Push data configuration method, device, equipment, medium and program product

Abstract

The present application provides a method, device, equipment, medium and program product for pushing data configuration, which parses the regulatory requirement information released by the regulatory node to determine the regulatory data collection table in the first database, then extracts the business data into the second database for preprocessing to determine the target data, and pushes the target data to the third database in a preset format, and then uses the preset configuration tool to configure the target data into the regulatory data collection table, wherein the first database is used to push the business data of the business node to the regulatory node, the second database is used to extract the business data of the business node, the first database and the second database include relational databases, and the third database includes a non-relational database. With the help of the non-relational third database, the technical problem that the transfer mapping of data between two relational databases in the prior art requires additional customized development and writing of special code is solved. The operation and maintenance workload of the data push platform is simplified.

Description

Technical Field

[0001] The present application relates to the field of database technology, and in particular to a method, device, equipment, medium and program product for pushing data configuration. Background Art

[0002] With the continuous development of economy and society, especially after the popularization of Internet technology, many business activities need network systems to assist in operation and management. Generally, in a network system, a business node is responsible for the execution of specific business activities and reports the data of business activities to the regulatory node where the regulatory agency is located, so that the regulatory agency can supervise whether the business activities of the business node meet the regulatory requirements.

[0003] The business data generated by the business node is generally stored in the business database, and the supervision node needs to review the business activities of the business node by reading the data in the supervision database. Therefore, it is necessary to push the data in the business database to the supervision database. However, in the prior art, since the two databases are built and maintained separately, generally speaking, the construction of the database will adopt more mature database technology, such as MySQL relational database, but the push of data between the two relational databases requires the development of specially customized SQL language code to achieve.

[0004] However, with the rapid development of business, business nodes continue to increase, and more regulatory nodes also need to be connected to the data push platform. This makes the operation and maintenance of the data push platform fall into the repetitive work of constantly customizing and developing data push between various databases, which is time-consuming and labor-intensive, and increases operation and maintenance costs. Therefore, there is a technical problem in the prior art that the transfer mapping of data between two relational databases requires additional customization and development of special codes. Summary of the invention

[0005] The present application provides a push data configuration method, device, equipment, medium and program product to solve the technical problem in the prior art that the transfer mapping of data between two relational databases requires additional customized development and writing of special codes.

[0006] In a first aspect, the present application provides a push data configuration method, comprising:

[0007] parsing the regulatory requirement information issued by at least one regulatory node to determine a regulatory data collection table in a first database, the first database being used to push business data of at least one business node to the regulatory node, the first database comprising a relational database;

[0008] Extracting the business data into a second database for preprocessing to determine target data, and pushing the target data into a third database in a preset format, wherein the second database includes a relational database and the third database includes a non-relational database;

[0009] Use the preset configuration tool to configure the target data into the regulatory data collection form.

[0010] In a possible design, the target data is pushed to the third database in a preset format, including:

[0011] Using a preset conversion tool, converting a target data table in the second database into key-value pair data, the target data table being used to store the target data;

[0012] The key-value pair data is sent to the third database.

[0013] In a possible design, the non-relational database includes a document database, and sending key-value pair data to a third database includes:

[0014] Store the key-value pair data into at least one document in a preset order;

[0015] Among them, the document database is used to store documents.

[0016] In a possible design, the document includes a text file, and a preset configuration tool is used to configure the target data into the regulatory data collection form, including:

[0017] Using the preset configuration tool, according to the preset correspondence, the string data in the text file is configured to the corresponding fields in the supervision data collection table.

[0018] In a possible design, the target data includes: basic data and business data, the basic data includes characteristic parameters of the business node, and correspondingly, the data table in the second database includes: a basic data table and a business data table, and the business data is extracted into the second database for preprocessing to determine the target data, including:

[0019] Use data extraction tools to extract basic data corresponding to business nodes based on basic data tables;

[0020] Use data extraction tools to extract business data corresponding to business nodes based on business data tables.

[0021] Optionally, before parsing the regulatory requirement information issued by at least one regulatory node, the method further includes:

[0022] When a preset trigger signal is detected, the supervision information of the target supervision node is obtained.

[0023] In a possible design, the preset trigger signal includes: a newly added business node, a newly added supervision node, a change in the scope of business nodes under the jurisdiction of the supervision node, and a change in the reporting requirement information of the supervision node.

