java - 如何从 Excel 文件中逐行读取值并将其放入 Map 中？

Question

我的目标是阅读具有已知格式的 Excel 文档，一次阅读每个单元格和列。每行将被设置到一个名为 Item 的 bean 中，该 bean 将被放入一个映射中，其键作为项目编号。一旦我这样做了，我就可以继续程序的其余部分并将其放入数据库中。我目前一次写一整个专栏，并试图弄清楚如何做到这一点。

public class Excel {

    private Items items;

    Excel(Items items) {
        this.items = items;
    }

    public static void main(String[] args) {

        JFileChooser fileChooser = new JFileChooser();
        int returnVlue = fileChooser.showOpenDialog(null);

        Map<Long, Items> map1 = new HashMap<Long, Items>();

        String mat, thick, size, lbsPerSheet, lbs;

        if (returnVlue == JFileChooser.APPROVE_OPTION) {

            try {
                Workbook workbook = new HSSFWorkbook(new FileInputStream(
                        fileChooser.getSelectedFile()));
                Sheet sheet = workbook.getSheetAt(0);

                for (Iterator<Row> rit = sheet.rowIterator(); rit.hasNext();) {

                    Row row = rit.next();

                    for (Iterator<Cell> cit = row.cellIterator(); cit.hasNext();) {
                        Cell cell = cit.next();
                        cell.setCellType(Cell.CELL_TYPE_STRING);

                        mat = cell.getStringCellValue();
                        thick = cell.getStringCellValue();
                        size = cell.getStringCellValue();
                        lbsPerSheet = cell.getStringCellValue();
                        lbs = cell.getStringCellValue();

                        System.out.println("Mat "+mat+" Thick "+ thick+" Size "+size+" lbs Per Sheet "+lbsPerSheet+" lbs "+lbs+ "\t");
                    }
                    System.out.println();

                }

            } catch (Exception e) {
                // TODO: handle exception
            }

        }

    }
}

输出

Mat 11960120 Thick 11960120 Size 11960120 lbs Per Sheet 11960120 lbs 11960120   
Mat 0.119 Thick 0.119 Size 0.119 lbs Per Sheet 0.119 lbs 0.119  
Mat 60x120 Thick 60x120 Size 60x120 lbs Per Sheet 60x120 lbs 60x120 
Mat 250 Thick 250 Size 250 lbs Per Sheet 250 lbs 250    
Mat 0.41 Thick 0.41 Size 0.41 lbs Per Sheet 0.41 lbs 0.41   

Row org.apache.poi.hssf.usermodel.HSSFRow@2a
Mat 18860120 Thick 18860120 Size 18860120 lbs Per Sheet 18860120 lbs 18860120   
Mat 0.188 Thick 0.188 Size 0.188 lbs Per Sheet 0.188 lbs 0.188  
Mat 60x120 Thick 60x120 Size 60x120 lbs Per Sheet 60x120 lbs 60x120 
Mat 383 Thick 383 Size 383 lbs Per Sheet 383 lbs 383    
Mat 0.41 Thick 0.41 Size 0.41 lbs Per Sheet 0.41 lbs 0.41   

Row org.apache.poi.hssf.usermodel.HSSFRow@2a
Mat 25060120 Thick 25060120 Size 25060120 lbs Per Sheet 25060120 lbs 25060120   
Mat 0.25 Thick 0.25 Size 0.25 lbs Per Sheet 0.25 lbs 0.25   
Mat 60x120 Thick 60x120 Size 60x120 lbs Per Sheet 60x120 lbs 60x120 
Mat 510 Thick 510 Size 510 lbs Per Sheet 510 lbs 510    
Mat 0.41 Thick 0.41 Size 0.41 lbs Per Sheet 0.41 lbs 0.41   

Row org.apache.poi.hssf.usermodel.HSSFRow@2a
Mat 25072144 Thick 25072144 Size 25072144 lbs Per Sheet 25072144 lbs 25072144   
Mat 0.25 Thick 0.25 Size 0.25 lbs Per Sheet 0.25 lbs 0.25   
Mat 72x144 Thick 72x144 Size 72x144 lbs Per Sheet 72x144 lbs 72x144 
Mat 734.4 Thick 734.4 Size 734.4 lbs Per Sheet 734.4 lbs 734.4  
Mat 0.41 Thick 0.41 Size 0.41 lbs Per Sheet 0.41 lbs 0.41   

Row org.apache.poi.hssf.usermodel.HSSFRow@2a
Mat 31360120 Thick 31360120 Size 31360120 lbs Per Sheet 31360120 lbs 31360120   
Mat 0.313 Thick 0.313 Size 0.313 lbs Per Sheet 0.313 lbs 0.313  
Mat 60x120 Thick 60x120 Size 60x120 lbs Per Sheet 60x120 lbs 60x120 
Mat 633.2616 Thick 633.2616 Size 633.2616 lbs Per Sheet 633.2616 lbs 633.2616   
Mat 0.41 Thick 0.41 Size 0.41 lbs Per Sheet 0.41 lbs 0.41   

Row org.apache.poi.hssf.usermodel.HSSFRow@2a
Mat 37560120 Thick 37560120 Size 37560120 lbs Per Sheet 37560120 lbs 37560120   
Mat 0.375 Thick 0.375 Size 0.375 lbs Per Sheet 0.375 lbs 0.375  
Mat 60x120 Thick 60x120 Size 60x120 lbs Per Sheet 60x120 lbs 60x120 
Mat 758.7 Thick 758.7 Size 758.7 lbs Per Sheet 758.7 lbs 758.7  
Mat 0.41 Thick 0.41 Size 0.41 lbs Per Sheet 0.41 lbs 0.41   

