MongoDB Knowledge share
Download as PPTX, PDF0 likes269 views
This document provides an overview of MongoDB including what MongoDB is, its advantages over SQL databases, different types of NoSQL databases, and basic CRUD operations in MongoDB using examples. Key points covered include MongoDB being a document-based and schema-less database, its advantages like scalability and flexibility with semi-structured data, the four main types of NoSQL databases, and examples of insert, find, update, and remove operations in MongoDB.
![SQL Insert Statement MongoDB Insert Statement
INSERT INTO users(user_id, age, status) VALUES
("bcd001", 45, "A")
db.users.insert( { user_id: "bcd001", age: 45, status: "A"
} )
SQL SELECT Statements MongoDB Find() Statements
SELECT * FROM users; db.users.find();
SELECT id, user_id, status FROM users; b.users.find( { }, { user_id: 1, status: 1 } ) ;
SELECT user_id, status FROM users; db.users.find( { }, { user_id: 1, status: 1, _id: 0 } );
SELECT * FROM users WHERE status = "A" db.users.find( { status: "A" } )
SELECT user_id, status FROM users WHERE status =
"A"
db.users.find( { status: "A" }, { user_id: 1, status: 1, _id:
0 } )
SELECT * FROM users WHERE status != "A" db.users.find( { status: { $ne: "A" } } )
SELECT * FROM users WHERE status = "A" AND age
= 50
db.users.find( { status: "A", age: 50 } )
SELECT * FROM users WHERE status = "A" OR age
= 50
db.users.find( { $or: [ { status: "A" } , { age: 50 } ] } )
SELECT * FROM users WHERE age > 25 db.users.find( { age: { $gt: 25 } } )
SELECT * FROM users WHERE age < 25 db.users.find( { age: { $lt: 25 } } )](https://image.slidesharecdn.com/mongodbkbshare-161010075529/85/MongoDB-Knowledge-share-14-320.jpg)
![Let’s see CRUD,find,Sort Operations with me
Use EmployeeDB;//Create the databae(EmployeeDB) using “use” command
db.Employee.insert({
Employeeid:1,
EmployeeName:”Jone Smith”,
PhoneNo:{HandPhone:099562365412,HomePhone:0126541230,OfficePhone:01652315}
});//Create a collection(Employee) using insert() command
Var objemp=[{
Employeeid:2,
EmployeeName:”Marry”},
{
Employeeid:3,
EmployeeName:”Steave:},
{Employeeid:4
EmployeeName:”akog02”}];
db.Employee.insert(objemp);//Adding an array of documents using insert() command](https://image.slidesharecdn.com/mongodbkbshare-161010075529/85/MongoDB-Knowledge-share-21-320.jpg)
![db.Employee.find().limit(2).forEach(printjson);
db.Empooyee.find().sort({Employeeid:-1}).forEach(printjson);//Sort by the descending order of Employee id
db.Employee.count();
db.Employee.remove({Employeeid:1});
db.Employee.find({
$or:[{Employeeid:2},{EmployeeName:”Jone Smith”}
]
});//OR Operator
db.Employee.find(
{
Employeeid:1,EmployeeName:”Jone Smith”
});// AND Operator
db.Employee.find({},Employeeid:1);//only show the Employee id BSON DOC
db.Employee.find({Employeeid /2/});// same LIKE Operator in RDBMS
db.Employee.find().limit(10);
db.Employee.find().skip(2).limit(1);
// specify the search criteria
db.Employee.find({EmployeeName:{$regx:”jon”}}).forEach(printjson); or
db.Employee.find({EmployeeName:{$regx:”jon”}}).pretty();
//specify the extrace text match
db.Employee.find({EmployeeName:{$regx:”^jon$”}}).pretty();](https://image.slidesharecdn.com/mongodbkbshare-161010075529/85/MongoDB-Knowledge-share-23-320.jpg)
MongoDB Knowledge share
- 1. { Knowledge Sharing:”MongoDB”, BY: “Mg Kyaing(PID department)” }
- 2. Agenda
- 3. What is NoSQL? Schema-less Capability to handle semi-structured, and unstructured data No need of ORM Agility Ease of scale-out High Availability
- 4. SQL vs NoSQL: High-Level Differences SQL databases are primarily called as Relational Databases (RDBMS); whereas NoSQL database are primarily called as non-relational or distributed database. SQL databases are table based databases whereas NoSQL databases are document based, key-value pairs, graph databases or wide-column stores. SQL databases have predefined schema whereas NoSQL databases have dynamic schema for unstructured data. SQL databases are vertically scalable whereas the NoSQL databases are horizontally scalable. SQL databases are scaled by increasing the horse-power of the hardware. NoSQL databases are scaled by increasing the databases servers in the pool of resources to reduce the load. SQL databases uses SQL ( structured query language ) for defining and manipulating the data, which is very powerful. In NoSQL database, queries are focused on collection of documents. Sometimes it is also called as UnQL (Unstructured Query Language). The syntax of using UnQL varies from database to database.
