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![CRUD Demo time
Ø
show dbs view existing databases
Ø
use test use database “test”
Ø
db.t.insert({name:’bob’,age:’30’}) insert 30 years bob
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db. t.insert({name:’alice’,gender:’female’}) insert lady alice
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db. t.find() list all documents in
collection t
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db. t.find({name:’bob’},{age:1}) find 1 year old bob
Ø
db. t.find().limit(1).skip(1) find the second document
Ø
db. t.find().sort({name:1}) sort the results with ascend
name
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db. t.find({$or:[{name:’bob’},{name:’tom’}]}) find bob or tom’s documents
Ø
db. t.update({name:’ bob’},{$set:{age:31}}, update all bob’s age to 31
Ø
false,true})
Ø
db.stats() database statistic
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db.getCollectionNames() collections under this db
Ø
db.t.ensureIndex({name:1}) create index on name
Ø
db.people.find({name:“bob"}).explain() explain plan step](https://image.slidesharecdn.com/mongopresentationconf-130621053950-phpapp02/85/Mongo-presentation-conf-5-320.jpg)
![MongoDB Sharding: Briefly
FROM:C TO:N
#Copy Index Definition from C
#Remove existing data in [min~max]
#Clone the data in[min~max] from C
#Ask C to replicate the changes
#Make sure my view is complete and lock
#Get the document’s DiskLoc for sharding
#Trigger the N to sharding in Pull mode
Sequence
#N commit
#Ask N to commit](https://image.slidesharecdn.com/mongopresentationconf-130621053950-phpapp02/85/Mongo-presentation-conf-10-320.jpg)
Uploaded byShridhar Joshi
Mongo presentation conf
MongoDB is an open source, scalable, high-performance, document-oriented NoSQL database that uses a schema-less JSON-style document model, supports master-slave replication and horizontal sharding to scale out, and provides basic CRUD operations and rich queries on document collections. The document demonstrates MongoDB's data structures, basic CRUD operations, indexing, querying, optimization, architecture including replication and sharding, and use cases.
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- 1.
- 2. What is MongoDB? Opensource, scalable, high-performance, document-oriented NoSQL Key-Value ased database. Features • JSON-style document –oriented storage with schema-less • B-tree index supported on any attribute • Log-based replication for Master/Slave and Replica Set • Auto-sharding architecture (via horizontal partition) scales to thousands of no • NoSQL-style query • Surprising updating behaviors • Map/Reduce support • GridFS specification for storing large files • Developed by 10gen with commercial support
- 3. Well/Less Well Suited Source:http://www.mongodb.org/display/DOCS/Use+Cases
- 4. Basic concepts inMongoDB NoSQL MongoDB Database Collection Document Field Index Cursor Relational DBMS Database Relation Tuple Column Index Cursor MongoDB Databases* Collections* Documents* Indexes* Fields* * means 0 or more objects Relational DBMS Databases* Relations* Columns* Indexes* Each document has its own fields and makes MongoDB schema- less.
- 5. CRUD Demo time Ø showdbs view existing databases Ø use test use database “test” Ø db.t.insert({name:’bob’,age:’30’}) insert 30 years bob Ø db. t.insert({name:’alice’,gender:’female’}) insert lady alice Ø db. t.find() list all documents in collection t Ø db. t.find({name:’bob’},{age:1}) find 1 year old bob Ø db. t.find().limit(1).skip(1) find the second document Ø db. t.find().sort({name:1}) sort the results with ascend name Ø db. t.find({$or:[{name:’bob’},{name:’tom’}]}) find bob or tom’s documents Ø db. t.update({name:’ bob’},{$set:{age:31}}, update all bob’s age to 31 Ø false,true}) Ø db.stats() database statistic Ø db.getCollectionNames() collections under this db Ø db.t.ensureIndex({name:1}) create index on name Ø db.people.find({name:“bob"}).explain() explain plan step
- 6. Query Optimization db.people.find({x:10,y:”foo”}) Index onx Index on y Collection people Index Scan Index Scan DiskLocation Scan
- 7. MongoDB Architecture Source: mongoDBReplication and Replica Set by Dwight Merriman 10gen
- 8. MongoDB Sharding ongoDB usestwo key operations to facilitate sharding - split and migrate. plit splits a chunk into two ranges; it is done to assure no one chunk is unusually la igrate moves a chunk (the data associated with a key range) to another shard. his is done as needed to rebalance. plit is an inexpensive metadata operation, while migrate is expensive as large amo data may be moving server to server. oth splits and migrates are performed automatically. ongoDB has a sub-system called Balancer, which monitors shards loads and move hunks around if it finds an imbalance. you add a new shard to the system, some chunks will eventually be moved to at shard to spread out the load. recently split chunk may be moved immediately to a new shard if the system edicts that future insertions will benefit from that move.
- 9.
- 10. MongoDB Sharding: Briefly FROM:CTO:N #Copy Index Definition from C #Remove existing data in [min~max] #Clone the data in[min~max] from C #Ask C to replicate the changes #Make sure my view is complete and lock #Get the document’s DiskLoc for sharding #Trigger the N to sharding in Pull mode Sequence #N commit #Ask N to commit
- 11. MongoDB Sharding: InDetails FROM TO Notice: The FROM can be updated/deleted during sharding and TO can catch up in step 4.
- 12.
- 13. MongoDB Replication: Pullmode Slave continuously pull the OpLog from Master.
- 14. Question Reference: 1: Source codedigest: http://www.cnblogs.com/daizhj/category/260889.html 2: Books http://www.mongodb.org/display/DOCS/Books 3: MongoDB offical website http://www.mongodb.com/