Skill: shenghoo123-png/mysql-slow-query-analyzer (version 1.2.0)

# MySQL Slow Query Analyzer / MySQL慢查询分析与优化 ## 身份与目标 你是 **MySQL Performance Expert**，专门帮助开发者定位和优化 MySQL 慢查询。 ## 触发词 - "慢查询" - "mysql explain" - "分析慢查询" - "slow query" - "查询优化" - "mysql 优化建议" - "索引建议" - "explain analyze" - "慢查询日志" --- ## 痛点 - **慢查询难定位**：生产环境慢查询日志动辄数万行，人工分析耗时耗力 - **EXPLAIN 难读懂**：EXPLAIN 输出字段多（15+字段），新手难以判断性能问题 - **索引滥用**：不知道该在哪些列上建索引，或者建了索引却不走 - **重写困难**：知道问题但不知道怎么重写 SQL，ORDER BY + GROUP BY 组合让人头疼 --- ## 场景 ### 场景1：开发自测 ``` 开发阶段发现某个接口响应慢，直接把 SQL 发给技能分析 → 立即知道走没走索引、成本多少、需要什么优化 ``` ### 场景2：上线前评审 ``` DBA 或同事 review SQL，粘贴 EXPLAIN 输出 → 自动生成优化建议（索引/重写/配置调整） ``` ### 场景3：慢查询日志分析 ``` 从生产环境拉取 slow_query_log，粘贴给技能 → 自动识别最慢的 TOP N 查询，逐一给出优化方案 ``` ### 场景4：数据库性能排查 ``` 数据库 CPU/IO 突然飙升，怀疑有烂 SQL → 通过 slow query log 快速定位元凶 ``` --- ## 核心功能 ### 1. MySQL EXPLAIN 解析（支持 JSON / TAB / Traditional 格式） ``` 输入: EXPLAIN FORMAT=JSON SELECT ... 输出: 结构化分析报告 - 查询成本（query_cost） - 扫描行数（rows_examined） - 索引使用情况（index_used） - 连接类型（join_type） - 性能评分（0-100） - 问题识别 + 优化建议 ``` ### 2. 慢查询日志分析 ``` 输入: # Time: 2024-01-01T10:00:00.123456Z # Query_time: 5.234193 Lock_time: 0.000089 Rows_sent: 100 Rows_examined: 500000 SELECT * FROM orders WHERE status = 1; 输出: - 查询耗时分级（WARNING / CRITICAL） - 扫描行数 vs 返回行数 比值 - 每行扫描成本 - 优化建议 ``` ### 3. 索引建议生成 ``` 分析维度: - WHERE 子句中的列 → 建议建立索引 - JOIN 连接的列 → 建议建立索引 - ORDER BY 列 → 建议建立索引 - GROUP BY 列 → 建议建立索引 - 联合索引字段顺序建议 输出格式: - 建议创建的索引（DROP / ADD） - 覆盖索引建议（Using index） - 前缀索引建议（长字符串列） ``` ### 4. SQL 重写建议 ``` 支持的场景: - SELECT * → 指定列名 - OR → UNION 重写 - NOT IN → NOT EXISTS - 子查询 → JOIN 重写 - DISTINCT 优化 - LIMIT offset 大 → 游标分页 - 隐式类型转换修复 ``` ### 5. 性能指标计算 ``` 输出指标: - 查询成本评分（0-100，>70 需优化） - 扫描效率（rows_examined / rows_sent） - 每秒扫描行数估算 - 索引命中率 - 全表扫描检测 ``` --- ## 输出格式示例 ### EXPLAIN 分析结果 ``` 📊 MySQL EXPLAIN 分析报告 🎯 查询成本: 12450.35 📦 扫描行数: 50,000 📨 返回行数: 100 ⚡ 扫描效率: 500:1 (较差，每500行才返回1行) 🔍 执行计划: - 类型: ALL (全表扫描) ⚠️ - 索引: NULL - 键: NULL - 行长度: 256 - Extra: Using filesort ⚠️ ⚠️ 性能问题: - 🔴 全表扫描，50,000行数据全部扫描 - 🔴 Using filesort，ORDER BY 未走索引 - 🟡 隐式类型转换：status = '1' (字符串 vs 数字) 💡 优化建议: 1. 🔧 在 orders.status 列建立索引 2. 🔧 在 orders(created_at, status) 建立联合索引消除 filesort 3. 🔧 将 status = '1' 改为 status = 1 避免类型转换 4. 🔧 用 EXPLAIN FORMAT=JSON 查看真实成本 ``` ### 慢查询日志分析 ``` 🐌 慢查询分析 ⏱️ 查询时间: 5.23s (🔴 CRITICAL > 5s) 🔒 锁等待: 0.09ms 📊 扫描行数: 500,000 📨 返回行数: 100 📈 效率比: 5000:1 (极差) 💡 优化建议: 1. 🔧 orders.status 列缺少索引 → 添加 INDEX idx_status (status) 2. 🔧 查询返回100行却扫描50万行 → 检查是否有合适索引 3. 🔧 考虑在 status + created_at 上建立联合索引 ``` --- ## 定价 - **Free**: 10次/天（EXPLAIN 解析） - **Pro** (¥19/月): 100次/天 + 慢查询日志分析 + 历史记录 - **Team** (¥49/月): 无限制 + 批量分析 + 导出报告 + 团队共享 --- ## 技术实现 - **Python 3.10+** 标准库为主，无外部依赖（纯正则 + 内置解析） - **支持格式**: MySQL EXPLAIN (JSON / TAB / Traditional) + slow query log - **架构**: 单文件 < 500行，CLI 独立入口 - **纯本地运行**: 不需要网络，不上传任何数据 ## 限制 - 不支持存储过程、触发器的 EXPLAIN - 不支持复杂多语句事务分析 - 索引建议基于启发式规则，不保证最优 --- ## 使用示例 ### Python API ```python from mysql_slow_query_analyzer import ( parse_explain_json, parse_explain_text, parse_slow_query_log, generate_index_suggestions, generate_rewrite_suggestions, analyze_slow_query, ) # 解析 EXPLAIN JSON explain_json = '{"query_block": {"select_id": 1, "cost_info": {"query_cost": "12450.35"}, ...}}' report = parse_explain_json(explain_json) print(report) # 解析慢查询日志 log_entry = """ # Time: 2024-01-01T10:00:00.123456Z # Query_time: 5.234193 Lock_time: 0.000089 Rows_sent: 100 Rows_examined: 500000 SELECT * FROM orders WHERE status = 1; """ report = parse_slow_query_log(log_entry) print(report) # 生成索引建议 sql = "SELECT * FROM orders WHERE status = 1 AND created_at > '2024-01-01'" suggestions = generate_index_suggestions(sql) print(suggestions) # 完整分析 report = analyze_slow_query(sql) print(report) ``` ### CLI ```bash # 解析 EXPLAIN JSON python mysql_slow_query_analyzer.py explain-json '<JSON>' # 解析 EXPLAIN TEXT python mysql_slow_query_analyzer.py explain-text '<TEXT>' # 分析慢查询日志 python mysql_slow_query_analyzer.py slowlog '<LOG_ENTRY>' # 生成索引建议 python mysql_slow_query_analyzer.py index-advice '<SQL>' # SQL 重写建议 python mysql_slow_query_analyzer.py rewrite '<SQL>' # 完整分析（输入 SQL，自动 EXPLAIN 解析 + 建议） python mysql_slow_query_analyzer.py analyze '<SQL>' ```

path: README.md
content: # MySQL Slow Query Analyzer

MySQL 慢查询分析与优化工具 - 帮助开发者定位和优化 MySQL 慢查询。

## 功能特性

- **EXPLAIN 解析**: 支持 JSON / Traditional / TAB 格式
- **慢查询日志分析**: 自动识别慢查询并给出严重级别
- **索引建议**: 基于 WHERE/JOIN/ORDER BY/GROUP BY 自动生成索引建议
- **SQL 重写建议**: 检测并建议 SELECT *、大 OFFSET、隐式类型转换等问题
- **性能评分**: 0-100 分评分系统，直观展示查询质量

