An Introduction to CouchDB (IPC11SE 2011-06-01)

AN INTRODUCTION TO COUCHDB

David Zülke

David Zuelke

http://en.wikipedia.org/wiki/File:München_Panorama.JPG

Founder

Lead Developer

@dzuelke

COUCHDB IN THREE SLIDES Full Of DIS IS SRS BSNS Bullet Points

COUCHDB STORES DOCUMENTS• CouchDB stores documents with arbitrary keys and values• Each document is identiﬁed by an ID and has a revision• Documents can have ﬁle attachments• Stored as JSON, so it’s easy to interface with

COUCHDB SPEAKS HTTP• CouchDB uses HTTP to communicate with clients & servers• That means scalability• That means a lot of kick ass stuff totally for free • Caching • Load Balancing • Content Negotiation

COUCHDB USES MVCC• Multiversion Concurrency Control• When updating, you must supply a revision number• Your change will be rejected if the revision is not the latest• All writes are serialized• No need for locks, but puts some responsibility on developers

THE DETAILSAn In-Depth Look At What Makes CouchDB Different

availability Do you know the partition CAP X theorem? toleranceconsistency

“So, CouchDB does not have consistency of CAP?”

“Booh, that means my data will be inconsistent. Fail!”

psssshhh

YOUR MOM IS INCONSISTENT

CouchDB is eventually consistent

When replicating, conﬂicting revisions will be marked as such

These conﬂicts can then be resolved (users, daemons,...)

and everything will be ﬁne o/

which brings us to...

REPLICATION• You can do Master-Master replication• Conﬂicts are detected and marked automatically• Conﬂicts are supposed to be resolved by applications • Or by users, who usually know best what to do!

CouchDB is Ground Computing

Imagine a world where every computer runs CouchDB

Ubuntu One already does, to sync bookmarks etc!

MAP/REDUCE

BASIC PRINCIPLE: MAPPER• The Mapper reads records and emits <key, value> pairs • Example: Apache access.log • Each line is a record • Extract client IP address and number of bytes transferred • Emit IP address as key, number of bytes as value• For hourly rotating logs, the job can be split across 24 nodes* * In pratice, it’s a lot smarter than that

BASIC PRINCIPLE: REDUCER•A Reducer is given a key and all values for this speciﬁc key • Even if there are many Mappers on many computers; the results are aggregated before they are handed to Reducers • Example: Apache access.log • The Reducer is called once for each client IP (that’s our key), with a list of values (transferred bytes) • We simply sum up the bytes to get the total trafﬁc per IP!

EXAMPLE OF MAPPED INPUT IP Bytes 212.122.174.13 18271 212.122.174.13 191726 212.122.174.13 198 74.119.8.111 91272 74.119.8.111 8371 212.122.174.13 43

REDUCER WILL RECEIVE THIS IP Bytes 18271 191726 212.122.174.13 198 43 91272 74.119.8.111 8371

AFTER REDUCTION IP Bytes212.122.174.13 210238 74.119.8.111 99643

COUCHDB INCREMENTAL MAPREDUCE

THE KEY DIFFERENCE• Maps and Reduces are incremental: • If one document changes, only that one document needs: • mapping • reduction • Then a few new reduce runs are performed to compute the ﬁnal result

MAPPER: DOCS BY TAGSfunction(doc) { if(doc.type == product) { (doc.tags || []).forEach(function(tag) { emit(tag, doc); }); }}

MAPREDUCE: COUNT TAGSfunction(doc) { if(doc.type == product) { (doc.tags || []).forEach(function(tag) { emit(tag, 1); }); }}function(key, values) { return sum(values);} built-in CouchDB function, very efficient_sum

BUT WAIT!There are no tables :(

so... how do you join data from related documents?

JOIN PRODUCTS WITH THEIR CATEGORIES function(doc) { if(doc.type == product) { emit([doc._id, 0], doc); emit([doc._id, 1], { _id: doc.category_id }); } } ["123", 0] {_id: "123", _rev: "5-‐a72", type: "product", "name": "Laser Beam"} ["123", 1] {_id: "est", _rev: "2-‐9af", type: "category", "name": "Evil Stuff"} ["817", 0] {_id: "817", _rev: "2-‐aa8", type: "product", "name": "Rocketship"} ["817", 1] {_id: "cst", _rev: "3-‐d8a", type: "category", "name": "Cool Stuff"} ["441", 0] {_id: "441", _rev: "19-‐fdf", type: "product", "name": "Sharks"} ["441", 1] {_id: "est", _rev: "2-‐9af", type: "category", "name": "Evil Stuff"}

JOIN CATEGORIES WITH ALL THEIR PRODUCTS function(doc) { if(doc.type == category) { emit([doc._id, 0], doc); } elseif(doc.type == product) { emit([doc.category_id, doc._id], doc); } }["est", 0] {_id: "est", _rev: "2-‐9af", type: "category", "name": "Evil Stuff"}["est", "123"] {_id: "123", _rev: "5-‐a72", type: "product", "name": "Laser Beam"}["est", "441"] {_id: "441", _rev: "19-‐fdf", type: "product", "name": "Sharks"}["cst", 0] {_id: "cst", _rev: "3-‐d8a", type: "category", "name": "Cool Stuff"}["cst", "817"] {_id: "817", _rev: "2-‐aa8", type: "product", "name": "Rocketship"}

BUT... BUT... WAIT!How to guarantee a documents structure if it’s all schema-less?

VALIDATE DOCUMENTSfunction (newDoc, savedDoc, userCtx) { if(savedDoc && savedDoc.created_at != newDoc.created_at) { throw({forbidden: created_at is immutable}); } if(doc.type == product) { if(!doc.price) { throw({forbidden: product must have a price}); } }}

VALIDATE DOCUMENTSfunction (newDoc, savedDoc, userCtx) { function require(beTrue, message) { if(!beTrue) throw({forbidden: message}); } require(savedDoc && savedDoc.created_at != newDoc.created_at, created_at is immutable ); if(doc.type == product) { require(!doc.price, product must have a price ); }}

LUCENE INTEGRATIONFull Control Over What Is Indexed, And How

COUCHAPPPython Tool For Development And Deployment

DEMO TIMELet’s Relax On The Couch

!e End

FURTHER READING• http://guide.couchdb.org/• http://couchdb.apache.org/• http://github.com/couchapp/couchapp• http://github.com/rnewson/couchdb-lucene/• http://www.couchbase.com/downloads/• http://j.mp/oqbQs (E4X in CouchDB for XML parsing)

Questions?

THANK YOU! This was http://joind.in/3521 by @dzuelke

An Introduction to CouchDB (IPC11SE 2011-06-01)

by David Zuelke

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