microwind 数据库迁移验证技能
概述
数据库迁移是系统演进的关键环节。不当的迁移会导致数据丢失、系统停机、性能问题。需要在执行前全面验证迁移方案。
核心原则: 好的迁移应该安全可靠、影响可控、可回滚、性能优良。坏的迁移会锁定生产、丢失数据、导致停机。
何时使用
始终:
- 执行数据库迁移前
- 审查迁移代码时
- 规划零停机部署
- 测试数据转换
- 验证模式变更
- 调查迁移失败
触发短语:
- "这个迁移安全吗？"
- "验证数据库迁移"
- "检查数据转换"
- "会导致停机吗？"
- "如何安全执行迁移？"
- "审查迁移策略"
迁移验证功能
安全检查
- 数据丢失检测
- 锁定分析
- 停机时间估算
- 回滚策略
- 备份验证
数据验证
- 数据类型兼容性
- 约束违规检测
- 数据转换正确性
- 空值处理
- 索引重建影响
性能影响
- 表锁定时间
- 索引重建时间
- 磁盘空间需求
- 查询性能影响
- 连接池影响
风险评估
- 迁移复杂度分析
- 失败概率评估
- 影响范围评估
- 回滚可行性
- 业务影响分析
常见迁移问题
长时间运行的迁移
问题:
在10亿行表上执行ALTER TABLE MODIFY COLUMN类型变更（数小时的表锁定）
后果:
- 生产数据库被锁定
- 所有查询被阻塞
- 系统停机
解决方案:
使用在线模式迁移工具或影子迁移
数据丢失迁移
问题:
在没有备份数据的情况下执行ALTER TABLE DROP COLUMN
后果:
- 数据永久丢失
- 无法恢复
- 违反合规要求
解决方案:
先备份数据，删除前验证
不可转换数据
问题:
在没有验证的情况下将字符串列转换为整数
后果:
- 非数值无法转换
- 迁移失败
- 部分数据丢失
解决方案:
转换前验证数据，创建临时列
索引重建问题
问题:
在大表上添加或删除索引导致长时间锁定
后果:
- 写操作被阻塞
- 查询性能下降
- 系统响应缓慢
解决方案:
使用在线索引创建或分批重建
代码实现示例
迁移验证器
import re
import json
import time
from typing import Dict, Any, List, Optional, Tuple
from dataclasses import dataclass
from enum import Enum
class MigrationRisk(Enum):
"""迁移风险等级"""
LOW = "low"
MEDIUM = "medium"
HIGH = "high"
CRITICAL = "critical"
class MigrationType(Enum):
"""迁移类型"""
SCHEMA_CHANGE = "schema_change"
DATA_MIGRATION = "data_migration"
INDEX_OPERATION = "index_operation"
CONSTRAINT_CHANGE = "constraint_change"
@dataclass
class MigrationIssue:
"""迁移问题"""
severity: MigrationRisk
type: str
description: str
suggestion: str
line_number: Optional[int] = None
@dataclass
class MigrationValidation:
"""迁移验证结果"""
migration_id: str
is_safe: bool
risk_level: MigrationRisk
issues: List[MigrationIssue]
estimated_downtime: float
estimated_duration: float
rollback_complexity: str
class DatabaseMigrationValidator:
def __init__(self):
self.risk_patterns = {
'DROP TABLE': MigrationRisk.CRITICAL,
'DROP COLUMN': MigrationRisk.HIGH,
'ALTER TABLE.*MODIFY.*COLUMN': MigrationRisk.HIGH,
'ALTER TABLE.*ADD.*INDEX': MigrationRisk.MEDIUM,
'ALTER TABLE.*DROP.*INDEX': MigrationRisk.MEDIUM,
'DELETE FROM.*WHERE': MigrationRisk.MEDIUM,
'UPDATE.*SET.*WHERE': MigrationRisk.LOW,
}
self.lock_patterns = {
'ALTER TABLE': '表级锁定',
'CREATE INDEX': '表级锁定',
'DROP INDEX': '表级锁定',
'TRUNCATE TABLE': '表级锁定',
}
def validate_migration(self, migration_sql: str, table_info: Dict[str, Any]) -> MigrationValidation:
"""验证迁移SQL"""
migration_id = self._generate_migration_id()
issues = []
# 解析SQL语句
statements = self._parse_sql_statements(migration_sql)
# 分析每个语句
for i, statement in enumerate(statements, 1):
statement_issues = self._analyze_statement(statement, table_info, i)
issues.extend(statement_issues)
# 计算风险等级
risk_level = self._calculate_risk_level(issues)
# 估算影响
estimated_downtime = self._estimate_downtime(statements, table_info)
estimated_duration = self._estimate_duration(statements, table_info)
rollback_complexity = self._assess_rollback_complexity(statements)
# 判断是否安全
is_safe = risk_level in [MigrationRisk.LOW, MigrationRisk.MEDIUM] and len([i for i in issues if i.severity == MigrationRisk.CRITICAL]) == 0
