Ana Sayfa / MongoDB / MongoDB Backing up and Restoring Data

MongoDB Backing up and Restoring Data

Basic mongodump of local default mongod instance

mongodump --db mydb --gzip --out "mydb.dump.$(date +%F_%R)"

This command will dump a bson gzipped archive of your local mongod ‘mydb’ database to the ‘mydb.dump.{timestamp}’ directory

Basic mongorestore of local default mongod dump

mongorestore --db mydb mydb.dump.2016-08-27_12:44/mydb --drop --gzip

This command will first drop your current ‘mydb’ database and then restore your gzipped bson dump from the ‘mydb mydb.dump.2016-08-27_12:44/mydb’ archive dump file.

Mongoimport with JSON

Sample zipcode dataset in zipcodes.json stored in c:\Users\yc03ak1\Desktop\zips.json

{ "_id" : "01001", "city" : "AGAWAM", "loc" : [ -72.622739, 42.070206 ], "pop" : 15338, "state" : "MA" }
{ "_id" : "01002", "city" : "CUSHMAN", "loc" : [ -72.51564999999999, 42.377017 ], "pop" : 36963, "state" : "MA" }
{ "_id" : "01005", "city" : "BARRE", "loc" : [ -72.10835400000001, 42.409698 ], "pop" : 4546, "state" : "MA" }
{ "_id" : "01007", "city" : "BELCHERTOWN", "loc" : [ -72.41095300000001, 42.275103 ], "pop" : 10579, "state" : "MA" }
{ "_id" : "01008", "city" : "BLANDFORD", "loc" : [ -72.936114, 42.182949 ], "pop" : 1240, "state" : "MA" }
{ "_id" : "01010", "city" : "BRIMFIELD", "loc" : [ -72.188455, 42.116543 ], "pop" : 3706, "state" : "MA" }
{ "_id" : "01011", "city" : "CHESTER", "loc" : [ -72.988761, 42.279421 ], "pop" : 1688, "state" : "MA" }

to import this data-set to the database named “test” and collection named “zips”

C:\Users\yc03ak1>mongoimport --db test --collection "zips" --drop --type json --host
"localhost:47019" --file "c:\Users\yc03ak1\Desktop\zips.json"
  • –db : name of the database where data is to be imported to
  • –collection: name of the collection in the database where data is to be improted
  • –drop : drops the collection first before importing
  • –type : document type which needs to be imported. default JSON
  • –host : mongodb host and port on which data is to be imported.
  • –file : path where the json file is

output :

2016-08-10T20:10:50.159-0700 connected to: localhost:47019
2016-08-10T20:10:50.163-0700 dropping: test.zips
2016-08-10T20:10:53.155-0700 [################……..] test.zips 2.1 MB/3.0 MB (68.5%)
2016-08-10T20:10:56.150-0700 [########################] test.zips 3.0 MB/3.0 MB (100.0%)
2016-08-10T20:10:57.819-0700 [########################] test.zips 3.0 MB/3.0 MB (100.0%)
2016-08-10T20:10:57.821-0700 imported 29353 documents

Mongoimport with CSV

Sample test dataset CSV file stored at the location c:\Users\yc03ak1\Desktop\testing.csv

id city loc pop state
1 A [10.0, 20.0] 2222 PQE
2 B [10.1, 20.1] 22122 RW
3 C [10.2, 20.0] 255222 RWE
4 D [10.3, 20.3] 226622 SFDS
5 E [10.4, 20.0] 222122 FDS

to import this data-set to the database named “test” and collection named “sample”

C:\Users\yc03ak1>mongoimport --db test --collection "sample" --drop --type csv --headerline --host  "localhost:47019" --file "c:\Users\yc03ak1\Desktop\testing.csv"
  • –headerline : use the first line of the csv file as the fields for the json document

output :

2016-08-10T20:25:48.572-0700 connected to: localhost:47019
2016-08-10T20:25:48.576-0700 dropping: test.sample
2016-08-10T20:25:49.109-0700 imported 5 documents

OR

C:\Users\yc03ak1>mongoimport --db test --collection "sample" --drop --type csv --fields  _id,city,loc,pop,state --host "localhost:47019" --file c:\Users\yc03ak1\Desktop\testing.csv"
  • –fields : comma seperated list of fields which needs to be imported in the json document. Output:
2016-08-10T20:26:48.978-0700 connected to: localhost:47019
2016-08-10T20:26:48.982-0700 dropping: test.sample
2016-08-10T20:26:49.611-0700 imported 6 documents

Bunada Göz Atın

Python Simple Mathematical Operators

Python does common mathematical operators on its own, including integer and float division, multiplication, exponentiation, …

Bir cevap yazın

E-posta hesabınız yayımlanmayacak.