Word word number statistical performance optimization method based on C #

Abstract

The invention discloses a Word word number statistical performance optimization method based on C #. The Word word number statistical performance optimization method comprises the following steps: step 1, calculating and setting the maximum number of bootable Word processes according to server hardware configuration; step 2, calculating a Hash value of an uploaded document, comparing the Hash value with a record in the cache, if the document is processed, directly returning a last statistical result, and if the document is newly uploaded or not processed, adding the document into a message queue to wait for processing; step 3, downloading and preprocessing a new document added in the monitored message queue; 4, counting the number of words of the pre-processed new document; and 5, capturing and processing various errors in the document processing process, and recording detailed log information. According to the method, the word counting efficiency and accuracy of Word when large-scale documents or complex-format documents are processed can be effectively improved, and meanwhile, the user experience is improved.

Description

Technical Field

[0001] The invention relates to the technical field of office software automation and programming, and in particular to a C#-based Word word count performance optimization method. Background Art

[0002] Microsoft Word is a widely used word processing software, and its built-in word count function plays an important role in document editing, academic writing, project management and other fields. However, with the increase in document size and the complexity of the format, traditional word count methods may face the following problems: 1. Performance bottleneck: When processing large-scale documents, the traditional Word word count method may cause the statistical process to be slow or even stuck due to inefficient algorithms and unreasonable data processing procedures, affecting the user's work efficiency; 2. Statistical accuracy issues: Documents with complex formats (such as those containing non-text content such as pictures, tables, hyperlinks, etc.) may cause traditional word count methods to be unable to accurately count the number of words in the text; 3. System stability and maintainability issues: When processing a large number of documents, the system may crash or fail to work properly due to various abnormal situations, affecting the normal use of users.

[0003] Therefore, it is necessary to design a C#-based Word word count performance optimization method to overcome the above problems. Summary of the invention

[0004] In order to avoid the above problems, this paper provides a C#-based Word word count performance optimization method, which can effectively improve the efficiency and accuracy of Word word count when processing large-scale documents or documents with complex formats, while improving the user experience.

[0005] The present invention provides a C#-based Word word count performance optimization method, comprising the following steps:

[0006] Step 1: Calculate and set the maximum number of Word processes that can be started based on the server hardware configuration;

[0007] Step 2: Calculate the Hash value of the uploaded document and compare it with the record in the cache. If the document has been processed, directly return the last statistical result. If the document is newly uploaded or has not been processed, add it to the message queue and wait for processing.

[0008] Step 3, download and pre-process the new document added to the monitored message queue;

[0009] Step 4, count the words of the new document after preprocessing;

[0010] Step 5: Capture and handle various errors in the document processing process and record detailed log information.

[0011] Preferably, the algorithm for the number of Word processes in step 1 is: first, obtain the total size of server memory (GB) and the number of server CPU cores; second, calculate the upper limits of the number of Word processes based on memory and CPU; finally, determine the final maximum number of Word processes, taking the smaller value of the two upper limits calculated based on memory and CPU.

[0012] Preferably, the message queue is a RabbitMQ queue.

[0013] Preferably, in step 3, Aspose.Words component is used to remove Word macros and images and format the document into a unified standard.

[0014] Preferably, in step 4, for small to medium-sized documents, the processed document is directly opened using the Microsoft.Office.Interop.Word component to perform word count; for large files exceeding 50M, the document is divided into multiple parts, each part is processed in parallel by a separate thread, and the results are summarized after the statistics are completed.

[0015] Preferably, in step 5, an error handling mechanism is used to capture and process various errors in the file reading, parsing, and statistics process; for recoverable errors, clear error prompts and repair suggestions are provided; for unrecoverable errors, detailed error logs are recorded and notified to administrators and users via email or system notifications; wherein all operations record detailed log information, including operation time, content, results, and error information.

[0016] Preferably, it also includes regularly monitoring resource usage and dynamically adjusting the number of Word processes according to the current load.

[0017] Compared with the prior art, the present invention has the following beneficial effects: the C#-based Word word count performance optimization method aims to solve the performance bottleneck problem faced by the traditional Word word count function when processing large-scale documents or documents in complex formats; by optimizing algorithms, improving data processing procedures and introducing advanced programming techniques, the present invention aims to significantly improve the efficiency, accuracy and user experience of word count, making the Word word count function more efficient, reliable and easy to use. DETAILED DESCRIPTION

[0018] This embodiment provides a C#-based Word word count performance optimization method, comprising the following steps:

[0019] Step 1: System initialization and resource allocation.

[0020] When the system starts, it automatically calculates and sets the maximum number of Word processes that can be started based on the server hardware configuration (CPU core number and memory size) to avoid excessive resource consumption and frequent startup / shutdown of Word processes. This mechanism ensures that the system can still run stably under high load.

[0021] Algorithm for calculating the number of word processes:

[0022] Get the total server memory size (GB) and the number of server CPU cores, and calculate the available memory. Considering that the server may also need to run other applications and services, we can allocate a certain proportion of the total memory (such as 70%) to the Word process. Assuming that the total server memory is 16G, the memory that can be allocated to the Word process is 16*0.7=11.2G.

