解析 kettle 日志文件
将 文本文件转成字符串
private String readInput(File file) {
StringBuffer buffer = new StringBuffer();
try {
FileInputStream fis = new FileInputStream(file);
InputStreamReader isr = new InputStreamReader(fis, "GBK");
Reader in = new BufferedReader(isr);
int i;
while ((i= in.read()) > -1) {
buffer.append((char) i);
}
in.close();
return buffer.toString();
} catch (IOException e) {
e.printStackTrace();
return null;
}
}
将字符串写入文件中
private void writeOutput(String str, File file) {
try {
FileOutputStream fos = new FileOutputStream(file);
Writer out = new OutputStreamWriter(fos, "GBK");
out.write(str);
out.close();
} catch (IOException e) {
e.printStackTrace();
}
}
存储解析的 kettle 信息的 日志类：
public class KettleLogParse {
// 表示第几张表
private int tableNumber;
// 表示表名
private String tableName;
// 表示抽取是否成功
private boolean isSuccess;
// 表示警告的数量
private int warnNumber;
// 表示抽取的数量
private int dataNumber;
// 日志添加在第几行
private int lineNumber;
public int getTableNumber() {
return tableNumber;
}
public void setTableNumber(int tableNumber) {
this.tableNumber = tableNumber;
}
public boolean isSuccess() {
return isSuccess;
}
public void setSuccess(boolean isSuccess) {
this.isSuccess = isSuccess;
}
public int getWarnNumber() {
return warnNumber;
}
public void setWarnNumber(int warnNumber) {
this.warnNumber = warnNumber;
}
public int getDataNumber() {
return dataNumber;
}
public void setDataNumber(int dataNumber) {
this.dataNumber = dataNumber;
}
public String getTableName() {
return tableName;
}
public void setTableName(String tableName) {
this.tableName = tableName;
}
public int getLineNumber() {
return lineNumber;
}
public void setLineNumber(int lineNumber) {
this.lineNumber = lineNumber;
}
@Override
public String toString() {
String flag = isSuccess == true ? "，抽取成功，共" : "，抽取失败，共";
return "表" + tableNumber + "：" + tableName + flag + warnNumber + "个警报，抽取量为" + dataNumber + "条";
}
}
解析 kettle 的日志文件，并返回解析好的信息：
// 传入日志文件解析得到的字符串
private List parseKettleLog(String kettle) {
String[] strs=kettle.split("\r\n");
// 默认第一张表为表1
int tableNumber = 1;
int lineNumber = 0;
List recordList = new ArrayList<>();
Stack stack = new Stack<>();
// 错误数
int errorNum = 0;
// 警告数
int warningNum = 0;
// 遍历解析日志文件
for(int i=0; i
//获取每行的字符串
String str = strs[i];
// 遇到开始项，则向stack里面压入一个 KettleLogParse (kettlelog解析实例)，开始对解析实例做处理
if (str.contains("开始项")) {
KettleLogParse addLogEntity = new KettleLogParse();
addLogEntity.setTableNumber(tableNumber);
addLogEntity.setLineNumber(lineNumber);
errorNum = 0;
warningNum = 0;
stack.push(addLogEntity);
}
// 获取该解析项的一些初始信息，表名，抽取文件路径等等
if (str.contains("Loading transformation from XML file")) {
KettleLogParse addLogEntity = stack.peek();
int tableNameStart = str.lastIndexOf("[");
int tableNameEnd = str.lastIndexOf("]");
String tableName = str.substring(tableNameStart+1, tableNameEnd);
int lastIndexOf;
if (tableName.contains("file")) {
lastIndexOf = tableName.lastIndexOf("/");
} else {
lastIndexOf = tableName.lastIndexOf("\\");
}
String tableName1 = tableName.substring(lastIndexOf+1);
addLogEntity.setTableName(tableName1);
tableNumber++;
}
// 对该处理项的结果进行解析
if (str.contains("完成处理")) {
KettleLogParse addLogEntity = stack.peek();
