09.Mongo DB - ALL

 

Project can be download from 

      https://github.com/LahiruPriyankara/SpringBootAppTwo-MongoDB

Mongo DB

Mongo DB යනු noSql open source database එකක් වේ. SQL database හෙවත් relational database වලදී data table වල තබා ගන්න අතර මෙම table table අතර relationship ද පවතී.නමුත් mongoDB වලදී data පවතිනුයේ document collection එකක් ලෙසට වන අතර මෙම documents අතර relations නැත.එනම් documents are not related with each other. Schema free වන අතර this is based on binary JSON එනම් BSON. Mongo DB simple query language එක ලෙස simple query language එක බාවිතා කරනු ලබයි (SQL වගේ). 

SQL and MongoDB Comparison.

Table – Collection

Row – Document

Column – File

Collection is not strict about what goes in it (it’s schema-less).

 

Download and install mongoDB

Go to https://www.mongodb.com/try/download/community and  download mongoDB.

Note: version 4.4.1 is only support in windows 10.If you want to install other versions of windows, please select an older mongo dB version.

 

Alter install go to bellow path…

C:\Program Files\MongoDB\Server\3.6\bin

Inside bin there are 2 excitable file can be seen.mongod.exe and mongo.exe

·       Mogod.exe. Mongo daemon which is going to run in the background it will accept the connections.

·       Mong.exe. command line shell from which you are going to work with your database.

 

Running mongoDB

If you want to run mogoDB, first you have to run mongod.exe then run mongo.exe.

To run, open C:\Program Files\MongoDB\Server\3.6\bin this location with cmd.

In the CMD, type monod.exe and press enter to run.පළමු පාර run කරන විට පහත error එක පැමිණේ.

That errors like that, please create this file (C:\data\db) and re execute the mongo.exe.

 

Then open this location in new CMD and execute mongo.exe.

When you execute the mongo.exe bellow part (connection accepted) can be seen on monod.exe executed cmd.

To test,

Type db and press enter.මෙය mongo.exe එක run වන CMD හි execute කරන්න.

නමුත් ඉහත පරිදි C:\Program Files\MongoDB\Server\3.6\bin location එකෙන් CMD  එක open  කරගෙන run කර කර ඉන්නට අවශ්‍ය වෙන්නේ නැ.ඒ සදහා environment variable එක set කරන්න.ඊට පස්සේ any location එකක ඉදන් database එකට අදාළ query run කරන්න  පුළුවන්.

Setting Environment variable.

Go to view advance system setting – environment variable – then select path and double click (select path and then click on edit) add C:\Program Files\MongoDB\Server\3.6\bin location at end. – OK

Then open the CMD from any location and do the above process agin.it will working fine.

ඉහත පරිදි mongoDB එක සමග CMD එක හරහා ගණදෙනු කල හැක(query execute කල හැක).SQL මෙය මෙලෙසම වන අතර නමුත් පහසුව පිණිස SQL සමග වැඩ කිරීමේදී GUI(graphical user interface) use කරනු ලබයි(MySQL Workbench , XAMP,WAP වගේ ඒවා).mongoDB  සමග ද පහසුවෙන් වැඩ කිරීමට මෙලෙස GUI use කර ගත හැක.

 

Download and install a GUI (MongoChef)

Go to https://studio3t.com/download/ and Download and install it.

 

Download MongoShell

Go to https://www.mongodb.com/try/download/shell and Download.

Then extract it.

Copy and paste extracted file in C drive (C:\mongosh-1.8.2-win32-x64).

Add its bin path to environment variables(C:\mongosh-1.8.2-win32-x64\bin).

Go to C:\mongosh-1.8.2-win32-x64\bin and run mongosh.exe.

Commands which we use in mongoDB.

Create a database

use company  // create a database

If it is already exist provide it, otherwise create it.

