文章目錄

• Mongodb實現多表join
• • 1、通過遍歷其他表，插入到當前表
  • 2、優化方式
  • • 2.1、mongodb的lookup, 也就是聚合功能
    • 2.2、mapreduce 分布式join多表

Mongodb實現多表join

千萬數量級的table, 如何實現join?

1、通過遍歷其他表，插入到當前表

from pymongo import MongoClientclient = MongoClient("mongodb://192.168.123.64:27017/") temp = client["gd_raw_data"]["temp"] prplregistex = client["gd_raw_data"]["prplregistex"] repairfee = client["gd_raw_data"]["repairfee"] prplcitemcar = client["gd_raw_data"]["prplcitemcar"] lossthirdparty_lossmain = client["gd_raw_data"]["lossthirdparty_lossmain"] lossthirdparty = client["gd_raw_data"]["lossthirdparty"] lossmain = client["gd_raw_data"]["lossmain"] citemkind = client["gd_raw_data"]["citemkind"] check = client["gd_raw_data"]["check"]query = {} cursor = temp.find(query, no_cursor_timeout=True) try:i = 0for doc in cursor:registno = doc['registno']print("報案號：{}".format(registno))prplregistex_info = prplregistex.find_one({ "registno": registno},no_cursor_timeout=True)repairfee_info = repairfee.find_one({ "registno": registno},no_cursor_timeout=True)prplcitemcar_info = prplcitemcar.find_one({ "registno": registno},no_cursor_timeout=True)lossthirdparty_lossmain_info = lossthirdparty_lossmain.find_one({ "registno": registno},no_cursor_timeout=True)lossthirdparty_info = lossthirdparty.find_one({ "registno": registno},no_cursor_timeout=True)lossmain_info = lossmain.find_one({ "registno": registno},no_cursor_timeout=True)citemkind_info = citemkind.find_one({ "registno": registno},no_cursor_timeout=True)check_info = check.find_one({ "registno": registno},no_cursor_timeout=True)newvalues = {"$set": {"prplregistex_info": prplregistex_info,"repairfee_info": repairfee_info,"prplcitemcar_info": prplcitemcar_info,"lossthirdparty_lossmain_info": lossthirdparty_lossmain_info,"lossthirdparty_info": lossthirdparty_info,"lossmain_info": lossmain_info,"citemkind_info": citemkind_info,"check_info": check_info}}temp.update_one({ "registno": registno}, newvalues)finally:client.close()

發現我的PC(i7 6代)實現1700萬多表join需要125個小時，也就是5天5夜，中途服務器容易掛死。

2、優化方式

要么多線程，要么分布式

2.1、mongodb的lookup, 也就是聚合功能

操作之前請務必為關聯的字段創建索引

db.getCollection("prplcmain").aggregate([{"$lookup": {"from": "lida","localField": "registno","foreignField": "registno","as": "carinfo"}},{"$lookup": {"from": "prpldriver","localField": "registno","foreignField": "registno","as": "prpldriver"}},{"$lookup": {"from": "prplinjured","localField": "registno","foreignField": "registno","as": "prplinjured"}},{"$lookup": {"from": "prplinsured","localField": "registno","foreignField": "registno","as": "prplinsured"}},{"$lookup": {"from": "regist","localField": "registno","foreignField": "registno","as": "regist"}},{"$out" : "total"}],{"allowDiskUse" : true} );

這個相同配置下2個小時內可以搞定

2.2、mapreduce 分布式join多表

這個還沒研究透徹
https://stackoverflow.com/questions/38882184/join-two-collections-with-mapreduce-in-mongodb

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