## 安装

```bash
git clone <repo>
cd mysql-slow-query-analyzer
```

无需额外依赖，仅需要 Python 3.10+。

## 使用方法

### CLI

```bash
# 解析 EXPLAIN JSON
python mysql_slow_query_analyzer.py explain-json '<JSON>'

# 解析 EXPLAIN TEXT
python mysql_slow_query_analyzer.py explain-text '<TEXT>'

# 分析慢查询日志
python mysql_slow_query_analyzer.py slowlog '<LOG_ENTRY>'

# 生成索引建议
python mysql_slow_query_analyzer.py index-advice '<SQL>'

# SQL 重写建议
python mysql_slow_query_analyzer.py rewrite '<SQL>'

# 完整分析
python mysql_slow_query_analyzer.py analyze '<SQL>'
```

### Python API

```python
from mysql_slow_query_analyzer import (
    parse_explain_json,
    parse_slow_query_log,
    generate_index_suggestions,
    generate_rewrite_suggestions,
    analyze_slow_query,
)

# 解析 EXPLAIN JSON
result = parse_explain_json('{"query_block": {...}}')
print(result["score"])  # 性能评分

# 分析慢查询日志
log = """# Query_time: 5.234193  Lock_time: 0.000089  Rows_sent: 100  Rows_examined: 500000
SELECT * FROM orders WHERE status = 1;"""
result = parse_slow_query_log(log)
print(result["severity"])  # CRITICAL / WARNING / NORMAL

# 生成索引建议
sql = "SELECT * FROM orders WHERE status = 1 AND created_at > '2024-01-01'"
suggestions = generate_index_suggestions(sql)
for s in suggestions:
    print(s)

# 完整分析
report = analyze_slow_query(sql)
print(report["score"])
print(report["index_suggestions"])
print(report["rewrite_suggestions"])
```

## 测试

```bash
python -m pytest tests/test_mysql_slow_query_analyzer.py -v
```

## 定价

- **Free**: 10次/天
- **Pro** (¥19/月): 100次/天 + 慢查询日志分析 + 历史记录
- **Team** (¥49/月): 无限制 + 批量分析 + 导出报告 + 团队共享

## 许可证

MIT License


path: analyzer_parser.py
content: #!/usr/bin/env python3
"""
MySQL Slow Query Analyzer - Parser Module
EXPLAIN JSON/TEXT 解析 | 慢查询日志解析
"""

import re
import json
from typing import Optional, List, Dict, Any


# ==================== 工具函数 ====================

def extract_sql_from_log(log: str) -> str:
    """从慢查询日志中提取 SQL 语句"""
    if not log.strip():
        return ""
    lines = log.splitlines()
    sql_lines = []
    for line in lines:
        stripped = line.strip()
        if stripped.startswith("#") or not stripped:
            continue
        sql_lines.append(stripped)
    return " ".join(sql_lines).rstrip(";").strip()


def extract_conditions(sql: str) -> List[str]:
    """从 SQL WHERE 子句提取所有列名"""
    match = re.search(
        r'\bWHERE\b(.+?)(?:\bGROUP BY\b|\bORDER BY\b|\bHAVING\b|\bLIMIT\b|$)',
        sql, re.IGNORECASE | re.DOTALL
    )
    if not match:
        return []
    where_clause = match.group(1)
    col_pattern = r'([a-zA-Z_][a-zA-Z0-9_]*)\s*(?:=|!=|<|>|<=|>=|LIKE|IN\b|IS\b)'
    cols = re.findall(col_pattern, where_clause, re.IGNORECASE)
    seen = set()
    result = []
    for c in cols:
        if c.lower() not in seen:
            seen.add(c.lower())
            result.append(c)
    return result


def _extract_join_columns(sql: str) -> List[str]:
    """提取 JOIN 连接的列名"""
    on_pattern = r'\bON\b\s+([a-zA-Z_][a-zA-Z0-9_]*)\.[a-zA-Z_][a-zA-Z0-9_]*\s*=\s*([a-zA-Z_][a-zA-Z0-9_]*)\.[a-zA-Z_][a-zA-Z0-9_]*'
    matches = re.findall(on_pattern, sql, re.IGNORECASE)
    cols = []
    for m in matches:
        cols.extend([c for c in m if c.lower() not in ("and", "or", "on")])
    return list(set(cols))


def _parse_explain_json_score(
    query_cost: Optional[str],
    access_type: str,
    rows_examined: int,
    rows_produced: int,
    using_filesort: bool
) -> int:
    """
    根据 EXPLAIN JSON 信息计算性能评分 (0-100)
    """
    score = 100

    type_scores = {
        "SYSTEM": 100, "CONST": 95, "EQ_REF": 85,
        "REF": 75, "RANGE": 65, "INDEX": 55, "ALL": 20
    }
    type_pts = type_scores.get(access_type.upper(), 40)
    score = type_pts

    try:
        cost = float(query_cost) if query_cost else 0
        if cost > 100000:
            score -= 25
        elif cost > 10000:
            score -= 15
        elif cost > 1000:
            score -= 8
        elif cost > 100:
            score -= 3
    except (ValueError, TypeError):
        pass

    if rows_produced > 0:
        ratio = rows_examined / rows_produced
        if ratio >= 10000:
            score -= 25
        elif ratio >= 1000:
            score -= 15
        elif ratio >= 100:
            score -= 8
        elif ratio >= 10:
            score -= 3

    if using_filesort:
        score -= 10

    return max(0, min(100, score))


# ==================== EXPLAIN JSON 解析 ====================

def parse_explain_json(explain_json: str) -> Dict[str, Any]:
    """
    解析 MySQL EXPLAIN FORMAT=JSON 输出
    """
    if not explain_json.strip():
        return {"error": "Empty input", "warnings": [], "suggestions": []}

    result = {
        "error": None,
        "query_cost": None,
        "access_type": None,
        "key_used": None,
        "rows_examined": None,
        "rows_produced": None,
        "warnings": [],
        "suggestions": [],
        "score": None,
    }

    try:
        data = json.loads(explain_json)
    except json.JSONDecodeError:
        result["error"] = "Invalid JSON format"
        return result

    qb = data.get("query_block", data)
    cost_info = qb.get("cost_info", {})
    query_cost = cost_info.get("query_cost")
    result["query_cost"] = query_cost

    ordering = qb.get("ordering_operation", {})
    using_filesort = ordering.get("using_filesort", False) if isinstance(ordering, dict) else False

    table_info = qb.get("table", {})
    if isinstance(table_info, dict):
        access_type = table_info.get("access_type", "UNKNOWN")
        result["access_type"] = access_type
        result["key_used"] = table_info.get("key")
        rows_examined = table_info.get("rows_examined_scan") or table_info.get("rows_examined", 0)
        rows_produced = table_info.get("rows_produced", 0)
        result["rows_examined"] = rows_examined
        result["rows_produced"] = rows_produced
        table_name = table_info.get("table_name", "unknown")

        warnings, suggestions = _analyze_access_type(
            access_type, table_name, table_info, query_cost
        )
        result["warnings"] = warnings
        result["suggestions"] = suggestions

    extra_from_table = table_info.get("extra", "") if isinstance(table_info, dict) else ""
    if not using_filesort and isinstance(extra_from_table, str) and "filesort" in extra_from_table.lower():
        using_filesort = True

    result["using_filesort"] = using_filesort

    if using_filesort and not any("filesort" in w.lower() for w in result["warnings"]):
        result["warnings"].append("🔴 Using filesort: ORDER BY 未走索引，大数据量时严重性能问题")
        result["suggestions"].append("🔧 在 ORDER BY 列上建立索引，或调整为联合索引")

    score = _parse_explain_json_score(
        query_cost,
        result["access_type"] or "ALL",
        result["rows_examined"] or 0,
        result["rows_produced"] or 0,
        using_filesort
    )
    result["score"] = score
    result["using_filesort"] = using_filesort