[0024] In a second aspect, the present application provides a push data configuration device, comprising:

[0025] A parsing module, used to parse the regulatory requirement information issued by at least one regulatory node to determine the regulatory data collection table in a first database, the first database is used to push the business data of at least one business node to the regulatory node, the first database includes a relational database;

[0026] An extraction module, used to extract the business data into a second database for preprocessing to determine target data, and push the target data into a third database in a preset format, the second database includes a relational database, and the third database includes a non-relational database;

[0027] The configuration module is used to configure the target data into the regulatory data collection table using a preset configuration tool.

[0028] In one possible design, the extraction module is specifically used to:

[0029] Using a preset conversion tool, converting a target data table in the second database into key-value pair data, the target data table being used to store the target data;

[0030] The key-value pair data is sent to the third database.

[0031] In one possible design, the non-relational database includes a document database, an extraction module for storing key-value pair data in at least one document in a preset order;

[0032] Among them, the document database is used to store documents.

[0033] In a possible design, the document includes a text file and a configuration module for using a preset configuration tool to configure the string data in the text file to the corresponding fields in the supervision data collection table according to a preset correspondence.

[0034] In a possible design, the target data includes: basic data and business data, the basic data includes characteristic parameters of the business node, and correspondingly, the data table in the second database includes: a basic data table and a business data table;

[0035] Correspondingly, the extraction module is specifically used for:

[0036] Use data extraction tools to extract basic data corresponding to business nodes based on basic data tables;

[0037] Use data extraction tools to extract business data corresponding to business nodes based on business data tables.

[0038] Optionally, the parsing module is further used to obtain the supervision information of the target supervision node when a preset trigger signal is detected.

[0039] In a possible design, the preset trigger signal includes: a newly added business node, a newly added supervision node, a change in the scope of business nodes under the jurisdiction of the supervision node, and a change in the reporting requirement information of the supervision node.

[0040] In a third aspect, the present application provides an electronic device, including:

[0041] A memory for storing program instructions;

[0042] The processor is used to call and execute the program instructions in the memory to execute any possible push data configuration method provided by the first aspect.

[0043] In a fourth aspect, the present application provides a storage medium, wherein the readable storage medium stores a computer program, and the computer program is used to execute any possible push data configuration method provided in the first aspect.

[0044] In a fifth aspect, the present application also provides a computer program product, including a computer program, which, when executed by a processor, implements any possible push data configuration method provided in the first aspect.

[0045] The present application provides a method, device, equipment, medium and program product for pushing data configuration, which parses the regulatory requirement information issued by at least one regulatory node to determine the regulatory data collection table in the first database, then extracts the business data into the second database for preprocessing to determine the target data, and pushes the target data to the third database in a preset format, and then uses the preset configuration tool to configure the target data into the regulatory data collection table, wherein the first database is used to push the business data of the business node to the regulatory node, the second database is used to extract the business data of the business node, the first database and the second database include relational databases, and the third database includes a non-relational database. With the help of the non-relational third database, the technical problem that the transfer mapping of data between two relational databases in the prior art requires additional customized development and writing of special codes is solved. The technical effect of saving the step of individually customizing the data reporting logic code for each business node when the business node reports data to the regulatory node is achieved, and the operation and maintenance workload of the data push platform is simplified. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0047] Figure 1 A schematic diagram of the structure of a data push platform provided in an embodiment of the present application;

[0048] Figure 2 A flowchart of a method for configuring push data provided in an embodiment of the present application;

[0049] Figure 3 A flowchart of another method for configuring push data provided in an embodiment of the present application;

[0050] Figure 4 A schematic diagram of the structure of a push data configuration device provided in an embodiment of the present application;

[0051] Figure 5 A schematic diagram of the structure of an electronic device provided in this application.

[0052] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work, including but not limited to the combination of multiple embodiments, belong to the scope of protection of this application.

[0054] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein, for example. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0055] The logic of the inventive concept of this application is introduced below:

[0056] A business management system generally includes multiple business nodes and at least one supervision node. With the continuous development of business in reality, the number of business nodes continues to increase. At the same time, it may cause the increase of supervision nodes, or the supervision nodes may update the supervision scope or the submission requirements of supervision data.

[0057] In all the above situations, the operation and maintenance personnel of the business management system need to carry out secondary development and maintenance of the business management system. Usually, the business management system uses a business database to extract and store the business data of each business node. Then, through the data push platform, the data required to be reported is pushed to the supervision nodes corresponding to different regulatory agencies, so that the regulatory agencies can supervise the business institutions corresponding to the business nodes.

