Download to read offline
![Document
BSON – Binary JSON.
{
"_id": " 34058 ",
"first_name" : "Ikram",
"last_name": "MANSERI",
"PreferredColors" : ["Black", "White"],
"address" : {"street": 2 , "city" : "Birkhadem"}
}
Fast Scannability
Data Types
Bsonspec.org](https://image.slidesharecdn.com/mongodb-180720102347/85/NoSQL-with-MongoDB-6-320.jpg)
![MongoDB
Schooling
DOC1
DOC2
DOC3
DOC4
DOC5
DOC6
DOC7
Students
{
"_id": " 34058 ",
"first_name" : "Ikram",
"last_name": "MANSERI",
"PreferredColors" : ["Black", "White"],
"address" : {"street": 2 , "city" : "Birkhadem"}
}
{
"_id": " 34059 ",
"first_name" : " Akram",
"last_name": " Beli",
"PreferredColors" : [« Brown", "White"],
"address" : {"street": 3 , "city" : "Birkhadem"}
" Parents_situations " : " divorced " }](https://image.slidesharecdn.com/mongodb-180720102347/85/NoSQL-with-MongoDB-8-320.jpg)
![Visualize the content of your collection « students »:
> db.students.find().pretty()
Insert multiple documents at once in your collection « students » :
> db.students.insert([{“first_name” : “yours”,
“last_name” : “yours”},
{“first_name”: “Amine”, “last_name” : “Ali”, “age”
: 45}])](https://image.slidesharecdn.com/mongodb-180720102347/85/NoSQL-with-MongoDB-13-320.jpg)
![CRUD Operations
> db.CollectionName.insert ({doc} / [{},{}],
…{writeConcern: {doc},
…ordered: true/false }
)](https://image.slidesharecdn.com/mongodb-180720102347/85/NoSQL-with-MongoDB-16-320.jpg)
![db.collection.ensureIndex({loc:”2dsphere”})
Geospatial indexes
db.collection.find({loc: {$near : {
geometry : {
{type : “Point”, coordinates : [2,3]},
spherique : true }
}
})](https://image.slidesharecdn.com/mongodb-180720102347/85/NoSQL-with-MongoDB-31-320.jpg)
More Related Content
Similar to NoSQL with MongoDB
NoSQL with MongoDB
- 1. MongoDB MANSERI Ikram 3CS –SIQ GDG Algiers Co-manager. Di_manseri@esi.dz
- 2. MongoDB is aDocument- Oriented NoSQL DBMS
- 3. DBMS DataBase Management System Software Managethe storage of your data. . CRUD Operations. Security, Availability, Concurrency Control, Consistency, Integrity to your data.
- 4. NoSQL Not Only SQL SQLNoSQL Schema-less.Predefined Schema Redundancy.Normalization (No redundancy). Scaling out (cluster-friendly).Scaling in. ACID principles. No ACID principles. No large data. Large data.
- 5.
- 6. Document BSON – BinaryJSON. { "_id": " 34058 ", "first_name" : "Ikram", "last_name": "MANSERI", "PreferredColors" : ["Black", "White"], "address" : {"street": 2 , "city" : "Birkhadem"} } Fast Scannability Data Types Bsonspec.org
- 7.
- 8. MongoDB Schooling DOC1 DOC2 DOC3 DOC4 DOC5 DOC6 DOC7 Students { "_id": " 34058", "first_name" : "Ikram", "last_name": "MANSERI", "PreferredColors" : ["Black", "White"], "address" : {"street": 2 , "city" : "Birkhadem"} } { "_id": " 34059 ", "first_name" : " Akram", "last_name": " Beli", "PreferredColors" : [« Brown", "White"], "address" : {"street": 3 , "city" : "Birkhadem"} " Parents_situations " : " divorced " }
- 9. Hands on ! -Initiate a connexion to MongoDB server. - CRUD Operations in MongoDB.
- 10. Hands on ! StartmongoDB instance (listener) : > mongod --port 27017 --dbpath C:datadb
- 11. Start mongoDB session: > mongo Visualize your databases: > show dbs Create new database called « scolarity » : > use schooling
- 12. Create a newcollection named « students » : > db.createCollection(“students”) Visualize the content of your collection « students »: > db.students.find() Create new document on your collection « students » : > db.students.insert({“first_name” : “yours”, “last_name” : “yours”})
- 13. Visualize the contentof your collection « students »: > db.students.find().pretty() Insert multiple documents at once in your collection « students » : > db.students.insert([{“first_name” : “yours”, “last_name” : “yours”}, {“first_name”: “Amine”, “last_name” : “Ali”, “age” : 45}])
- 14.
