我在2个PostgreSQL数据库中有大量数据，我想将其写入excel文件，我已经很好地工作了代码，但是问题是需要很长时间。另外，当我选择数据周期超过3个月时，服务器中将出现“ Java堆空间”错误，因为它多于200万行。我需要一种更有效的方式将数据写入excel文件，而且timestamp列需要在写入文件之前将其更改为DateTime列。我将文件制作为服务器，然后将文件路径返回到客户端以进行下载。
请编写示例代码来解决我的问题。
public String exportRmsValues(String path, String query, String query2) {
System.out.println(query);
System.out.println(query2);
dateFormat = new SimpleDateFormat("yyyy/MM/dd HH:mm:ss");
Calendar cal = Calendar.getInstance();
System.out.println("start exportRmsValues \n" + dateFormat.format(cal.getTime()));
Connection c = null;
Statement st = null;
Connection c2 = null;
Statement st2 = null;
XSSFWorkbook wb = new XSSFWorkbook();
XSSFSheet sheet = wb.createSheet("RMS Data Sheet 1");
XSSFSheet sheet2 = wb.createSheet("RMS Data Sheet 2");
XSSFSheet sheet3 = wb.createSheet("RMS Data Sheet 3");
//XSSFCellStyle my_style = wb.createCellStyle();
//XSSFFont my_font = wb.createFont();
//my_font.setBoldweight(XSSFFont.BOLDWEIGHT_BOLD);
//my_style.setFont(my_font);
Row rowhead = sheet.createRow(0);
rowhead.createCell(0).setCellValue("Va");
rowhead.createCell(1).setCellValue("Vb");
rowhead.createCell(2).setCellValue("Vc");
rowhead.createCell(3).setCellValue("Ia");
rowhead.createCell(4).setCellValue("Ib");
rowhead.createCell(5).setCellValue("Ic");
rowhead.createCell(6).setCellValue("datatime");
Row rowhead2 = sheet2.createRow(0);
rowhead2.createCell(0).setCellValue("Va");
rowhead2.createCell(1).setCellValue("Vb");
rowhead2.createCell(2).setCellValue("Vc");
rowhead2.createCell(3).setCellValue("Ia");
rowhead2.createCell(4).setCellValue("Ib");
rowhead2.createCell(5).setCellValue("Ic");
rowhead2.createCell(6).setCellValue("datatime");
Row rowhead3 = sheet3.createRow(0);
rowhead3.createCell(0).setCellValue("Va");
rowhead3.createCell(1).setCellValue("Vb");
rowhead3.createCell(2).setCellValue("Vc");
rowhead3.createCell(3).setCellValue("Ia");
rowhead3.createCell(4).setCellValue("Ib");
rowhead3.createCell(5).setCellValue("Ic");
rowhead3.createCell(6).setCellValue("datatime");
try {
Class.forName("org.postgresql.Driver");
String conString = "jdbc:postgresql://" + host + ":" + port + "/" + DBName
+ "?user=" + user + "&pass=" + pass;
String conString1 = "jdbc:postgresql://" + host + ":" + port2 + "/" + DBName2
+ "?user=" + user + "&pass=" + pass;
c = DriverManager.getConnection(conString);
c2 = DriverManager.getConnection(conString1);
st = c.createStatement();
st2 = c2.createStatement();
String file_name = "RMS_"+dateFormat2.format(cal.getTime())+".xlsx";
//path = "/opt/jetty/files/"+file_name;
path = path + file_name;
List<ResultSet> resultSets = new ArrayList<>();
resultSets.add(st.executeQuery(query));
resultSets.add(st2.executeQuery(query2));
ResultSets rs = new ResultSets(resultSets);
int index = 1; // row index 0 for columns name
int index2 = 1;
int index3 = 1;
int sheetCount = 1;
Row row = null;
Calendar calendar = Calendar.getInstance();
//TimeZone tz = TimeZone.getDefault();
while (rs.next()) {
//XSSFRow row = sheet.createRow((long) index);
if ( sheetCount <= 1000000 ) {
row = sheet.createRow(index);
index++;
}
if ( sheetCount > 1000000 && sheetCount <= 2000000) {
