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这篇文章主要介绍关于mongodb复杂查询的案例,文中示例代码介绍的非常详细,具有一定的参考价值,感兴趣的小伙伴们一定要看完!
m内嵌文档复杂查询
1、数据结构
{ "_id":"1412243", "info":{ "data":[ { "broker_id":0, "receive_status":0, "house_id":"1412243", "gov_id":4127238, "owner_phone":"", "owner_name":"经纪人", "source_name":"中原地产", "source_logo":"http://file.zhugefang.com/5a351abc8fe131513429692_80_80.png", "small_logo_url":"http://file.zhugefang.com/5a351abbbca1b1513429691_32_32.png", "source":2, "house_type":"1", "pay_type":0, "renzheng":"", "header_pic":"", "receive_time":0, "city":7, "service_phone":"4008985666,133188", "house_source_desc":"房屋信息发布经纪人", "source_url":"https://tj.centanet.com/ershoufang/tjnk0007892545.html", "house_price":450, "fee":"0.00", "fee_new":"买方1% 卖方1%", "feedback_total":"", "feedback_content":[ ] }, { "broker_id":0, "receive_status":0, "house_id":"1412243", "gov_id":2964975, "owner_phone":"", "owner_name":"经纪人", "source_name":"链家地产", "source_logo":"http://file.zhugefang.com/5a37669b7b3c21513580187_80_80.png", "small_logo_url":"http://file.zhugefang.com/5a37669a87fc11513580186_32_32.png", "source":1, "house_type":"1", "pay_type":0, "renzheng":"", "header_pic":"", "receive_time":0, "city":7, "service_phone":"4008790056,7048", "house_source_desc":"房屋信息发布经纪人", "source_url":"http://tj.lianjia.com/ershoufang/101101622982.html", "house_price":450, "fee":"0.00", "fee_new":"买方2.5%", "feedback_total":"", "feedback_content":[ ] } ], "company_ids":4 }, "city_name":"天津", "city":"tj", "cityid":"7", "craw_date":"2018-06-30" }
2、db.books.find({"info.data":{"$elemMatch":{"owner_name":"经纪人","source_name":"中原地产"}}})
这种数据结构 info 是一个对象,data中是一个列表,使用上面的命令就可以把数据筛选出来。
如果info是一个列表,data也是一个列表
db.books.find({info:{"$elemMatch":{data:{"$elemMatch":{house_id:"2185216"}}}}})
使用上面的命令就能把数据筛选出来
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