Mongodb Learning Notes

Mongo DB

• About NoSQL
• About MongoDB
• Installing MONGO under the Windows platform
• Mongo DB Official documentation

MongoDB basic Commands

• The default installation path for MongoDB is C:\Program Files\mongodb
• Create the default database storage path c:\data\db, using the command line to associate the path to MONGO C:\Program Files\mongodb\server\3.2\bin\mongod.exe--dbpath c:\data\db, The database service opens and starts listening after successful execution

Mongo Shell

• Run the C:\Program files\mongodb\server\3.2\bin\mongod.exe file to open the MongoDB shell, which is a self-brought interactive JavaScript shell, An interactive environment for manipulating and managing MongoDB
• The help command can display a command line that can be used

DB-related operations

use tutorial

Use this command to attempt to connect to a database named tutorial and create if it does not exist. Use the Db.help () command to view command-line Help

show dbs

Displays information about the database.

If the database related name contains spaces and other characters, you can also use the following command

db["dbname"].find()db.getCollection("dbname").find()

Inserting data

Add data by using the following format:

db.restaurants.insert(   {    "address" : {    "street" : "2 Avenue",    "zipcode" : "10075",    "building" : "1480",    "coord" : [ -73.9557413, 40.7720266 ],  },  "borough" : "Manhattan",  "cuisine" : "Italian",  "grades" : [ {    "date" : ISODate("2014-10-01T00:00:00Z"),    "grade" : "A",    "score" : 11 }, {    "date" : ISODate("2014-01-16T00:00:00Z"),    "grade" : "B",    "score" : 17 }  ],  "name" : "Vella",  "restaurant_id" : "41704620"   })

Find data

If you want to find all the data, then:

db.collectionname.find()

Specify criteria:

Specify a field condition to filter by using the following format:

{ <field1>: <value1>, <field2>: <value2>, ... }

Specific examples are:

db.restaurants.find( { "borough": "Manhattan" } )

Greater than, less than the condition of the filter

db.restaurants.find( { "grades.score": { $gt: 30 } } )db.restaurants.find( { "grades.score": { $lt: 10 } } )

And And OR

db.restaurants.find( { "cuisine": "Italian", "address.zipcode": "10075" } )db.restaurants.find( { $or: [ { "cuisine": "Italian" }, { "address.zipcode": "10075" } ] } )

Sort

db.restaurants.find().sort( { "borough": 1, "address.zipcode": 1 } )

Update data

The following action updates the record for name Juni and updates the Cuisine field with the $set action. To update the LastModified field with the $currentDate operator:

db.restaurants.update({ "name" : "Juni" },{  $set: { "cuisine": "American (New)" },  $currentDate: { "lastModified": true }})

To update the embedded data:

db.restaurants.update(  { "restaurant_id" : "41156888" },  { $set: { "address.street": "East 31st Street" } })

Update multiple data: By default the Update method updates only one piece of data. To update more than one piece of data, use multi option.

db.restaurants.update(  { "address.zipcode": "10016", cuisine: "Other" },  {    $set: { cuisine: "Category To Be Determined" },    $currentDate: { "lastModified": true }  },  { multi: true})

Replace a record with information from a _id field and replace it with a new record.

db.restaurants.update(   { "restaurant_id" : "41704620" },   {     "name" : "Vella 2",     "address" : {      "coord" : [ -73.9557413, 40.7720266 ],      "building" : "1480",      "street" : "2 Avenue",      "zipcode" : "10075"      }   })

Delete a record

Delete all records that meet a certain condition:

db.restaurants.remove( { "borough": "Manhattan" } )

To delete only one record that meets a certain condition, use the Justone option:

db.restaurants.remove( { "borough": "Queens" }, { justOne: true } )

To delete all records:

db.restaurants.remove( { } )

Delete a table:

db.restaurants.drop()

Aggregation operation aggregation and accumulation

Use $group to GROUP by a keyword, and in $group, specify the keyword to be grouped as _id. $group Access the field by field path, the field name needs to be prefixed with $. $sum represents an accumulator, the following statement represents the number of cases in which the Borough field is calculated.

db.restaurants.aggregate(   [    { $group: { "_id": "$borough", "count": { $sum: 1 } } }   ]);

The output is:

{ "_id" : "Staten Island", "count" : 969 }{ "_id" : "Brooklyn", "count" : 6086 }{ "_id" : "Manhattan", "count" : 10259 }{ "_id" : "Queens", "count" : 5656 }{ "_id" : "Bronx", "count" : 2338 }{ "_id" : "Missing", "count" : 51 }

Aggregating and filtering

Use $match to filter records

db.restaurants.aggregate(   [     { $match: { "borough": "Queens", "cuisine": "Brazilian" } },     { $group: { "_id": "$address.zipcode" , "count": { $sum: 1 } } }   ]);

Mongodb Learning Notes