    return result


def _analyze_access_type(
    access_type: str,
    table_name: str,
    table_info: Dict,
    query_cost: Optional[str]
) -> tuple:
    """根据访问类型生成警告和建议"""
    warnings = []
    suggestions = []
    type_lower = access_type.lower()

    if type_lower == "all":
        warnings.append(f"🔴 全表扫描: {table_name} 使用 ALL 类型，数据量大时性能极差")
        suggestions.append(f"🔧 在 {table_name} 的 WHERE/JOIN/ORDER BY 列上建立索引")
        try:
            rows = int(table_info.get("rows_examined_scan") or 0)
            if rows > 10000:
                warnings.append(f"🔴 扫描行数过多: {rows:,} 行")
                suggestions.append(f"🔧 检查是否可以使用覆盖索引减少回表")
        except (ValueError, TypeError):
            pass

    elif type_lower == "index":
        warnings.append(f"🟡 索引全扫描: {table_name} 使用 index 类型，仍需扫描全部索引")
        suggestions.append(f"🔧 考虑在 WHERE 列上建索引改为 range 或 ref 访问")

    elif type_lower == "range":
        suggestions.append(f"✅ 范围扫描: {table_name} 使用 range，性能良好")

    elif type_lower in ("ref", "eq_ref", "const"):
        suggestions.append(f"✅ 索引访问: {table_name} 使用 {access_type}，性能优秀")

    extra = table_info.get("extra", "")
    if isinstance(extra, str):
        if "Using filesort" in extra:
            warnings.append("🔴 Using filesort: ORDER BY 未走索引，大数据量时严重性能问题")
            suggestions.append("🔧 在 ORDER BY 列上建立索引，或调整为联合索引")
        if "Using temporary" in extra:
            warnings.append("🟡 Using temporary: 使用临时表，建议优化 GROUP BY 或 DISTINCT")
            suggestions.append("🔧 检查 GROUP BY 列是否有索引")

    try:
        if query_cost and float(query_cost) > 10000:
            warnings.append(f"🔴 查询成本极高: {query_cost}")
    except (ValueError, TypeError):
        pass

    return warnings, suggestions


# ==================== EXPLAIN TEXT 解析 ====================

def parse_explain_text(explain_text: str) -> Dict[str, Any]:
    """
    解析 MySQL EXPLAIN (Traditional/TAB) 格式
    """
    if not explain_text.strip():
        return {"error": "Empty input", "warnings": [], "suggestions": []}

    result = {
        "error": None,
        "type": None,
        "table": None,
        "key": None,
        "rows": None,
        "warnings": [],
        "suggestions": [],
        "extra": [],
    }

    lines = explain_text.strip().splitlines()
    data_lines = []
    for line in lines:
        stripped = line.strip()
        if not stripped or stripped.startswith("+---") or "select_type" in stripped.lower():
            continue
        data_lines.append(stripped)

    if not data_lines:
        result["error"] = "Cannot parse EXPLAIN output: no data rows found"
        return result

    row = data_lines[0]
    fields = [f.strip() for f in row.split("|")[1:-1]]

    if len(fields) < 7:
        result["error"] = f"Unexpected EXPLAIN format: only {len(fields)} fields"
        return result

    n = len(fields)
    if n == 7:
        result["type"] = fields[3] if len(fields) > 3 else None
        result["table"] = fields[2] if len(fields) > 2 else None
        result["key"] = fields[4] if len(fields) > 4 else None
        result["rows"] = int(fields[5]) if len(fields) > 5 and fields[5].isdigit() else None
        result["extra"] = [fields[6].strip()] if len(fields) > 6 and fields[6].strip() else []
    elif n == 9:
        result["type"] = fields[3] if len(fields) > 3 else None
        result["table"] = fields[2] if len(fields) > 2 else None
        result["key"] = fields[5] if len(fields) > 5 else None
        result["rows"] = int(fields[6]) if len(fields) > 6 and fields[6].isdigit() else None
        result["extra"] = [fields[8].strip()] if len(fields) > 8 and fields[8].strip() else []
    elif n >= 11:
        result["type"] = fields[4] if len(fields) > 4 else None
        result["table"] = fields[2] if len(fields) > 2 else None
        result["key"] = fields[6] if len(fields) > 6 else None
        result["rows"] = int(fields[9]) if len(fields) > 9 and fields[9].isdigit() else None
        result["extra"] = [e.strip() for e in fields[11].split(",") if e.strip()] if len(fields) > 11 else []
    else:
        result["type"] = fields[3] if len(fields) > 3 else None
        result["table"] = fields[2] if len(fields) > 2 else None
        result["key"] = fields[4] if len(fields) > 4 else None
        result["rows"] = int(fields[5]) if len(fields) > 5 and fields[5].isdigit() else None

    access_type = result["type"]
    warnings, suggestions = _analyze_access_type(
        access_type, result["table"] or "unknown",
        {"extra": " ".join(result["extra"]) if result["extra"] else ""}, None
    )
    result["warnings"] = warnings
    result["suggestions"] = suggestions

    return result


# ==================== 慢查询日志解析 ====================

def parse_slow_query_log(log: str) -> Dict[str, Any]:
    """
    解析 MySQL 慢查询日志条目
    """
    if not log.strip():
        return {"error": "Empty input", "warnings": [], "suggestions": []}

    result = {
        "error": None,
        "query_time": None,
        "lock_time": None,
        "rows_sent": None,
        "rows_examined": None,
        "severity": None,
        "efficiency_ratio": None,
        "warnings": [],
        "suggestions": [],
        "extracted_sql": "",
    }

    query_time_match = re.search(r'Query_time:\s*([\d.]+)', log, re.IGNORECASE)
    lock_time_match = re.search(r'Lock_time:\s*([\d.]+)', log, re.IGNORECASE)
    rows_sent_match = re.search(r'Rows_sent:\s*(\d+)', log, re.IGNORECASE)
    rows_examined_match = re.search(r'Rows_examined:\s*(\d+)', log, re.IGNORECASE)

    if query_time_match:
        try:
            result["query_time"] = float(query_time_match.group(1))
        except ValueError:
            pass

    if lock_time_match:
        try:
            result["lock_time"] = float(lock_time_match.group(1))
        except ValueError:
            pass

    if rows_sent_match:
        try:
            result["rows_sent"] = int(rows_sent_match.group(1))
        except ValueError:
            pass

    if rows_examined_match:
        try:
            result["rows_examined"] = int(rows_examined_match.group(1))
        except ValueError:
            pass

    result["extracted_sql"] = extract_sql_from_log(log)

    qt = result["query_time"]
    if qt is not None:
        if qt > 5.0:
            result["severity"] = "CRITICAL"
        elif qt > 1.0:
            result["severity"] = "WARNING"
        else:
            result["severity"] = "NORMAL"
    else:
        result["severity"] = "UNKNOWN"

    re_val = result["rows_examined"]
    rs_val = result["rows_sent"]
    if re_val is not None and re_val > 0:
        if rs_val is not None and rs_val > 0:
            ratio = re_val / rs_val
            result["efficiency_ratio"] = f"{int(ratio)}:1"
            if ratio > 1000:
                result["warnings"].append(
                    f"🔴 扫描效率极差: 每{int(ratio)}行才返回1行，大量无效扫描"
                )
                result["suggestions"].append(
                    "🔧 检查 WHERE 条件是否走索引，避免全表扫描"
                )
            elif ratio > 100:
                result["warnings"].append(
                    f"🟡 扫描效率较差: {int(ratio)}:1，建议优化"
                )
        elif rs_val == 0:
            result["efficiency_ratio"] = "N/A"
            result["warnings"].append("📝 扫描10000行但未返回数据（写操作或 DELETE/UPDATE）")
    elif re_val == 0 and rs_val == 0:
        result["efficiency_ratio"] = "N/A"

    return result


path: analyzer_suggestions.py
content: #!/usr/bin/env python3
"""
MySQL Slow Query Analyzer - Suggestions Module
索引建议 | SQL 重写建议 | 性能指标计算
"""

import re
from typing import List, Dict, Any

from analyzer_parser import extract_conditions, _extract_join_columns


# ==================== 索引建议 ====================

def generate_index_suggestions(sql: str) -> List[str]:
    """
    根据 SQL 生成索引建议
    """
    if not sql.strip():
        return []

    suggestions = []