- 5. For complex queries: SQL databases are good fit for the complex query intensive environment whereas NoSQL databases are not good fit for complex queries. For the type of data to be stored: SQL databases are not best fit for hierarchical data storage. But, NoSQL database fits better for the hierarchical data storage as it follows the key-value pair way of storing data similar to JSON data. NoSQL database are highly preferred for large data set (i.e for big data). For scalability: In most typical situations, SQL databases are vertically scalable. You can manage increasing load by increasing the CPU, RAM, SSD, etc, on a single server. On the other hand, NoSQL databases are horizontally scalable. For properties: SQL databases emphasizes on ACID properties ( Atomicity, Consistency, Isolation and Durability) whereas the NoSQL database follows the Brewers CAP theorem ( Consistency, Availability and Partition tolerance ) SQL vs NoSQL: High-Level Differences
- 6. NOSQL:4 TYPE OF NOSQL DATABASES Key-Value pair Documents Column family Graph
- 7. Key/ Value Column - Family Graph Document AVAILABLE DBMS
- 8. What is MongoDB? MongoDB (from "humongous")is a document-based open-source database. MongoDB is a leading NoSQL database. It provides high performance, high availability, auto sharding and automatic scaling. MongoDB database is written mainly in C++ . It's drivers and client libraries are typically written in their respective languages, although some drivers use C extensions for better performance. MongoDB differs from relational databases because it is a schema-less database. Such databases usually have lower transaction safety but are faster in accessing data and scale better than relational databases. History of MongoDB MongoDB was developed in October 2007 by a New York based organization 10gen that is now called MongoDB Inc. It is written is C , C++ and JavaScript. MongoDB is developed as a Platform as a Service (PAAS) initially. In 2009 MongoDB was introduced as an open-source database server. MongoDB provides backend services to many websites and to other services. For examle, eBay, Foursquare , Viacom, Craigslist and the New York Times.
- 9. Advantages of MongoDB over RDBMS Schema less : MongoDB is document database in which one collection holds different different documents. Number of fields, content and size of the document can be differ from one document to another. Structure of a single object is clear No complex joins Deep query-ability. MongoDB supports dynamic queries on documents using a document-based query language that's nearly as powerful as SQL Tuning Ease of scale-out: MongoDB is easy to scale Conversion / mapping of application objects to database objects not needed Uses internal memory for storing the (windowed) working set, enabling faster access of data
- 10. Why should use MongoDB? Document Oriented Storage : Data is stored in the form of JSON style documents Index on any attribute Replication & High Availability Auto-Sharding Rich Queries Fast In-Place Updates Professional Support By MongoDB Where should use MongoDB? Big Data Content Management and Delivery Mobile and Social Infrastructure User Data Management Data Hub
- 11. SQL Terms/Concepts MongoDB Terms/Concepts Database Database Table Collection Row document or BSON document Column Field Index Index Table joins Embedded documents and linking Primary key Primary key Specify any unique column or column combination as primary key The primary key is automatically set to the _id field. The following table presents the various SQL terminology and concepts and the corresponding MongoDB terminology and concepts
- 12. MongoDB MySQL Oracle Informax DB2 Database Server Mongod Mysqld Oracle IDS DB2 Server Database Client Mongo Mysql Sqlplus DB-Access DB2 Client DataBase Server and Client between MySQL,Oracle,Informax,DB2