return MigrationValidation(
migration_id=migration_id,
is_safe=is_safe,
risk_level=risk_level,
issues=issues,
estimated_downtime=estimated_downtime,
estimated_duration=estimated_duration,
rollback_complexity=rollback_complexity
)
def _parse_sql_statements(self, sql: str) -> List[str]:
"""解析SQL语句"""
# 移除注释和多余空白
cleaned_sql = re.sub(r'--.*?\n', '\n', sql)
cleaned_sql = re.sub(r'/\*.*?\*/', '', cleaned_sql, flags=re.DOTALL)
cleaned_sql = re.sub(r'\s+', ' ', cleaned_sql).strip()
# 分割语句
statements = []
current_statement = ""
in_quotes = False
quote_char = None
for char in cleaned_sql:
if char in ["'", '"'] and not in_quotes:
in_quotes = True
quote_char = char
elif char == quote_char and in_quotes:
in_quotes = False
quote_char = None
elif char == ';' and not in_quotes:
if current_statement.strip():
statements.append(current_statement.strip())
current_statement = ""
continue
current_statement += char
if current_statement.strip():
statements.append(current_statement.strip())
return statements
def _analyze_statement(self, statement: str, table_info: Dict[str, Any], line_number: int) -> List[MigrationIssue]:
"""分析单个SQL语句"""
issues = []
statement_upper = statement.upper()
# 检查风险模式
for pattern, risk in self.risk_patterns.items():
if re.search(pattern, statement_upper):
issue = self._create_risk_issue(pattern, risk, statement, line_number)
issues.append(issue)
# 检查数据丢失风险
if 'DROP' in statement_upper:
if 'DROP TABLE' in statement_upper:
issues.append(MigrationIssue(
severity=MigrationRisk.CRITICAL,
type='data_loss',
description='删除表可能导致数据永久丢失',
suggestion='确保已备份数据，考虑使用软删除',
line_number=line_number
))
elif 'DROP COLUMN' in statement_upper:
issues.append(MigrationIssue(
severity=MigrationRisk.HIGH,
type='data_loss',
description='删除列可能导致数据丢失',
suggestion='先备份数据，验证后再删除',
line_number=line_number
))
# 检查锁定风险
for pattern, lock_type in self.lock_patterns.items():
if re.search(pattern, statement_upper):
table_size = table_info.get('estimated_rows', 0)
if table_size > 1000000: # 100万行
issues.append(MigrationIssue(
severity=MigrationRisk.HIGH,
type='locking',
description=f'大表操作可能导致长时间{lock_type}',
suggestion='考虑使用在线迁移工具或分批处理',
line_number=line_number
))
# 检查数据类型转换
if 'ALTER TABLE' in statement_upper and 'MODIFY' in statement_upper and 'COLUMN' in statement_upper:
issues.append(MigrationIssue(
severity=MigrationRisk.MEDIUM,
type='data_conversion',
description='列类型变更可能导致数据转换问题',
suggestion='验证数据兼容性，考虑使用临时列',
line_number=line_number
))
# 检查索引操作
if 'CREATE INDEX' in statement_upper or 'DROP INDEX' in statement_upper:
issues.append(MigrationIssue(
severity=MigrationRisk.MEDIUM,
type='index_operation',
description='索引操作可能影响查询性能',
suggestion='在低峰期执行，监控性能影响',
line_number=line_number
))
return issues
def _create_risk_issue(self, pattern: str, risk: MigrationRisk, statement: str, line_number: int) -> MigrationIssue:
"""创建风险问题"""
descriptions = {
'DROP TABLE': '删除表是高风险操作，可能导致数据永久丢失',
'DROP COLUMN': '删除列可能导致数据丢失',