[0058] Before pushing, the data push platform can build a supervision configuration database specifically for storing pushed data. Before pushing data to the supervision node, the supervision configuration database first extracts and configures the data collection table from the business database.

[0059] Furthermore, in order to meet the diverse and non-uniform data push requirements between multiple regulatory nodes and multiple business nodes, developers are required to continuously update the push code and configuration code for secondary development, which is also a problem that this application needs to further solve.

[0060] Generally speaking, databases are divided into relational databases and non-relational databases. Relational databases are more widely used and mature. SQL (Structured Query Language) databases are the most widely used databases. The above-mentioned business databases, databases established and managed by the supervisory nodes themselves, and supervisory configuration databases are generally relational databases.

[0061] The inventors of the present application have discovered that data push between relational databases must comply with the strict standardization requirements of the SQL language, which requires special code customization and development.

[0062] The inventive concept of this application is to break this inertial thinking, use non-relational databases as intermediate media, decouple and disassemble strict and rigid structured data, simplify the requirements for data push, and improve the scalability of data push. It only takes simple setting of configuration parameters to complete the push configuration of business data from the business database to the regulatory configuration database, and the push of the regulatory configuration database to the regulatory node does not require secondary development, which greatly reduces the workload of developers and reduces operation and maintenance costs.

[0063] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0064] Figure 1 This is a schematic diagram of the structure of a data push platform provided in an embodiment of the present application. Figure 1 As shown, two ends of the data push platform are connected to the business layer 10 and the supervision layer 30 respectively. The business layer 10 includes a plurality of business nodes 11 , and the supervision layer 30 includes a plurality of supervision nodes 31 .

[0065] Each business node 11 must report its business data to its corresponding supervision node 31 to meet the regulatory requirements of laws and regulations and realize the supervision and management function of the supervision node 31 on the business node 11.

[0066] The business data generated by any business node 11 will be collected and stored by the first database 21 at regular intervals, and then pushed to the third database 22 at regular intervals according to a preset format, such as filling in a pre-designed record table corresponding to the business node, and attaching the characteristic parameters corresponding to the business node 11, such as the name and code of the organization corresponding to the business node 11 and other basic information. The third database 22 is a non-relational database. The data pushed from the first database is decoupled by reverse structuring, such as breaking it up into key-value pairs for storage. In this way, it will not be subject to the structural limitations of the table in the first database. When a new business node 11 is added, there is no need to customize the push code from the first database 21 to the second database 23 separately, thereby avoiding repetitive development work and reducing operation and maintenance costs.

[0067] When the supervision node 31 sends a data reporting request to the data push platform, the second database 23 extracts the corresponding target data from the third database 22 , configures it into the corresponding data collection table, and then pushes it to the supervision node 31 .

[0068] The following is a step-by-step introduction to the specific steps of pushing data configuration in the above scenario.

[0069] Figure 2 The following is a flow chart of a method for configuring push data provided in an embodiment of the present application. Figure 2 As shown, the specific steps of the push data configuration method include:

[0070] S201. Parse supervision requirement information issued by at least one supervision node to determine a supervision data collection table in a first database.

[0071] In this step, when a new service node is added to the data push platform, or a new supervision requirement is issued by a supervision node, that is, the data submission format is changed, the push data reconfiguration of this embodiment is triggered.

[0072] In this embodiment, the first database is used to push the service data of at least one service node to the supervision node, and the first database includes a relational database.

[0073] It should be noted that a relational database refers to a database that uses a relational model to organize data. It stores data in the form of rows and columns to facilitate user understanding. This series of rows and columns in a relational database is called a table, and a group of tables constitutes a database. Users retrieve data from the database through queries, and a query is an execution code used to limit certain areas in the database. The relational model can be simply understood as a two-dimensional table model, and a relational database is a data organization composed of two-dimensional tables and the relationships between them.

[0074] Since the relational database is the earliest and most widely used database solution with the most mature technology, the first database in this embodiment retains the setting of the relational database.

[0075] The regulatory requirements information released by the regulatory node is generally released in the form of a table. After receiving the regulatory requirements table, the data push platform extracts each field in the table to obtain the data fields that need to be configured.

