Method and system for efficiently importing large-scale community population data

Abstract

The invention discloses an efficient import method and system for large-scale community population data, and belongs to the technical field of databases and computer software, the implementation of the method comprises the following steps: data acquisition: collecting to-be-imported data from various data sources, and sending the to-be-imported data to a message queue; the message queue is used as middleware for storing data messages from different data sources and forwarding the data messages to the data import module in sequence; data importing: consuming the data message from the message queue, and importing the data into a target database in batches; and error processing: for any error occurring in the importing process, recording error information by the system, and providing a retry mechanism to ensure that the data is finally correctly imported. According to the method, large-scale population data import tasks can be effectively processed, the efficiency and accuracy of population data import are improved, and more reliable support is provided for data processing and basic data management.

Description

Technical Field

[0001] The present invention relates to the technical fields of databases and computer software, and specifically to an efficient method and system for importing large-scale community population data. Background Art

[0002] With the rapid development of information technology, enterprises and organizations are facing a large number of data processing requirements. Especially in grass-roots population management, there is often a large amount of data and a large number of information fields involved. In the data import process, the traditional batch import method often leads to tight server resources, especially prone to performance bottlenecks when dealing with a large amount of data. At the same time, due to the diversity and complexity of the data, multi-level data verification and processing are required to ensure the quality and consistency of the data. Therefore, it is particularly important to develop a system and method that can improve the data import efficiency and ensure data integrity. Summary of the Invention

[0003] The technical task of the present invention is to provide an efficient method and system for importing large-scale community population data in view of the above deficiencies, which can effectively handle the large-scale population data import task, improve the efficiency and accuracy of population data import, and provide more reliable support for data processing and grass-roots data management.

[0004] The technical solution adopted by the present invention to solve its technical problems is:

[0005] An efficient method for importing large-scale community population data uses a message queue to achieve efficient and stable import of large-scale data into a database; the implementation of this method includes:

[0006] Data collection: Collect the data to be imported from various data sources and send it to the message queue;

[0007] Message queue: As middleware, store the data messages from different data sources and forward them to the data import module in sequence;

[0008] Data import: Consume the data messages from the message queue and batch import the data into the target database;

[0009] Error handling: For any error occurring during the import process, the system records the error information and provides a retry mechanism to ensure that the data is finally imported correctly.

[0010] Furthermore, the specific implementation of this method includes the following steps:

[0011] Step S1: The data import request is sent to the message queue in batches through the API interface;

[0012] Step S2: The message queue distributes the data import tasks to the processing nodes in sequence or according to priority;

[0013] Step S3: The processing node reads the data import task from the message queue and performs data preprocessing;

[0014] Step S4: Verify the preprocessed data, including data format verification, integrity verification, etc.;

[0015] Step S5: Perform the operation of importing the verified data into the database;

[0016] Step S6: Record the import result and feedback the result to the user.

[0017] Furthermore, for the data collection,

[0018] Use a lightweight client program or script to implement the data collection function, supporting multiple data source formats, including CSV, EXCEL, and JSON formats;

[0019] Specify the collection rules and frequencies through a configuration file, supporting scheduled task scheduling.

[0020] Furthermore, for the message queue,

[0021] Use a high-performance message middleware to ensure reliable message delivery;

[0022] Configure a reasonable partitioning strategy and persistence settings to support data processing requirements in a high-concurrency environment.

[0023] Furthermore, the high-performance message middleware is Kafka.

[0024] Furthermore, for the data import,

[0025] Quickly extract the key fields in the data through an efficient data parsing algorithm;

[0026] Reduce the number of database operations through a batch processing mechanism to improve the data import efficiency; improve the exception handling logic, including network exceptions, database connection exceptions, etc.

