Efficient data entry method based on double caches

Abstract

The invention provides an efficient data entry method based on double caches. The method comprises the steps that an entry work order is created, and a unique identifier is generated according to the work order and a manufacturer; loading the produced bar code data and the non-persistent bar code data from the persistent database and the Redis cache to the browser cache based on the unique identifier; establishing connection between the code scanning equipment and a computer; scanning and inputting bar code data, and executing bar code range verification, bar code continuity verification and data consistency verification; submitting the bar code data passing the front-end verification to a rear end; checking whether the passed bar code data is valid or not based on a MongoDB checking front end; storing the verified bar code data to a Redis cache through a non-repeatable write-in command, and synchronously updating the verified bar code data to a browser cache; asynchronously calling the persistent database, and executing data deduplication operation; and storing the de-duplicated data in a persistent database to solve the problem that data entry cannot effectively consider both speed and accuracy.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data entry, and in particular to a data efficient entry method based on double cache. BACKGROUND

[0002] In the product barcode and anti-counterfeit code management scenarios, the participation of massive data (such as hundreds of millions of barcode records) and numerous manufacturers and producers leads to complicated data statistics and cost settlement processes. The data entry process involves frequent cross-order verification, which puts strict requirements on efficiency, accuracy and real-time response.

[0003] In related technical solutions, a business data processing system adopts a double cache mechanism, including a database, a cache module and a microservice module; when the microservice module receives a data query instruction, the cache is queried first, and when the cache is missing, the database is loaded and the cache is updated to improve the response speed. Another data consistency guarantee method operates under a multi-active architecture, which realizes the identification and automatic processing of data conflicts through private line monitoring, communication quality analysis and multi-layer (such as Web layer, microservice layer and data storage layer) request forwarding mechanism, and ensures system availability and consistency.

[0004] Although the above solutions can partially optimize the response and consistency, they cannot effectively balance speed and accuracy in large-scale data entry tasks. Especially in the cross-production order verification and concurrent operation scenarios, the data entry process is easily affected by delay and conflict, leading to barcode omission or duplication, thereby affecting the overall data integrity. Therefore, there is an urgent need for a mechanism to solve the core bottleneck problem in efficient entry. SUMMARY

[0005] The present application provides a data efficient entry method based on double cache to solve the problem that data entry cannot effectively balance speed and accuracy.

[0006] The present application provides a data efficient entry method based on double cache, which comprises:

[0007] Creating an entry work order and generating a unique identifier according to the work order and the manufacturer to which the user belongs;

[0008] Loading the produced barcode data from the persistent database to the browser cache based on the unique identifier;

[0009] Incrementally loading the non-persistent barcode data from the Redis cache to the browser cache based on the unique identifier;

[0010] Establishing a communication connection between the code scanning device and the computer, which includes the configuration of the serial port entry mode or the keyboard entry mode;

[0011] The barcode data is scanned and entered, and barcode range verification, barcode continuity verification and data consistency verification are performed to obtain front-end verified barcode data;

[0012] The front end submits the front-end verified barcode data to the back end through an HTTP request;

[0013] The back end verifies whether the front-end verified barcode data is valid based on MongoDB to obtain verified barcode data;

[0014] The verified barcode data is stored in the Redis cache through a non-repeatable write command;

[0015] The Redis cache data is synchronously updated to the browser cache;

[0016] The persistent database is called asynchronously, and a data deduplication operation is performed;

[0017] The deduplicated data is saved to the persistent database.

[0018] The application realizes efficient barcode data entry by generating a unique identifier and loading data from the persistent database and Redis cache to the browser cache, combined with the serial port or keyboard entry mode configuration of the code scanning device; Through front-end barcode range, continuity and data consistency verification, the back end further verifies based on MongoDB and stores in the Redis cache using a non-repeatable write command, synchronously updates the browser cache and asynchronously persists and deduplicates data, so as to balance speed and accuracy during data entry, reduce data redundancy risk, and improve entry efficiency and data consistency.

[0019] Optionally, the unique identifier is generated by string splicing of the manufacturer code, order number and product material code.

[0020] By splicing the manufacturer code, order number and product material code to generate a unique identifier, the distinguishability and traceability of data identification can be enhanced, the confusion risk between data of different sources can be reduced, and subsequent data retrieval and management can be facilitated, improving the standardization of data entry and storage.

