大数据导出是当我们的导出数量在几万,到上百万的数据时,一次从数据库查询这么多数据加载到内存然后写入会对我们的内存和CPU都产生压力,这个时候需要我们像分页一样处理导出分段写入Excel缓解Excel的压力 EasyPoi提供的是两个方法 ***强制使用 xssf版本的Excel*** ~~~ /** * @param entity * 表格标题属性 * @param pojoClass * Excel对象Class * @param dataSet * Excel对象数据List */ public static Workbook exportBigExcel(ExportParams entity, Class<?> pojoClass, Collection<?> dataSet) { ExcelBatchExportServer batachServer = ExcelBatchExportServer .getExcelBatchExportServer(entity, pojoClass); return batachServer.appendData(dataSet); } public static void closeExportBigExcel() { ExcelBatchExportServer batachServer = ExcelBatchExportServer.getExcelBatchExportServer(null, null); batachServer.closeExportBigExcel(); } ~~~ 添加数据和关闭服务,关闭服务不是必须的,可以调也可以不掉 我们只需要for循环写入Excel就可以了 ~~~ @Test public void bigDataExport() throws Exception { List<MsgClient> list = new ArrayList<MsgClient>(); Workbook workbook = null; Date start = new Date(); ExportParams params = new ExportParams("大数据测试", "测试"); for (int i = 0; i < 1000000; i++) { //一百万数据量 MsgClient client = new MsgClient(); client.setBirthday(new Date()); client.setClientName("小明" + i); client.setClientPhone("18797" + i); client.setCreateBy("JueYue"); client.setId("1" + i); client.setRemark("测试" + i); MsgClientGroup group = new MsgClientGroup(); group.setGroupName("测试" + i); client.setGroup(group); list.add(client); if(list.size() == 10000){ workbook = ExcelExportUtil.exportBigExcel(params, MsgClient.class, list); list.clear(); } } ExcelExportUtil.closeExportBigExcel(); System.out.println(new Date().getTime() - start.getTime()); File savefile = new File("D:/excel/"); if (!savefile.exists()) { savefile.mkdirs(); } FileOutputStream fos = new FileOutputStream("D:/excel/ExcelExportBigData.bigDataExport.xlsx"); workbook.write(fos); fos.close(); } ~~~ 生成的Excel数据  Cpu和内存  多次测试用时统计,速度还是可以接受的,^^ | 数据量 | 用时 | 文件大小 | 列数 | | --- | --- | --- | --- | | 100W| 16.4s| 24.3MB | 5| | 100W| 15.9s | 24.3MB| 5 | | 200W| 29.5s | 48.5MB | 5 | | 100W | 30.8s | 37.8MB | 10 | | 200W | 58.7s | 76.1MB | 10 |