View all databases

show dbs

Database එකක් අලුතෙන් create කර මෙම command එක run කලද එම අලුත් database එකට document එකක් add වන තුරු එම database එක පෙන්වන්නේ නැත.

Drop a data base

db.dropDatabase() //Dropping a current woking database

 

 Create a collection.

db.createCollection("branch")

db.branch.insert({"code":"001", "name":"branch one"})

// create a document. Inhere branch Collection also create and then document is created.

View Collections

show collections // show created collection

 

View Collection data

db.branch.find()

 

Drop a Collection

db.employee.drop() // remove collection

 

Adding Document.

මෙහෙදී Binary Jason Format හෙවත් BSON එක යොදා ගනු ලබයි.

Single record.

db.branch.insert({"code":"001", "name":"branch one"})

 

 Multiple record.

db.branch.insert(

[

{"bId":"001", "bLocation":"Colombo","bTP":"b0771234567"},

{"bId":"002", "bLocation":"Kandy","bTP":"b0771235567"},

{"bId":"003", "bLocation":"Galle","bTP":"b0771230000"}

]

)

අපි Database එකට  data insert කරන විට mongoDB වලින් ඒ ඒ record එකට default ම unique id එකක් generate කරගනු ලබයි.එම ID එක අපට provide කරනටද පුළුවන් වේ.

Finding data.

find() and fIndOne() සැලකිමේදී find() මගින් entire collection එකේම search කර අදාළ සියලුම document ලබා දෙන අතර, findOne() මගින් පලවෙනි එක හොයාගත්තම document එක return කිරීම කරයි.එම නිසා find() ට වඩා findOne() එක speed වේ.

db.employee.find()

db.employee.findOne()

db.employee.find({"code":"001"})

db.employee.findOne({"code":"001"})

// find one is more speed because it find 1st result and return it.Bu in find() it will find all the record in the entire collection.

db.employee.find({"salary":"23000"}) // equal

db.employee.find({"salary":{$ne :"23000"}}) // not equal

db.employee.find({"salary":{$gt :"23000"}}) // gt - breater than

db.employee.find({"salary":{$gte :"23000"}}) //gte - greater than or equal

db.employee.find({"salary":{$lt :"29000"}}) // lt - breater than

db.employee.find({"salary":{$lte :"29000"}}) //lte - greater than or equal

AND, OR conditions (SQL වලනම් && සහ ||).

//And

db.employee.find({"salary":"23000","age":45})

db.employee.find({"salary":{$gt :"20000"},"age":{$gt :35}})

//Or

db.employee.find({$or : [{"salary":"23000","age":45}]})

db.employee.find({$or : [{"salary":{$gt :"20000"},"age":{$gt :35}}]})

//both

db.employee.find({"age":{$lt :55},$or : [{"code":"002","salary":{$gt :"20000"}}]})

Updating

// updating

db.employee.update({"_id" : ObjectId("5f5ca367ccb1774f207b1dd7")},{$set:{"salary" : "28000"}})

db.employee.update({"age":{$lt :50}},{$set:{"salary" : "25000"}})//age එක 50 ට අඩු පළමු document එක විතරක් update කරයි.

db.employee.update({"age":{$lt :50}},{$set:{"salary" : "25000"}},{multi:true})// age එක 50 ට අඩු සියලුම document update කරයි.

db.employee.save({ "_id" : ObjectId("5f5ca367ccb1774f207b1dd7"), "code" : "002", "addrss" : "Main Steet,Kandy 04", "salary" : "25000", "age" : 36.0})

save වලදී id = "5f5ca367ccb1774f207b1dd7" search කරන අතර එහෙම එකක් තියනවනම් new valuess වලින් old එක update කරන අතර එහෙම එකක් නැත්තන් new document එකක් create කරනු ලබයි.