[0023] To calculate the upper limit of the number of Word processes based on memory, divide the available memory by the estimated memory occupied by each Word process. Assuming that each Word process occupies about 500 MB of memory after starting and loading basic components, the number of Word processes that can be supported is: 11.2*1024 / 500=22.9, rounded to 22.

[0024] Calculate the upper limit of the number of Word processes based on the CPU. Assuming that each Word process may occupy 50% of the CPU cores at peak times, each core supports 2 Word processes. If there are 8 cores, it supports 16 Word processes.

[0025] The final maximum number of processes is determined to be the smaller of the two upper limits calculated based on memory and CPU. So it is finally determined that an 8-core 16GB memory can support a maximum of 16 word processes.

[0026] Step 2: Check the document before processing.

[0027] After uploading a Word document, the system first calculates the document's hash value and compares it with the records in the cache. If the document has been processed, the last statistical result is directly returned to improve processing efficiency. If the document is newly uploaded or has not been processed, it will be added to the RabbitMQ queue and wait for further processing.

[0028] Step 3: Document preprocessing and queue monitoring.

[0029] The system monitors the RabbitMQ queue and immediately downloads and preprocesses new documents once they are added. Use Aspose.Words components to remove Word macros and images to reduce the memory usage of the Word process when opening documents and improve security. At the same time, format the documents to a unified standard, including setting the Chinese font to Songti and the Western font to Arial to ensure the accuracy of word count.

[0030] Step 4: Efficient word count.

[0031] For small to medium-sized documents, the Microsoft.Office.Interop.Word component is used to directly open the processed document and count the words. For large files over 50M, a strategy combining multithreading and asynchronous technology is adopted. The document is divided into multiple parts, each of which is processed in parallel by a separate thread, and the results are summarized after the statistics are completed. Asynchronous IO operations ensure that the thread is not blocked while waiting for the file to be read, thereby maximizing resource utilization.

[0032] Step 5: Error handling and logging.

[0033] The system has a built-in perfect error handling mechanism, which can capture and handle various errors in the process of file reading, parsing, statistics, etc. For recoverable errors, clear error prompts and repair suggestions are provided; for unrecoverable errors, detailed error logs are recorded and notified to administrators and users through emails or system notifications. At the same time, all operations record detailed log information, including operation time, content, results and error information, which is convenient for subsequent problem troubleshooting and performance optimization.

[0034] Step 6: Resource release and optimization.

[0035] After each word count task is completed, the system automatically releases the occupied Word process resources to ensure that resources can be recycled. At the same time, the system resource usage is regularly monitored and the number of Word processes is dynamically adjusted according to the current load to achieve the optimal resource configuration. In addition, the system processing speed and stability are further improved by continuously optimizing the code and algorithm.

[0036] The present invention effectively solves the performance bottleneck problem and improves the statistical speed by optimizing file parsing and reading strategies, adopting multi-threading and asynchronous processing technologies, and introducing caching and reuse mechanisms; designs an intelligent content screening algorithm that can automatically identify and ignore non-text content and only count text content, thereby improving statistical accuracy; introduces a complete error handling mechanism and log recording function to ensure the stability and maintainability of the system, and can promptly recover and handle errors even when abnormal situations occur.

[0037] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention 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 invention.

Claims

1. A C#-based Word word count performance optimization method, characterized in that: The steps include: Step 1: Calculate and set the maximum number of Word processes that can be started based on the server hardware configuration; Step 2: Calculate the Hash value of the uploaded document and compare it with the record in the cache. If the document has been processed, directly return the last statistical result. If the document is newly uploaded or has not been processed, add it to the message queue and wait for processing. Step 3, download and pre-process the new document added to the monitored message queue; Step 4, count the words of the new document after preprocessing; Step 5: Capture and handle various errors in the document processing process and record detailed log information.

2. The Word word count performance optimization method based on C# as described in claim 1, characterized in that: The algorithm for calculating the number of Word processes in step 1 is as follows: first, obtain the total server memory size (GB) and the number of server CPU cores; second, calculate the upper limits of the number of Word processes based on memory and CPU; finally, determine the final maximum number of Word processes, taking the smaller value of the two upper limits calculated based on memory and CPU.

3. The Word word count performance optimization method based on C# as described in claim 1, characterized in that: The message queue is RabbitMQ queue.

4. The Word word count performance optimization method based on C# as described in claim 1, characterized in that: In step 3, use Aspose.Words component to remove Word macros and images and format the document to a unified standard.

5. The Word word count performance optimization method based on C# as described in claim 1 is characterized in that: In step 4, for small to medium-sized documents, directly use the Microsoft.Office.Interop.Word component to open the processed document and perform word count; for large files exceeding 50M, split the document into multiple parts, each part is processed in parallel by a separate thread, and the results are summarized after the statistics are completed.

6. The Word word count performance optimization method based on C# as described in claim 1, characterized in that: In step 5, an error handling mechanism is used to capture and handle various errors in the file reading, parsing, and statistics process; For recoverable errors, provide clear error prompts and repair suggestions; For unrecoverable errors, detailed error logs are recorded and notified to administrators and users via email or system notifications; all operations record detailed log information, including operation time, content, results and error information.

7. The Word word count performance optimization method based on C# as described in claim 1 is characterized in that: It also includes regular monitoring of resource usage and dynamically adjusting the number of Word processes based on the current load.