'ALTER TABLE.*MODIFY.*COLUMN': '修改列类型可能导致长时间锁定',
'ALTER TABLE.*ADD.*INDEX': '添加索引可能影响写性能',
'ALTER TABLE.*DROP.*INDEX': '删除索引可能影响查询性能',
'DELETE FROM.*WHERE': '批量删除可能影响性能',
'UPDATE.*SET.*WHERE': '批量更新可能影响性能',
}
suggestions = {
'DROP TABLE': '确保已备份数据，考虑使用软删除策略',
'DROP COLUMN': '先备份数据，验证数据完整性后再删除',
'ALTER TABLE.*MODIFY.*COLUMN': '使用在线迁移工具或分批处理',
'ALTER TABLE.*ADD.*INDEX': '在低峰期执行，考虑使用CONCURRENTLY',
'ALTER TABLE.*DROP.*INDEX': '在低峰期执行，监控查询性能',
'DELETE FROM.*WHERE': '分批删除，避免长时间锁定',
'UPDATE.*SET.*WHERE': '分批更新，减少锁定时间',
}
return MigrationIssue(
severity=risk,
type='pattern_match',
description=descriptions.get(pattern, f'检测到风险模式: {pattern}'),
suggestion=suggestions.get(pattern, '仔细评估操作风险'),
line_number=line_number
)
def _calculate_risk_level(self, issues: List[MigrationIssue]) -> MigrationRisk:
"""计算整体风险等级"""
if not issues:
return MigrationRisk.LOW
critical_count = len([i for i in issues if i.severity == MigrationRisk.CRITICAL])
high_count = len([i for i in issues if i.severity == MigrationRisk.HIGH])
medium_count = len([i for i in issues if i.severity == MigrationRisk.MEDIUM])
if critical_count > 0:
return MigrationRisk.CRITICAL
elif high_count > 2:
return MigrationRisk.HIGH
elif high_count > 0 or medium_count > 3:
return MigrationRisk.MEDIUM
else:
return MigrationRisk.LOW
def _estimate_downtime(self, statements: List[str], table_info: Dict[str, Any]) -> float:
"""估算停机时间（分钟）"""
total_downtime = 0
table_size = table_info.get('estimated_rows', 0)
for statement in statements:
statement_upper = statement.upper()
if 'DROP TABLE' in statement_upper:
total_downtime += 5
elif 'ALTER TABLE' in statement_upper and 'MODIFY' in statement_upper:
# 基于表大小估算
if table_size > 10000000: # 1000万行
total_downtime += 60
elif table_size > 1000000: # 100万行
total_downtime += 30
else:
total_downtime += 10
elif 'CREATE INDEX' in statement_upper or 'DROP INDEX' in statement_upper:
if table_size > 1000000:
total_downtime += 20
else:
total_downtime += 5
elif 'DELETE FROM' in statement_upper or 'UPDATE' in statement_upper:
total_downtime += 2
return total_downtime
def _estimate_duration(self, statements: List[str], table_info: Dict[str, Any]) -> float:
"""估算执行时间（分钟）"""
total_duration = 0
table_size = table_info.get('estimated_rows', 0)
for statement in statements:
statement_upper = statement.upper()
if 'DROP TABLE' in statement_upper:
total_duration += 2
elif 'ALTER TABLE' in statement_upper:
total_duration += self._estimate_alter_time(statement_upper, table_size)
elif 'CREATE INDEX' in statement_upper:
total_duration += self._estimate_index_time(table_size)
elif 'DROP INDEX' in statement_upper:
total_duration += 5
elif 'DELETE FROM' in statement_upper:
total_duration += 10
elif 'UPDATE' in statement_upper:
total_duration += 15
return total_duration
def _estimate_alter_time(self, statement: str, table_size: int) -> float:
"""估算ALTER TABLE时间"""
if 'MODIFY' in statement and 'COLUMN' in statement:
# 修改列类型
if table_size > 10000000:
return 120 # 2小时