[0076] S202: extract the business data into the second database for preprocessing to determine target data, and push the target data into the third database in a preset format.

[0077] In this embodiment, the second database includes a relational database, and the third database includes a non-relational database.

[0078] In this step, at the first preset time, the second database uses a data extraction tool to extract business data from each business node, and stores it in a data table designed by the second database according to the different personalized business characteristics of each business node. Optionally, the first preset time can be a fixed time period, or a reporting time triggered by each business node, or different extraction cycles can be set for each business node.

[0079] It should be noted that the second database is generally designed as a relational database, which can ensure the accuracy and logical rigor of the extracted data.

[0080] Thus, in a possible design, the first database and the second database are relational databases that use SQL language to write management logic, which ensures the rigorous structure and logic of business data input and output, thereby improving data accuracy.

[0081] Next, what needs to be solved is the scalability of the database or the flexibility of data management when transferring data within the data push platform. This embodiment introduces a non-relational database, namely a third database, as an intermediary to achieve inverse structural decoupling when pushing data between the first database and the second database.

[0082] Non-relational database (NoSQL): With the rise of web2.0 websites on the Internet, traditional relational databases have become unable to handle web2.0 websites, especially ultra-large-scale and highly concurrent SNS-type web2.0 purely dynamic websites, and many difficult-to-overcome problems have emerged. However, non-relational databases have developed very rapidly due to their own characteristics. The emergence of NoSQL databases is to solve the challenges brought by large-scale data sets with multiple data types, especially the application of big data.

[0083] Non-relational databases include:

[0084] (1) Key-Value storage database: This type of database mainly uses a hash table, which has a specific key and a pointer to specific data. The advantage of the key / value model for IT systems is that it is simple and easy to deploy. Examples include: Tokyo Cabinet / Tyrant, Redis, Voldemort, and Oracle BDB.

[0085] (2) Column-store databases: These databases are usually used to handle massive amounts of data in distributed storage. Keys still exist, but their characteristic is that they point to multiple columns. These columns are arranged by column family. Examples include Cassandra, HBase, and Riak.

[0086] (3) Document database: The inspiration of document database comes from Lotus Notes office software, and it is similar to the first type of key-value storage. The data model of this type is versioned documents, and semi-structured documents are stored in a specific format, such as JSON. Document database can be regarded as an upgraded version of key-value database, allowing nested keys and values. When processing complex data such as web pages, document database has higher query efficiency than traditional key-value database. For example: CouchDB, MongoDb. There is also a document database SequoiaDB in China, which has been open sourced.

[0087] (4) Graph database: Graph-structured databases are different from other row-column and rigid-structured SQL databases. They use a flexible graph model and can be expanded to multiple servers. NoSQL databases do not have a standard query language (SQL), so a data model needs to be developed to query the database. Many NoSQL databases have REST-style data interfaces or query APIs. For example: Neo4J, InfoGrid, Infinite Graph.

[0088] In a possible design, the second database classifies the extracted business data, such as business basic data and node basic information data, and then converts it into a string in the form of a key-value pair, such as a Json string, and then combines it in a certain order and stores it in a document, which is then stored in the third database. Alternatively, the business basic data and node basic information data are converted into image data, such as a QR code, and stored in the third database.

[0089] This embodiment introduces a non-relational database, i.e., a third database, so that when a business node is added, a supervision node is added, the supervision scope corresponding to the supervision node is changed, or the data report format required by the supervision node is changed, the developer or operation and maintenance personnel only needs to perform a simple corresponding relationship setting in the third database to complete the update of the push data configuration mapping, without having to redesign and write SQL codes to add, delete, modify, and query the first database and the second database as in the prior art, thereby achieving the technical effect of reducing operation and maintenance costs and alleviating the workload of developers.

[0090] S203. Use a preset configuration tool to configure the target data into the regulatory data collection table.

[0091] In this step, the supervision data collection table is the data pushed by the first database to each supervision node, and the content data required to be filled in is extracted from the third database through a preset configuration tool.

[0092] It should be noted that the preset configuration tool is provided with rules for mapping data between the third database and the first database. For example, if the third database is a Json string, a corresponding relationship between it and the field name in the first database needs to be established in advance.

[0093] The target data consists of two parts: the basic information of the business node and the business data generated by the business node.

