The Excel data stream reading performance optimization method based on the Streaming Excel Reader framework in the Java class library

The Excel data stream reading performance optimization method based on the Streaming Excel Reader framework in the Java class library Overview: In Java development, processing Excel files is a common task.Many Java class libraries provide the function of processing Excel files. Among them, Excel data streaming based on the Streaming Excel Reader framework can handle large excel files more efficiently.This article will introduce how to improve the execution efficiency of Excel data streaming operations based on the Streaming Excel Reader framework through some techniques and performance optimization methods. 1. Use the appropriate Streaming Excel Reader framework version: Make sure to use the latest version of Streaming Excel Reader to obtain new performance optimization and repair.Regularly upgrade to ensure better performance. 2. Use the appropriate buffer settings: Increasing the size of the buffer can improve the performance of reading large excel files.By adjusting the size of the buffer area, the number of IO operations can be reduced, thereby improving reading performance.The following is an example code that sets the size of a buffer: import org.apache.poi.ss.usermodel.DataCacheConfig; import org.apache.poi.xssf.streaming.SXSSFWorkbook; // Create SXSSFWORKBOOK objects and set up a buffer size SXSSFWorkbook workbook = new SXSSFWorkbook(); DataCacheConfig dataCacheConfig = workbook.getSheetDataWriter().getOrCreateDataCacheConfig(); dataCacheConfig.setBufferSize(1000); In the above example, set the buffer size to 1000, which is a adjustable parameter.You can find the best performance by constantly trying different values. 3. Reasonable use of batch writing: Streaming Excel Reader framework supports batch writing functions, which can be written into multi -line data at one time, thereby reducing the number of IO operations and improving performance.The following is an example code using batch writing: import org.apache.poi.ss.usermodel.Sheet; import org.apache.poi.ss.util.CellRangeAddress; import org.apache.poi.xssf.streaming.SXSSFSheet; import org.apache.poi.xssf.streaming.SXSSFWorkbook; // Create SXSSFORKBOOK objects and sheet objects SXSSFWorkbook workbook = new SXSSFWorkbook(); SXSSFSheet sheet = workbook.createSheet("Sheet1"); // Batch writing multiple lines of data SheetUtil.writeRows(sheet, 1, rowsList); // Batch write to the merger cell SheetUtil.mergeCells(sheet, new CellRangeAddress(1, 10, 0, 0)); In the above example, `Sheetutil.writerows` function can be written into multi -line data at one time, and the data set` ROWSLIST` is passed as a parameter.Similarly, the function of `SheetUtil.mergeells` can be written into multiple merging cells at one time. 4. Limit the cache size: To avoid using too much memory, the Streaming Excel Reader framework will automatically limit the cache size.When the cache area is full, the cache will be written to the disk and the memory will be released.You can set the cache size limit through the following code example: import org.apache.poi.xssf.streaming.SXSSFWorkbook; // Create SXSSFWORKBOOK objects and set up the maximum number of cache lines int maxRowCount = 10000; SXSSFWorkbook workbook = new SXSSFWorkbook(maxRowCount); In the above example, set the maximum cache line to 10000.This value can be adjusted according to memory usage and performance requirements. in conclusion: By using these performance optimization methods, the Excel data stream reading efficiency based on the Streaming Excel Reader framework can be improved.According to actual needs, the parameter value can be adjusted according to the situation to achieve the best performance.When processing large Excel files, these optimization methods will help you improve the execution speed of the program and improve the user experience. The above is an introduction to the Excel data streaming performance optimization method based on the Streaming Excel Reader framework.Hope to help you!