[0021] Optionally, the serial port entry mode includes:

[0022] A virtual serial port communication channel is established to realize data transmission between the code scanning device and the computer;

[0023] A preset baud rate parameter is set to control the data transmission rate;

[0024] The serial port listening function is activated in the system entry interface to receive barcode data stream in real time.

[0025] By establishing a virtual serial port communication channel and configuring preset baud rate parameters, the data transmission rate between the code scanning device and the computer can be stably controlled, and the reliability and real-time performance of data transmission can be improved by receiving the barcode data stream in real time through the serial port monitoring function of the system input interface, thereby improving the input efficiency.

[0026] Optionally, the barcode data is a 24-bit continuous code segment containing manufacturer code, product material, and date information; and the persistent database uses a non-relational database to store over 100 million pieces of barcode data.

[0027] Using a 24-bit continuous code segment containing manufacturer code, product material, and date information as barcode data can enhance the standardization and identifiability of the data structure; and storing over 100 million pieces of barcode data through a non-relational database can optimize the storage efficiency of large-scale data, reduce the complexity of data management, and improve the scalability of the system.

[0028] Optionally, the keyboard input mode includes:

[0029] Setting a set of data end identifiers at the front end;

[0030] Configuring a data reading interval threshold;

[0031] Automatically ending reading when the interval threshold is reached or a 24-bit barcode is inputted.

[0032] By setting a set of data end identifiers at the front end and configuring a data reading interval threshold, the judgment condition for automatically ending reading in the keyboard input mode can be achieved, thereby reducing the need for manual intervention; and automatically terminating reading when the interval threshold is reached or a 24-bit barcode is inputted can help improve the degree of automation of data input, reduce the probability of misoperation, and maintain the smoothness of the input process.

[0033] Optionally, the barcode range verification includes:

[0034] Obtaining the barcode long integer range boundary value corresponding to the work order;

[0035] Determining whether the input barcode data is within the boundary value range.

[0036] By obtaining the barcode long integer range boundary value corresponding to the work order and determining whether the input barcode data is within the range, abnormal barcode data that exceeds the predetermined range can be effectively identified, thereby reducing the probability of invalid data input, improving the accuracy of data input, and reducing the workload of subsequent data processing steps.

[0037] Optionally, the barcode continuity verification includes:

[0038] Converting the 24-bit barcode to a long integer value;

[0039] Perform continuous and incremental comparison with the long integer value of the last entered barcode data.

[0040] By converting the 24-bit barcode into a long integer value and comparing it with the previously entered data in a continuous and incremental manner, the continuity of the barcode sequence can be detected, thereby identifying possible missing or duplicate barcode entries, helping to maintain the integrity of the data sequence and improve the accuracy of data entry.

[0041] Optionally, the data consistency check includes:

[0042] Repeated comparison is performed based on the long integer value and the historical barcode dataset in the browser cache.

[0043] By repeatedly comparing the long integer value of the entered barcode with the historical data in the browser cache, possible duplicate entries can be identified, thereby reducing data redundancy, improving data entry accuracy, and optimizing data storage efficiency.

[0044] Optionally, the non-rewritable command is a SET command of the Redis cache, which stores the barcode data using the work order unique identifier as the key.

[0045] Using the SET command of Redis cache and storing barcode data with the work order unique identifier as the key can ensure the uniqueness of barcode data under the same work order and prevent duplicate writing, thereby maintaining the accuracy of data storage. At the same time, it uses the efficient key-value storage feature of Redis to improve data access efficiency.

[0046] Optionally, the data deduplication operation includes:

[0047] Extracting the existing barcode data set from the persistent database to the first memory buffer;

[0048] Extract the barcode dataset to be persisted for the current work order from the Redis cache to the second memory buffer;

[0049] Traverse the barcode data in the second memory buffer and remove all barcode items that are duplicated with those in the first memory buffer;

[0050] Generate duplicate data removal records and push notification messages;

[0051] Write the deduplicated barcode dataset to the persistent database.

[0052] By extracting barcode data from the persistent database and Redis cache into independent memory buffers and performing traversal comparisons, duplicate barcode items can be identified and removed, and removal records and notification messages can be generated at the same time, thereby reducing data redundancy, improving storage space utilization, ensuring data uniqueness in the persistent database, and optimizing subsequent data processing efficiency.

