Download MongoDB JSON Description and working and more Lecture notes Advanced Data Analysis in PDF only on Docsity!
Unit-III
MongoDB
Introduction to MongoDB :What is MongoDB-Why-Datatypes-
MongoDb Query Language.
What is mongoDB?
- MongoDB is a - Cross-platform - Open source - Non-relational - Distributed
Mongodb is a document-oriented NoSQL database used for high volume data storage. MongoDB is a database which came into light around the mid-2000s. It falls under the category of a NoSQL database. The MongoDb contains the features such as “Auto Sharding”, “Replication”, its “Rich query language”. “fast in-place update”, etc.
As said before MongoDB is a document database. Each database contains collections which in turn contains documents. Each document can be different with varying number of fields. The size and content of each document can be different from each other.
Why MongoDb?
- The document structure is more in line with how developers construct their classes and objects in their respective programming languages. Developers will often say that their classes are not rows and columns but have a clear structure with key-value pairs.
- As seen in the introduction with NoSQL databases, the rows are called as documents in MongoDB doesn't need to have a schema.
- The data model available within MongoDB allows you to represent hierarchical relationships, to store arrays, and other more complex structures more easily.
- Scalability – The MongoDB environments are very scalable.
- Document-oriented – Since MongoDB is a NoSQL type database, instead of having data in a relational type format, it stores the data in documents. This makes MongoDB very flexible and adaptable to real business world situation and requirements.
- Ad hoc queries - MongoDB supports searching by field, range queries, and regular expression searches. Queries can be made to return specific fields within documents.
- Indexing - Indexes can be created to improve the performance of searches within MongoDB. Any field in a MongoDB document can be indexed.
- Replication - MongoDB can provide high availability with replica sets. A replica set consists of two or more mongo DB instances. Each replica set member may act in the role of the primary or secondary replica at any time. The primary replica is the main server which interacts with the client and performs all the read/write operations. The Secondary replicas maintain a copy of the data of the primary using built-in replication. When a primary replica fails, the replica set automatically switches over to the secondary and then it becomes the primary server.
- Load balancing - MongoDB uses the concept of sharding to scale horizontally by splitting data across multiple MongoDB instances. MongoDB can run over multiple servers, balancing the load and/or duplicating data to keep the system up and running in case of hardware failure. Common terms used in MongoDB
1._id – This is a field required in every MongoDB document. The _id field
represents a unique value in the MongoDB document. The _id field is like the document's primary key. If you create a new document without an _id field, MongoDB will automatically create the field. So for example, if we see the example of the above customer table, Mongo DB will add a 24 digit unique identifier to each document in the collection. _Id CustomerID CustomerName 563479cc8a8a4246bd27d784 11 Guru 563479cc7a8a4246bd47d784 22 Trevor Smith 563479cc9a8a4246bd57d784 33 Nicole
2. Database
It is a collection of collections. In other words its is like a container for collections. Each database gets its own set of files on the file system. A MongoDB server can store multiple databases. It is created when the first time that your collection makes a reference to it.
single primary and several secondary’s. Each write request from the client is directed to the primary. The primary logs all write requests into its Oplog(Operations log). The Oplog is then used by the secondary replica members to synchronize their data. This way there is strict adherence to consistency. The clients usually read from the primary. However, the client can also specify a read preference that will then direct the read operation to the secondary.
Writes Reads
Replication Replication
The process of REPLICATION in MongoDb
8. Sharding
Logical database (Collection 1)
The process of SHARDING in MongoDB
Replication Client ApplicationSecondarySecondarySecondaryCollection 1Primary 1 TB database
Shard 4 (256 GB)
Shard 2 (256 GB)
Shard 3 (256 GB)
Shard 1 (256 GB)
Sharding is akin to horizontal scaling. It means that the large dataset is divided and distributed over multiple servers or shards. Each shard is an independent database and collectively they would constitute a logical database.
The prime advantages of sharding are as follows:
1. Sharding reduces the amount of data that each shard needs to store and manage. For example, if the dataset was 1TB in size and we were to distribute this over four shards, each shard would house just 256GB data. The above example as the cluster grows, the amount of data that each shard will store and manage will decrease. 2. Sharding reduces the number of operations that each shard handles. For example, if we were to insert data, the application needs to access only that shard which houses that data.
