學習地址：MongoDB 2014北京大會
第一章 MongoDB歡迎致辭及MongoDB簡介
General purpose
Document database
Open-source
Create Applications — Never Before Possible
MongoDB Business Value:
- Enabiling New Apps
- BetterCustomer Experience
- Faster Time to Marker
- Lower TCO
What we sell?
- MongoDB Enterprise Advanced
Management platform, advanced security, proactive support, and more. - MongoDB Management Service(MMS)
Automated deployment, upgrades, backup and monitoring in the cloud. - Production Support
Support for production deployments. - Development Support
Support, on-demand training and health check for teams in development. - Consulting
Packaged service offerings for critical points in the project lifecycle. - Training
Certification and training in development and ops - online & in-person.
THE LARGEST ECOSYSTEM
- 9,000,000+
MongoDB Downloads
- 250,000+
Online Education Registrants
- 35,000+
MongoDB User Group Members
- 40,000+
MongoDB Management Service(MMS) Users
- 600+
Technology and Services Partners
- 1,000+
Custormers Across All Industries
Document Level Locking
( Coming early 2015 )
pluggable : In-memory, RocksDB, TokuKV, FusionIO
What is the storage engine today?
MMAP & WiredTiger
Automation
第2章 MongoDB模式設計的藝術：該做的與不該做的
The Fine Art of Schema Design: Dos and Don’ts
(Matias Cas callares
Senior Solutions Architect, MongoB Inc.
[email protected])
RDBMs
- Relational databases are made up of tables
Tables are made up of rows:
- All rows have identical structure
- Each row has the same number of columns
- Every cell in a column stores the same type of data
MongoDB is a Document Oriented database
Document Model
- MongoDB is made up of collections
- Collections are composed of documents
- Each document is a set of key-value pairs
- No predefined schema
- Keys are always strings
- Values can be any(supported) data type
- Values can also be an array
- Values can also be a document
document inside documents
Benifits of these document model….?
Flexibility
- Each document can have different fields
- No need of long migrations, easier to be agile
- Common structure enforced at application level
Arrays
- Documents can have field with array values
- Ability to query and index array elements
- We can model relationships with no need of different tables or collections
Embedded documents
- Documents can have field with document values
- Ability to query and index nested documents
- Semantic closer to Object Oriented Programming
Relational Schema Design:
Focus on data storage.
Document Schema Design:
Focus on data usage.
SCHEMA DESIGN IS AN ART
A task tracking app
Requirement #1
“We need to store user information” like name, email and their addresses…yes they can have mort than one.”
—Bill, a project manager, contemporary
Requirement #2
“We have to be able to store tasks, assign them to users and track their progress…”
—Bill, a project manager, contemporary
Embedding tasks
- Tasks are unbounded items: initially we do not know how many tasks we are going to have
- A user along time can end with thousands of tasks
- Maximum document size in MongoDB: 16MB!
- It is harder to access task information without a user context
Array update operators
- pop
- push
- pull
- pullAll
Why is expensive to move a document?
We need to write the document in another locaion($$)
We need to mark the original position as free for new documents($)
- We need to update all those index entries pointing to the moved document to the new location($$$)
Considerations with arrays
- Limited number of items
- Avoid document movements
- Document movements can be delayed with padding factor
- Document movement can be mitigated with preallocation
RECIPE #4
USE DATA MODELS THAT MINIMIZE THE NEED FOR DOCUMENT GROWTH
RECIPE #5
DENORMALIZE TO AVOID APP-LEVEL JOINS
RECIPI #6
DENORMALIZE ONLY WHEN YOU HAVE A HIGH READ TO WRITE RATIO
Bucketing
What’s th idea?
- Reduce number of documents to be retrieved
- Less documents to retrieve mean less disk seeks
- Using arrays we can store more than one entity per document
- We group things that are accessed together