使用(POI)SAX处理Excel大文件,防止内存溢出

时间:2024-12-01 16:06:37

POISAXReader

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解决POI读取XLSX文件内存占用过过多

poi处理excel分别提供比较友好的用户模式以及比较底层的事件模式。其中,用户模式提供良好的封装,同时兼容2003以及2007以上的格式,使用相当方便。不过,代价是花费巨大的内存。只要超过6w条以后,基本是就是内存溢出了。
  好在POI团队也提供了更底层的的流处理模式eventMode,对于大数据的Xlsx文件的写入,poi 3.8 提供SXSSF,采用缓存方式写如文件。对于文件的读取采用sax的方式直接读取每个sheet对应的xml文件。添加微信,回复poi,邀请你加群

使用(POI)SAX处理Excel大文件,防止内存溢出

POI SheetContentsHandler 接口

在POI中已经对SAX当时读取对应的Sheet的xml文件已经做了基本的封装,所以我们仅仅需要实现接口SheetContentsHandler,就可以完成SAX的方式读取。这个接口中需要是实现三个方法

  • public void startRow(int rowNum) 读取某行开始
  • public void endRow(int rowNum) 读取某行结束
  • public void cell(String cellReference, String formattedValue,XSSFComment comment) 读取某行中的单元格
  • public void headerFooter(String text, boolean isHeader, String tagName) 暂时不清楚

POI SheetContentsHandler实现

这里我主要参照poi XLSX2CSV.java实现方式,需要提供对应的xlsx文件最大列数。其次,我在此基础上做了扩展,在 endRow 提供了一个事件,当前处理的的行数据,让这个解析功能更加独立。
实现思路,在startRow方法中构造一个List对象,在cell函数中添加每个单元内容,在endRow函数中判断当前列是否等于最大列数,如果不等循环补齐,并出发添加行事件
SheetSaxHandler详细代码

protected class SheetSaxHandler implements SheetContentsHandler {
private int currentRow = -1;
private int currentCol = -1;
private int minColumns; public void setMinColumns(int minColumns) {
this.minColumns = minColumns;
} public SheetSaxHandler(int minColumns) {
super();
this.minColumns = minColumns;
} public SheetSaxHandler() {
} private List<SheetRowListener> listeners = new ArrayList<SheetRowListener>();
private List<String> lRows = new ArrayList<String>(); // 处理一行信息 public void rowAdded(SheetRowListener add) {
listeners.add(add);
} private void postRowAdded(List<String> row, int rowNum)
throws SQLException {
for (SheetRowListener hl : listeners)
hl.addRow(row, rowNum);
} @Override
public void startRow(int rowNum) {
currentRow = rowNum;
currentCol = -1;
lRows.clear();
} @Override
public void endRow(int rowNum) {
// 添加数据
for (int i = currentCol; i < minColumns; i++) {
lRows.add("");
}
try {
postRowAdded(lRows, rowNum);
} catch (SQLException e) {
e.printStackTrace();
}
} @Override
public void cell(String cellReference, String formattedValue,
XSSFComment comment) {
if (cellReference == null) {
cellReference = new CellAddress(currentRow, currentCol)
.formatAsString();
}
int thisCol = (new CellReference(cellReference)).getCol();
int missedCols = thisCol - currentCol - 1;//处理数据中间存在空白
for (int i = 0; i < missedCols; i++) {
this.lRows.add("");
}
currentCol = thisCol; // TODO 数据类型处理
try {
Double.parseDouble(formattedValue);
this.lRows.add(formattedValue);
} catch (NumberFormatException e) {
this.lRows.add(formattedValue);
}
} @Override
public void headerFooter(String text, boolean isHeader, String tagName) {
System.out.println(text + "==" + isHeader + "==" + tagName);
} }

