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open-source, high-performance,
schema-free, document-oriented
           database
RDBMS

• Great for many applications
• Shortcomings
 • Scalability
 • Availability
 • Flexibility
Key-value stores
CouchDB
JSON-style documents
Schema-free

• Loosening constraints - added flexibility
• Dynamically typed languages (RuPy!)
• Migrations
Dynamic queries

• Administration
• Ease of development
• Familiarity
Focus on performance
Replication
Auto-sharding
Many supported
platforms / languages
Good at

• The web
• Caching
• High volume data
• Scalability
Less good at

• Highly transactional
• Ad-hoc business intelligence
• Problems that require SQL
MongoDB Basics
Document

• Unit of storage (think row)
• BSON (Binary JSON)
• Represented as a dict / Hash
Collection

• Schema-free equivalent of a table
• Logical groups of documents
• Indexes are per-collection
_id

• Special key
• Present in all documents
• Unique across a Collection
• Any type you want
Blog back-end
Post

{“author”: “mike”,
 “date”: datetime.datetime.utcnow(),
 “text”: “my blog post...”,
 “tags”: [“mongodb”, “python”, “ruby”]}
Comment


{“author”: “eliot”,
 “date”: datetime.datetime.utcnow(),
 “text”: “great post!”}
New post

post = {“author”: “mike”,
        “date”: datetime.datetime.utcnow(),
        “text”: “my blog post...”,
        “tags”: [“mongodb”, “python”, “ruby”]}

post_id = db.posts.save(post)
Embedding a comment

c = {“author”: “eliot”,
     “date”: datetime.datetime.utcnow(),
     “text”: “great post!”}

db.posts.update({“_id”: post_id},
                {“$push”: {“comments”: c}})
Posts by author


db.posts.find({“author”: “mike”})
Last 10 posts

query = db.posts.find()
          .sort(“date”, DESCENDING)
          .limit(10)

for post in query:
    print post[“text”]
Posts in the last week

last_week = datetime.datetime.utcnow() +
            datetime.timedelta(days=-7)

db.posts.find({“date”: {“$gt”: last_week}})
Posts ending with
              ‘RuPy’


db.posts.find({“text”: re.compile(“RuPy$”)})
Posts with a tag
db.posts.find({“tags”: “mongodb”})




          ... and fast
db.posts.create_index(“tags”)
Counting posts


db.posts.count()

db.posts.find({“author”: “mike”}).count()
Basic paging

page = 2
page_size = 15

db.posts.find().limit(page_size)
               .skip(page * page_size)
Migration: adding titles
  • Easy - just start adding them:
post = {“author”: “mike”,
        “date”: datetime.datetime.utcnow(),
        “text”: “another blog post...”,
        “tags”: [“conference”, “rupy”],
        “title”: “Review from RuPy”}

post_id = db.posts.save(post)
Advanced queries

    • $gt, $lt, $gte, $lte, $ne, $all, $in, $nin
    • where()
db.posts.find().where(“this.author==‘mike’ ||
                         this.title==‘hello’”)
    • group()
Other cool stuff
• Aggregation and map reduce
• Capped collections
• Unique indexes
• Mongo shell
• GridFS
• MongoKit, Mongoid, MongoMapper, etc.
Sharding
Terminology
• Shard key
• Chunk
 • Range of the value space
 • (collection, key, min_val, max_val)
• Shard
 • Single node (or replica pair)
 • Responsible for set of chunks
client
mongos


client
Shards

mongod   mongod    mongod
                            ...
mongod   mongod    mongod




         mongos


          client
Shards

mongod   mongod    mongod
                            ...
mongod   mongod    mongod




         mongos    mongos ...


          client
Shards

          mongod   mongod    mongod
                                      ...
Config     mongod   mongod    mongod
Servers

mongod

mongod

mongod             mongos    mongos ...


                    client
• Download MongoDB
  http://www.mongodb.org

• Try it out
• Let us know what you think!

• Oh, and get stickers!
• http://www.mongodb.org
• irc.freenode.net#mongodb
• mongodb-user on google groups
• @mongodb, @mdirolf
• mike@10gen.com
• http://www.slideshare.net/mdirolf

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MongoDB at RuPy

Editor's Notes

  1. Order Preserving Partitioning Split Migrate
  2. Server Layout
  3. blog post twitter