- 13. SQL Schema Statements MongoDB Schema Statements CREATE TABLE users ( id MEDIUMINT NOT NULL AUTO_INCREMENT, user_id Varchar(30), age Number, status char(1), PRIMARY KEY (id) ) Implicitly created on first insert() operation. The primary key _id is automatically added if _id field is not specified. db.users.insert( { user_id: "abc123", age: 55, status: "A" } ) ; However, you can also explicitly create a collection: db.createCollection("users") ; ALTER TABLE users ADD join_date DATETIME Collections do not describe or enforce the structure of its documents; i.e. there is no structural alteration at the collection level. However, at the document level, update() operations can add fields to existing documents using the $set operator. db.users.update( { }, { $set: { join_date: new Date() } }, { multi: true } ) ALTER TABLE users DROP COLUMN join_date Collections do not describe or enforce the structure of its documents; i.e. there is no structural alteration at the collection level. However, at the document level, update() operations can remove fields from documents using the $unset operator. db.users.update( { }, { $unset: { join_date: "" } }, { multi: true } ) CREATE INDEX idx_user_id_asc ON users(user_id) db.users.createIndex( { user_id: 1 } ) CREATE INDEX idx_user_id_asc_age_desc ON users(user_id, age DESC) db.users.createIndex( { user_id: 1, age: -1 } ) DROP TABLE users db.users.drop()
- 14. SQL Insert Statement MongoDB Insert Statement INSERT INTO users(user_id, age, status) VALUES ("bcd001", 45, "A") db.users.insert( { user_id: "bcd001", age: 45, status: "A" } ) SQL SELECT Statements MongoDB Find() Statements SELECT * FROM users; db.users.find(); SELECT id, user_id, status FROM users; b.users.find( { }, { user_id: 1, status: 1 } ) ; SELECT user_id, status FROM users; db.users.find( { }, { user_id: 1, status: 1, _id: 0 } ); SELECT * FROM users WHERE status = "A" db.users.find( { status: "A" } ) SELECT user_id, status FROM users WHERE status = "A" db.users.find( { status: "A" }, { user_id: 1, status: 1, _id: 0 } ) SELECT * FROM users WHERE status != "A" db.users.find( { status: { $ne: "A" } } ) SELECT * FROM users WHERE status = "A" AND age = 50 db.users.find( { status: "A", age: 50 } ) SELECT * FROM users WHERE status = "A" OR age = 50 db.users.find( { $or: [ { status: "A" } , { age: 50 } ] } ) SELECT * FROM users WHERE age > 25 db.users.find( { age: { $gt: 25 } } ) SELECT * FROM users WHERE age < 25 db.users.find( { age: { $lt: 25 } } )
- 15. SQL SELECT Statements MongoDB find() statements SELECT * FROM users WHERE age > 25 AND age <= 50 db.users.find( { age: { $gt: 25, $lte: 50 } } ) SELECT * FROM users WHERE user_id like "%bc%" db.users.find( { user_id: /bc/ } ) SELECT * FROM users WHERE user_id like "bc%" db.users.find( { user_id: /^bc/ } ) SELECT * FROM users WHERE status = "A" ORDER BY user_id ASC db.users.find( { status: "A" } ).sort( { user_id: 1 } ) SELECT * FROM users WHERE status = "A" ORDER BY user_id DESC db.users.find( { status: "A" } ).sort( { user_id: -1 } ) SELECT COUNT(*) FROM users db.users.count() or db.users.find().count() SELECT COUNT(user_id) FROM users db.users.count( { user_id: { $exists: true } } ) or db.users.find( { user_id: { $exists: true } } ).count() SELECT COUNT(*) FROM users WHERE age > 30 db.users.count( { age: { $gt: 30 } } ) or db.users.find( { age: { $gt: 30 } } ).count()
- 16. SQL SELECT Statements MongoDB find Statements SELECT DISTINCT(status) FROM users db.users.distinct( "status" ) SELECT * FROM users LIMIT 1 db.users.findOne() or db.users.find().limit(1) SELECT * FROM users LIMIT 5 SKIP 10 db.users.find().limit(5).skip(10) EXPLAIN SELECT * FROM users WHERE status = "A" db.users.find( { status: "A" } ).explain()
- 17. SQL UPDATE Statements MongoDB Update Statements UPDATE users SET status = "C" WHERE age > 25 db.users.update( { age: { $gt: 25 } }, { $set: { status: "C" } }, { multi: true } ) UPDATE users SET age = age + 3 WHERE status = "A" db.users.update( { status: "A" } , { $inc: { age: 3 } }, { multi: true } ) UPDATE users SET status=“D”,age=10 WHERE status=“A” db.users.update({status:”A”},{$set:{status:”D”,age:10} }); SQL DELETE Statements MongoDB remove Statements DELETE FROM users WHERE status = "D" db.users.remove( { status: "D" } ) DELETE FROM users db.users.remove({})
- 18. Type Number Alias Notes Double 1 “double” String 2 “String” Object 3 “object” Array 4 “array” Binary data 5 “binData” Undefined 6 “undefined” Deprecated Objectid 7 “objected” Boolean 8 “bool” Date 9 “date” Null 10 “null” Regular Expression 11 “regx” DBPointer 12 “dbPinter” JavaScript 13 “javascript” Symbol 14 “symbol” JavaScript(with scope) 15 “javascriptWithScope” 32-bit integer 16 “int” Timestamp 17 “timestamp” 64-bit integer 18 “long” Min Key -1 “minkey” Max Key 127 “maxkey” BSON supports the followng data types as values in documents. Each data type has a corresponding number and string alias that can be used with the $type operator to query documents by BSON type.