row = sheet2.createRow(index2);
index2++;
}
if ( sheetCount > 2000000 && sheetCount <= 3000000) {
row = sheet3.createRow(index3);
index3++;
}
/*else {
row = sheet2.createRow(index2);
index2++;
if ( sheetCount >= 2000000 ) {
row = sheet3.createRow(index3);
index3++;
}
}*/
row.createCell(0).setCellValue(rs.getDoubleValues("va"));
row.createCell(1).setCellValue(rs.getDoubleValues("vb"));
row.createCell(2).setCellValue(rs.getDoubleValues("vc"));
row.createCell(3).setCellValue(rs.getDoubleValues("ia"));
row.createCell(4).setCellValue(rs.getDoubleValues("ib"));
row.createCell(5).setCellValue(rs.getDoubleValues("ic"));
long datatime = rs.getLongValues("datatime");
calendar.setTimeInMillis(datatime * 1000);
SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
Date currenTimeZone = (Date) calendar.getTime();
row.createCell(6).setCellValue(sdf.format(currenTimeZone));
sheetCount++;
}
FileOutputStream fileOut = new FileOutputStream(path);
wb.write(fileOut);
fileOut.close();
System.out.println("Data is saved in excel file.");
rs.close();
st.close();
c.close();
st2.close();
c2.close();
} catch (Exception e) {
System.out.println(e);
e.printStackTrace();
}
Calendar cal1 = Calendar.getInstance();
System.out.println("finish exportRmsValues \n" + dateFormat.format(cal1.getTime()));
return path;
}
答案 0 :(得分：2)
我有很好的方法而且很快
query = "select name, to_timestamp(datatime) from x ";
CopyManager copyManager = new CopyManager((BaseConnection) c);
File file = new File(path);
FileOutputStream fileOutputStream = new FileOutputStream(file);
//and finally execute the COPY command to the file with this method:
copyManager.copyOut("COPY (" + query + ") TO STDOUT WITH (FORMAT CSV)", fileOutputStream);
这会将查询中的所有数据写入CSV文件。
答案 1 :(得分：0)
您可以使用 BCP实用工具来实现。命令行查询只是将查询返回的数据复制为所需格式而已。在计算机上安装BCP实用程序后，运行以下代码段：
public class ExcelExport {
public static void main(String[] args) {
String excelFileName = "excel/myExcelFile.xls"; // Other formats also supported like .csv, .xlsx etc
String query = "The SQL Query goes here";
String databaseName = "DatabseName";
String ServerUrl = "DatabaseServerUrl/IP";
String userName = "DatabaseUsername";
String password = "DatabasePassword";
String bcpCommand = "bcp \"" + query + "\" queryout \"" + excelFileName + "\" -c -d \"" + databaseName
+ "\" -S " + ServerUrl + " -U \"" + userName + "\" -P \"" + password + "\"";
System.out.println("BCP Command : " + bcpCommand);
// Executes BCP command using command line
ProcessBuilder processBuilder = new ProcessBuilder("cmd.exe", "/c", bcpCommand);
try {
Process process = processBuilder.start();
BufferedReader reader = new BufferedReader(new InputStreamReader(process.getInputStream()));
String line;
while (true) {
line = reader.readLine();
if (line == null) {
break;
}
System.out.println(line);
}
System.out.println("Excel File Created !!!");
} catch (IOException ioException) {
ioException.printStackTrace();
System.out.println("Failed to export data to excel !!!");
}
}
}
注意：：它不能像Apache POI那样精美地格式化excel文件，但是要导出数百万个数据。这样可以节省大量时间。您可以手动进行格式化。该代码复制查询返回的所有数据。因此，请记住您的记录数不应超过excel文件的行限制，即当前版本的 1,048,576 行和Office 2003之前的 65536 行。因此，您的情况是200万如果需要，行可以创建多个文件。