int beginIndex = str.lastIndexOf("(");
int endIndex = str.lastIndexOf(")");
String record = str.substring(beginIndex+1, endIndex);
List asList = Arrays.asList(record.split(","));
Map map = getKettleMap(asList);
addLogEntity.setWarnNumber(warningNum);
addLogEntity.setDataNumber(map.get(" W"));
if (errorNum == 0) {
addLogEntity.setSuccess(true);
}
}
完成时出栈，并设置最终的解析结果
if (str.contains("完成作业项")) {
KettleLogParse addLogEntity = stack.pop();
if(addLogEntity.getTableName()!=null) {
recordList.add(addLogEntity);
}
}
// 记录错误数
if (str.contains("- ERROR")) {
errorNum++;
}
// 记录警告数
if (str.contains("- Warning:")) {
warningNum++;
}
lineNumber++;
}
return recordList;
}
根据解析信息，获取新的日志文本字符串
private String pageKettle (String kettle, List recordList) {
String[] strs=kettle.split("\r\n");
StringBuilder result = new StringBuilder("");
for (int i = 0; i < strs.length; i++) {
String string = strs[i];
KettleLogParse insertLine = isInsertLine(i, recordList);
if(insertLine!=null) {
String warning = insertLine.getWarnNumber() > 0 ? "
" : "
";
if (insertLine.isSuccess() == false) {
warning = "
";
}
result.append(warning+insertLine.toString()+"
}else {
result.append("
}
}
return result.toString();
}
// 判断是否在该行插入新的解析数据,是则返回插入数据，否返回空
private KettleLogParse isInsertLine(int index, List list) {
for(KettleLogParse logEntity : list) {
if(index==logEntity.getLineNumber()) {
return logEntity;
}
}
return null;
}
对文本文件进行修改，添加标签。
/**
* 在文本文件中插入的字符串，不同 HTML 标签
* @param kettle
* @param recordList
* @return
*/
private String pageLogFile (String kettle, List recordList) {
String[] strs=kettle.split("\r\n");
StringBuilder result = new StringBuilder("");
for (int i = 0; i < strs.length; i++) {
String string = strs[i];
KettleLogParse insertLine = isInsertLine(i, recordList);
if(insertLine!=null) {
result.append(insertLine.toString()+"\r\n"+string+"\r\n");
}else {
result.append(string+"\r\n");
}
}
return result.toString();
}
日志解析过程中，获取其中的特殊数据：
// 获取日志中I=0, O=0, R=77175, W=77175, U=0, E=0，并将其解析成map结构
private Map getKettleMap(List list){
Map map = new HashMap();
for (String str : list) {
String[] split = str.split("=");
map.put(split[0], Integer.parseInt(split[1]));
}
return map;
}
获取日志文件
private File requiredLogFile(Map kettleLog, boolean isTrusted) {
File logFile = null;
try {
Object logTime = kettleLog.get("logDate");
String rootPath = ResourceUtil.getConfigByName("data.kettle.path");
// 获取文件路径
String filePath = rootPath + "/" + (isTrusted ? "Trusted_Log_" : "Print_Log_")
+ logTime.toString().replace("-", "") + ".log";
// 获取文件对象
logFile = new File(filePath);
// 如果文件存在，则返回，不存在，则写入。
if (logFile.exists() && logFile.isFile() && logFile.length() != 0) {
String readInput = readInput(logFile);
if(readInput.contains("个警报，抽取量为")) {
return logFile;
}
List parseKettleLog = parseKettleLog(readInput);
String pageLogFile = pageLogFile(readInput, parseKettleLog);
writeOutput(pageLogFile, logFile);
return logFile;
}
// 如果文件存在，但文件内容为空
if (logFile.exists() && logFile.length() == 0) {
logFile.delete();
}
if (!logFile.getParentFile().exists()) {
logFile.getParentFile().mkdirs();
}
logFile.createNewFile();
Object fileContent = kettleLog.get("dataLog");
FileWriter writer = new FileWriter(logFile);