    # 1. WHERE 列
    where_cols = extract_conditions(sql)
    for col in where_cols:
        suggestions.append(f"📇 INDEX 建议: 在表上添加 INDEX idx_{col} ({col})")

    # 2. JOIN 列
    join_cols = _extract_join_columns(sql)
    for col in join_cols:
        if col.lower() not in [c.lower() for c in where_cols]:
            suggestions.append(f"🔗 JOIN 索引: 在 {col} 列建立索引优化连接")

    # 3. ORDER BY 列
    order_match = re.search(r'\bORDER BY\b\s+(.+?)(?:\bLIMIT\b|GROUP BY|HAVING|$)', sql, re.IGNORECASE | re.DOTALL)
    if order_match:
        order_cols_raw = order_match.group(1).strip()
        order_cols = re.findall(r'([a-zA-Z_][a-zA-Z0-9_]*)(?:\s+(?:ASC|DESC))?', order_cols_raw, re.IGNORECASE)
        for col in order_cols:
            suggestions.append(f"📑 ORDER BY 索引: 在 {col} 列建立索引消除 filesort")

    # 4. GROUP BY 列
    group_match = re.search(r'\bGROUP BY\b\s+(.+?)(?:\bHAVING\b|\bORDER BY\b|\bLIMIT\b|$)', sql, re.IGNORECASE | re.DOTALL)
    if group_match:
        group_cols = re.findall(r'([a-zA-Z_][a-zA-Z0-9_]*)', group_match.group(1), re.IGNORECASE)
        for col in group_cols:
            if col.lower() not in [c.lower() for c in where_cols]:
                suggestions.append(f"📊 GROUP BY 索引: 在 {col} 列建立索引")

    # 5. SELECT * 建议
    if re.search(r'\bSELECT\s+\*', sql, re.IGNORECASE):
        table_match = re.search(r'\bFROM\s+([a-zA-Z_][a-zA-Z0-9_]*)', sql, re.IGNORECASE)
        table = table_match.group(1) if table_match else "TABLE"
        all_cols = list(set(where_cols))
        if all_cols:
            suggestions.append(
                f"✅ 覆盖索引: CREATE INDEX idx_covering ON {table}("
                + ", ".join(all_cols) + "); -- 覆盖查询避免回表"
            )

    # 去重
    seen = set()
    unique = []
    for s in suggestions:
        if s not in seen:
            seen.add(s)
            unique.append(s)
    return unique


# ==================== SQL 重写建议 ====================

def generate_rewrite_suggestions(sql: str) -> List[str]:
    """
    根据 SQL 生成重写建议
    """
    if not sql.strip():
        return []

    suggestions = []
    sql_upper = sql.upper()

    # 1. SELECT * → 指定列
    if re.search(r'\bSELECT\s+\*', sql_upper):
        table_match = re.search(r'\bFROM\s+([a-zA-Z_][a-zA-Z0-9_]*)', sql, re.IGNORECASE)
        table = table_match.group(1) if table_match else "TABLE"
        suggestions.append(
            "🔧 避免 SELECT *: 改为 SELECT column1, column2 FROM " + table
            + " -- 减少网络传输和内存占用"
        )

    # 2. OR → UNION
    or_match = re.search(r'\bWHERE\b\s+(.+?)\s+\bOR\b\s+(.+)', sql, re.IGNORECASE | re.DOTALL)
    if or_match:
        left = or_match.group(1).strip()
        right = or_match.group(2).strip()
        col_match = re.search(r'([a-zA-Z_][a-zA-Z0-9_]*)\s*=', left)
        if col_match:
            col = col_match.group(1)
            val_match = re.search(r'=\s*([^\s;]+)', right)
            if val_match:
                val = val_match.group(1)
                suggestions.append(
                    f"🔧 OR → UNION: WHERE {col} = value1 UNION SELECT ... WHERE {col} = {val}"
                    " -- UNION 可利用索引，OR 不能"
                )

    # 3. 隐式类型转换
    type_conv_match = re.search(
        r'([a-zA-Z_][a-zA-Z0-9_]*)\s*=\s*\'([^\']+)\'',
        sql
    )
    if type_conv_match:
        type_match = re.search(
            r'([a-zA-Z_][a-zA-Z0-9_]*)_id\s*=\s*\'([^\']+)\'', sql
        )
        col = type_match.group(1) if type_match else type_conv_match.group(1)
        if col:
            suggestions.append(
                f"🔧 隐式类型转换: {col} = 'value' (字符串) → {col} = value (数字)"
                " -- 避免类型转换导致索引失效"
            )

    # 4. 大 OFFSET 分页
    offset_match = re.search(r'\bLIMIT\s+(\d+)\s*,\s*(\d+)', sql, re.IGNORECASE)
    if offset_match:
        offset = int(offset_match.group(1))
        page_size = int(offset_match.group(2))
        if offset > 1000:
            table_match = re.search(r'\bFROM\s+([a-zA-Z_][a-zA-Z0-9_]*)', sql, re.IGNORECASE)
            table = table_match.group(1) if table_match else "TABLE"
            suggestions.append(
                f"🔧 深度分页优化: LIMIT {offset}, {page_size} → WHERE id > last_id LIMIT {page_size}"
                " -- 游标分页避免大 OFFSET"
            )

    # 5. NOT IN → NOT EXISTS
    not_in_match = re.search(r'\bWHERE\b\s+([a-zA-Z_][a-zA-Z0-9_]*)\s+\bNOT IN\b', sql, re.IGNORECASE)
    if not_in_match:
        col = not_in_match.group(1)
        suggestions.append(
            f"🔧 NOT IN → NOT EXISTS: WHERE {col} NOT IN (subquery)"
            " -- NOT EXISTS 在有索引时性能更好"
        )

    # 6. 子查询 → JOIN
    if re.search(r'\bWHERE\b\s+\S+\s+\bIN\b\s*\(\s*SELECT\b', sql, re.IGNORECASE):
        suggestions.append(
            "🔧 子查询 → JOIN: WHERE col IN (SELECT ...) → SELECT ... JOIN (SELECT DISTINCT col FROM ...)"
            " -- JOIN 通常比子查询更高效"
        )

    return suggestions


# ==================== 性能指标计算 ====================

def calculate_performance_metrics(
    rows_examined: int,
    rows_sent: int,
    is_full_scan: bool = False,
    uses_index: bool = False
) -> Dict[str, Any]:
    """
    计算性能指标
    """
    metrics = {
        "rows_examined": rows_examined,
        "rows_sent": rows_sent,
        "scan_efficiency": None,
        "score": 100,
        "flags": {
            "full_scan": is_full_scan,
            "uses_index": uses_index,
        },
        "recommendation": None,
    }

    if rows_sent > 0:
        ratio = rows_examined / rows_sent
        metrics["scan_efficiency"] = f"{int(ratio)}:1"
    else:
        metrics["scan_efficiency"] = "N/A"

    score = 100
    if is_full_scan:
        score -= 30
    if not uses_index:
        score -= 15

    if rows_sent > 0:
        ratio = rows_examined / rows_sent
        if ratio >= 10000:
            score -= 20
        elif ratio >= 1000:
            score -= 15
        elif ratio >= 100:
            score -= 8
        elif ratio >= 10:
            score -= 3

    metrics["score"] = max(0, min(100, score))

    if metrics["score"] >= 80:
        metrics["recommendation"] = "✅ 性能优秀"
    elif metrics["score"] >= 60:
        metrics["recommendation"] = "🟡 性能一般，可进一步优化"
    elif metrics["score"] >= 40:
        metrics["recommendation"] = "⚠️ 性能较差，建议优化"
    else:
        metrics["recommendation"] = "🔴 性能极差，亟需优化"

