from pymongo import MongoClient def sample_data(N): # 连接MongoDB数据库 db = MongoClient('192.168.3.149', 27180, unicode_decode_error_handler="ignore").data_quality coll_user = db["bidding_919ai_norepeat"] # 统计总的数据量 # count_all = coll_user.estimated_document_count() count_all = coll_user.count_documents({"tag": 1}) print("Total Document Count:", count_all) # 把符合条件的站点名称存起来 site_list = {} n = 0 site_count = coll_user.aggregate([ {"$match": {"tag": 1}}, {"$group": {"_id": "$site", "count": {"$sum": 1}}}, {"$sort": {"count": -1}}]) for item in site_count: if (n / count_all) <= 0.95: n += item["count"] site_list[item["_id"]] = item["count"] # 计算每个站点相对于N的目标抽取数量的总和 total_ratio = sum([min(site_list[key] / count_all, 1) for key in site_list]) # 初始化已标记的文档数量 marked_count = 0 # 选取每个站点数据量 for key in site_list: if marked_count >= N: break # 如果已经达到或超过目标数量,停止处理 # 计算每个站点的目标比例 target_ratio = min(site_list[key] / count_all, 1) / total_ratio # 计算每个站点应该抽取的文档数量,确保至少为1 num = max(int(target_ratio * N), 2) # 如果加上这个站点的数量会超过总目标,调整数量 num = min(num, N - marked_count) print(f"{key} - Count: {site_list[key]}, Num: {num}, Ratio: {target_ratio}") # 计算每次抽取的间隔 jiange = int(site_list[key] / num) # 从每个站点等间隔地取数据 for i in range(num): if marked_count >= N: break # 再次检查是否已达到目标数量 for info in coll_user.find({"tag": 1, "site": key}).sort("title", 1).skip(i*2).limit(1): print(f"Updating document with _id: {info['_id']}") # 更新文档,设置标记 update_result = coll_user.update_one({"_id": info["_id"]}, {"$set": {"flag": 9}}) if update_result.modified_count == 0: print("No document updated for _id:", info["_id"]) else: print("Document updated successfully for _id:", info["_id"]) marked_count += 1 if marked_count >= N: break # 再次检查是否已达到目标数量 print(f"Total marked documents: {marked_count}") sample_data(1000)