Row org.apache.poi.hssf.usermodel.HSSFRow@2a
Mat 50060120 Thick 50060120 Size 50060120 lbs Per Sheet 50060120 lbs 50060120   
Mat 0.5 Thick 0.5 Size 0.5 lbs Per Sheet 0.5 lbs 0.5    
Mat 60x120 Thick 60x120 Size 60x120 lbs Per Sheet 60x120 lbs 60x120 
Mat 1011.6 Thick 1011.6 Size 1011.6 lbs Per Sheet 1011.6 lbs 1011.6 
Mat 0.41 Thick 0.41 Size 0.41 lbs Per Sheet 0.41 lbs 0.41   

Row org.apache.poi.hssf.usermodel.HSSFRow@2a
Mat 75060120 Thick 75060120 Size 75060120 lbs Per Sheet 75060120 lbs 75060120   
Mat 0.75 Thick 0.75 Size 0.75 lbs Per Sheet 0.75 lbs 0.75   
Mat 60x120 Thick 60x120 Size 60x120 lbs Per Sheet 60x120 lbs 60x120 
Mat 1517.4 Thick 1517.4 Size 1517.4 lbs Per Sheet 1517.4 lbs 1517.4 
Mat 0.41 Thick 0.41 Size 0.41 lbs Per Sheet 0.41 lbs 0.41   

Row org.apache.poi.hssf.usermodel.HSSFRow@2a
Mat 10060120 Thick 10060120 Size 10060120 lbs Per Sheet 10060120 lbs 10060120   
Mat 1 Thick 1 Size 1 lbs Per Sheet 1 lbs 1  
Mat 60x120 Thick 60x120 Size 60x120 lbs Per Sheet 60x120 lbs 60x120 
Mat 2023.2 Thick 2023.2 Size 2023.2 lbs Per Sheet 2023.2 lbs 2023.2 
Mat 0.41 Thick 0.41 Size 0.41 lbs Per Sheet 0.41 lbs 0.41   

Excel文件

11960120        0.119   60x120  250.00   $0.4100 
18860120        0.188   60x120  383.00   $0.4100 
25060120        0.250   60x120  510.00   $0.4100 
25072144        0.250   72x144  734.40   $0.4100 
31360120        0.313   60x120  633.26   $0.4100 
37560120        0.375   60x120  758.70   $0.4100 
50060120        0.500   60x120  1011.60  $0.4100 
75060120        0.750   60x120  1517.40  $0.4100 
10060120        1.000   60x120  2023.20  $0.4100 

我想像读取二维数组一样读取上面的 Excel 文件。例如:

array[0][0] = 11960120; array[0][1] = 0.119; array[0][2]= "60x120";

如果我可以像上面那样读取行和列，则使用 Items 类中的 getter 和 setter，然后只需将“Item”放入 map 中并用项目编号将其包装起来，例如 11960120 位于单元格 [0] 中[0] 在上面的 Excel 示例中。

更清楚地说，我想像这样读取 Excel 文件

11960120    0.119   60x120  250.00   $0.4100 

然后阅读下一行

18860120    0.188   60x120  383.00   $0.4100

每个单元格都将被设置到 Items 类中。

Answer 1

您可以使用Apache Metamodel用于查询 Excel 电子表格的库。下面我展示的方法保留了列名称，因此您可以编写一个方法来按列名称和行号获取值。如果您不想要/没有列名，则必须调整此代码:

private static org.slf4j.Logger logger = LoggerFactory.getLogger( "Data" );

public static Object[][] getExcelData( File excelFile, String sheetName ) 
{   
    ExcelConfiguration conf = new ExcelConfiguration( 1, true, false );
    DataContext dataContext = DataContextFactory.createExcelDataContext( excelFile, conf );
    DataSet dataSet = dataContext.query()
            .from( sheetName )
            .selectAll()
            .where("run").eq("Y")
            .execute();
    List<Row> rows = dataSet.toRows();
    Object[][] myArray = get2ArgArrayFromRows( rows );
    return myArray;
}

/**
 * Gets a 2D Object array from a List of Row objects that is only 2 args wide.
 * @param rows
 * @return
 */
public static Object[][] get2ArgArrayFromRows( List<Row> rows ) {
    Object[][] myArray = new Object[rows.size()][2];
    int i = 0;
    SelectItem[] cols = rows.get(0).getSelectItems();
    for ( Row r : rows ) {
        Object[] data = r.getValues();
        for ( int j = 0; j < cols.length; j++ ) {
            if ( data[j] == null ) data[j] = ""; // force empty string where there are NULL values
        }
        myArray[i][0] = cols;
        myArray[i][2] = data;
        i++;
    }
    logger.info( "Row count: " + rows.size() );
    logger.info( "Column names: " + Arrays.toString( cols ) );
    return myArray;
}

然后，如果您愿意，可以使用 Google Guava将二维数组转换为列表。 (我认为如果存在欺骗，转换为 map 会出现问题？):

Double[][] array;
List<List<Double>> list = Lists.transform(Arrays.asList(array),
  new Function<Double[], List<Double>>() {
    @Override public List<Double> apply(Double[] row) {
      return Arrays.asList(row);
    }
  }
}