[0053] From the above technical solutions, the application provides a kind of based on double cache data efficient entry method, by creating entry work order and according to the work order and the unique identifier of manufacturer to which user belongs is generated;Based on the unique identifier, load the bar code data produced from persistent database to browser cache;Based on the unique identifier, load the non-persistent bar code data from Redis cache increment to browser cache;Establish the communication connection of scanning code equipment and computer;Scan entry bar code data, and execute bar code range check, bar code continuity check and data consistency check;Front end passes through HTTP request and submits the bar code data that front end check passes to back end;Back end is based on MongoDB, and whether the bar code data that front end check passes is valid is checked, to obtain check passed bar code data;The check passed bar code data is stored to Redis cache by non-repetitive write command;Redis cache data is synchronously updated to browser cache;Asynchronous call persistent database, and execute data deduplication operation;The data after deduplication is saved to persistent database, to solve the problem that data entry cannot effectively consider speed and accuracy. BRIEF DESCRIPTION OF DRAWINGS

[0054] In order to more clearly illustrate the technical solutions of the present application, the drawings needed in the embodiments will be briefly introduced as follows. Obviously, for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0055] Figure 1 The flowchart of the data efficient entry method based on double cache provided by the embodiments of the present application is shown.

[0056] Figure 2 The flowchart of data deduplication operation in the data efficient entry method based on double cache provided by the embodiments of the present application is shown. DETAILED DESCRIPTION

[0057] The embodiments will be described in detail below, and their examples are shown in the drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following embodiments do not represent all embodiments consistent with the present application. They are only examples of systems and methods consistent with some aspects of the present application.

[0058] In the product bar code and anti-counterfeit code management scene, massive data (such as hundreds of millions of bar code records) and the participation of many manufacturers and producers result in complicated data statistics and cost settlement process. The data entry process involves frequent cross-order check, which puts strict requirements on efficiency, accuracy and real-time response.

[0059] In related embodiments, the business data processing system adopts a double cache mechanism, including a database, a cache module, and a microservice module; when the microservice module receives a data query instruction, it prioritizes querying the cache, and if the data is missing, it loads the data from the database and updates the cache to improve response speed. Another data consistency guarantee method operates under a multi-active architecture, through dedicated line monitoring, communication quality analysis, and multi-layer (such as Web layer, microservice layer, and data storage layer) request forwarding mechanism, to realize data conflict identification and automatic processing, ensuring system availability and consistency.

[0060] Although the above solutions can partially optimize response and consistency, in large-scale data entry tasks, they fail to effectively balance speed and accuracy. Especially in cross-production order verification and concurrent operation scenarios, the data entry process is easily affected by delays and conflicts, leading to barcode omission or duplication, thereby affecting the overall data integrity. Therefore, there is an urgent need for a mechanism to solve the core bottleneck problem in efficient entry.

[0061] To solve the problem that data entry fails to effectively balance speed and accuracy, see Figure 1 The embodiments of the present application provide a double cache-based efficient data entry method, which comprises:

[0062] S100: Create an entry work order and generate a unique identifier based on the work order and the manufacturer to which the user belongs.

[0063] It should be understood that the user can create an entry work order based on the order number and product material.

[0064] In some embodiments, the unique identifier is generated by string splicing the manufacturer code, order number, and product material code.

[0065] For example, the manufacturer code is M001, the order number is O20231001, and the product material code is 123456, then the unique identifier (product_order_key) is M001_O20231001_123456.

[0066] By splicing the manufacturer code, order number, and product material code to generate a unique identifier, the distinguishability and traceability of data identification can be enhanced, the risk of confusion between different source data can be reduced, and subsequent data retrieval and management can be facilitated, improving the standardization of data entry and storage.

[0067] S110: Load the produced barcode data from the persistent database into the browser cache based on the unique identifier.

[0068] It should be understood that the system can quickly locate the barcode range associated with the work order according to the unique identifier (product_order_key), quickly query the produced barcode data from the persisted entry data, load only the barcode range corresponding to the current work order, avoid full data transmission, and cache the results to the browser cache (such as localStorage or sessionStorage), reduce redundant data loading, and the data format example: {"M001_O20231001_123456":["xxx001","xxx002",...}. The data preloading stage dynamically associates production order information through the unique identifier, can accurately locate the target data range, and reduces redundant data transmission.