[0094] This embodiment provides a method for pushing data configuration, which parses the regulatory requirement information issued by at least one regulatory node to determine the regulatory data collection table in the first database, then extracts the business data into the second database for preprocessing to determine the target data, and pushes the target data to the third database in a preset format, and then uses the preset configuration tool to configure the target data into the regulatory data collection table, wherein the first database is used to push the business data of the business node to the regulatory node, the second database is used to extract the business data of the business node, the first database and the second database include relational databases, and the third database includes a non-relational database. With the help of the non-relational third database, the technical problem that the transfer mapping of data between two relational databases in the prior art requires additional customized development and writing of special codes is solved. The technical effect of saving the step of individually customizing the data reporting logic code for each business node when the business node reports data to the regulatory node is achieved, and the operation and maintenance workload of the data push platform is simplified.

[0095] To facilitate understanding, the following is a further detailed explanation taking the supervision of various medical institutions by provincial-level medical regulatory departments as an example.

[0096] Figure 3 A flowchart of another method for configuring push data provided in an embodiment of the present application. Figure 3 As shown, the specific steps of the push data configuration method include:

[0097] S301: When a preset trigger signal is detected, obtain supervision information of a target supervision node.

[0098] In this embodiment, the preset trigger signal includes: a newly added service node, a newly added supervision node, a change in the scope of service nodes under the supervision of a supervision node, and a change in the reporting requirement information of a supervision node.

[0099] In this embodiment, each business node corresponds to each medical institution, and each regulatory node corresponds to the provincial regulatory agency corresponding to the location of the medical structure.

[0100] When a new medical institution joins the business management platform, the business management platform will detect whether it falls within the supervision scope corresponding to the existing supervision node. If so, it will identify its corresponding target supervision node and read the supervision information released by the target supervision node, such as the diagnosis and treatment data collection form that the medical institution needs to report.

[0101] S302: parse the supervision requirement information issued by at least one supervision node to determine the supervision data collection table in the first database.

[0102] In this step, the first database is used to push the service data of at least one service node to the supervision node, and the first database includes a relational database.

[0103] It should be noted that, in this embodiment, the first database is a MySQL database cluster, which includes multiple MySQL relational databases.

[0104] MySQL is a relational database management system that stores data in different tables instead of putting all data in a large warehouse, which increases speed and flexibility. The SQL language used by MySQL is the most commonly used standardized language for accessing databases. However, the realization of these advantages is determined by the custom development of strict SQL codes, which is also the root cause of the repetitive development work for developers when relational databases face increasingly frequent updates, maintenance, migration and expansion.

[0105] In this embodiment, the supervisory configuration database, namely the first database, still retains the advantage of using a relational database, so that its mature and complete advantages can continue to be utilized with less impact on the original code.

[0106] However, in order to make the first database adapt to the push data configuration method provided by this embodiment, the inventor of the present application redesigned its data table, namely the supervision data collection table. Instead of having only one table as before, it is classified hierarchically.

[0107] In this embodiment, the supervision data collection table includes: a service node table, an interface table, and a service data table.

[0108] The business node table is used to store information such as the business node code, introduction, and operation overview.

[0109] The interface table is used to store the interface ID number and interface description corresponding to the service node.

[0110] The business data table is used to store specific data fields corresponding to the interface and corresponding relationship information of fields with the same meaning as those in the third database.

[0111] Specifically, in this embodiment, the business node table is a hospital table (hospital): storing corresponding hospital code ID number, hospital introduction, hospital overview and other information;

[0112] The interface table is the interface data table (hospital_interface) required by different hospitals: it generates the interface ID and interface description that different hospitals need to push to the supervision platform, for example: the interfaces for Internet medical records, Internet medical prescriptions, and Internet medical basic information generated for Huiai Hospital;

[0113] The business data table is the field data table in the interfaces required by different hospitals (hospital_interface_detail): Generate the corresponding relationship between the specific fields required by different data interfaces of different hospitals and the JSONPath expression forms of the fields with the same meaning as those in the corresponding tables in the MongoDB cluster.

[0114] For example, the patient data in MongoDB is: {"name":"Zhang San","age":20,"sex":"male"}, but the patient data fields required by the supervision platform are different, and the corresponding relationship is shown in Table 1:

[0115]

[0116]

[0117] Table 1

[0118] It should be noted that the MongoDB cluster is the specific implementation method of the third database in this embodiment. The JSONPath expression form is the storage form of the data in the third database and is a text-based data type.

