Mongodb introduction and_internal(simple)


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Mongodb introduction and_internal(simple)

  1. 1. MongoDBIntroduction and Internalby Kai Zhao
  2. 2. What is MongoDB?•Open source, scalable, high-performance, document-oriented NoSQL Key-Value based 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 nodes •NoSQL-style query •Surprising updating behaviors •Map/Reduce support •GridFS specification for storing large files •Developed by 10gen with commercial support
  3. 3. Well/Less Well Suited Source:
  4. 4. Basic concepts in MongoDB MongoDB Relational DBMS Databases* Databases* Collections* Relations* Documents* Indexes* Columns* Indexes* Fields* NoSQL MongoDB Relational DBMS Each document has its own fields and Database Database makes MongoDB schema-less. Collection Relation Document Tuple Field Column Index Index Cursor Cursor* means 0 or more objects
  5. 5. CRUD Demo time show dbs view existing databases use test use database “test” db.t.insert({name:’bob’,age:’30’}) insert 30 years bob db. t.insert({name:’alice’,gender:’female’}) insert lady alice db. t.find() list all documents in collection t db. t.find({name:’bob’},{age:1}) find 1 year old bob db. t.find().limit(1).skip(1) find the second document db. t.find().sort({name:1}) sort the results with ascend name db. t.find({$or:[{name:’bob’},{name:’tom’}]}) find bob or tom’s documents db. t.update({name:’ bob’},{$set:{age:31}}, update all bob’s age to 31 false,true}) db.stats() database statistic db.getCollectionNames() collections under this db db.t.ensureIndex({name:1}) create index on name db.people.find({name:“bob"}).explain() explain plan step
  6. 6. Query Optimizationdb.people.find({x:10,y:”foo”}) Collection people DiskLocation Scan Index on x Index Scan Index on y Index Scan
  7. 7. MongoDB Architecture Source: mongoDB Replication and Replica Set by Dwight Merriman 10gen
  8. 8. MongoDB ShardingMongoDB uses two key operations to facilitate sharding - split and migrate.Split splits a chunk into two ranges; it is done to assure no one chunk is unusually large.Migrate moves a chunk (the data associated with a key range) to another shard.This is done as needed to rebalance.Split is an inexpensive metadata operation, while migrate is expensive as large amountsof data may be moving server to server.Both splits and migrates are performed automatically.MongoDB has a sub-system called Balancer, which monitors shards loads and moveschunks around if it finds an imbalance.If you add a new shard to the system, some chunks will eventually be moved tothat shard to spread out the load.A recently split chunk may be moved immediately to a new shard if the systempredicts that future insertions will benefit from that move.
  9. 9. MongoDBShardingPull mode
  10. 10. MongoDB Sharding: Briefly Sequence FROM:C TO:N #Make sure my view is complete and lock #Get the document’s DiskLoc for sharding #Trigger the N to sharding in Pull mode #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 #Ask N to commit #N commit
  11. 11. MongoDB Sharding: In Details FROM TO Notice: The FROM can be updated/deleted during sharding and TO can catch up in step 4.
  12. 12. Replication and ShardingSource:
  13. 13. MongoDB Replication: Pull modeSlave continuously pull the OpLog from Master.
  14. 14. QuestionReference:1: Source code digest: Books MongoDB offical website