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- 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)
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