[0119] S303. Extract the business data into the second database for preprocessing to determine the target data.

[0120] In this embodiment, the target data includes: basic data and business data. The basic data includes the characteristic parameters of the business nodes. Correspondingly, the data tables in the second database include: basic data tables and business data tables.

[0121] It should be noted that the second database is a relational database, such as the Hive data warehouse.

[0122] Specifically, extract the data in each microservice into the Hive data warehouse to facilitate data correlation processing. The specific steps include:

[0123] S3031. Use the data extraction tool to extract the basic data corresponding to the business nodes according to the basic data table.

[0124] In this embodiment, the data extraction tool is similar to Sqoop, which is mainly used to transfer data between Hadoop (Hive) and traditional databases (mysql, postgresql...). It can import data from a relational database (such as MySQL, Oracle, Postgres, etc.) into HDFS (Hadoop Distributed File System) provided by Hadoop, and can also import HDFS data into a relational database.

[0125] For example, after the data is extracted into the data warehouse, different data are integrated according to the different fields required by different hospitals through hive SQL and stored in the specified hive table.

[0126] Use Hive SQL to assemble the business data extracted regularly from the business data layer to form two types of basic data and business data:

[0127] Basic data includes: patient data, doctor data, department data, and hospital data.

[0128] S3032. Use a data extraction tool to extract business data corresponding to the business node according to the business data table.

[0129] In this embodiment, only one table is designed for business data:

[0130] Patients’ diagnosis and treatment business data (including necessary data of patient data, necessary data of doctor data, necessary data of department data, necessary data of hospital data, consultation order data, prescription data, and medicine purchase order data).

[0131] In this way, basic data plus business data constitute the target data for pushing supervision nodes.

[0132] S304: Use a preset conversion tool to convert the target data table in the second database into key-value pair data.

[0133] In this embodiment, the target data table is used to store target data.

[0134] It should be noted that

[0135] S305: Send key-value pair data to the third database.

[0136] In one possible design, it specifically includes:

[0137] Store the key-value pair data into at least one document in a preset order;

[0138] Among them, the document database is used to store documents.

[0139] It should be noted that, in this embodiment, the third database is set to a MongoDB database cluster.

[0140] Mongodb is a non-relational database (nosql), which belongs to the document database. Documents are the basic unit of data in mongoDB, similar to rows in relational databases. Multiple key-value pairs placed together in order are documents. The syntax is similar to JavaScript object-oriented query language. It is a collection-oriented, schema-free document database.

[0141] Storage method: virtual memory + persistence.

[0142] Query statement: It is a unique MongoDB query method.

[0143] Suitable scenarios: event recording, content management or blog platform, etc.

[0144] Architectural features: High availability can be achieved through replica sets and sharding.

[0145] Data processing: Data is stored on the hard disk, but the data that needs to be read frequently will be loaded into the memory, storing the data in the physical memory, thereby achieving high-speed reading and writing.

[0146] The first database is set as a MySQL database cluster.

[0147] MySQL is a relational database.

[0148] Advantages: Different storage methods are used on different engines.

[0149] The query statement uses traditional SQL statements, which has a relatively mature system and is very mature.

[0150] Disadvantages: The efficiency will be significantly slowed down when processing massive amounts of data.

[0151] In this embodiment,

[0152] 1) MySQL database cluster designs three core tables:

[0153] Hospital table, interface data table required by different hospitals, and field data table in the interface required by different hospitals.

[0154] 2) Core data tables in the MongoDB library (a set of data tables is designed for different hospitals):

[0155] The data stored in MongoDB corresponds to the basic data and business data integrated in the hive data warehouse. Including:

[0156] Basic data: patient data, doctor data, department data, hospital data.

[0157] Business data: patient diagnosis and treatment business data (including necessary data of patient data, necessary data of doctor data, necessary data of department data, necessary data of hospital data, consultation order data, prescription data, and drug purchase order data).

[0158] S306. Using a preset configuration tool, according to a preset correspondence, the character string data in the text file is configured to correspond to the corresponding fields in the supervision data collection table.

[0159] Specifically, when the medical business data layer Figure 1 In the business layer 10, when there are different hospital data, the hive data warehouse processes the data and pushes the patient data, doctor data, department data, hospital data, and patient diagnosis and treatment business data of different hospitals to the MongoDB database. Through the scheduled task loop of different hospitals, the interfaces in different interface data tables (hospital_interface), according to the corresponding relationship between the fields required by the supervision platform stored in the field data table (hospital_interface_detail) in the interface required by different hospitals and the Jsonpath expression of the fields in MongoDB, the data is extracted from MongoDB, assembled into corresponding data, and pushed to the supervision platform.

