Redis 多机房同步实现主从跨地域复制延迟与数据一致性

# 在主节点执行
set key value timestamp
# 在从节点执行
get key
```

# 在主节点执行
time
# 在从节点执行
time
```

# prometheus redis exporter 配置示例
redis_exporter:
  enabled: true
  image: oliver006/redis_exporter
  ports:
    - name: redis-exporter
      containerport: 9121
      protocol: tcp
  resources:
    limits:
      cpu: 100m
      memory: 128mi
    requests:
      cpu: 100m
      memory: 128mi

# 读写分离客户端示例
class redisreadwriteclient:
    def __init__(self, master_nodes, slave_nodes):
        self.master_nodes = master_nodes
        self.slave_nodes = slave_nodes
        self.current_master = self.select_master(master_nodes)
        self.current_slave = self.select_slave(slave_nodes)
    def select_master(self, nodes):
        # 根据网络延迟、负载选择最优主节点
        pass
    def select_slave(self, nodes):
        # 根据网络延迟、负载选择最优从节点
        pass
    def write(self, key, value):
        # 写操作到主节点
        return self.current_master.set(key, value)
    def read(self, key):
        # 读操作到从节点
        return self.current_slave.get(key)

# 基于时间戳的冲突解决
class conflictresolver:
    def resolve_conflict(self, current_value, new_value, timestamp):
        if timestamp > current_value.get('timestamp', 0):
            return new_value
        return current_value

# 基于版本号的冲突解决
class versionresolver:
    def __init__(self):
        self.versions = {}
    
    def resolve_conflict(self, key, current_value, new_value):
        current_version = self.versions.get(key, 0)
        new_version = new_value.get('version', 0)
        
        if new_version > current_version:
            self.versions[key] = new_version
            return new_value
        return current_value

# 网络优化客户端示例
class optimizedredisclient:
    def __init__(self, master_nodes, slave_nodes):
        self.master_nodes = master_nodes
        self.slave_nodes = slave_nodes
        self.batch_buffer = []
        self.batch_size = 100
        self.batch_timeout = 0.1  # 100ms
    
    def write(self, key, value):
        # 批量处理写操作
        self.batch_buffer.append((key, value))
        if len(self.batch_buffer) >= self.batch_size:
            self.flush_batch()
    
    def flush_batch(self):
        if self.batch_buffer:
            # 批量执行写操作
            pipeline = self.master_nodes[0].pipeline()
            for key, value in self.batch_buffer:
                pipeline.set(key, value)
            pipeline.execute()
            self.batch_buffer = []

# 故障转移管理器示例
class failovermanager:
    def __init__(self, nodes):
        self.nodes = nodes
        self.current_master = nodes[0]
        self.slaves = nodes[1:]
        self.monitor_interval = 5  # 5秒
        self.timeout_threshold = 30  # 30秒
    
    def monitor(self):
        # 监控节点状态
        while true:
            if not self.is_node_alive(self.current_master):
                self.failover()
            time.sleep(self.monitor_interval)
    
    def is_node_alive(self, node):
        # 检查节点是否存活
        try:
            response = node.ping()
            return response == 'pong'
        except:
            return false
    
    def failover(self):
        # 执行故障转移
        for slave in self.slaves:
            if self.is_node_alive(slave):
                self.promote_to_master(slave)
                self.current_master = slave
                break
    
    def promote_to_master(self, slave):
        # 将从节点提升为主节点
        slave.slaveof('no', 'one')
        # 更新客户端配置
        self.update_client_config()