JSON(Java Script Object Notation)
This is known as JavaScript Object Notation. This is a human-readable, plain text format for expressing structured data. JSON is currently supported in many programming languages.
JSON is extremely expressive. MongoDB actually does not JSON but BSON-it is Binary JSON. It is an open standard. It is used to store complex data structures. BSON extends the JSON model to provide additional data types.JSON and BSON are very similar, but BSON provides extra speed. In the relational database, these are tables, which are responsible for storing data in form of rows and columns. JSON uses objects and arrays. objects are key-value pairs and arrays are the list of values. They can be nested recursively.
Basic Constructs of JSON
connection.
Later on, this data can be retrieved. Because of the very nature of the JSON, it is useful for storing or representing semi structured data.
Documents have the following restrictions on field names:
- The field name _id is reserved for use as a primary key; its value must be unique in the collection, is immutable, and may be of any type other than an array.
- The field names cannot start with the dollar sign ($) character.
- The field names cannot contain the dot (.) character.
- The field names cannot contain the null character.
BSON documents may have more than one field with the same name. Most MongoDB interfaces, however, represent MongoDB with a structure (e.g. a hash table) that does not support duplicate field names. If you need to manipulate documents that have more than one field with the same name, see the driver documentation for your driver.
Some documents created by internal MongoDB processes may have duplicate fields, but no MongoDB process will ever add duplicate fields to an existing user document.
Terms used in RDBMS and MongoDB
RDBMS MongoDB Database Database Table Collection Record Document Columns Fields/Key Value pairs Index Index Joins Embedded documents Primary Key Primary key(_id)
To create a database in MongoDb
The syntax for creating databse is
Use DATABASE_Name
To create a database by the name “myDB” the syntax is
use myDB
To confirm the existing of the database
db;
To get a list of all databases, type
show dbs
Admin (empty)
Local 0.078GB
Test 0.078GB
To Drop a database in mongoDB
Update-> Update to data is accomplished using the update() method with UPSERT set to false.
Delete-> A document is deleted using the remove() method.
1 .To Create a inventory database
use inventory;
Or it can be also created using
db.createCollection(“inventory”)
{ “ok” : 1}
To list the collections(databases) use the following command
show collections;
inventory
person
food
system.indexes
System.js
To drop the collection named by food
db.food.drop();
It drops the collection food.
2.Insert method
To insert the values in the student database use the following command
Firstly create the student collection
use student;
The student database contains the following fields
▲ Rollno
▲ Name
▲ Grade
▲ Phone no
INSERT RECORD
db.student.insert({_id:1,rollno:101,name:"raja",grade:100,phno:9876543210});
One document gets inserted.
To check if the document for the student “raja” has been successfully inserted use the following command.
db.student.find();
To format the result use the following command
db.student.find().pretty();
To insert the another document into the collection use the following command
db.student.insert({_id:2,rollno:102,name:"ram",grade:90,phno:9876543211});
Similarly insert other documents into the collection
db.student.insert({_id:3,rollno:103,name:"raji",grade:80,phno:9876543212});
db.student.insert({_id:4,rollno:104,name:"rasi",grade:70,phno:9876543213});
db.student.insert({_id:5,rollno:105,name:"raki",grade:60,phno:9876543214});
So, Now the collection contains 5 documents.