- 15.
- 16. CRUD Operations > db.CollectionName.insert({doc} / [{},{}], …{writeConcern: {doc}, …ordered: true/false } )
- 17. CRUD Operations > db.CollectionName.find({“field”:value},{“field”:0/1, “field”:0/1}) Document criteria Visualized fields
- 18.
- 19.
- 20. Di_manseri@esi.dz CRUD Operations Partial update >db.CollectionName.update({},{$cmd:{}},true/false,true/false) $set $unset $inc $push $pop + 50
- 21.
- 22. > mongoimport -cproducts -d prd --file Products.json Hands on !
- 23. CRUD Operations Increment term_yearsby 3, for all products of type : tv. > db.products.update({type:”tv”}, {$inc:{term_year:3}},false,true)
- 24. CRUD Operations find productswhich have term_years > 3. > db.products.find({term_years : {$gt : 3}})
- 25. CRUD Operations find productswhich have the field “limits” set. > db.products.find({limits : {$exists : true}})
- 26. CRUD Operations Insert aset of documents at once. > var bulk = db.products.initializeUnorderedBulkOp(); > bulk.insert({“name”:””, “type”:””}) > bulk.insert ({“name”:””, “type”:””}) > bulk.execute ()
- 27.
- 28. Great stuff aboutMongoDB Different type of Indexes. Replication. Sharding.
- 29. Indexes - Index bydefault : _id. - Compound indexes. - Unique Indexes. - Sparse indexes. - Geospatial indexes. - Text indexes … +2
- 30. Indexes Unique indexes : db.collection.ensureIndex({field:1,…},{unique:true}) Sparse indexes db.collection.ensureIndex({field:1,…}, {sparse:true})
- 31. db.collection.ensureIndex({loc:”2dsphere”}) Geospatial indexes db.collection.find({loc: {$near: { geometry : { {type : “Point”, coordinates : [2,3]}, spherique : true } } })
- 32. db.collection.find(phrase : “/word/”) Textindexes db.collection.ensureIndex({phrase : “text”}) db.collection.find({$text : {$search: “word”} })
- 33.
- 34. Explain plans &execution statistics How do I examine the performance of my query ? How can I know the indexes which have been used for my query ? > db.coll.explain().find({a:1}).sort({b:-1})
- 35. Replication Primary server Seconday serverSecondayserverSeconday server oplog Replica Set
- 36. Sharding My Data Shard 3Shard2Shard 1
- 37. Thank you! MANSERI Ikram 3CS– SIQ GDG Algiers Co-manager. Di_manseri@esi.dz
- 38. MANSERI Ikram 3CS –SIQ GDG Algiers Co-manager. Di_manseri@esi.dz
Editor's Notes
- #4 security, avalaibility, disaster recovery, integrity, Concurrency control, consistency.
- #5 Easy to scale !
- #8 Fast scannability : to skip fields that aren’t relevant to the request Data types : date data types (in Bson, not in JSON), BinData (like an image, UUID). Object_ID : JSON types : boolean, null, int, string, arrays, nested doc.
- #12 Speak about system databases.
- #17 Ordered = true (by default), all or nothing. Ordered = false, it can insert few of them. Write concern : add some constraintes to the request.
- #20 Full update, delete and insert Partial Update : only modify.
- #29 without indexes : iterate over all the documents that appear in the collection Btree indexes
- #30 Sparse : when we want to create an index over a field, which has a lot of null values
- #31 Geospecial indexes : for app who have some notions of Geospacial locality, supports 2 and 3 dimensional queries. For example, it can response to the query: the nearest coffee shop. Loc : [log, lat]
- #33 For example to search a word on a field that contains a phrase. We can define a text index over that field.
- #36 4 members, Replication factor = 4 Automatic failover : If the primary server goes down, another server will be elected to become the new primary server Writes are on the primary, reads may occure on secondaries = slaves . Every node has a priority, the node with the highest priority will be the primary node. ArbiterOnly : is a node dedicated to vote, it cannot vote for itself and it doesn’t have data on it. If priority = 0, the node would never be primary. Reasons behind replication : high availability and data safety (disaster recovery).
- #37 partitions