Removing Elements.

db.employee.remove()//කිසිම augment එකක් pass නොකරන්නේ නම් employee collection එකේ ඇති සියලුම documents remove කරනු ලබයි.

db.employee.remove({"_id" : ObjectId("5f5ca367ccb1774f207b1dd7")})

db.employee.remove({"age":45})// remove all documents, which age is = 45

db.employee.remove({"age":45},1)// even given condition find multiple documents, then delete one document only

Projection

Selecting only necessary data rather than selection the all data from a document.

// Syntax - db.COLLECTION.remove({},{KEY:1 OR 0})

db.employee.find({},{"age":1,"_id":0})// first one should be empty {}. 1 - we want that data , 0 - we do not want that data

limit, skip and sort

db.employee.find({},{"age":1,"_id":0,"code":1, "addrss":1,"salary":1}).limit(2) // employee collection එකෙන් document 2k පමණක් fetch කරන්න

db.employee.find({},{"age":1,"_id":0,"code":1, "addrss":1,"salary":1}).skip(2) // employee collection එකෙන් document වල පළමු 2k අත්හැර ඉතුරු ටික පමණක් fetch කරන්න

db.employee.find({},{"age":1,"_id":0,"code":1, "addrss":1,"salary":1}).limit(2).skip(1)

db.employee.find({},{"age":1,"_id":0,"code":1, "addrss":1,"salary":1}).skip(1).limit(2) // Both are same.පළමුවෙනි document එක අතහැර ඊලග document දෙක ගන්න

db.employee.find({},{"age":1,"_id":0,"code":1, "addrss":1,"salary":1}).sort({"salary":1}) // get document according acceding order of salary.[23000,290000,33000]

db.employee.find({},{"age":1,"_id":0,"code":1, "addrss":1,"salary":1}).sort({"salary":-1}) // get document according descending order of salary.[33000,290000,23000]

Indexing

Indexes are the special data structure that sores a small portion of data set to easy to pass way. Mongo database is really large, it can have millions of records. If we want to find one document among those it is very important to use indexing.

Adding large amount of document to test the indexing.

for(i = 5; i<1000000;i++){

db.employee.insert(

{"code":"003"+i, "addrss":"Main Steet,Galle "+i,"salary":"33000","age":55}

)

}

Create index

db.employee.createIndex({"salary":1})

 

Fetch document

db.employee.find({"salary":"23000"})

 

Drop Index

db.employee.dropIndex({"salary":1})

 

MongoDB Aggregation

 This groups values from multiple documents together and can perform variety of operations on that grouped data.it is going to return single result after the aggregation.

 In the SQL we query select count and in the bracket Astrix this count for aggregation. It return the number of rows. This is same in mongoDB.

db.employee.aggregate([

{ $group: { _id: "$gender", genderCount: { $sum: 1 } } }

]) // $sum: 1 :1 - true

db.employee.aggregate([

{ $group: { _id: "$gender", maxAge: { $max: "$age" } } }

])

Bellow example is from https://docs.mongodb.com/manual/aggregation/

Single Purpose Aggregation Operations

db.collection.estimatedDocumentCount(), db.collection.count() and db.collection.distinct().

db.employee.estimatedDocumentCount()

db.employee.count()

db.employee.distinct("salary")

MongoDB Backup and Restore

 

Backup

Open lib location (C:\Program Files\MongoDB\Server\3.6\bin) in CMD administrative mode

 

To back up all the databases

Run mongodump in CMD.

 

To back up a specific databases

Run mogodump --db databasename in CMD.

Example: mogodump --db company

 

To back up a specific collection.

Run mogodump --db databasename --collection collectionname in CMD.

Example: mogodump --db company --collection employee

 

Restore

Open lib location (C:\Program Files\MongoDB\Server\3.6\bin) in CMD administrative mode

To restore all the databases

Run mongorestore in CMD.

 

To restore a specific databases

Run mongorestore --db databasename dump/databasename in CMD.

Example: mongorestore --db company dump/company

 

To restore a specific collection

Run mongorestore --db databasename --collection collectionname in CMD.

Example: mongorestore --db company --collection employee dump/employee/employee.bson