[0069] S120: Incrementally loading non-persistent barcode data from the Redis cache to the browser cache based on the unique identifier.

[0070] It should be understood that the system queries non-persistent barcode data from the Redis cache according to the unique identifier (product_order_key), and incrementally combines these data into the browser cache.

[0071] S130: Establishing a communication connection between the code scanning device and the computer.

[0072] It should be understood that the communication connection includes the configuration of the serial port entry mode or the keyboard entry mode. The code scanning device can be a code scanning gun, and the communication connection between the code scanning device and the computer can be a wired connection or a wireless connection.

[0073] In some embodiments, the serial port entry mode includes:

[0074] Establishing a virtual serial port communication channel to realize data transmission between the code scanning device and the computer;

[0075] Setting a preset baud rate parameter to control the data transmission rate;

[0076] Activating the serial port listening function in the system entry interface to receive the barcode data stream in real time.

[0077] It should be understood that the preset baud rate can be selected as 115200, and data transmission is performed through the virtual com serial port.

[0078] By establishing a virtual serial port communication channel and configuring a preset baud rate parameter, the data transmission rate between the code scanning device and the computer can be stably controlled, and the serial port listening function of the system entry interface is used to receive the barcode data stream in real time, thereby improving the reliability and real-time performance of data transmission and improving the entry efficiency.

[0079] In some embodiments, the keyboard entry mode includes:

[0080] Setting a set of data end identifiers in the front end;

[0081] Configuring a data reading interval threshold;

[0082] Automatically ending reading when the interval threshold is reached or a 24-bit barcode is entered.

[0083] It should be understood that the keyboard entry mode sets the read data end identifier in the front end, compatible with common end identifiers such as \n and \t, and sets a data reading interval. When the interval is exceeded or a 24-bit barcode data is entered, the reading is automatically ended.

[0084] By setting a set of data end identifiers in the front end and configuring a data reading interval threshold, the judgment condition for automatically ending reading in the keyboard entry mode can be realized, thereby reducing the need for manual intervention. When the interval threshold is reached or a 24-bit barcode is entered, the reading is automatically terminated, which helps to improve the automation level of data entry, reduce the probability of misoperation, and maintain the smoothness of the entry process.

[0085] S140: Scan the entered barcode data and perform barcode range verification, barcode continuity verification, and data consistency verification to obtain front-end verified barcode data.

[0086] In some embodiments, the barcode range verification includes:

[0087] Obtaining a barcode long integer range boundary value corresponding to the work order;

[0088] Determining whether the entered barcode data is within the boundary value range.

[0089] It should be understood that the barcode long integer range boundary value can be used to determine whether the entered barcode is within the range, so that barcodes outside the range are rejected and an error prompt is played.

[0090] By obtaining a barcode long integer range boundary value corresponding to the work order and determining whether the entered barcode data is within the range, abnormal barcode data outside the predetermined range can be effectively identified, thereby reducing the probability of invalid data entry, improving data input accuracy, and reducing the workload of subsequent data processing steps.

[0091] In some embodiments, the barcode continuity verification includes:

[0092] Converting a 24-bit barcode to a long integer value;

[0093] Comparing the long integer value with the long integer value of the last entered barcode data for consecutive increments.

[0094] It should be understood that after the barcode range verification passes, by converting the 24-bit barcode to a long integer value and comparing it with the previous entry data in a continuous incremental manner, it is ensured that the data is entered continuously and incrementally. If it is not continuous, the customer service will be prompted and the next data entry will be continued only after confirmation.

[0095] By converting the 24-bit barcode to a long integer value and comparing it with the previous entry data in a continuous incremental manner, the continuity of the barcode sequence can be detected, so as to identify the possible missing or repeated entry of the barcode, which helps to maintain the integrity of the data sequence and improve the accuracy of data entry.

[0096] In some embodiments, the data consistency verification includes:

[0097] Based on the long integer value, the historical barcode data set in the browser cache is repeatedly compared.

[0098] It should be understood that by repeatedly comparing whether the current barcode has been entered, if the verification fails, the voice will broadcast an error prompt and the next data entry will be continued only after confirmation, so as to ensure the integrity of the barcode generation rule (such as no omission or confusion).