To insert many documents(Records) to the collection
> db.inventory. insertMany ([
{ item: "journal", qty: 25, size: { h: 14, w: 21, uom: "cm" }, status: "A" },
{ item: "notebook", qty: 50, size: { h: 8.5, w: 11, uom: "in" }, status: "A" },
{ item: "paper", qty: 100, size: { h: 8.5, w: 11, uom: "in" }, status: "D" },
{ item: "planner", qty: 75, size: { h: 22.85, w: 30, uom: "cm" }, status: "D" },
{ item: "postcard", qty: 45, size: { h: 10, w: 15.25, uom: "cm" }, status: "A" }
]);
It adds the location:”Newark” to the document
Removing a field from an existing document in update method using UNSET
command
The field can be removed in general by using
db.student.remove({Age:{$gt:18}});
By using the UNSET command it can be removed
db.student.update{_id:4},{$unset:{Location:”Newark”}});
It removes the location from the document
3.SAVE ()Method
db.student.save({name:”rakshitha”,grade:55});
It saves the document with the collection
4.FIND method –finding documents based on Search criteria
To find the document using the name use the following command
db.student.find({name:"raki"});
It list the document raki in the collection
To find the document using the _id
db.student.find({_id:1},pretty();
It lists the document in the _id:
To display the id,name and rollno
db.student.find({_id:1},{rollno:1,name:1}).pretty();
To display the rollno and name but should not display the _id value use the
command
db.student.find({_id:1},{rollno:1,name:1,_id:0}).pretty();
Relational operators
$eq – equal to
$ne – not equal
$gte – greater than or equal to
$lte – less than or equal to
$gt – greater than
$lt – less than
To display the student document with the grade greater than 70
db.student.find({grade:{$gt:70}});
To display the student document with the grade not equal to 70 use the command
db.student.find({grade:{$ne:70}});
To list the student document with the grade less than or equal to 35 use
db.student.find({grade:{$lte:35}});
IN AND NOT IN function
To find those documents from the student collection where the hobby is set to
either
“chess” or is set to “skating” use the command
db.student.find({Hobby:{$in:[‘Chess’,’skating’]}}).pretty();
To find those documents from the student collection where hobby is not in chess
and skating
db.student.find({Hobby:{$nin:[‘Chess’,’skating’]}}).pretty();
The above command list out the documents without the chess and skating
documents
To list out the name of the student whose name starts with R use the command
db.student.find().sort({Name:1}).pretty();
To sort the student collection in the descending order of the studentname
db.student.find().sort({Name:-1}).pretty();
To skip the first 2 documents in the collection
db.student.find().skip(2).pretty();
To display the last 2 records from the student collection
db.student.find().pretty()skip(db.stuent.count()-2);
7.Arrays
To create a collection by name “inventoryarray” and insert documents into the
“inventoryarray” collection. Each document should contain “tags” array
use inventoryarray;
db.inventoryarray.insertMany([
{ item: "journal", qty: 25, tags: ["black", "red"], dim_cm: [ 14, 21 ] },
{ item: "notebook", qty: 50, tags: ["red", "black"], dim_cm: [ 14, 21 ] },
{ item: "paper", qty: 100, tags: ["red", "black", "plain"], dim_cm: [ 14, 21 ] },
{ item: "planner", qty: 75, tags: ["black", "red"], dim_cm: [ 22.85, 30 ] },
{ item: "postcard", qty: 45, tags: ["blue"], dim_cm: [ 10, 15.25 ] }
]);
To list the documents in the collection”inventoryarray” with “tags” in red and
black
db.inventoryarray.find( { tags: ["red", "black"] } );
To find tags in “red”
db.inventoryarray.find( { tags: "red" } );
All documents where array dim_cm contains at least one element whose value is greater than 25.
db.inventoryarray.find( { dim_cm: { $gt: 25 } } );
dim_cm array that contains at least one element that is both greater than ($gt) 22 and less than ($lt) 30:
db.inventoryarray.find( { dim_cm: { $elemMatch: { $gt: 22, $lt: 30 } } } );
Query an Array by Array Length: $size operator the following selects documents where the array tags has 3 elements.
db.inventory.find( { "tags": { $size: 3 } } );
Query for an Element by the Array Index Position
Using dot notation, you can specify query conditions for an element at a particular
index or position of the array. The array uses zero-based indexing.When querying
using dot notation, the field and nested field must be inside quotation marks.
All documents where the second element in the array dim_cm is greater than 25:
db.inventoryarray.find( { "dim_cm.1": { $gt: 25 } } );
8.Using the AND and OR Operator
It finds the status A& D documents in the collection
db.inventory.find( { status: { $in: [ "A", "D" ] } } );
It finds the documents with status A and qty less than 30
db.inventory.find( { status: "A", qty: { $lt: 30 } } );
It finds the documents with status A or qty less than 30
db.inventory.find( { $or: [ { status: "A" }, { qty: { $lt: 30 } } ] } );