writer.write(fileContent.toString());
writer.close();
String readInput = readInput(logFile);
List parseKettleLog = parseKettleLog(readInput);
String pageLogFile = pageLogFile(readInput, parseKettleLog);
writeOutput(pageLogFile, logFile);
} catch (Exception e) {
e.printStackTrace();
}
return logFile;
}
对日志文件进行压缩处理
/**
* 压缩一个文件集合中的所有文件，并返回压缩文件
* @param fileList
* @return
*/
private File logToZip(List fileList) {
File zipFile = null;
ZipOutputStream zos = null;
try {
zipFile = File.createTempFile("ketteLogZip", ".zip");
zos = new ZipOutputStream(new FileOutputStream(zipFile));
int i = 0;
for (File srcFile : fileList) {
byte[] buf = new byte[2048];
// 防止文件重名导致压缩失败
String fileName = srcFile.getName();
String prefix = fileName.substring(fileName.lastIndexOf("."));
String newFileName = fileName.substring(0, fileName.length()-prefix.length()) + "_" +i+ prefix;
zos.putNextEntry(new ZipEntry(newFileName));
int len;
FileInputStream in = new FileInputStream(srcFile);
while ((len = in.read(buf)) != -1){
zos.write(buf, 0, len);
}
zos.closeEntry();
in.close();
zos.flush();
i++;
}
} catch (Exception e) {
e.printStackTrace();
} finally {
if(zos != null) {
try {
zos.close();
} catch (IOException e) {
e.printStackTrace();
}
}
}
return zipFile;
}
查询接口
@Override
public Map queryKettleLog(String beginTime,String endTime,String logFlag,Integer pageId, Integer pageNum){
// 查询日志的SQL
String sql = "SELECT ID_JOB as id, left(LOGDATE,10) as logDate, `ERRORS` as logFlag, REPLAYDATE AS STARTDATE, LOGDATE AS ENDDATE, LOG_FIELD as dataLog FROM t_sdrs_data_extraction_log";
// 日志总数
String sql1 = "SELECT COUNT(*) FROM t_sdrs_data_extraction_log";
// 筛选条件
String condition = " WHERE 1=1";
if(!StringUtils.isBlank(beginTime)){
condition = condition +" AND LOGDATE >='"+beginTime+"'";
}
if(!StringUtils.isBlank(endTime)){
condition = condition +" AND LOGDATE <='"+endTime+"'";
}
if(!StringUtils.isBlank(logFlag)){
if(logFlag.equals("1")) {
condition = condition +" AND `ERRORS` !='0'";
}else {
condition = condition +" AND `ERRORS` ='0'";
}
}
condition = condition + " ORDER BY LOGDATE DESC";
sql = sql + condition;
sql1 = sql1 + condition;
// dao层查询方法
Map map = Maps.newHashMap();
Long total = systemService.getCountForJdbc(sql1);
List> kettleLogList = systemService.findForJdbc(sql,pageId,pageNum);
// 开始解析，目标是统计没条日志中有无错误，或警告
Iterator> iterator = kettleLogList.iterator();
while (iterator.hasNext()){
Map queryMap = iterator.next();
Object object = queryMap.get("dataLog");
List parseKettleLog = parseKettleLog(object.toString());
int sumRecord = 0; //每条日志中的记录总数
int resultFlag = 0; // 记录的标志：0正常，1错误，2警告
for (KettleLogParse parse : parseKettleLog) {
int dataNumber = parse.getDataNumber();
sumRecord = sumRecord + dataNumber;
// error 检查
if (resultFlag!=1) {
if(parse.isSuccess()==false) {
resultFlag = 1;
}
}
if(resultFlag == 0) {
if(parse.getWarnNumber()>0) {
resultFlag = 2;
}
}
}
//当日志的解析结果和查询的条件不一致时，将其从所有数据中移除。
if(!StringUtils.isBlank(logFlag)&&!logFlag.equals(String.valueOf(resultFlag))) {
iterator.remove();
continue;
}
queryMap.put("sumRecord", sumRecord);
queryMap.put("resultFlag", resultFlag);
}
map.put("ketteLog", kettleLogList);
map.put("total", total);
return map;
}