MongoDB的数据库导入和导出

MongoDB的数据库导入和导出

MongoDB的导出

//导出为csv格式
mongoexport -d dbname -c 集合名称 -q {} -f filed1,filed2,... --type=csv > filename.csv 
//导出为json格式
mongoexport -d dbname -c 集合名称 -q {} -f filed1,filed2,... filename.json

//带条件的导出
mongoexport -d dbname -c 集合名称 -q '{"age":{"$gt":20}}' -f filed1,filed2,... --type=csv > filename.csv 

导出的示例

D:\Program Files\MongoDB\Server\4.0\bin>mongoexport.exe -h localhost:27001 -d mldn -c emps -q {} -f name,age,job,salary --csv > emps.csv
2018-09-10T10:25:54.582+0800    csv flag is deprecated; please use --type=csv instead
2018-09-10T10:25:54.604+0800    connected to: localhost:27001
2018-09-10T10:25:54.610+0800    exported 8 records

D:\Program Files\MongoDB\Server\4.0\bin>mongoexport.exe -h localhost:27001 -d mldn -c emps -q {} -f name,age,job,salary > emps.json
2018-09-10T10:30:06.945+0800    connected to: localhost:27001
2018-09-10T10:30:06.971+0800    exported 8 records

带条件的导出windows的-q "{}"，linux的则是-q '{}'。两者有区别，大家切记。

D:\Program Files\MongoDB\Server\4.0\bin>mongoexport.exe -h localhost:27001 -d mldn -c emps -q "{age:{$gt:20}}" -f name,age,job,salary --type=csv > emps1.csv
2018-09-10T10:50:06.952+0800    connected to: localhost:27001
2018-09-10T10:50:06.969+0800    exported 2 records

MongoDB的导入

//导入csv格式的文件
mongoimport -d dbname -c collectionName --type csv --headerline --drop < filename.csv
//导入json格式的文件
mongoimport -d dbname -c collectionName --type json --drop < filename.json

导入的示例

D:\Program Files\MongoDB\Server\4.0\bin>mongoimport.exe -h localhost:27001 -d mldn -c emps --type csv --headerline --drop < emps1.csv
2018-09-10T11:00:09.704+0800    connected to: localhost:27001
2018-09-10T11:00:09.721+0800    dropping: mldn.emps
2018-09-10T11:00:10.991+0800    imported 2 documents

D:\Program Files\MongoDB\Server\4.0\bin>mongoimport.exe -h localhost:27001 -d mldn -c emps --type json --drop < emps.json
2018-09-10T11:02:31.431+0800    connected to: localhost:27001
2018-09-10T11:02:31.442+0800    dropping: mldn.emps
2018-09-10T11:02:32.688+0800    imported 8 documents

检查数据，正常。

 db.emps.find();
{ "_id" : ObjectId("5b95de7d2dd48cac697bfbc2"), "name" : "孙七", "age" : 21, "job" : "manager", "salary" : 6000 }
{ "_id" : ObjectId("5b95de7d2dd48cac697bfbc3"), "name" : "李四", "age" : 10, "job" : "clerk", "salary" : 2000 }
{ "_id" : ObjectId("5b95de7d2dd48cac697bfbc4"), "name" : "钱九", "age" : 18, "job" : "president", "salary" : 10000 }
{ "_id" : ObjectId("5b95de7d2dd48cac697bfbc5"), "name" : "吴十", "age" : 19, "job" : "clerk", "salary" : 2000 }
{ "_id" : ObjectId("5b95de7d2dd48cac697bfbc0"), "name" : "王五", "age" : 25, "job" : "manager", "salary" : 7000 }
{ "_id" : ObjectId("5b95de7d2dd48cac697bfbc6"), "name" : "周八", "age" : 17, "job" : "clerk", "salary" : 2000 }
{ "_id" : ObjectId("5b95de7d2dd48cac697bfbbf"), "name" : "张三", "age" : 20, "job" : "clerk", "salary" : 2000 }
{ "_id" : ObjectId("5b95de7d2dd48cac697bfbc1"), "name" : "赵六", "age" : 20, "job" : "clerk", "salary" : 2000 }

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