranteed.
  • the normal operation of the library by performing log records on the received data access requests, it is possible to provide maintenance personnel with troubleshooting clues and improve maintenance efficiency after a problem occurs in the user attribute library after the maintenance process.
  • the user attribute library also provides a monitoring interface for the external monitoring server for monitoring the interface service of the user attribute library.
  • the monitoring server continuously detects whether the monitoring interface returns a normal response packet for 24 hours. When the normal response packet is not received, it indicates that the interface service is abnormal. At this time, the monitoring server will issue an alarm prompt, so that the operation and maintenance personnel can quickly perform troubleshooting and restore the interface service as soon as possible, so that the user interface can be improved based on the monitoring interface. Reliability to avoid disruption of business systems.
  • the application database is interconnected with the life insurance system database, the property insurance system database, and the financial fund database through a network.
  • the application database is used to synchronize the basic information of each user in the life insurance system database, the property insurance system database and the wealth management fund database to the local, so that the application database is constructed as the above user attribute library.
  • the application database utilizes the SPARK calculation engine to perform comprehensive analysis and processing on the basic information of each user that has been synchronized locally, and for any user, based on the life insurance insurance status of the user, the property insurance insurance status, and the purchase of the financial fund, etc.,
  • the database will fully evaluate the user's consumption behavior characteristics data.
  • the short MMS push system inside the enterprise requests and acquires the consumption behavior characteristic data of the user A in the application database via the user unified view query interface provided by the application database, and the short multimedia message pushing system returns the characteristics according to the application database.
  • Data knowing that user A is accustomed to purchasing stock funds and hybrid funds, so the short-letter push system is selected to send push information about stock funds and hybrid funds, and the push information is sent to user A's mobile phone through SMS. . Therefore, based on the interface provided by the application database and the user characteristic data summarized and analyzed based on the application database, the business system such as the short multimedia messaging system realizes personalized customization of the user and service recommendation.
  • FIG. 6 is a structural block diagram of the device for acquiring user feature data provided by the embodiment of the present application. For the convenience of description, only the embodiment of the present application is shown. Related parts.
  • a device for acquiring user feature data includes:
  • the synchronization module 61 is configured to synchronize user basic data in each service database to a distributed file system to construct a user attribute library.
  • the summary module 62 is configured to analyze and summarize the synchronized user basic data by using a calculation engine to obtain feature data corresponding to each user.
  • the obtaining module 63 is configured to obtain a data access request sent by the service system based on the interface of the user attribute library.
  • the returning module 64 is configured to verify the validity of the data access request, and if the data access request is legal, return the feature data that matches the data access request to the service system.
  • the returning module 74 includes:
  • the determining submodule is configured to determine whether the IP address carried by the data access request and the access key are both present in a configuration file of the user attribute database.
  • a first obtaining submodule configured to acquire attribute information in the data access request, if the IP address and the access key carried by the data access request are both in a configuration file of the user attribute database,
  • the attribute information includes the visitor signature and the data request parameters.
  • a first returning submodule configured to: if the decrypted signature of the visitor is the same as the signature in the configuration file, and the data request parameter satisfies a preset condition, the data access request is legal, and the The feature data matched by the data access request is returned to the business system.
  • the synchronization module 61 includes:
  • the first synchronization sub-module is configured to synchronize the user-based data in each service database to the distributed file system at a preset time interval based on the JOB mode to construct a user attribute library.
  • the device for acquiring user feature data further includes:
  • a storage module configured to save feature data corresponding to each user to a temporary table of the user attribute library, and delete the user basic data in each service database to the user attribute database next time The feature data already stored in the temporary table.
  • the returning module 64 includes:
  • the second obtaining submodule is configured to obtain an IP address of the data access request.
  • the third obtaining submodule is configured to obtain a total number of historical data access requests based on the IP address within a preset duration.
  • a cache submodule configured to cache the data access request if the total number of historical data access requests based on the IP address is greater than a preset threshold within a preset duration, and to cache the The validity of the data access request is verified.
  • a second returning submodule configured to return the feature data that matches the data access request to the service system if the data access request is legal.
  • the synchronization module 61 includes:
  • the second synchronization sub-module is configured to synchronize user basic data in a preset time period to a distributed file system in each service database to construct a user attribute library.
  • the preset time period is the first day of the current month to the day before the current time.
  • FIG. 7 is a schematic diagram of a server according to an embodiment of the present application.
  • the server 7 of this embodiment includes a processor 70 and a memory 71 in which computer readable instructions 72, such as user feature data, are executable to run on the processor 70. program.
  • the processor 70 executes the computer readable instructions 72, the steps in the foregoing method for acquiring the respective user feature data are implemented, for example, steps 101 to 104 shown in FIG.
  • the processor 70 when executing the computer readable instructions 72, implements the functions of the various modules/units in the various apparatus embodiments described above, such as the functions of the modules 61-64 shown in FIG.
  • the computer readable instructions 72 may be partitioned into one or more modules/units that are stored in the memory 71 and executed by the processor 70, To complete this application.
  • the one or more modules/units may be a series of computer readable instruction segments capable of performing a particular function for describing the execution of the computer readable instructions 72 in the server 7.
  • the server 7 can be a computing device such as a desktop computer, a notebook, a palmtop computer, and a cloud server.
  • the server may include, but is not limited to, processor 70 and memory 71. It will be understood by those skilled in the art that FIG. 7 is only an example of the server 7, and does not constitute a limitation on the server 7, and may include more or less components than those illustrated, or combine some components, or different components, such as
  • the server may also include an input and output device, a network access device, a bus, and the like.
  • the so-called processor 70 can be a central processing unit (Central Processing Unit, CPU), can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (Application Specific Integrated Circuit (ASIC), Field-Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, etc.
  • the general purpose processor may be a microprocessor or the processor or any conventional processor or the like.
  • the memory 71 may be an internal storage unit of the server 7, such as a hard disk or a memory of the server 7.
  • the memory 71 may also be an external storage device of the server 7, such as a plug-in hard disk equipped with the server 7, a smart memory card (SMC), and a Secure Digital (SD) card. Flash card, etc.
  • the memory 71 may also include both an internal storage unit of the server 7 and an external storage device.
  • the memory 71 is configured to store the computer readable instructions and other programs and data required by the server.
  • the memory 71 can also be used to temporarily store data that has been output or is about to be output.
  • each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
  • the above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.
  • the integrated unit if implemented in the form of a software functional unit and sold or used as a standalone product, may be stored in a computer readable storage medium.
  • a computer readable storage medium A number of instructions are included to cause a computer device (which may be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present application.
  • the foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and the like, which can store program codes. .

