The performance optimization skills and best practice of the CLJ Excel framework
The CLJ Excel framework is a powerful functional to generate an open source framework for generating excel files, but it may encounter performance problems when dealing with a large amount of data.This article will introduce the performance optimization skills and best practices of some CLJ Excel frameworks, and provide some Java code examples.
1. Improve writing performance
When processing a large amount of data, writing the excel file may become very slow.In order to improve the writing performance, the following measures can be taken:
-Swritten data: Avoid writing data one by one, but to write a batch of data at a time to reduce the number of file IO times.
-Addling with buffer: The use of buffer can reduce the impact of IO operation on performance.Before writing the data, store the data in the buffer area in memory, and then write it to the Excel file at once.
-Ad the multi -thread: On the multi -core processor, you can consider using multi -threaded parallel writing data to improve the writing performance.
The following is a sample code that shows how to use the CLJ Excel framework in batches:
// Import the required class
import com.monitorjbl.xlsx.StreamingWriter;
import com.monitorjbl.xlsx.impl.StreamingRow;
import org.apache.poi.ss.usermodel.Cell;
import org.apache.poi.ss.usermodel.Row;
// Create an excel file
StreamingWriter writer = StreamingWriter.builder().rowCacheSize(100).bufferSize(4096).build();
OutputStream out = new FileOutputStream("data.xlsx");
// data input
for (int i = 0; i < data.length; i++) {
Row row = new StreamingRow();
for (int j = 0; j < data[i].length; j++) {
Cell cell = row.createCell(j);
cell.setCellValue(data[i][j]);
}
writer.write(row);
}
// Close the file stream
writer.close();
out.close();
2. Use the appropriate data structure
When processing a large amount of data, choosing the appropriate data structure can greatly improve performance.For example, the use of arrays rather than a list can reduce memory consumption and access time.
The following is a sample code that shows how to use array to save data, and improve performance when writing the excel file:
// Create a two -dimensional array as a data source
String[][] data = {
{"Name", "age", "gender"},
{"Zhang San", "25", "Male"},
// ... more data
};
// Create an excel file
StreamingWriter writer = StreamingWriter.builder().rowCacheSize(100).bufferSize(4096).build();
OutputStream out = new FileOutputStream("data.xlsx");
// data input
for (int i = 0; i < data.length; i++) {
Row row = new StreamingRow();
for (int j = 0; j < data[i].length; j++) {
Cell cell = row.createCell(j);
cell.setCellValue(data[i][j]);
}
writer.write(row);
}
// Close the file stream
writer.close();
out.close();
3. Avoid frequent style operations
When processing a large amount of data, frequent style operations may affect performance.In order to improve performance, the following measures can be taken:
-Colon the style in advance: Before writing the data, create a styling object in advance and cache to avoid repeatedly creating styles of expenses.
-Stake style: Avoid setting styles one by one, but set a batch of cell styles at a time to reduce the number of style operations.
The following is an example code that shows how to create style objects in advance and perform batch settings:
// Create an excel file
StreamingWriter writer = StreamingWriter.builder().rowCacheSize(100).bufferSize(4096).build();
OutputStream out = new FileOutputStream("data.xlsx");
// Create style
CellStyle cellStyle = writer.getWorkbook().createCellStyle();
cellStyle.setAlignment(HorizontalAlignment.CENTER);
cellStyle.setVerticalAlignment(VerticalAlignment.CENTER);
// ... more style settings
// data input
for (int i = 0; i < data.length; i++) {
Row row = new StreamingRow();
for (int j = 0; j < data[i].length; j++) {
Cell cell = row.createCell(j);
cell.setCellValue(data[i][j]);
Cell.SetCellStyle (CellStyle); // Batch setting style
}
writer.write(row);
}
// Close the file stream
writer.close();
out.close();
In addition to the techniques and practice mentioned above, you can also consider using paging reading and writing data, saving the Excel file with compression formats, etc. to further optimize the performance of the CLJ Excel framework.However, it is necessary to adjust and test according to the specific scenario and data amount to obtain better performance effects.