elif table_size > 1000000:
return 60 # 1小时
else:
return 15 # 15分钟
elif 'ADD' in statement and 'COLUMN' in statement:
return 5
elif 'DROP' in statement and 'COLUMN' in statement:
return 10
else:
return 20
def _estimate_index_time(self, table_size: int) -> float:
"""估算索引操作时间"""
if table_size > 10000000:
return 90 # 1.5小时
elif table_size > 1000000:
return 45 # 45分钟
else:
return 10 # 10分钟
def _assess_rollback_complexity(self, statements: List[str]) -> str:
"""评估回滚复杂度"""
complexity_score = 0
for statement in statements:
statement_upper = statement.upper()
if 'DROP TABLE' in statement_upper:
complexity_score += 10
elif 'DROP COLUMN' in statement_upper:
complexity_score += 8
elif 'ALTER TABLE' in statement_upper and 'MODIFY' in statement_upper:
complexity_score += 6
elif 'DELETE FROM' in statement_upper:
complexity_score += 5
elif 'UPDATE' in statement_upper:
complexity_score += 3
if complexity_score >= 20:
return "复杂"
elif complexity_score >= 10:
return "中等"
else:
return "简单"
def _generate_migration_id(self) -> str:
"""生成迁移ID"""
timestamp = int(time.time())
return f"migration_{timestamp}"
def generate_rollback_script(self, migration_sql: str) -> str:
"""生成回滚脚本"""
statements = self._parse_sql_statements(migration_sql)
rollback_statements = []
# 反向处理语句
for statement in reversed(statements):
rollback = self._generate_statement_rollback(statement)
if rollback:
rollback_statements.append(rollback)
return '\n'.join(rollback_statements)
def _generate_statement_rollback(self, statement: str) -> Optional[str]:
"""为单个语句生成回滚"""
statement_upper = statement.upper()
if 'CREATE TABLE' in statement_upper:
# 回滚：删除表
table_match = re.search(r'CREATE TABLE\s+(\w+)', statement_upper)
if table_match:
table_name = table_match.group(1)
return f"DROP TABLE {table_name};"
elif 'DROP TABLE' in statement_upper:
# 回滚：需要从备份恢复
return "-- 需要从备份恢复表数据"
elif 'ALTER TABLE' in statement_upper:
# 回滚ALTER TABLE比较复杂，需要具体分析
return "-- ALTER TABLE回滚需要根据具体变更生成"
elif 'CREATE INDEX' in statement_upper:
# 回滚：删除索引
index_match = re.search(r'CREATE INDEX\s+(\w+)', statement_upper)
if index_match:
index_name = index_match.group(1)
return f"DROP INDEX {index_name};"
elif 'DROP INDEX' in statement_upper:
# 回滚：重新创建索引
return "-- 需要重新创建索引"
return None
# 迁移计划生成器
class MigrationPlanGenerator:
def __init__(self):
self.validator = DatabaseMigrationValidator()
def generate_migration_plan(self, migration_sql: str, table_info: Dict[str, Any]) -> Dict[str, Any]:
"""生成迁移计划"""
# 验证迁移
validation = self.validator.validate_migration(migration_sql, table_info)
# 生成回滚脚本
rollback_script = self.validator.generate_rollback_script(migration_sql)
# 生成执行计划
execution_plan = self._generate_execution_plan(validation, table_info)
# 生成检查清单
checklist = self._generate_checklist(validation)
return {
'validation': validation,
'rollback_script': rollback_script,
'execution_plan': execution_plan,
'checklist': checklist,
'recommendations': self._generate_recommendations(validation)
}