[0160] The push data configuration method provided in this embodiment saves time for multiple hospitals in multiple provinces to connect with supervision. It only needs to enter the hospital information, the interface information required by the hospital, and the mapping relationship between the various field information required by the hospital interface and the Jsonpath expression of each field in the original MongoDB library table on the page, and then the data can be pushed to the supervision platforms of different provinces in a configured manner without involving additional development work.

[0161] This embodiment provides a method for pushing data configuration, which parses the regulatory requirement information issued by at least one regulatory node to determine the regulatory data collection table in the first database, then extracts the business data into the second database for preprocessing to determine the target data, and pushes the target data to the third database in a preset format, and then uses the preset configuration tool to configure the target data into the regulatory data collection table, wherein the first database is used to push the business data of the business node to the regulatory node, the second database is used to extract the business data of the business node, the first database and the second database include relational databases, and the third database includes a non-relational database. With the help of the non-relational third database, the technical problem that the transfer mapping of data between two relational databases in the prior art requires additional customized development and writing of special codes is solved. The technical effect of saving the step of individually customizing the data reporting logic code for each business node when the business node reports data to the regulatory node is achieved, and the operation and maintenance workload of the data push platform is simplified.

[0162] Figure 4 A schematic diagram of the structure of a push data configuration device provided in an embodiment of the present application.

[0163] The push data configuration device 400 can be implemented by software, hardware or a combination of both.

[0164] like Figure 4 As shown, the push data configuration device 400 includes:

[0165] A parsing module 401, configured to parse the regulatory requirement information issued by at least one regulatory node to determine a regulatory data collection table in a first database, the first database being configured to push business data of at least one business node to the regulatory node, the first database comprising a relational database;

[0166] An extraction module 402 is used to extract the business data into a second database for preprocessing to determine target data, and push the target data into a third database in a preset format, wherein the second database includes a relational database and the third database includes a non-relational database;

[0167] The configuration module 402 is used to configure the target data into the supervision data collection table using a preset configuration tool.

[0168] In one possible design, the extraction module 402 is specifically configured to:

[0169] Using a preset conversion tool, converting a target data table in the second database into key-value pair data, the target data table being used to store the target data;

[0170] The key-value pair data is sent to the third database.

[0171] In one possible design, the non-relational database includes a document database, and the extraction module 402 is used to store the key-value pair data in at least one document in a preset order;

[0172] Among them, the document database is used to store documents.

[0173] In a possible design, the document includes a text file, and the configuration module 402 is used to use a preset configuration tool to configure the string data in the text file to the corresponding field in the supervision data collection table according to the preset correspondence relationship.

[0174] In a possible design, the target data includes: basic data and business data, the basic data includes characteristic parameters of the business node, and correspondingly, the data table in the second database includes: a basic data table and a business data table;

[0175] Correspondingly, the extraction module 402 is specifically used for:

[0176] Use data extraction tools to extract basic data corresponding to business nodes based on basic data tables;

[0177] Use data extraction tools to extract business data corresponding to business nodes based on business data tables.

[0178] Optionally, the parsing module 401 is further configured to obtain the supervision information of the target supervision node when a preset trigger signal is detected.

[0179] In a possible design, the preset trigger signal includes: a newly added business node, a newly added supervision node, a change in the scope of business nodes under the jurisdiction of the supervision node, and a change in the reporting requirement information of the supervision node.

[0180] It is worth mentioning that Figure 4 The device provided in the illustrated embodiment can execute the method provided in any of the above method embodiments. Its specific implementation principles, technical features, professional terminology explanations and technical effects are similar and will not be repeated here.

[0181] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 5 As shown, the electronic device 500 may include: at least one processor 501 and a memory 502 . Figure 5 An electronic device is shown using a processor as an example.

[0182] The memory 502 is used to store programs. Specifically, the programs may include program codes, and the program codes include computer operation instructions.

[0183] The memory 502 may include a high-speed RAM memory, and may also include a non-volatile memory, such as at least one disk memory.

[0184] The processor 501 is used to execute the computer-executable instructions stored in the memory 502 to implement the methods described in the above method embodiments.