事件接口

interface SheetRowListener {
void addRow(List<String> row, int rowNum);
}

调用方式

  1. 打开文件
  2. 找到对应sheet的xml文件
  3. 使用上边的方法依次处理每一个sheet
处理文件
             @Override
public int saveToOracle(String filePath, String pcId)
throws FileNotFoundException, EncryptedDocumentException,
InvalidFormatException, IOException, ClassNotFoundException,
SQLException, OpenXML4JException, SAXException,
ParserConfigurationException {
File f = new File(filePath);
OPCPackage p = null;
int num = 0;
Connection conn = null;
if (f.exists()) {
try {
JSONArray sheetCfgs = this.cfgJson.getJSONArray("sheets");
dataBuferRows = this.cfgJson.getInteger("dataBuferRows");
dataBuferRows = dataBuferRows == null ? 1000 : dataBuferRows;
conn = ca.getConnection(ca.getSqlCfg(serverPath));
String importTime = new SimpleDateFormat(
"yyyy-MM-dd HH:mm:ss.SSS").format(new Date());
p = OPCPackage.open(f, PackageAccess.READ);
ReadOnlySharedStringsTable strings = new ReadOnlySharedStringsTable(
p);
XSSFReader xssfReader = new XSSFReader(p);
StylesTable styles = xssfReader.getStylesTable();
XSSFReader.SheetIterator iter = (XSSFReader.SheetIterator) xssfReader
.getSheetsData();
HashMap<Integer, JSONObject> hSheetCfg = new HashMap<Integer, JSONObject>();
for (int i = 0; i < sheetCfgs.size(); i++) {
JSONObject sheetCfg = sheetCfgs.getJSONObject(i);
hSheetCfg.put(sheetCfg.getInteger("sheetIndex"), sheetCfg);
}
int index = 1;
while (iter.hasNext()) {
InputStream sheetStream = iter.next();
if (hSheetCfg.containsKey(index)) {
processSheet(styles, strings, new SheetSaxHandler(),
sheetStream, hSheetCfg.get(index), conn, pcId,
this.fileName, importTime);
}
index++;
} p.close();
f = null;
conn.close();
} catch (SQLException e) {
conn.close();
conn = null;
throw e;
}
}
return num;
}

处理Sheet

public void processSheet(StylesTable styles,
ReadOnlySharedStringsTable strings, SheetSaxHandler sheetHandler,
InputStream sheetInputStream, final JSONObject sheetCfg,
final Connection conn, String PcID, String fileName,
String importTime) throws IOException,
ParserConfigurationException, SAXException, SQLException { final PreparedStatement ps = conn.prepareStatement(ca.buildInsertSql(
sheetCfg, PcID, fileName, importTime));
final int dataStartNum = sheetCfg.getIntValue("dataStartNum");
sheetHandler.setMinColumns(sheetCfg.getJSONArray("fieldReference")
.size());
sheetHandler.rowAdded(new SheetRowListener() {
@Override
public void addRow(List<String> row, int rowNum) {
if (rowNum < dataStartNum - 1)
return;
try {
ca.setParamter(ps, sheetCfg, row, rowNum - dataStartNum);
if (rowNum % dataBuferRows == 0) {
ps.executeBatch();
ps.clearBatch();
}
} catch (SQLException e) {
try {
ps.close();
conn.close();
throw e;
} catch (SQLException e1) {
e1.printStackTrace();
}
e.printStackTrace();
} }
});
XMLReader sheetParser = SAXHelper.newXMLReader();
DataFormatter formatter = new DataFormatter();
InputSource sheetSource = new InputSource(sheetInputStream);
ContentHandler handler = new XSSFSheetXMLHandler(styles, null, strings,
sheetHandler, formatter, false);
sheetParser.setContentHandler(handler);
sheetParser.parse(sheetSource);
// 处理剩下的数据
ps.executeBatch();
ps.clearBatch();
// 关闭当前ps
ps.close();
}
`

总结

在最初使用poi的用户模式,很快的就完成一个excel文件的解析,很方便。随着项目的逐渐深入,处理的excel文件越来越大,用户模式已经不能胜任。于是开始查找资料,在官网上看到了转csv的实例。
这段代码的主要功能将excel文件中的数据导入到oracle数据库对应的表中,在实现功能方面,我主要遇到了以下问题

  1. 解决excel文件解析内存泄露(2007以后文件采用sax方式基本解决)
  2. 对应大量数据的保存,速度一直很慢,尽管我这里采用了批量提交的方式(目前这问题我依然没找到很好的方案,如果有同行看到的,还希望多多指教