def _generate_execution_plan(self, validation: MigrationValidation, table_info: Dict[str, Any]) -> Dict[str, Any]:
"""生成执行计划"""
plan = {
'phases': [],
'total_duration': validation.estimated_duration,
'estimated_downtime': validation.estimated_downtime,
'risk_level': validation.risk_level.value
}
if validation.risk_level == MigrationRisk.CRITICAL:
plan['phases'].append({
'phase': 'preparation',
'description': '准备阶段',
'actions': [
'创建完整数据备份',
'在测试环境验证迁移',
'准备回滚脚本',
'通知相关团队'
],
'duration': 60
})
plan['phases'].append({
'phase': 'execution',
'description': '执行阶段',
'actions': [
'在低峰期执行',
'监控系统性能',
'记录执行日志',
'验证结果'
],
'duration': validation.estimated_duration
})
if validation.estimated_downtime > 0:
plan['phases'].append({
'phase': 'downtime',
'description': '停机窗口',
'actions': [
'通知用户停机',
'停止相关服务',
'执行迁移',
'验证系统',
'恢复服务'
],
'duration': validation.estimated_downtime
})
plan['phases'].append({
'phase': 'verification',
'description': '验证阶段',
'actions': [
'验证数据完整性',
'检查应用功能',
'监控系统性能',
'确认无异常'
],
'duration': 30
})
return plan
def _generate_checklist(self, validation: MigrationValidation) -> List[str]:
"""生成检查清单"""
checklist = [
"□ 已创建数据库备份",
"□ 在测试环境验证通过",
"□ 已准备回滚脚本",
"□ 已通知相关人员",
f"□ 风险等级: {validation.risk_level.value}",
f"□ 预计停机时间: {validation.estimated_downtime}分钟",
f"□ 预计执行时间: {validation.estimated_duration}分钟",
]
if validation.issues:
checklist.append("□ 已检查所有风险问题:")
for issue in validation.issues:
checklist.append(f" - {issue.description}")
checklist.extend([
"□ 系统监控已就位",
"□ 回滚计划已确认",
"□ 应急联系人已通知",
"□ 文档已更新"
])
return checklist
def _generate_recommendations(self, validation: MigrationValidation) -> List[str]:
"""生成建议"""
recommendations = []
if validation.risk_level == MigrationRisk.CRITICAL:
recommendations.append("建议重新设计迁移方案，降低风险等级")
recommendations.append("考虑分多个小步骤执行")
recommendations.append("必须在维护窗口期间执行")
if validation.estimated_downtime > 30:
recommendations.append("建议寻找零停机迁移方案")
recommendations.append("考虑使用蓝绿部署策略")
if validation.rollback_complexity == "复杂":
recommendations.append("建议简化回滚策略")
recommendations.append("准备详细的回滚文档")
critical_issues = [i for i in validation.issues if i.severity == MigrationRisk.CRITICAL]
if critical_issues:
recommendations.append("必须解决所有关键风险问题才能执行")
if validation.is_safe:
recommendations.append("迁移相对安全，可以按计划执行")
recommendations.append("建议在低峰期执行")
return recommendations
# 使用示例
def main():
print("=== 数据库迁移验证器 ===")
# 创建验证器
validator = DatabaseMigrationValidator()
# 示例迁移SQL
migration_sql = """
-- 添加新列
ALTER TABLE users ADD COLUMN email_verified BOOLEAN DEFAULT FALSE;
-- 创建索引
CREATE INDEX idx_users_email ON users(email);
-- 更新数据
UPDATE users SET email_verified = TRUE WHERE email IS NOT NULL;
"""
# 表信息
table_info = {
'table_name': 'users',
'estimated_rows': 5000000, # 500万行
'table_size_gb': 10,
'indexes': ['PRIMARY KEY', 'idx_username']
}
# 验证迁移
validation = validator.validate_migration(migration_sql, table_info)
print("迁移验证结果:")
print(f"迁移ID: {validation.migration_id}")
print(f"是否安全: {'是' if validation.is_safe else '否'}")