- 20. Access the mongo Shell And Command Helpers mongoDB Shell Methods db.collection.aggregate() Provides access to the aggregation pipeline db.collection.bulkWrite() Provides bulk write operation functionality. db.collection.count() Wraps count to return a count of the number of documents in a collection or matching a query. db.collection.copyTo() Deprecated. Wraps eval to copy data between collections in a single MongoDB instance db.collection.createIndex() Builds an index on a collection db.collection.dataSize() Returns the size of the collection. Wraps the size field in the output of the collStats db.colletion.deleteOne() Deletes a single document in a collection db.collection.deleteMany() Deletes multiple documents in a collection. db.collection.distinct() Returns an array of documents that have distinct values for the specified field db.collection.drop() Removes the specified collection from the database db.collection.dropIndex() Removes a specified index on a collection db.collection.dropIndexes() Removes all indexes on a collection And much and more ………………………………………………. Command Helpers help Show Help db.help() Show help for database method db.collection.help() Show help on collection methods Show dbs Print a list of all databases on Server Use <db> Switch current database Show collections Print a list of all collection for current db Show users Print a list of all users for current db. Show roles Print a list of all roles,both user-defined and built-in for current db Show profile Print the five most recent operations that took 1 millisecond or more Show.databases Print a list of all available databases db.Auth() If running in secure mode, authenticate the user db.cloneDatabase<host> Clone the current database from the <host> specified. The <host> database instance must be in noauth mode. db.repaireDatabase() Repair and compact the current database. This operation can be very slow on large databases db.copyDatabase(<from>, <to>, <host>) Copy the <from> database from the <host> to the <to> database on the current server And much and more ……………………………………….. https://docs.mongodb.com/manual/reference/method/
- 21. Let’s see CRUD,find,Sort Operations with me Use EmployeeDB;//Create the databae(EmployeeDB) using “use” command db.Employee.insert({ Employeeid:1, EmployeeName:”Jone Smith”, PhoneNo:{HandPhone:099562365412,HomePhone:0126541230,OfficePhone:01652315} });//Create a collection(Employee) using insert() command Var objemp=[{ Employeeid:2, EmployeeName:”Marry”}, { Employeeid:3, EmployeeName:”Steave:}, {Employeeid:4 EmployeeName:”akog02”}]; db.Employee.insert(objemp);//Adding an array of documents using insert() command
- 22. db.Employee.find().forEach(printjson); or db.Employee.find().pretty();//show the EmployeeCollection. ================================ db.Employee.find({});//show all of the EmployeeCollection. ================================ db.Employee.find({EmployeeName:”smith”}).foreach(printjson);//show by EmployeeName is Smith. ================================ db.Employe.find({Employeeid:{$gt:2}}).forEach(printjson);//show by Employeeid is greator than 2. ================================ var myEmployee = db.Employee.find( { Employeeid : { $gt:2 }}); while(myEmployee.hasNext()) { print(tojson(myCursor.next())); } =================================== db.Employee.update( {Employeeid:1}{$set:{EmployeeName:”David Jone”}} );//Update Document using update() =================================== db.Employee.update( {Employeeid:2},{$set:{EmployeeName:”Mory”,Employeeid:33}} );//Updating Multiple Values using update()
- 23. db.Employee.find().limit(2).forEach(printjson); db.Empooyee.find().sort({Employeeid:-1}).forEach(printjson);//Sort by the descending order of Employee id db.Employee.count(); db.Employee.remove({Employeeid:1}); db.Employee.find({ $or:[{Employeeid:2},{EmployeeName:”Jone Smith”} ] });//OR Operator db.Employee.find( { Employeeid:1,EmployeeName:”Jone Smith” });// AND Operator db.Employee.find({},Employeeid:1);//only show the Employee id BSON DOC db.Employee.find({Employeeid /2/});// same LIKE Operator in RDBMS db.Employee.find().limit(10); db.Employee.find().skip(2).limit(1); // specify the search criteria db.Employee.find({EmployeeName:{$regx:”jon”}}).forEach(printjson); or db.Employee.find({EmployeeName:{$regx:”jon”}}).pretty(); //specify the extrace text match db.Employee.find({EmployeeName:{$regx:”^jon$”}}).pretty();