"""
Redis查询和数据比较模块
负责Redis数据的查询、随机key获取和数据比较
"""

import time
import logging
import random
from redis.cluster import key_slot
from redis.exceptions import RedisError
from .redis_client import RedisPerformanceTracker

logger = logging.getLogger(__name__)

def get_random_keys_from_redis(redis_client, count=100, pattern="*", performance_tracker=None):
    """
    从Redis集群中获取随机keys
    
    Args:
        redis_client: Redis客户端
        count: 要获取的key数量
        pattern: key匹配模式，默认为 "*"
        performance_tracker: 性能追踪器
    
    Returns:
        list: 随机key列表
    """
    start_time = time.time()
    keys = set()
    
    logger.info(f"开始扫描获取随机keys，目标数量: {count}，模式: {pattern}")
    
    try:
        # 使用scan_iter获取keys
        scan_count = max(count * 2, 1000)  # 扫描更多key以确保随机性
        
        for key in redis_client.scan_iter(match=pattern, count=scan_count):
            keys.add(key)
            if len(keys) >= count * 3:  # 获取更多key以便随机选择
                break
        
        # 如果获取的key数量超过需要的数量，随机选择
        if len(keys) > count:
            keys = random.sample(list(keys), count)
        else:
            keys = list(keys)
        
        end_time = time.time()
        scan_duration = end_time - start_time
        
        if performance_tracker:
            performance_tracker.record_scan_time(scan_duration)
        
        logger.info(f"扫描获取 {len(keys)} 个随机keys，耗时 {scan_duration:.3f} 秒")
        return keys
        
    except RedisError as e:
        end_time = time.time()
        scan_duration = end_time - start_time
        
        if performance_tracker:
            performance_tracker.record_scan_time(scan_duration)
        
        logger.error(f"获取随机keys失败: {e}，耗时 {scan_duration:.3f} 秒")
        return []

def get_redis_values_by_keys(redis_client, keys, cluster_name="Redis集群", performance_tracker=None):
    """
    批量查询Redis中指定keys的值，自动适配单节点和集群模式
    
    Args:
        redis_client: Redis客户端
        keys: 要查询的key列表
        cluster_name: 集群名称用于日志
        performance_tracker: 性能追踪器
    
    Returns:
        list: 对应keys的值列表，如果key不存在则为None
    """
    start_time = time.time()
    result = [None] * len(keys)
    
    logger.info(f"开始从{cluster_name}批量查询 {len(keys)} 个keys")
    
    try:
        # 检查是否是集群模式
        is_cluster = hasattr(redis_client, 'cluster_nodes')
        
        if is_cluster:
            # 集群模式：按slot分组keys以优化查询性能
            slot_groups = {}
            for idx, key in enumerate(keys):
                slot = key_slot(key)
                slot_groups.setdefault(slot, []).append((idx, key))
            
            logger.info(f"集群模式：keys分布在 {len(slot_groups)} 个slot中")
            
            # 分组批量查询
            for group in slot_groups.values():
                indices, slot_keys = zip(*group)
                values = redis_client.mget(slot_keys)
                for i, v in zip(indices, values):
                    result[i] = v
        else:
            # 单节点模式：直接批量查询
            logger.info(f"单节点模式：直接批量查询")
            result = redis_client.mget(keys)
        
        end_time = time.time()
        query_duration = end_time - start_time
        
        if performance_tracker:
            performance_tracker.record_query(f"{cluster_name}_batch_query", query_duration)
        
        # 统计成功获取的key数量
        successful_count = sum(1 for v in result if v is not None)
        logger.info(f"从{cluster_name}查询完成，成功获取 {successful_count}/{len(keys)} 个值，耗时 {query_duration:.3f} 秒")
        
        return result
        
    except Exception as e:
        end_time = time.time()
        query_duration = end_time - start_time
        
        if performance_tracker:
            performance_tracker.record_query(f"{cluster_name}_batch_query_error", query_duration)
        
        logger.error(f"从{cluster_name}批量查询失败: {e}，耗时 {query_duration:.3f} 秒")
        return result

def compare_redis_data(client1, client2, keys, cluster1_name="生产集群", cluster2_name="测试集群", performance_tracker=None):
    """
    比较两个Redis集群中指定keys的数据
    
    Args:
        client1: 第一个Redis客户端（生产）
        client2: 第二个Redis客户端（测试）
        keys: 要比较的key列表
        cluster1_name: 第一个集群名称
        cluster2_name: 第二个集群名称
        performance_tracker: 性能追踪器
    
    Returns:
        dict: 比较结果，包含统计信息和差异详情
    """
    comparison_start_time = time.time()
    
    logger.info(f"开始比较 {cluster1_name} 和 {cluster2_name} 的数据")
    
    # 获取两个集群的数据
    values1 = get_redis_values_by_keys(client1, keys, cluster1_name, performance_tracker)
    if values1 is None:
        return {'error': f'从{cluster1_name}获取数据失败'}
    
    values2 = get_redis_values_by_keys(client2, keys, cluster2_name, performance_tracker)
    if values2 is None:
        return {'error': f'从{cluster2_name}获取数据失败'}
    
    # 开始数据比对
    compare_start = time.time()
    
    # 初始化统计数据
    stats = {
        'total_keys': len(keys),
        'identical_count': 0,
        'different_count': 0,
        'missing_in_cluster1': 0,
        'missing_in_cluster2': 0,
        'both_missing': 0
    }
    