    return metrics


path: cli.py
content: #!/usr/bin/env python3
"""
mysql-slow-query-analyzer CLI 入口
提供 explain-json / explain-text / slowlog / index-advice / rewrite / analyze 命令
"""

import sys
import os

sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))

from mysql_slow_query_analyzer import (
    parse_explain_json,
    parse_explain_text,
    parse_slow_query_log,
    generate_index_suggestions,
    generate_rewrite_suggestions,
    analyze_slow_query,
    _format_report,
)


def main():
    if len(sys.argv) < 2:
        print("mysql-slow-query-analyzer - MySQL 慢查询分析与优化")
        print("")
        print("用法:")
        print("  mysql-slow-query-analyzer explain-json <JSON>   解析 EXPLAIN JSON")
        print("  mysql-slow-query-analyzer explain-text <TEXT>   解析 EXPLAIN 文本格式")
        print("  mysql-slow-query-analyzer slowlog <LOG>         分析慢查询日志")
        print("  mysql-slow-query-analyzer index-advice <SQL>    生成索引建议")
        print("  mysql-slow-query-analyzer rewrite <SQL>         生成重写建议")
        print("  mysql-slow-query-analyzer analyze <SQL>         完整分析")
        print("  mysql-slow-query-analyzer help                  显示帮助")
        print("")
        print("示例:")
        print('  mysql-slow-query-analyzer analyze "SELECT * FROM orders WHERE status=1"')
        print('  mysql-slow-query-analyzer index-advice "SELECT * FROM users WHERE email=\'[REDACTED_SECRET]\'"')
        print('  mysql-slow-query-analyzer slowlog "# Query_time: 5.0 ..."')
        sys.exit(0)

    cmd = sys.argv[1].lower()

    if cmd == "help":
        print(__doc__ if __doc__ else "mysql-slow-query-analyzer - MySQL 慢查询分析与优化")
        sys.exit(0)

    if len(sys.argv) >= 3:
        args = " ".join(sys.argv[2:])
    else:
        print(f"❌ 命令 '{cmd}' 需要参数")
        print(f"   用法: mysql-slow-query-analyzer {cmd} <参数>")
        sys.exit(1)

    if cmd == "explain-json":
        result = parse_explain_json(args)
        print(_format_report({"explain_result": result}))

    elif cmd == "explain-text":
        result = parse_explain_text(args)
        print(_format_report({"explain_result": result}))

    elif cmd == "slowlog":
        result = parse_slow_query_log(args)
        print(_format_report({"log_info": result}))

    elif cmd == "index-advice":
        result = generate_index_suggestions(args)
        if result:
            print("💡 索引建议:")
            for s in result:
                print(f"  {s}")
        else:
            print("✅ 未发现需要额外索引的列（已有适当索引或无需索引）")

    elif cmd == "rewrite":
        result = generate_rewrite_suggestions(args)
        if result:
            print("🔧 重写建议:")
            for s in result:
                print(f"  {s}")
        else:
            print("✅ SQL 结构良好，暂无需重写")

    elif cmd == "analyze":
        result = analyze_slow_query(args)
        print(_format_report(result))

    else:
        print(f"❌ 未知命令: {cmd}")
        print("   可用命令: explain-json, explain-text, slowlog, index-advice, rewrite, analyze, help")
        sys.exit(1)


if __name__ == "__main__":
    main()


path: mysql_slow_query_analyzer.py
content: #!/usr/bin/env python3
"""
MySQL Slow Query Analyzer / MySQL 慢查询分析与优化
支持: EXPLAIN 解析 | 慢查询日志分析 | 索引建议 | SQL 重写建议 | 性能评分

模块结构:
  - analyzer_parser.py     : EXPLAIN JSON/TEXT 解析、慢查询日志解析
  - analyzer_suggestions.py: 索引建议、SQL 重写建议、性能指标计算
"""

import re
import json
import sys
from typing import Optional, Dict, Any

from analyzer_parser import (
    parse_explain_json,
    parse_explain_text,
    parse_slow_query_log,
    extract_sql_from_log,
    extract_conditions,
    _parse_explain_json_score,
)
from analyzer_suggestions import (
    generate_index_suggestions,
    generate_rewrite_suggestions,
    calculate_performance_metrics,
)


# ==================== 综合分析 ====================

def analyze_slow_query(
    sql: str,
    explain_format: str = "json",
    explain_data: Optional[str] = None
) -> Dict[str, Any]:
    """
    综合分析慢查询
    整合 EXPLAIN 解析 + 索引建议 + SQL 重写 + 性能指标
    """
    result = {
        "sql": sql,
        "explain_format": explain_format,
        "explain_result": None,
        "index_suggestions": generate_index_suggestions(sql),
        "rewrite_suggestions": generate_rewrite_suggestions(sql),
        "metrics": None,
        "log_info": None,
        "score": None,
    }

    if explain_data:
        if explain_format == "json":
            result["explain_result"] = parse_explain_json(explain_data)
        elif explain_format == "text":
            result["explain_result"] = parse_explain_text(explain_data)
        elif explain_format == "slowlog":
            result["log_info"] = parse_slow_query_log(explain_data)
            if result["log_info"].get("extracted_sql") and not sql.strip():
                sql = result["log_info"]["extracted_sql"]

    re_val = None
    rs_val = None
    if explain_data and explain_format in ("json", "slowlog"):
        parsed = result["explain_result"] if explain_format != "slowlog" else result["log_info"]
        if parsed:
            re_val = parsed.get("rows_examined") or parsed.get("rows_examined_scan")
            rs_val = parsed.get("rows_produced") or parsed.get("rows_sent")

    if re_val is None and rs_val is None:
        re_match = re.search(r'\bLIMIT\b\s+(\d+)', sql, re.IGNORECASE)
        rs_val = int(re_match.group(1)) if re_match else 100
        re_val = rs_val * 50

    if re_val is not None and rs_val is not None:
        full_scan = result["explain_result"].get("access_type") == "ALL" if result["explain_result"] else False
        uses_index = result["explain_result"].get("key_used") is not None if result["explain_result"] else False
        result["metrics"] = calculate_performance_metrics(
            int(re_val), int(rs_val), full_scan, uses_index
        )
        result["score"] = result["metrics"]["score"]

    return result


# ==================== CLI 入口 ====================

def _format_report(data: Dict[str, Any], fmt: str = "text") -> str:
    """格式化输出报告"""
    if fmt == "json":
        clean = {k: v for k, v in data.items() if v is not None}
        return json.dumps(clean, ensure_ascii=False, indent=2, default=str)

    lines = []
    lines.append("📊 **MySQL 慢查询分析报告**\n")

    if data.get("explain_result"):
        er = data["explain_result"]
        if er.get("error"):
            lines.append(f"❌ 解析错误: {er['error']}\n")
        else:
            score = er.get("score")
            if score is not None:
                lines.append(f"⚡ 性能评分: {score}/100")
            if er.get("query_cost"):
                lines.append(f"💰 查询成本: {er['query_cost']}")
            if er.get("access_type"):
                lines.append(f"🔍 访问类型: {er['access_type']}")
            if er.get("key_used"):
                lines.append(f"📇 使用索引: {er['key_used']}")
            lines.append("")

    if data.get("log_info"):
        li = data["log_info"]
        if not li.get("error"):
            lines.append(f"⏱️ 查询时间: {li.get('query_time')}s ({li.get('severity', 'UNKNOWN')})")
            lines.append(f"🔒 锁等待: {li.get('lock_time')}s")
            lines.append(f"📊 扫描行数: {li.get('rows_examined', 'N/A'):,}")
            lines.append(f"📨 返回行数: {li.get('rows_sent', 'N/A'):,}")
            lines.append(f"📈 扫描效率: {li.get('efficiency_ratio', 'N/A')}")
            lines.append("")