[0099] By repeatedly comparing the long integer value of the entered barcode with the historical data in the browser cache, the possible repeated entry can be identified, thereby reducing data redundancy, improving the accuracy of data entry, and optimizing data storage efficiency.

[0100] S150: The front end submits the front-end verified barcode data to the back end through an HTTP request.

[0101] S160: The back end verifies whether the front-end verified barcode data is valid based on MongoDB to obtain verified barcode data.

[0102] It should be understood that MongoDB is an open source NoSQL database that uses a document-based data storage model and has high performance, high scalability and flexible data processing capabilities. MongoDB verification refers to a mechanism for verifying the structure of a document when data is written to a collection to ensure that the data meets predefined rules.

[0103] S170: Store the verified barcode data in the Redis cache through a non-repeatable write command.

[0104] In some embodiments, the non-repeatable write command is a SET command of the Redis cache, and the barcode data is stored with the ticket unique identifier as the key.

[0105] It should be understood that in the Redis cache, the SET command is used to store a key-value pair into the cache, and is one of the most basic and most commonly used commands in Redis cache.

[0106] Using the SET command of the Redis cache and storing the barcode data with the order unique identifier as the key can ensure the uniqueness of the barcode data under the same order, avoid data conflicts caused by concurrent operations, and thus maintain the accuracy of data storage, while using the efficient key-value storage characteristics of Redis to improve data access efficiency.

[0107] S180: synchronously update the Redis cache data to the browser cache.

[0108] S190: asynchronously call the persistent database and perform data deduplication operation.

[0109] In some embodiments, referring to Figure 2 , the data deduplication operation includes:

[0110] S191: extract the existing barcode data set from the persistent database to the first memory buffer.

[0111] S192: extract the current order to-be-persisted barcode data set from the Redis cache to the second memory buffer.

[0112] S193: traverse the second memory buffer barcode data and remove all barcode items that are duplicated in the first memory buffer.

[0113] S194: generate a duplicate data removal record and push a notification message.

[0114] S195: write the deduplicated barcode data set to the persistent database.

[0115] It should be understood that according to the order information, the recorded data is obtained from the persistent database, written into the first memory buffer buffer1, the order recorded data is taken out from the Redis cache according to the unique identifier (product_order_key), written into the second memory buffer buffer2, and all elements appearing in buffer1 are removed from the second memory buffer buffer2, the record is made and the notification is pushed, and finally the processed buffer2 is persisted to the database, which can ensure the accuracy and consistency of the final data storage.

[0116] By extracting barcode data from the persistent database and Redis cache to separate memory buffers respectively and traversing comparison, duplicate barcode items can be identified and removed, and removal records and notification messages can be generated, thereby reducing data redundancy, improving storage space utilization, ensuring the uniqueness of the data in the persistent database, and optimizing the efficiency of subsequent data processing.

[0117] S200: Save the deduplicated data to the persistent database.

[0118] The application generates a unique identifier and loads data from the persistent database and Redis cache to the browser cache, and combines the serial port or keyboard input mode configuration of the scanning device to achieve efficient entry of barcode data, significantly reducing the pressure of direct database query and improving response speed. Through front-end barcode range, continuity and data consistency verification, back-end MongoDB further verification and non-repeatable write command storage to Redis cache, synchronous update of browser cache and asynchronous persistence of deduplicated data, the speed and accuracy are considered during data entry, the risk of data redundancy is reduced, and the entry efficiency and data consistency are improved.

[0119] In some embodiments, the barcode data is a 24-bit continuous code segment containing manufacturer code, product material, and date information; the persistent database uses a non-relational database to store over 100 million barcode data.

[0120] Using a 24-bit continuous code segment containing manufacturer code, product material, and date information as barcode data can enhance the standardization and identifiability of the data structure; at the same time, storing over 100 million barcode data in a non-relational database can optimize the storage efficiency of large-scale data, reduce the complexity of data management, and improve the scalability of the system.