[0185] The processor 501 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0186] Optionally, the memory 502 may be independent or integrated with the processor 501. When the memory 502 is a device independent of the processor 501, the electronic device 500 may further include:

[0187] The bus 503 is used to connect the processor 501 and the memory 502. The bus may be an industry standard architecture (ISA) bus, a peripheral component interconnect (PCI) bus, or an extended industry standard architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc., but it does not mean that there is only one bus or one type of bus.

[0188] Optionally, in a specific implementation, if the memory 502 and the processor 501 are integrated on a chip, the memory 502 and the processor 501 can communicate through an internal interface.

[0189] An embodiment of the present application also provides a computer-readable storage medium, which may include: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, and other media that can store program codes. Specifically, the computer-readable storage medium stores program instructions, and the program instructions are used for the methods in the above-mentioned method embodiments.

[0190] An embodiment of the present application further provides a computer program product, including a computer program, which implements the methods in the above-mentioned method embodiments when executed by a processor.

[0191] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the claims of the present application.

[0192] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

[0193] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for configuring push data, characterized in that: include: parsing regulatory requirement information issued by at least one regulatory node to determine a regulatory data collection table in a first database, the first database being used to push business data of at least one business node to the regulatory node, the first database comprising a relational database; The second database extracts the business data into the second database for preprocessing to determine target data, and pushes the target data to a third database in a preset format, wherein the second database includes the relational database, and the third database includes a non-relational database; Utilize the preset configuration tool to extract the target data from the third database to the first database, and configure the extracted target data into the supervision data collection table in the first database; the preset configuration tool is provided with data mapping rules between the third database and the first database.

2. The push data configuration method according to claim 1, characterized in that: The pushing the target data to the third database in a preset format includes: Using a preset conversion tool, converting a target data table in the second database into key-value pair data, wherein the target data table is used to store the target data; The key-value pair data is sent to the third database.

3. The push data configuration method according to claim 2, characterized in that: The non-relational database includes a document database, and sending the key-value pair data to the third database includes: Storing the key-value pair data in at least one document in a preset order; Wherein, the document-type database is used to store the document.

4. The push data configuration method according to claim 3, characterized in that: The document includes a text file, and the using of a preset configuration tool to extract the target data from the third database to the first database, and configuring the extracted target data into a supervision data collection table in the first database, includes: By using a preset configuration tool, according to a preset correspondence, the character string data in the text file is configured to correspond to the corresponding fields in the regulatory data collection table.

5. The push data configuration method according to any one of claims 1 to 4, characterized in that: The target data includes: basic data and the service data, the basic data includes characteristic parameters of the service node, and correspondingly, the data table in the second database includes: a basic data table and a service data table, and the second database extracts the service data into the second database for preprocessing to determine the target data, including: Using a data extraction tool, extracting the basic data corresponding to the service node according to the basic data table; The data extraction tool is used to extract the business data corresponding to the business node according to the business data table.

6. The push data configuration method according to claim 1, characterized in that: Before parsing the regulatory requirement information issued by at least one regulatory node, the method further includes: When a preset trigger signal is detected, the supervision information of the target supervision node is obtained.

7. The push data configuration method according to claim 6, characterized in that: The preset trigger signal includes: adding the service node, adding the supervision node, changing the scope of the service nodes under the supervision of the supervision node, and changing the reporting requirement information of the supervision node.

8. A push data configuration device, characterized in that: include: a parsing module, configured to parse the regulatory requirement information issued by at least one regulatory node to determine a regulatory data collection table in a first database, wherein the first database is used to push the business data of at least one business node to the regulatory node, and the first database includes a relational database; An extraction module, used for the second database to extract the business data into the second database for preprocessing to determine target data, and push the target data to a third database in a preset format, wherein the second database includes the relational database and the third database includes a non-relational database; A configuration module is used to extract the target data from the third database to the first database using a preset configuration tool, and configure the extracted target data into the supervision data collection table in the first database; the preset configuration tool is provided with data mapping rules between the third database and the first database.

9. An electronic device, characterized in that: include: processor and memory; wherein, The memory is used to store a computer program of the processor; The processor is configured to perform the push data configuration method according to any one of claims 1 to 7 by executing the computer program.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the push data configuration method according to any one of claims 1 to 7 is implemented.

11. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the push data configuration method according to any one of claims 1 to 7 is implemented.

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