Java项目添加慢SQL查询工具的实践指南

spring:
  datasource:
    driver-class-name: com.p6spy.engine.spy.P6SpyDriver
    url: jdbc:p6spy:oracle:thin:@// **********  /orcl
    username: *********
    password: **********************

appender=com.p6spy.engine.spy.appender.Slf4JLogger
executionThreshold=1000      # 超过1秒才记录
logMessageFormat=com.p6spy.engine.spy.appender.SingleLineFormat
resultSetLoggable=false

<appender name="SLOW_SQL_FILE" class="ch.qos.logback.core.rolling.RollingFileAppender">
    <file>${LOG_PATH}/slow-sql.log</file>
    <rollingPolicy class="ch.qos.logback.core.rolling.SizeAndTimeBasedRollingPolicy">
        <fileNamePattern>${LOG_PATH}/slow-sql-%d{yyyy-MM-dd}.%i.log</fileNamePattern>
        <maxFileSize>50MB</maxFileSize>
        <maxHistory>30</maxHistory>
    </rollingPolicy>
    <encoder>
        <pattern>%d{yyyy-MM-dd HH:mm:ss.SSS} %msg%n</pattern>
    </encoder>
</appender>

<logger name="p6spy" level="INFO" additivity="false">
    <appender-ref ref="SLOW_SQL_FILE"/>
</logger>

import java.io.*;
import java.util.*;
import java.util.regex.*;

public class SlowSqlAnalyzer {

    public static void main(String[] args) throws IOException {
        if (args.length < 1) {
            System.out.println("Usage: java SlowSqlAnalyzer <slow-sql.log>");
            return;
        }

        String logFile = args[0];

        // 正则匹配 P6Spy SQL 日志行
        Pattern sqlPattern = Pattern.compile("\\|\\d+\\|statement\\|.*?\\|(SELECT|INSERT|UPDATE|DELETE).*", Pattern.CASE_INSENSITIVE);

        Map<String, SqlStats> statsMap = new HashMap<>();

        try (BufferedReader reader = new BufferedReader(new FileReader(logFile))) {
            String line;
            while ((line = reader.readLine()) != null) {
                String[] parts = line.split("\\|", 6);
                if (parts.length < 6) continue;
                int execTime;
                try {
                    execTime = Integer.parseInt(parts[1]);
                } catch (NumberFormatException e) {
                    continue;
                }
                String sqlText = parts[5].trim();
                Matcher matcher = sqlPattern.matcher(line);
                if (matcher.find()) {
                    // 用前200字符作为 key，避免重复太多
                    String key = sqlText.length() > 200 ? sqlText.substring(0, 200) : sqlText;
                    SqlStats s = statsMap.getOrDefault(key, new SqlStats(sqlText));
                    s.count++;
                    s.totalTime += execTime;
                    s.maxTime = Math.max(s.maxTime, execTime);
                    s.like = s.like || sqlText.toUpperCase().contains("LIKE");
                    s.groupBy = s.groupBy || sqlText.toUpperCase().contains("GROUP BY");
                    statsMap.put(key, s);
                }
            }
        }

        // 输出统计结果
        System.out.printf("%5s | %12s | %12s | %6s | %8s | %s%n",
                "次数", "平均耗时(ms)", "最大耗时(ms)", "LIKE", "GROUP BY", "SQL示例前200字符");
        System.out.println("--------------------------------------------------------------------------------------------------------");

        statsMap.values().stream()
                .sorted((a,b) -> Long.compare(b.totalTime, a.totalTime))
                .forEach(s -> {
                    long avg = s.totalTime / s.count;
                    System.out.printf("%5d | %12d | %12d | %6b | %8b | %s%n",
                            s.count, avg, s.maxTime, s.like, s.groupBy, s.sqlSnippet);
                });
    }

    static class SqlStats {
        String sqlSnippet;
        int count = 0;
        long totalTime = 0;
        long maxTime = 0;
        boolean like = false;
        boolean groupBy = false;

        SqlStats(String sql) {
            this.sqlSnippet = sql;
        }
    }
}

javac SlowSqlAnalyzer.java
java SlowSqlAnalyzer /data/javaApp/rest-tonp-realization/logs/slow-sql.log