[0027] Furthermore, for the error handling,

[0028] Establish a complete error logging system, or verify each piece of information in the background, generate an exportable error information stream for the data that does not conform to the rules; record all abnormal situations during the import process;

[0029] Provide a visual monitoring interface to display the data import status and performance metrics in real time; set a reasonable retry mechanism and alarm strategy to ensure the accuracy and integrity of the data import.

[0030] The present invention also claims to protect a large-scale community population data efficient import system, including:

[0031] Data acquisition module: Collects the data to be imported from various data sources and sends it to the message queue;

[0032] Message queue: As middleware, stores the data messages from different data sources and forwards them to the data import module in sequence;

[0033] Data import module: Consumes the data messages from the message queue and batch-imports the data into the target database;

[0034] Error handling module: For any errors occurring during the import process, the system records the error information and provides a retry mechanism to ensure the correct import of the data eventually;

[0035] The system realizes the efficient import of large-scale community population data through the above methods.

[0036] The present invention also claims to protect an apparatus for efficiently importing large-scale community population data, including at least one memory and at least one processor;

[0037] The at least one memory is used to store machine-readable programs;

[0038] The at least one processor is used to call the machine-readable program to implement the above method.

[0039] The present invention also claims to protect a computer-readable medium, on which computer instructions are stored, and when the computer instructions are executed by a processor, the processor is caused to implement the above method.

[0040] Compared with the prior art, the method and system for efficiently importing large-scale community population data of the present invention have the following beneficial effects:

[0041] By using the message queue, asynchronous processing of data import tasks can be achieved, improving the response speed and throughput of the system; Utilizing the load balancing ability of the message queue, the number of processing nodes can be dynamically adjusted according to the load condition of the system, thereby improving the availability and stability of the system.

[0042] Through data preprocessing and verification, the quality and consistency of the data are ensured, and problems caused by data errors can be reduced.

[0043] Flexible scalability is provided, and the number of processing nodes can be easily increased or decreased as needed. Brief Description of the Drawings

[0044] Figure 1 It is a flowchart of the method for efficiently importing large-scale community population data provided by an embodiment of the present invention. Detailed Embodiments

[0045] The present invention will be further described below in conjunction with specific embodiments.

[0046] An embodiment of the present invention provides an efficient method for importing large-scale community population data, which uses a message queue to achieve efficient and stable import of large-scale data into a database; the implementation of this method includes:

[0047] 1. Data collection: Collect the data to be imported from various data sources and send it to the message queue.

[0048] Use a lightweight client program or script to implement the data collection function, supporting multiple data source formats, including CSV, EXCEL, and JSON formats.

[0049] Specify the collection rules and frequencies through a configuration file, supporting scheduled task scheduling.

[0050] 2. Message queue: As middleware, store the data messages from different data sources and forward them to the data import module in sequence.

[0051] Use a high-performance message middleware (such as Kafka, etc.) to ensure reliable message delivery.

[0052] Configure reasonable partitioning strategies and persistence settings to support data processing requirements in a high-concurrency environment.

[0053] 3. Data import: Consume the data messages from the message queue and batch-import the data into the target database.

[0054] Quickly extract the key fields in the data through an efficient data parsing algorithm.

[0055] Reduce the number of database operations through a batch processing mechanism and improve the data import efficiency. Improve the exception handling logic, including network exceptions, database connection exceptions, etc.

[0056] 4. Error handling mechanism: For any errors that occur during the import process, the system records the error information and provides a retry mechanism to ensure that the data is finally imported correctly.

[0057] Establish a complete error logging system, or verify each piece of information in the background, generate an exportable error information stream for the data that does not conform to the rules; record all abnormal situations during the import process.

[0058] Provide a visual monitoring interface to display the data import status and performance metrics in real time. Set reasonable retry mechanisms and alarm policies to ensure the accuracy and integrity of data import.