[0121] According to the technical scheme, the embodiment of the application provides a data efficient entry method based on double caches, creates an entry work order, generates a unique identifier according to the work order and a manufacturer to which a user belongs, loads produced barcode data from a persistent database to a browser cache based on the unique identifier, loads non-persistent barcode data from a Redis cache to the browser cache based on the unique identifier, establishes a communication connection between a code scanning device and a computer, scans and enters barcode data, and performs barcode range checking, barcode continuity checking and data consistency checking, the front end submits the barcode data that passes the front end checking to the back end through an HTTP request, the back end checks whether the barcode data that passes the front end checking is valid based on MongoDB to obtain barcode data that passes checking, stores the barcode data that passes checking to the Redis cache through a non-repeatable write command, synchronously updates Redis cache data to the browser cache, asynchronously calls a persistent database, and performs a data deduplication operation, and saves the deduplicated data to the persistent database, so that the problem that data entry cannot effectively balance speed and accuracy is solved.

[0122] The similar parts among the embodiments provided in the application can be referred to each other, the specific embodiments provided above are only several examples under the general concept of the application, and do not limit the protection scope of the application. Any other embodiments extended according to the application scheme without creative labor belong to the protection scope of the application for those skilled in the art.

Claims

1. A method for efficient data entry based on double buffering, characterized in that: The method comprises: Creating an entry work order and generating a unique identifier based on the work order and the manufacturer to which the user belongs; Loading the generated barcode data from the persistent database to the browser cache based on the unique identifier; Incrementally loading non-persistent barcode data from the Redis cache to the browser cache based on the unique identifier; Establishing a communication connection between the code scanning device and the computer, wherein the communication connection includes configuring a serial port input mode or a keyboard input mode; Scan and enter barcode data, and perform barcode range verification, barcode continuity verification, and data consistency verification to obtain barcode data that passes front-end verification; The front end submits the barcode data verified by the front end to the back end via HTTP request; The backend verifies whether the front-end verified barcode data is valid based on MongoDB to obtain the verified barcode data; The verification barcode data is stored in the Redis cache through a non-repeatable write command; Synchronize the Redis cache data to the browser cache; Asynchronously call the persistence database and perform data deduplication operations; Save the deduplicated data to a persistent database.

2. The method for efficient data entry based on double buffering according to claim 1, characterized in that: The unique identifier is generated by concatenating the manufacturer code, order number and product material code.

3. The method for efficient data entry based on double buffering according to claim 1, characterized in that: The serial port input mode includes: Establish a virtual serial port communication channel to realize data transmission between the scanning device and the computer; Set the preset baud rate parameter to control the data transmission rate; Activate the serial port monitoring function in the system input interface to receive barcode data stream in real time.

4. The method for efficient data entry based on double buffering according to claim 1, characterized in that: The barcode data is a 24-bit continuous code segment containing manufacturer code, product material, and date information; the persistent database adopts a non-relational database to achieve the storage of hundreds of millions of barcode data.

5. The method for efficient data entry based on double buffering according to claim 4, characterized in that: The keyboard input mode includes: Set the data end identifier set in the front end; Configure the data reading interval threshold; The reading process ends automatically when the interval threshold is reached or a full 24-digit barcode is entered.

6. The method for efficient data entry based on double buffering according to claim 5, characterized in that: The barcode range verification includes: Get the barcode long integer range boundary value corresponding to the work order; Determine whether the input barcode data is within the boundary value range.

7. The method for efficient data entry based on double buffering according to claim 6, characterized in that: The barcode continuity check includes: Convert 24-bit barcode to long integer value; Perform continuous and incremental comparison with the long integer value of the last entered barcode data.

8. The method for efficient data entry based on double buffering according to claim 7, characterized in that: The data consistency check includes: Repeated comparison is performed based on the long integer value and the historical barcode dataset in the browser cache.

9. The method for efficient data entry based on double buffering according to claim 1, characterized in that: The non-rewritable command is a SET command of the Redis cache, which stores the barcode data using the unique identifier as a key.

10. The method for efficient data entry based on double buffering according to claim 1, characterized in that: The data deduplication operation includes: Extracting the existing barcode data set from the persistent database to the first memory buffer; Extract the barcode dataset to be persisted for the current work order from the Redis cache to the second memory buffer; Traverse the barcode data in the second memory buffer and remove all barcode items that are duplicated with those in the first memory buffer; Generate duplicate data removal records and push notification messages; Write the deduplicated barcode dataset to the persistent database.

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