print(f"风险等级: {validation.risk_level.value}")
print(f"预计停机时间: {validation.estimated_downtime}分钟")
print(f"预计执行时间: {validation.estimated_duration}分钟")
print(f"回滚复杂度: {validation.rollback_complexity}")
if validation.issues:
print("\n发现的问题:")
for i, issue in enumerate(validation.issues, 1):
print(f"{i}. [{issue.severity.value.upper()}] {issue.description}")
print(f" 建议: {issue.suggestion}")
if issue.line_number:
print(f" 行号: {issue.line_number}")
# 生成回滚脚本
rollback_script = validator.generate_rollback_script(migration_sql)
print(f"\n回滚脚本:")
print(rollback_script)
# 生成完整迁移计划
plan_generator = MigrationPlanGenerator()
migration_plan = plan_generator.generate_migration_plan(migration_sql, table_info)
print(f"\n=== 迁移执行计划 ===")
execution_plan = migration_plan['execution_plan']
print(f"总执行时间: {execution_plan['total_duration']}分钟")
print(f"预计停机时间: {execution_plan['estimated_downtime']}分钟")
print(f"风险等级: {execution_plan['risk_level']}")
print("\n执行阶段:")
for phase in execution_plan['phases']:
print(f"- {phase['phase']}: {phase['description']} ({phase['duration']}分钟)")
for action in phase['actions']:
print(f" • {action}")
print(f"\n=== 检查清单 ===")
for item in migration_plan['checklist']:
print(item)
print(f"\n=== 建议 ===")
for recommendation in migration_plan['recommendations']:
print(f"- {recommendation}")
if __name__ == '__main__':
main()
迁移监控器
import time
import threading
from typing import Dict, Any, List, Optional
from dataclasses import dataclass
@dataclass
class MigrationMetrics:
"""迁移指标"""
start_time: float
current_statement: str
completed_statements: int
total_statements: int
estimated_remaining_time: float
current_progress: float
class MigrationMonitor:
def __init__(self):
self.active_migrations: Dict[str, Dict[str, Any]] = {}
self.monitoring_thread = None
self.is_monitoring = False
def start_migration(self, migration_id: str, statements: List[str]) -> str:
"""开始监控迁移"""
self.active_migrations[migration_id] = {
'statements': statements,
'start_time': time.time(),
'current_statement_index': 0,
'completed_statements': 0,
'status': 'running',
'metrics': None
}
if not self.is_monitoring:
self.start_monitoring()
return migration_id
def update_progress(self, migration_id: str, current_statement_index: int):
"""更新迁移进度"""
if migration_id in self.active_migrations:
migration = self.active_migrations[migration_id]
migration['current_statement_index'] = current_statement_index
migration['completed_statements'] = current_statement_index + 1
def complete_migration(self, migration_id: str, success: bool):
"""完成迁移"""
if migration_id in self.active_migrations:
migration = self.active_migrations[migration_id]
migration['status'] = 'completed' if success else 'failed'
migration['end_time'] = time.time()
def get_migration_metrics(self, migration_id: str) -> Optional[MigrationMetrics]:
"""获取迁移指标"""
if migration_id not in self.active_migrations:
return None
migration = self.active_migrations[migration_id]