[0059] As Figure 1 shown, the specific implementation of this method includes the following steps:

[0060] Step S1: The data import request is sent to the message queue in batches through the API interface;

[0061] Step S2: The message queue distributes the data import tasks to the processing nodes in order or by priority;

[0062] Step S3: The processing node reads the data import task from the message queue and performs data preprocessing;

[0063] Step S4: Verify the preprocessed data, including data format verification, integrity verification, etc.;

[0064] Step S5: The data that passes the verification is imported into the database;

[0065] Step S6: Record the import result and feedback the result to the user.

[0066] The embodiment of the present invention also provides a large-scale community population data efficient import system, including:

[0067] 1. Data collection module: Collect the data to be imported from various data sources and send it to the message queue.

[0068] The data collection function is implemented by a lightweight client program or script, supporting multiple data source formats, including CSV, EXCEL, and JSON formats. Specify the collection rules and frequencies through configuration files, and support scheduled task scheduling.

[0069] 2. Message queue: As middleware, store the data messages from different data sources and forward them to the data import module in order.

[0070] Use a high-performance message middleware (such as Kafka, etc.) to ensure reliable message delivery. Configure reasonable partition strategies and persistence settings to support data processing requirements in a high-concurrency environment.

[0071] 3. Data import module: Consume data messages from the message queue and batch import the data into the target database.

[0072] Quickly extract the key fields in the data through an efficient data parsing algorithm. Reduce the number of database operations through the batch processing mechanism and improve the data import efficiency. Improve the exception handling logic, including network exceptions, database connection exceptions, etc.

[0073] 4. Error handling module: For any errors that occur during the import process, the system records the error information and provides a retry mechanism to ensure that the data is finally imported correctly.

[0074] Establish a complete error logging system, or verify each piece of information in the background, generate an exportable error information stream for data that does not conform to the rules; record all abnormal situations during the import process. Provide a visual monitoring interface to display the data import status and performance metrics in real time. Set reasonable retry mechanisms and alarm policies to ensure the accuracy and integrity of data import.

[0075] This system realizes the efficient import of large-scale community population data through the efficient import method of large-scale community population data described in the above embodiments. The specific implementation steps are as follows:

[0076] Step S1: The data import request is sent to the message queue in batches through the API interface;

[0077] Step S2: The message queue distributes the data import tasks to the processing nodes in order or by priority;

[0078] Step S3: The processing node reads the data import task from the message queue and performs data preprocessing;

[0079] Step S4: Verify the preprocessed data, including data format verification, integrity verification, etc.;

[0080] Step S5: Perform the operation of importing the verified data into the database;

[0081] Step S6: Record the import result and feedback the result to the user.

[0082] An embodiment of the present invention also provides an efficient import device for large-scale community population data, including at least one memory and at least one processor;

[0083] The at least one memory is used to store machine-readable programs;

[0084] The at least one processor is used to call the machine-readable program to implement the efficient import method of large-scale community population data described in the above embodiments.

[0085] An embodiment of the present invention also provides a computer-readable medium, on which computer instructions are stored. When the computer instructions are executed by a processor, the processor executes the efficient import method of large-scale community population data described in the above embodiments. Specifically, a system or device equipped with a storage medium can be provided, on which software program codes for implementing the functions of any one of the above embodiments are stored, and the computer (or CPU or MPU) of the system or device reads and executes the program codes stored in the storage medium.

[0086] In this case, the program code read from the storage medium itself can implement the functions of any one of the above embodiments. Therefore, the program code and the storage medium storing the program code constitute a part of the present invention.

[0087] Examples of the storage medium for providing the program code include floppy disks, hard disks, magneto-optical disks, optical disks (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), magnetic tapes, non-volatile memory cards, and ROMs. Optionally, the program code can be downloaded from a server computer via a communication network.

[0088] In addition, it should be clear that not only can the functions of any one of the above embodiments be realized by executing the program code read by the computer, but also by causing an operating system or the like operating on the computer based on the instructions of the program code to complete part or all of the actual operations.

