$30 off During Our Annual Pro Sale. View Details »
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
RethinkDB Primer
Search
Marcelo Alves
April 09, 2015
Programming
2
150
RethinkDB Primer
A short introduction to RethinkDB
Marcelo Alves
April 09, 2015
Tweet
Share
Other Decks in Programming
See All in Programming
これならできる!個人開発のすゝめ
tinykitten
PRO
0
110
Rubyで鍛える仕組み化プロヂュース力
muryoimpl
0
120
dotfiles 式年遷宮 令和最新版
masawada
1
770
なあ兄弟、 余白の意味を考えてから UI実装してくれ!
ktcryomm
11
11k
宅宅自以為的浪漫:跟 AI 一起為自己辦的研討會寫一個售票系統
eddie
0
500
AtCoder Conference 2025「LLM時代のAHC」
imjk
2
480
【Streamlit x Snowflake】データ基盤からアプリ開発・AI活用まで、すべてをSnowflake内で実現
ayumu_yamaguchi
1
120
リリース時」テストから「デイリー実行」へ!開発マネージャが取り組んだ、レガシー自動テストのモダン化戦略
goataka
0
130
非同期処理の迷宮を抜ける: 初学者がつまづく構造的な原因
pd1xx
1
720
複数人でのCLI/Infrastructure as Codeの暮らしを良くする
shmokmt
5
2.3k
How Software Deployment tools have changed in the past 20 years
geshan
0
29k
UIデザインに役立つ 2025年の最新CSS / The Latest CSS for UI Design 2025
clockmaker
18
7.4k
Featured
See All Featured
Improving Core Web Vitals using Speculation Rules API
sergeychernyshev
21
1.3k
Put a Button on it: Removing Barriers to Going Fast.
kastner
60
4.1k
Six Lessons from altMBA
skipperchong
29
4.1k
What's in a price? How to price your products and services
michaelherold
246
13k
The Illustrated Children's Guide to Kubernetes
chrisshort
51
51k
Balancing Empowerment & Direction
lara
5
800
The Straight Up "How To Draw Better" Workshop
denniskardys
239
140k
Making Projects Easy
brettharned
120
6.5k
How Fast Is Fast Enough? [PerfNow 2025]
tammyeverts
3
390
Visualizing Your Data: Incorporating Mongo into Loggly Infrastructure
mongodb
48
9.8k
Building Better People: How to give real-time feedback that sticks.
wjessup
370
20k
4 Signs Your Business is Dying
shpigford
186
22k
Transcript
RethinkDB a primer
What is RethinkDB? An open-source distributed database built with .
"MongoDB with joins"
Features JSON data model Distributed joins, subqueries, aggregation and atomic
updates Hadoop-style map/reduce Friendly web and command-line administration tools Multi-datacenter replication and failover Sharding and replication Queries are automatically parallelized and distributed
Getting Started
Installation tyrion@kings-landing:~$ brew update tyrion@kings-landing:~$ brew install rethinkdb
Set Up tyrion@kings-landing:~$ rethinkdb
Web UI
Clustering tyrion@kings-landing:~$ rethinkdb create –d /tmp/db1 tyrion@kings-landing:~$ rethinkdb –j –d
/tmp/db1 --port-offset 1
Clustering
Clustering
Gem tyrion@kings-landing:~$ gem install rethinkdb [1] pry(main)> require "rethinkdb" [2]
pry(main)> include RethinkDB::Shortcuts [3] pry(main)> r.connect(host: 'localhost', database: 'marvel').repl()
Working with RethinkDB
Get All [1] pry(main)> r.table('characters').run
Get Document [1] pry(main)> r.table('characters').get(1).run
Filter [1] pry(main)> r.table('characters').filter({ age: 30 }).run
Update [1] pry(main)> r.table('characters').get(1).update({ age: 50}).run
Delete [1] pry(main)> r.table('characters').get(1).delete.run
ReQL
Principles 1. ReQL embeds into your programming language. 2. All
ReQL queries are chainable. 3. All queries execute on the server.
Embeds into your Language [1] pry(main)> require "rethinkdb" [2] pry(main)>
include RethinkDB::Shortcuts [3] pry(main)> r.connect(host: 'localhost', database: 'marvel').repl() [1] pry(main)> r.table('characters').get(1).delete.run
Chainable Queries [1] pry(main)> r.table('characters').run [2] pry(main)> r.table('characters').pluck('last_name').distinct().run [3] pry(main)>
r.table('characters').pluck('last_name').distinct().count().run
Server-Side Execution [1] pry(main)> query = r.table('characters').pluck('last_name').distinct [2] pry(main)> query.run
Examples
Filter + Contains [1] pry(main)> r.table('user').filter{|user| user['emails'].contains('
[email protected]
')}.run
Filter Dates [1] pry(main)> r.table("posts").filter{ |post| [2] pry(main)> post.during(r.time(2012, 1,
1, 'Z'), r.time(2013, 1, 1, 'Z')) [3] pry(main)> }.run
Filter + Pluck + Order + Limit [1] pry(main)> r.table('snippets').
[1] pry(main)* filter({lang: 'ruby'}). [1] pry(main)* pluck('id', 'title', 'created_at'). [1] pry(main)* order_by(r.desc('created_at')). [1] pry(main)* limit(10). [1] pry(main)* run()
Group + Merge [1] pry(main)> r.table('invoices').group( [1] pry(main)* [r.row['date'].year(), r.row['date'].month()]
[1] pry(main)* ).ungroup().merge( [1] pry(main)* {invoices: r.row['reduction'], month: r.row['group']} [1] pry(main)* ).without('reduction', 'group').order_by('month').run
Cool Features
Geospatial [1] pry(main)> point1 = r.point(-122.423246,37.779388) [2] pry(main)> point2 =
r.point(-117.220406,32.719464) [3] pry(main)> r.distance(point1, point2, {:unit => 'm'}).run [4] pry(main)> r.circle(point1, 2000).includes(point2).run
HTTP [1] pry(main)> r.table('comics').insert(r.http('http://foo.com/comics')).run
Changes [1] pry(main)> r.table('games').changes().run.each{|change| p change}
None