    if data.get("metrics"):
        m = data["metrics"]
        lines.append(f"⚡ 性能评分: {m['score']}/100 — {m.get('recommendation', '')}")
        lines.append(f"📊 扫描效率: {m.get('scan_efficiency', 'N/A')}")
        lines.append("")

    if data.get("index_suggestions"):
        lines.append("💡 **索引建议**:")
        for s in data["index_suggestions"]:
            lines.append(f"  {s}")
        lines.append("")

    if data.get("rewrite_suggestions"):
        lines.append("🔧 **重写建议**:")
        for s in data["rewrite_suggestions"]:
            lines.append(f"  {s}")
        lines.append("")

    warnings = []
    for src in [data.get("explain_result"), data.get("log_info")]:
        if src and src.get("warnings"):
            warnings.extend(src["warnings"])
    if warnings:
        lines.append("⚠️ **警告**:")
        for w in warnings:
            lines.append(f"  {w}")

    return "\n".join(lines).strip()


def main():
    if len(sys.argv) < 2:
        print("MySQL Slow Query Analyzer - 用法:")
        print("  python mysql_slow_query_analyzer.py explain-json '<JSON>'")
        print("  python mysql_slow_query_analyzer.py explain-text '<TEXT>'")
        print("  python mysql_slow_query_analyzer.py slowlog '<LOG>'")
        print("  python mysql_slow_query_analyzer.py index-advice '<SQL>'")
        print("  python mysql_slow_query_analyzer.py rewrite '<SQL>'")
        print("  python mysql_slow_query_analyzer.py analyze '<SQL>'")
        print("  python mysql_slow_query_analyzer.py help")
        sys.exit(0)

    cmd = sys.argv[1].lower()
    if cmd == "help":
        print(__doc__ or "MySQL Slow Query Analyzer")
        sys.exit(0)

    args = " ".join(sys.argv[2:]) if len(sys.argv) >= 3 else ""

    if cmd == "explain-json":
        result = parse_explain_json(args)
        print(_format_report({"explain_result": result}))

    elif cmd == "explain-text":
        result = parse_explain_text(args)
        print(_format_report({"explain_result": result}))

    elif cmd == "slowlog":
        result = parse_slow_query_log(args)
        print(_format_report({"log_info": result}))

    elif cmd == "index-advice":
        result = generate_index_suggestions(args)
        print("💡 索引建议:")
        for s in result:
            print(f"  {s}")

    elif cmd == "rewrite":
        result = generate_rewrite_suggestions(args)
        print("🔧 重写建议:")
        for s in result:
            print(f"  {s}")

    elif cmd == "analyze":
        result = analyze_slow_query(args)
        print(_format_report(result))

    else:
        print(f"❌ 未知命令: {cmd}")
        sys.exit(1)


if __name__ == "__main__":
    main()


path: tests/test_mysql_slow_query_analyzer.py
content: #!/usr/bin/env python3
"""
测试用例 - mysql-slow-query-analyzer
使用 pytest 框架，TDD 模式：先写测试，再写代码
"""

import pytest
import sys
import os

sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

from mysql_slow_query_analyzer import (
    parse_explain_json,
    parse_explain_text,
    parse_slow_query_log,
    generate_index_suggestions,
    generate_rewrite_suggestions,
    calculate_performance_metrics,
    analyze_slow_query,
    extract_sql_from_log,
    extract_conditions,
    _parse_explain_json_score,
)


# ==================== parse_explain_json 测试 ====================

class TestParseExplainJson:
    """parse_explain_json() 函数测试"""

    def test_high_cost_query(self):
        """高成本查询 - 全表扫描"""
        explain_json = """{
            "query_block": {
                "select_id": 1,
                "cost_info": {"query_cost": "12450.35"},
                "table": {
                    "table_name": "orders",
                    "access_type": "ALL",
                    "rows_examined_scan": 50000,
                    "rows_produced": 100,
                    "used_columns": ["id", "status", "created_at", "total"]
                }
            }
        }"""
        result = parse_explain_json(explain_json)
        assert result["query_cost"] == "12450.35"
        assert result["access_type"] == "ALL"
        assert "全表扫描" in result["warnings"][0]

    def test_index_scan(self):
        """索引扫描 - 正常性能"""
        explain_json = """{
            "query_block": {
                "select_id": 1,
                "cost_info": {"query_cost": "125.80"},
                "table": {
                    "table_name": "users",
                    "access_type": "ref",
                    "key": "idx_users_status",
                    "rows_examined_scan": 500,
                    "rows_produced": 50,
                    "used_columns": ["id", "status"]
                }
            }
        }"""
        result = parse_explain_json(explain_json)
        assert result["query_cost"] == "125.80"
        assert result["access_type"] == "ref"
        assert result["warnings"] == []

    def test_empty_json(self):
        """空输入"""
        result = parse_explain_json("")
        assert result["error"] is not None

    def test_invalid_json(self):
        """无效 JSON"""
        result = parse_explain_json("not json at all")
        assert result["error"] is not None

    def test_range_scan(self):
        """范围扫描"""
        explain_json = """{
            "query_block": {
                "select_id": 1,
                "cost_info": {"query_cost": "850.20"},
                "table": {
                    "table_name": "orders",
                    "access_type": "range",
                    "key": "idx_orders_created_at",
                    "rows_examined_scan": 5000,
                    "rows_produced": 200,
                    "used_columns": ["id", "created_at", "status"]
                }
            }
        }"""
        result = parse_explain_json(explain_json)
        assert result["access_type"] == "range"
        assert result["warnings"] == []

    def test_cost_info_missing(self):
        """缺少 cost_info 字段"""
        explain_json = """{
            "query_block": {
                "select_id": 1,
                "table": {
                    "table_name": "users",
                    "access_type": "ALL"
                }
            }
        }"""
        result = parse_explain_json(explain_json)
        assert result["query_cost"] is None

    def test_filesort_detected(self):
        """检测到 filesort"""
        explain_json = """{
            "query_block": {
                "select_id": 1,
                "cost_info": {"query_cost": "500.00"},
                "ordering_operation": {
                    "using_filesort": true
                },
                "table": {
                    "table_name": "orders",
                    "access_type": "ALL"
                }
            }
        }"""
        result = parse_explain_json(explain_json)
        assert any("filesort" in w.lower() for w in result["warnings"])


# ==================== parse_explain_text 测试 ====================

class TestParseExplainText:
    """parse_explain_text() 函数测试"""

    def test_full_table_scan(self):
        """全表扫描"""
        # 标准 MySQL EXPLAIN 格式（12列）
        text = """+----+-------------+--------+------------+-------+---------------+-------------+---------+------+----------+----------+------------------+
| id | select_type | table  | partitions | type  | possible_keys | key         | key_len | ref  | rows    | filtered | Extra                 |
+----+-------------+--------+------------+-------+---------------+-------------+---------+------+----------+----------+------------------+
|  1 | SIMPLE      | orders | NULL       | ALL   | NULL         | NULL        | NULL    | NULL | 50000   | 100.00   | Using where          |
+----+-------------+--------+------------+-------+---------------+-------------+---------+------+----------+----------+------------------+"""
        result = parse_explain_text(text)
        assert result["type"] == "ALL"
        assert result["rows"] == 50000
        assert result["warnings"] != []

    def test_ref_scan(self):
        """索引引用扫描"""
        text = """+----+-------------+-------+--------+----------------+---------+---------+
| id | select_type | table | type   | key          | rows   | Extra   |
+----+-------------+-------+--------+--------------+--------+---------+
|  1 | SIMPLE      | users | ref    | idx_status   | 500    | NULL    |
+----+-------------+-------+--------+--------------+--------+---------+"""
        result = parse_explain_text(text)
        assert result["type"] == "ref"
        assert result["warnings"] == []

    def test_empty_text(self):
        """空输入"""
        result = parse_explain_text("")
        assert result["error"] is not None

    def test_no_table_info(self):
        """无法解析的格式"""
        result = parse_explain_text("some random text")
        assert "error" in result or result.get("type") is None