[0089] In addition, it can be understood that the program code read from the storage medium is written into the memory provided in the expansion board inserted into the computer or into the memory provided in the expansion unit connected to the computer, and then based on the instructions of the program code, the CPU or the like installed on the expansion board or the expansion unit is caused to execute part or all of the actual operations, thereby realizing the functions of any one of the above embodiments.

[0090] The present invention has been described in detail above with reference to the accompanying drawings and preferred embodiments. However, the present invention is not limited to these disclosed embodiments. Based on the above-mentioned multiple embodiments, those skilled in the art can know that the code review means in different embodiments can be combined to obtain more embodiments of the present invention, and these embodiments are also within the protection scope of the present invention.

Claims

1. A method for efficiently importing large-scale community population data, characterized in that: The implementation of this method includes: Data collection: collects data to be imported from various data sources and sends it to the message queue; Message queue: As a middleware, it stores data messages from different data sources and forwards them to the data import module in sequence; Data import: consume data messages from the message queue and import the data in batches into the target database; Error handling: For any errors that occur during the import process, the system records the error information and provides a retry mechanism to ensure that the data is eventually imported correctly.

2. According to claim 1, a method for efficiently importing large-scale community population data is characterized in that: The specific implementation of this method includes the following steps: Step S1: Data import requests are sent to the message queue in batches through the API interface; Step S2: the message queue distributes the data import task to the processing node according to the sequence or priority; Step S3: The processing node reads the data import task from the message queue and performs data preprocessing; Step S4: Verify the preprocessed data, including data format verification and integrity verification; Step S5: import the verified data into the database; Step S6: Record the import result and feed the result back to the user.

3. According to claim 1, a method for efficiently importing large-scale community population data is characterized in that: The data collection, Use lightweight client programs or scripts to implement data collection functions, and support multiple data source formats, including CSV, EXCEL, and JSON formats; The collection rules and frequency are specified through the configuration file, and scheduled task scheduling is supported.

4. According to claim 1, a method for efficiently importing large-scale community population data is characterized in that: The message queue, Use high-performance message middleware to ensure reliable message delivery; Configure reasonable partitioning strategies and persistence settings to support data processing requirements in a high-concurrency environment.

5. According to claim 1, a method for efficiently importing large-scale community population data is characterized in that: The high-performance message middleware is Kafka.

6. The method for efficiently importing large-scale community population data according to claim 1, characterized in that: The data is imported, Quickly extract key fields from data through efficient data parsing algorithms; Reduce the number of database operations through batch processing mechanism; improve exception handling logic, including network exceptions and database connection exceptions.

7. The method for efficiently importing large-scale community population data according to claim 1, characterized in that: The error handling, Establish a complete error log system, or verify each piece of information in the background, and generate an exportable error information stream for data that does not meet the rules; Record all exceptions during the import process; Provides a visual monitoring interface to display data import status and performance indicators in real time; Set up retry mechanisms and alarm strategies to ensure the accuracy and completeness of data import.

8. A system for efficiently importing large-scale community population data, characterized in that: include: Data collection module: collects data to be imported from various data sources and sends it to the message queue; Message queue: As a middleware, it stores data messages from different data sources and forwards them to the data import module in sequence; Data import module: consumes data messages from the message queue and imports the data in batches into the target database; Error handling module: For any errors that occur during the import process, the system records the error information and provides a retry mechanism to ensure that the data is eventually imported correctly; The system realizes efficient import of large-scale community population data through any method described in claims 1 to 7.

9. A device for efficiently importing large-scale community population data, characterized in that: comprising at least one memory and at least one processor; The at least one memory is used to store a machine-readable program; The at least one processor is used to call the machine-readable program to implement the method described in any one of claims 1 to 7.

10. A computer-readable medium, characterized in that The computer readable medium stores computer instructions, which, when executed by a processor, enable the processor to implement the method according to any one of claims 1 to 7.

Images