statements = migration['statements']
current_index = migration['current_statement_index']
elapsed_time = time.time() - migration['start_time']
if current_index > 0:
avg_statement_time = elapsed_time / current_index
remaining_statements = len(statements) - current_index
estimated_remaining_time = avg_statement_time * remaining_statements
else:
estimated_remaining_time = 0
progress = (current_index / len(statements)) * 100 if statements else 0
return MigrationMetrics(
start_time=migration['start_time'],
current_statement=statements[current_index] if current_index < len(statements) else "",
completed_statements=current_index,
total_statements=len(statements),
estimated_remaining_time=estimated_remaining_time,
current_progress=progress
)
def start_monitoring(self):
"""开始监控"""
self.is_monitoring = True
self.monitoring_thread = threading.Thread(target=self._monitoring_loop)
self.monitoring_thread.daemon = True
self.monitoring_thread.start()
def stop_monitoring(self):
"""停止监控"""
self.is_monitoring = False
if self.monitoring_thread:
self.monitoring_thread.join()
def _monitoring_loop(self):
"""监控循环"""
while self.is_monitoring:
for migration_id, migration in self.active_migrations.items():
if migration['status'] == 'running':
metrics = self.get_migration_metrics(migration_id)
migration['metrics'] = metrics
# 打印进度
print(f"迁移 {migration_id}: {metrics.current_progress:.1f}% 完成")
print(f"当前语句: {metrics.current_statement[:50]}...")
print(f"预计剩余时间: {metrics.estimated_remaining_time:.1f}秒")
time.sleep(5) # 每5秒更新一次
# 使用示例
def main():
print("=== 迁移监控器 ===")
# 创建监控器
monitor = MigrationMonitor()
# 模拟迁移
migration_statements = [
"ALTER TABLE users ADD COLUMN email_verified BOOLEAN DEFAULT FALSE;",
"CREATE INDEX idx_users_email ON users(email);",
"UPDATE users SET email_verified = TRUE WHERE email IS NOT NULL;",
]
# 开始监控
migration_id = monitor.start_migration("test_migration", migration_statements)
print(f"开始监控迁移: {migration_id}")
# 模拟执行过程
for i in range(len(migration_statements)):
print(f"\n执行语句 {i+1}: {migration_statements[i][:50]}...")
time.sleep(2) # 模拟执行时间
monitor.update_progress(migration_id, i)
# 完成迁移
monitor.complete_migration(migration_id, True)
print("\n迁移完成!")
# 获取最终指标
final_metrics = monitor.get_migration_metrics(migration_id)
if final_metrics:
print(f"总执行时间: {time.time() - final_metrics.start_time:.1f}秒")
print(f"完成语句数: {final_metrics.completed_statements}")
monitor.stop_monitoring()
if __name__ == '__main__':
main()
数据库迁移验证最佳实践
迁移策略
- 分批执行: 将大迁移拆分为多个小步骤
- 蓝绿部署: 使用零停机迁移策略
- 影子迁移: 在不影响生产的情况下验证
- 功能开关: 使用功能开关控制新功能
- 回滚计划: 准备详细的回滚方案
安全保障
- 数据备份: 执行前必须备份相关数据
- 测试验证: 在测试环境充分验证
- 监控告警: 实时监控迁移过程
- 权限控制: 限制迁移执行权限
- 审计日志: 记录所有迁移操作
风险控制
- 风险评估: 全面评估迁移风险
- 影响分析: 分析对系统的影响
- 应急预案: 准备应急处理方案
- 团队协作: 确保团队沟通顺畅
- 时间窗口: 选择合适的执行时间
质量保证
- 代码审查: 严格审查迁移代码
- 自动化测试: 编写自动化测试
- 性能测试: 测试迁移性能影响
- 数据验证: 验证数据完整性
- 文档更新: 及时更新相关文档
相关技能
- backup-recovery - 备份与恢复
- sql-optimization - SQL优化
- transaction-management - 事务管理
- database-query-analyzer - 数据库查询分析