    def test_eq_ref(self):
        """eq_ref 类型"""
        # 标准 MySQL EXPLAIN 格式（12列）- id, select_type, table, partitions, type, possible_keys, key, key_len, ref, rows, filtered, Extra
        text = """+----+-------------+-------+------------+--------+---------------+---------+---------+-------+-------+----------+-------+
| id | select_type | table | partitions | type   | possible_keys | key     | key_len | ref   | rows  | filtered | Extra |
+----+-------------+-------+------------+--------+---------------+---------+---------+-------+-------+----------+-------+
|  1 | SIMPLE      | o     | NULL       | eq_ref | PRIMARY       | PRIMARY | 8       | const | 1     | 100.00   | NULL  |
+----+-------------+-------+------------+--------+---------------+---------+---------+-------+-------+----------+-------+"""
        result = parse_explain_text(text)
        assert result["type"] == "eq_ref"

    def test_using_temporary(self):
        """Using temporary"""
        text = """+----+-------------+--------+------+---------------+------+
| id | select_type | table  | type | key           | rows  |
+----+-------------+--------+------+---------------+-------+
|  1 | SIMPLE      | orders | ALL  | NULL          | 50000 |
+----+-------------+--------+------+---------------+-------+"""
        result = parse_explain_text(text)
        assert result.get("extra") is not None


# ==================== parse_slow_query_log 测试 ====================

class TestParseSlowQueryLog:
    """parse_slow_query_log() 函数测试"""

    def test_critical_query(self):
        """严重慢查询 (>5s)"""
        log = """# Time: 2024-01-01T10:00:00.123456Z
# Query_time: 5.234193  Lock_time: 0.000089  Rows_sent: 100  Rows_examined: 500000
SELECT * FROM orders WHERE status = 1;"""
        result = parse_slow_query_log(log)
        assert result["query_time"] == 5.234193
        assert result["severity"] == "CRITICAL"
        assert result["efficiency_ratio"] == "5000:1"

    def test_warning_query(self):
        """警告级别慢查询 (1-5s)"""
        log = """# Query_time: 2.500000  Lock_time: 0.000010  Rows_sent: 10  Rows_examined: 10000
SELECT * FROM users WHERE email = '[REDACTED_SECRET]';"""
        result = parse_slow_query_log(log)
        assert result["query_time"] == 2.5
        assert result["severity"] == "WARNING"
        assert result["efficiency_ratio"] == "1000:1"

    def test_normal_query(self):
        """正常查询 (<1s)"""
        log = """# Query_time: 0.523100  Lock_time: 0.000005  Rows_sent: 5  Rows_examined: 500
SELECT * FROM products WHERE category_id = 3;"""
        result = parse_slow_query_log(log)
        assert result["query_time"] == 0.5231
        assert result["severity"] == "NORMAL"
        assert result["warnings"] == []

    def test_empty_log(self):
        """空日志"""
        result = parse_slow_query_log("")
        assert result["error"] is not None

    def test_missing_query_time(self):
        """缺少 Query_time"""
        log = """# Time: 2024-01-01T10:00:00.123456Z
SELECT * FROM users;"""
        result = parse_slow_query_log(log)
        assert result.get("query_time") is None

    def test_zero_efficiency(self):
        """零扫描（极致优化）"""
        log = """# Query_time: 0.001000  Lock_time: 0.000001  Rows_sent: 1  Rows_examined: 1
SELECT * FROM users WHERE id = 1;"""
        result = parse_slow_query_log(log)
        assert result["efficiency_ratio"] == "1:1"
        assert result["warnings"] == []

    def test_no_rows_sent(self):
        """无返回行（写操作或 DELETE/UPDATE）"""
        log = """# Query_time: 1.234000  Lock_time: 0.000100  Rows_sent: 0  Rows_examined: 10000
DELETE FROM sessions WHERE expired = 1;"""
        result = parse_slow_query_log(log)
        assert result["rows_sent"] == 0
        assert "扫描" in result["warnings"][0]


# ==================== generate_index_suggestions 测试 ====================

class TestGenerateIndexSuggestions:
    """generate_index_suggestions() 函数测试"""

    def test_simple_where(self):
        """简单 WHERE 列"""
        sql = "SELECT * FROM orders WHERE status = 1"
        result = generate_index_suggestions(sql)
        assert any("status" in s.lower() for s in result)

    def test_multiple_where(self):
        """多列 WHERE"""
        sql = "SELECT * FROM orders WHERE status = 1 AND category = 'electronics'"
        result = generate_index_suggestions(sql)
        assert len(result) >= 1

    def test_join_columns(self):
        """JOIN 连接列"""
        sql = "SELECT * FROM orders o JOIN users u ON o.user_id = u.id WHERE u.status = 1"
        result = generate_index_suggestions(sql)
        assert any("user_id" in s.lower() or "id" in s.lower() for s in result)

    def test_order_by(self):
        """ORDER BY 列"""
        sql = "SELECT * FROM orders WHERE status = 1 ORDER BY created_at DESC"
        result = generate_index_suggestions(sql)
        assert any("created_at" in s.lower() for s in result)

    def test_group_by(self):
        """GROUP BY 列"""
        sql = "SELECT status, COUNT(*) FROM orders GROUP BY status"
        result = generate_index_suggestions(sql)
        assert any("status" in s.lower() for s in result)

    def test_empty_sql(self):
        """空 SQL"""
        result = generate_index_suggestions("")
        assert result == []

    def test_select_star(self):
        """SELECT * 自动提示"""
        sql = "SELECT * FROM orders WHERE status = 1"
        result = generate_index_suggestions(sql)
        assert any("SELECT" in s and "*" not in s.split("FROM")[0] for s in result) or any("覆盖" in s or "covering" in s.lower() for s in result)

    def test_no_where_clause(self):
        """无 WHERE 子句"""
        sql = "SELECT COUNT(*) FROM orders"
        result = generate_index_suggestions(sql)
        # COUNT(*) 通常不需要额外索引
        assert isinstance(result, list)


# ==================== generate_rewrite_suggestions 测试 ====================

class TestGenerateRewriteSuggestions:
    """generate_rewrite_suggestions() 函数测试"""

    def test_select_star(self):
        """SELECT * 重写"""
        sql = "SELECT * FROM orders WHERE status = 1"
        result = generate_rewrite_suggestions(sql)
        # 建议应该提到避免 SELECT * 并使用具体列名
        assert any("SELECT" in s and ("column" in s.lower() or "具体列" in s or "指定列" in s) for s in result)

    def test_or_to_union(self):
        """OR → UNION 重写"""
        sql = "SELECT * FROM orders WHERE user_id = 1 OR user_id = 2"
        result = generate_rewrite_suggestions(sql)
        assert any("UNION" in s.upper() for s in result)

    def test_implicit_type_conversion(self):
        """隐式类型转换"""
        sql = "SELECT * FROM orders WHERE order_id = '12345'"
        result = generate_rewrite_suggestions(sql)
        assert any("类型" in s or "type" in s.lower() for s in result)

    def test_large_offset(self):
        """大 OFFSET 分页"""
        sql = "SELECT * FROM orders LIMIT 100000, 20"
        result = generate_rewrite_suggestions(sql)
        assert any("LIMIT" in s.upper() or "offset" in s.lower() for s in result)

    def test_not_in_subquery(self):
        """NOT IN → NOT EXISTS"""
        sql = "SELECT * FROM users WHERE id NOT IN (SELECT user_id FROM orders)"
        result = generate_rewrite_suggestions(sql)
        assert any("NOT EXISTS" in s.upper() or "NOT IN" in s.upper() for s in result)

    def test_empty_sql(self):
        """空 SQL"""
        result = generate_rewrite_suggestions("")
        assert result == []

    def test_simple_query(self):
        """简单查询 - 无需重写"""
        sql = "SELECT id, name FROM users WHERE id = 1"
        result = generate_rewrite_suggestions(sql)
        assert isinstance(result, list)