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Abstract

L'invention concerne un procédé et un dispositif d'acquisition de données de caractéristiques d'utilisateur, un serveur et un support, applicables au domaine technique de l'Internet. Le procédé consiste à : synchroniser des données de base d'utilisateur dans chaque base de données de service avec un système de fichiers distribué pour construire une bibliothèque d'attributs d'utilisateur; utiliser un moteur informatique pour analyser et résumer les données de base d'utilisateur synchronisées afin d'obtenir des données de caractéristiques correspondant à chaque utilisateur; sur la base d'une interface de la bibliothèque d'attributs d'utilisateur, obtenir une demande d'accès à des données envoyée par un système de service; et vérifier la validité de la demande d'accès à des données, et si la demande d'accès à des données est valide, renvoyer, au système de service, des données de caractéristiques d'utilisateur correspondant à la demande d'accès à des données. Lorsque de multiples bases de données de service sont séparées, la solution peut rapidement obtenir des données de caractéristiques correspondant à chaque utilisateur. Les données de caractéristiques d'utilisateur sont évaluées de manière globale, et les opérations du système de service ne sont pas affectées. Un support de données précis est fourni pour des fonctions telles qu'une personnalisation de service personnalisée et une recommandation de service.
PCT/CN2018/083298 2017-04-26 2018-04-17 Procédé et dispositif d'acquisition de données de caractéristiques d'utilisateur, serveur et support WO2018196650A1 (fr)

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CN107798037A (zh) * 2017-04-26 2018-03-13 平安科技（深圳）有限公司 用户特征数据的获取方法及服务器
CN108959337A (zh) * 2018-03-22 2018-12-07 中国平安人寿保险股份有限公司 大数据获取方法、装置、设备及存储介质
CN109375913B (zh) * 2018-09-11 2022-04-08 中铁程科技有限责任公司 数据处理方法及装置
CN110990466B (zh) * 2018-09-29 2023-04-07 北京国双科技有限公司 一种数据同步方法及装置
CN111367782B (zh) * 2018-12-25 2023-08-15 中国移动通信集团浙江有限公司 回归测试数据自动生成的方法及装置
CN110336791B (zh) * 2019-05-29 2022-02-22 平安科技（深圳）有限公司 一种断点数据传输方法、装置、设备及计算机存储介质
CN110598993B (zh) * 2019-08-19 2023-04-18 深圳市鹏海运电子数据交换有限公司 数据加工方法及装置
CN110515967B (zh) * 2019-08-30 2020-09-08 望海康信(北京)科技股份公司 基于spark计算框架的数据分析方法及电子设备
CN111813405A (zh) * 2020-06-29 2020-10-23 四川长虹电器股份有限公司 一种快速更新和发布目标数据接口的方法
CN112364021B (zh) * 2020-11-10 2023-10-13 中国平安人寿保险股份有限公司 业务数据处理方法、装置及存储介质
CN113987324A (zh) * 2021-10-21 2022-01-28 北京达佳互联信息技术有限公司 一种数据处理方法、装置、设备及存储介质

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103034650A (zh) * 2011-09-29 2013-04-10 北京新媒传信科技有限公司 一种数据处理系统和方法
CN103136335A (zh) * 2013-01-31 2013-06-05 北京千分点信息科技有限公司 一种基于数据平台的数据控制方法
US20150332337A1 (en) * 2014-05-14 2015-11-19 Korea Electronics Technology Institute Technology of assisting context based service
CN105512336A (zh) * 2015-12-29 2016-04-20 中国建设银行股份有限公司 一种基于Hadoop的海量数据处理方法和装置
CN106547766A (zh) * 2015-09-18 2017-03-29 华为技术有限公司 一种数据访问方法和装置
CN107798037A (zh) * 2017-04-26 2018-03-13 平安科技（深圳）有限公司 用户特征数据的获取方法及服务器

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103034650A (zh) * 2011-09-29 2013-04-10 北京新媒传信科技有限公司 一种数据处理系统和方法
CN103136335A (zh) * 2013-01-31 2013-06-05 北京千分点信息科技有限公司 一种基于数据平台的数据控制方法
US20150332337A1 (en) * 2014-05-14 2015-11-19 Korea Electronics Technology Institute Technology of assisting context based service
CN106547766A (zh) * 2015-09-18 2017-03-29 华为技术有限公司 一种数据访问方法和装置
CN105512336A (zh) * 2015-12-29 2016-04-20 中国建设银行股份有限公司 一种基于Hadoop的海量数据处理方法和装置
CN107798037A (zh) * 2017-04-26 2018-03-13 平安科技（深圳）有限公司 用户特征数据的获取方法及服务器

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