    # 详细结果列表
    identical_results = []
    different_results = []
    missing_results = []
    
    # 逐个比较
    for i, key in enumerate(keys):
        val1 = values1[i]
        val2 = values2[i]
        
        # 将bytes转换为字符串用于显示（如果是bytes类型）
        display_val1 = val1.decode('utf-8') if isinstance(val1, bytes) else val1
        display_val2 = val2.decode('utf-8') if isinstance(val2, bytes) else val2
        
        if val1 is None and val2 is None:
            # 两个集群都没有这个key
            stats['both_missing'] += 1
            missing_results.append({
                'key': key.decode('utf-8') if isinstance(key, bytes) else key,
                'status': 'both_missing',
                'message': '两个集群都不存在该key'
            })
        elif val1 is None:
            # 只有第一个集群没有
            stats['missing_in_cluster1'] += 1
            missing_results.append({
                'key': key.decode('utf-8') if isinstance(key, bytes) else key,
                'status': 'missing_in_cluster1',
                'cluster1_value': None,
                'cluster2_value': display_val2,
                'message': f'在{cluster1_name}中不存在'
            })
        elif val2 is None:
            # 只有第二个集群没有
            stats['missing_in_cluster2'] += 1
            missing_results.append({
                'key': key.decode('utf-8') if isinstance(key, bytes) else key,
                'status': 'missing_in_cluster2',
                'cluster1_value': display_val1,
                'cluster2_value': None,
                'message': f'在{cluster2_name}中不存在'
            })
        elif val1 == val2:
            # 值相同
            stats['identical_count'] += 1
            identical_results.append({
                'key': key.decode('utf-8') if isinstance(key, bytes) else key,
                'value': display_val1
            })
        else:
            # 值不同
            stats['different_count'] += 1
            different_results.append({
                'key': key.decode('utf-8') if isinstance(key, bytes) else key,
                'cluster1_value': display_val1,
                'cluster2_value': display_val2,
                'message': '值不同'
            })
    
    compare_end = time.time()
    comparison_duration = compare_end - compare_start
    total_duration = compare_end - comparison_start_time
    
    if performance_tracker:
        performance_tracker.record_comparison_time(comparison_duration)
    
    # 计算百分比
    def safe_percentage(part, total):
        return round((part / total * 100), 2) if total > 0 else 0
    
    stats['identical_percentage'] = safe_percentage(stats['identical_count'], stats['total_keys'])
    stats['different_percentage'] = safe_percentage(stats['different_count'], stats['total_keys'])
    stats['missing_percentage'] = safe_percentage(
        stats['missing_in_cluster1'] + stats['missing_in_cluster2'] + stats['both_missing'], 
        stats['total_keys']
    )
    
    result = {
        'success': True,
        'stats': stats,
        'identical_results': identical_results,
        'different_results': different_results,
        'missing_results': missing_results,
        'performance': {
            'comparison_time': comparison_duration,
            'total_time': total_duration
        },
        'clusters': {
            'cluster1_name': cluster1_name,
            'cluster2_name': cluster2_name
        }
    }
    
    logger.info(f"数据比对完成，耗时 {comparison_duration:.3f} 秒")
    logger.info(f"比对统计: 总计{stats['total_keys']}个key，相同{stats['identical_count']}个，不同{stats['different_count']}个，缺失{stats['missing_in_cluster1'] + stats['missing_in_cluster2'] + stats['both_missing']}个")
    
    return result

def execute_redis_comparison(config1, config2, query_options):
    """
    执行Redis数据比较的主要函数
    
    Args:
        config1: 第一个Redis集群配置
        config2: 第二个Redis集群配置
        query_options: 查询选项，包含查询模式和参数
    
    Returns:
        dict: 完整的比较结果
    """
    from .redis_client import create_redis_client
    
    # 创建性能追踪器
    performance_tracker = RedisPerformanceTracker()
    
    cluster1_name = config1.get('name', '生产集群')
    cluster2_name = config2.get('name', '测试集群')
    
    logger.info(f"开始执行Redis数据比较: {cluster1_name} vs {cluster2_name}")
    
    # 创建连接
    client1 = create_redis_client(config1, cluster1_name, performance_tracker)
    client2 = create_redis_client(config2, cluster2_name, performance_tracker)
    
    if not client1:
        return {'error': f'{cluster1_name}连接失败'}
    
    if not client2:
        return {'error': f'{cluster2_name}连接失败'}
    
    try:
        # 获取要比较的keys
        keys = []
        query_mode = query_options.get('mode', 'random')
        
        if query_mode == 'random':
            # 随机获取keys
            count = query_options.get('count', 100)
            pattern = query_options.get('pattern', '*')
            source_cluster = query_options.get('source_cluster', 'cluster2')  # 默认从第二个集群获取
            
            source_client = client2 if source_cluster == 'cluster2' else client1
            source_name = cluster2_name if source_cluster == 'cluster2' else cluster1_name
            
            logger.info(f"从{source_name}随机获取 {count} 个keys")
            keys = get_random_keys_from_redis(source_client, count, pattern, performance_tracker)
            
        elif query_mode == 'specified':
            # 指定keys
            keys = query_options.get('keys', [])
            # 如果keys是字符串，需要转换为bytes（Redis通常使用bytes）
            keys = [k.encode('utf-8') if isinstance(k, str) else k for k in keys]
        
        if not keys:
            return {'error': '未获取到任何keys进行比较'}
        
        logger.info(f"准备比较 {len(keys)} 个keys")
        
        # 执行比较
        comparison_result = compare_redis_data(
            client1, client2, keys, 
            cluster1_name, cluster2_name, 
            performance_tracker
        )
        
        # 添加性能报告
        comparison_result['performance_report'] = performance_tracker.generate_report()
        comparison_result['query_options'] = query_options
        
        return comparison_result
        
    except Exception as e:
        logger.error(f"Redis数据比较执行失败: {e}")
        return {'error': f'执行失败: {str(e)}'}
    
    finally:
        # 关闭连接
        try:
            if client1:
                client1.close()
            if client2:
                client2.close()
        except:
            pass