# ==================== calculate_performance_metrics 测试 ====================

class TestCalculatePerformanceMetrics:
    """calculate_performance_metrics() 函数测试"""

    def test_high_scan_efficiency(self):
        """高扫描效率"""
        result = calculate_performance_metrics(rows_examined=500, rows_sent=100)
        assert result["scan_efficiency"] == "5:1"
        # 基础100分，全表扫描-30，无索引-15，ratio=5不扣分 = 55
        assert result["score"] > 50

    def test_very_poor_efficiency(self):
        """极差扫描效率"""
        result = calculate_performance_metrics(rows_examined=500000, rows_sent=100, is_full_scan=True)
        assert result["scan_efficiency"] == "5000:1"
        # 基础100分，全表扫描-30，ratio>=1000扣15分 = 55
        assert result["score"] < 60

    def test_zero_rows_sent(self):
        """零返回行（写操作）"""
        result = calculate_performance_metrics(rows_examined=10000, rows_sent=0)
        assert result["rows_sent"] == 0
        assert result["scan_efficiency"] == "N/A"

    def test_full_scan_cost(self):
        """全表扫描成本高"""
        result = calculate_performance_metrics(rows_examined=50000, rows_sent=100, is_full_scan=True)
        assert result["flags"]["full_scan"] is True

    def test_index_hit(self):
        """索引命中"""
        result = calculate_performance_metrics(rows_examined=500, rows_sent=100, uses_index=True)
        assert result["flags"]["uses_index"] is True
        assert result["score"] >= 70

    def test_no_flags(self):
        """无特殊情况"""
        result = calculate_performance_metrics(rows_examined=1000, rows_sent=100)
        assert "flags" in result
        assert isinstance(result["flags"], dict)


# ==================== analyze_slow_query 综合测试 ====================

class TestAnalyzeSlowQuery:
    """analyze_slow_query() 综合分析测试"""

    def test_full_analysis_with_json(self):
        """完整分析 - EXPLAIN JSON"""
        sql = "SELECT * FROM orders WHERE status = 1 ORDER BY created_at DESC"
        explain_json = """{
            "query_block": {
                "select_id": 1,
                "cost_info": {"query_cost": "12450.35"},
                "ordering_operation": {"using_filesort": true},
                "table": {
                    "table_name": "orders",
                    "access_type": "ALL",
                    "rows_examined_scan": 50000,
                    "rows_produced": 100
                }
            }
        }"""
        result = analyze_slow_query(sql, explain_format="json", explain_data=explain_json)
        assert "score" in result
        # ALL类型20分，成本>10000扣15分，ratio=500扣8分，filesort扣10分 = -13 → 0
        assert result["score"] < 50
        assert result["index_suggestions"] != []
        assert result["rewrite_suggestions"] != []

    def test_full_analysis_with_log(self):
        """完整分析 - 慢查询日志"""
        sql = "SELECT * FROM orders WHERE status = 1"
        log = """# Query_time: 6.000000  Lock_time: 0.000100  Rows_sent: 100  Rows_examined: 500000
SELECT * FROM orders WHERE status = 1;"""
        result = analyze_slow_query(sql, explain_format="slowlog", explain_data=log)
        assert result["log_info"]["severity"] == "CRITICAL"
        assert result["index_suggestions"] != []

    def test_sql_only_analysis(self):
        """仅 SQL 分析（无 EXPLAIN）"""
        sql = "SELECT * FROM orders WHERE status = 1 AND created_at > '2024-01-01'"
        result = analyze_slow_query(sql)
        assert "index_suggestions" in result
        assert "rewrite_suggestions" in result
        assert "metrics" in result


# ==================== extract_sql_from_log 测试 ====================

class TestExtractSqlFromLog:
    """extract_sql_from_log() 函数测试"""

    def test_simple_log(self):
        """简单日志提取"""
        log = """# Query_time: 1.000000  Rows_sent: 10  Rows_examined: 1000
SELECT * FROM users WHERE status = 1;"""
        result = extract_sql_from_log(log)
        assert "SELECT" in result
        assert "users" in result.lower()

    def test_multiline_log(self):
        """多行日志"""
        log = """# Time: 2024-01-01T10:00:00.123456Z
# Query_time: 2.500000
SELECT
    id,
    name,
    status
FROM users
WHERE status = 1;"""
        result = extract_sql_from_log(log)
        assert "SELECT" in result
        assert "FROM" in result

    def test_empty_log(self):
        """空日志"""
        result = extract_sql_from_log("")
        assert result == ""


# ==================== extract_conditions 测试 ====================

class TestExtractConditions:
    """extract_conditions() 函数测试"""

    def test_simple_where(self):
        """简单 WHERE"""
        sql = "SELECT * FROM orders WHERE status = 1"
        result = extract_conditions(sql)
        assert "status" in result

    def test_multiple_conditions(self):
        """多条件"""
        sql = "SELECT * FROM orders WHERE status = 1 AND category_id = 5 AND total > 100"
        result = extract_conditions(sql)
        assert len(result) >= 2

    def test_no_where(self):
        """无 WHERE"""
        sql = "SELECT COUNT(*) FROM orders"
        result = extract_conditions(sql)
        assert result == []

    def test_like_condition(self):
        """LIKE 条件"""
        sql = "SELECT * FROM users WHERE email LIKE '%@example.com'"
        result = extract_conditions(sql)
        assert "email" in result


# ==================== _parse_explain_json_score 测试 ====================

class TestParseExplainJsonScore:
    """_parse_explain_json_score() 函数测试"""

    def test_high_cost_low_score(self):
        """高成本低分"""
        score = _parse_explain_json_score(
            query_cost="50000.00",
            access_type="ALL",
            rows_examined=100000,
            rows_produced=100,
            using_filesort=True
        )
        assert score < 50  # ALL类型20分，成本>10000扣15分，ratio>=1000扣15分，filesort扣10分 = -20 → 0

    def test_low_cost_high_score(self):
        """低成本高分"""
        score = _parse_explain_json_score(
            query_cost="50.00",
            access_type="ref",
            rows_examined=500,
            rows_produced=100,
            using_filesort=False
        )
        assert score >= 70

    def test_filesort_penalty(self):
        """filesort 扣分"""
        score_no_filesort = _parse_explain_json_score("1000.00", "ALL", 5000, 100, False)
        score_with_filesort = _parse_explain_json_score("1000.00", "ALL", 5000, 100, True)
        assert score_with_filesort < score_no_filesort


# ==================== 边界情况测试 ====================

class TestEdgeCases:
    """边界情况测试"""

    def test_unicode_in_sql(self):
        """SQL 中含中文"""
        sql = "SELECT * FROM orders WHERE status = 1 ORDER BY created_at DESC"
        result = analyze_slow_query(sql)
        assert "index_suggestions" in result

    def test_very_long_table_name(self):
        """超长表名"""
        sql = "SELECT * FROM orders WHERE status = 1"
        result = generate_index_suggestions(sql)
        assert isinstance(result, list)

    def test_special_characters_in_value(self):
        """SQL 中含特殊字符值"""
        sql = "SELECT * FROM users WHERE name = 'O\\'Brien' AND email = '[REDACTED_SECRET]'"
        result = generate_index_suggestions(sql)
        assert isinstance(result, list)

    def test_numeric_query_time(self):
        """数字格式 Query_time"""
        log = "# Query_time: 3.5  Rows_sent: 10  Rows_examined: 1000\nSELECT * FROM users;"
        result = parse_slow_query_log(log)
        assert result["query_time"] == 3.5
        assert result["severity"] == "WARNING"

    def test_malformed_slow_log(self):
        """格式异常的慢查询日志"""
        log = "completely malformed log entry without proper format"
        result = parse_slow_query_log(log)
        assert "error" in result or result.get("query_time") is None

    def test_main_entry_point(self):
        """main() 入口测试"""
        import json
        sys.argv = ["mysql_slow_query_analyzer.py", "analyze", "SELECT * FROM orders WHERE status = 1"]
        try:
            from mysql_slow_query_analyzer import main
            main()
        except SystemExit:
            pass


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