The document provides an agenda for a presentation on Redis, an in-memory data structure store. It discusses what Redis is, available clients, data types, operations on data types, performance, persistence, use cases, design considerations, adopters, and more. The presentation aims to familiarize the audience with Redis and its capabilities.

2. Redis – Memory is
the new Disk

3. 1. What isRedis
2. Available clients
3. Data types
4. Operations on data types
5. Performance
6. Persistence
7. Sweet spots
8. Design considerations / Bestpractices
9. Adopters
3
Agenda

4. ● Familiarity with NoSQL?
● Memcache?
● Redis?
4
Poll

5. Key/value store
like
Memcached onsteroids
5
What is Redis

6. In-memory
NoSQL database
backed bydisk
6
What is Redis

7. Collection of data structures exposed
over the network
7
What is Redis

8. NotjustStrings!
Keys can contain
Strings, Hashes, Lists, Sets and
Sorted Sets
8
What is Redis

9. What is Redis
9
“ Isee redis definitely more as a flexible tool than as a
solution specialized to solve a specific problem.
- SalvatoreSanfilippo

10. A Brief History of Redis
1
0
• Started in 2009 by SalvatoreSanfillipo
• VMWare hires Salvatore & Pieter Noordhuis
• Financially supported and promoted by VMWare

11. Redis Characteristics
10
• Issingle-threaded
• Has queryble keynamespace
• Isextremely fast (~100K operations/second)
• Iseasy to install (no dependencies)
• Issimple and flexible
• Stores everything inmemory
• Written in ANSI C and BSD licensed (free, open)

12. Language Support
12
Ruby, Python, PHP,Erlang,
Tcl, Perl, Lua, Java, Scala,
Clojure, C#, C/C++,
JavaScript/Node.js, Haskell,
IO,Go

13. Data Types
13
• Strings (Integers)
• Lists
• Hashes
• Sets
• Sorted Sets

14. Thinking in Redis
14
• Thisis not an RDBMS
• Itsall about the KEYS, and NOT the
values
• There is no querying onvalues
• There are no indexes
• There are no schemas

15. Operations on Strings/Integers
15
• SETkey value
• GETkey
• MGET/MSET
• INCR/DECR
• INCRBYDECRBY
• APPENDkey value
• SETNXkey value
• GETSETkey value

16. Installation
16
• $ wget
http://redis.googlecode.com/files/re
dis-2.4.2.tar.gz
• $ tar xzf redis-2.4.2.tar.gz
• $ cd redis-2.4.2
• $make
• $ ./src/redis-server

17. Atomicity of Commands
17
• All of the built-in commands of Redis are atomic
• Commands can be chained together (pipelined) to
create complex atomic transactions
• Redis is single threaded and therefore, no locking is
necessary
• In other words, commands like INCR won’t tread on
each other’s toes coming from multiple clients
simultaneously!

18. Key Expiration
18
• When caching, we don’t want things to live forever
• Any item in Redis can be made to expire after or at a
certain time
• EXPIREmy_key60
• EXPIREATmy_key 1293840000

19. Operations on Lists
19
• LPUSH/RPUSHkey value [value...]
• LPOP/RPOPkey
• LRANGEkey start stop
• LSETkey index value
• LLENkey
• LTRIMkey startstop
• LINSERTkey before|after pivot
value
• BLPOPkey [key ...] timeout
• LREMkey count value

20. Operations on Sets
20
SINTERkey [key ...]
SUNIONkey [key ...]
SISMEMBER key member
• SADDkey member
• SPOPkey
• SMEMBERSkey
•
•
•
• SCARD key

21. Operations on Sorted Sets
20
• ZADDkey score member [score]
[member]
• ZCARDkey
• ZCOUNTkey min max
• ZINCRBYkey increment member
• ZRANKkey member
• ZRANGEkey start stop [WITHSCORES]
• ZSCOREkey member

22. Operations on Hashes
22
HVALSkey
HLENkey
HEXISTSkey field
• HSETkey field value
• HGETkey field
• HKEYSkey
•
•
•
• HDELkey field [field ...]

23. Operations on Keys
23
EXPIREkey seconds
EXPIREATkey timestamp
EXISTSkey
• TYPEkey
• TTLkey
• KEYSpattern
•
•
•
• DELkey

24. Redis Administration Commands
24
DBSIZE
• MONITOR
• SAVE/BGSAVE
• INFO
•
•
•
FLUSHALL
CONFIG SETparameter value

25. Performance
25
We added two million items into a list in 1.28 seconds, with
a networking layer between us and the server
- SalvatoreSanfilippo,Creator

26. Performance
26
• Almost same for read and write, handles writes
faster than read
• 100 Kops/second
• Performance depends a lot on
Operation complexity
• Hardware
• Persistence configuration
•
•
•
Payload size
Batch size(pipelining)

27. Redis-benchmark
27

28. Demo
28
Key Expiry
• Redis CLI
• Getting Help
• Operations on Strings
•
•
•
Operations on Lists,Set
Groovy program operating on Sorted Set and
Hash
• MONITOR / INFO / DBSIZE/TYPE
• Redis benchmark

29. Data Durability
29
Dump data to disk after certain conditions are met
OR
Manually
AND/OR
Append Only File (AOF)

30. Advantages of Persistence
30
• On server restart, Redis re-populates its cache from files stored on
disk
• No issue of “cache warm-up”
• Itis possible to back-up and replicate the files/cache

31. Memory Requirements?
30
• Depends upon the payload size, and the data-type used
• Instagram reports that they stored 300 million key-value pairs in
about 5 GB of memory =>16 MB/million pairs (they also report that
Memcache requires 52 MB for the same million keys)

32. Sweet Spots / Use-cases
32
Most read / shared articles
Share state betweenprocesses / Session Tokens
Auto-completion
API rate limiting
Activity Feeds
Job Queue (LPUSH & RPOP)
• Cache Server
• Stats collection
• Tag Cloud
•
•
•
•
•
•
• URL Shortener mapping

33. Case Studies
33
• Video Marketing Platform
• Real-time analytics
• Stats for usage reports toclients
• Content Publishing application
• Tag Cloud
• Top Read Articles
• URL Shortening information
• Social Media Marketingapplication
• Daily, Monthly and overall stats collection
• List of online users

34. Design Considerations / Best Practices
34
Use consistent key namespace nomenclature
Have human readable keys
• Avoid excessively longkeys
•
•
• Since there is no querying on values, keys should be thought-out
before hand
• Store data based on use-cases. Ad-hoc queries can-be very
expensive
• Multiple databases are useful for segmenting key namespaces,
especially where key queries are needed

35. Design Considerations / Best Practices
35
• All datamust fit in memory
•
•
Data duplication/redundancy isOK
Persistence strategy should be chosen based on the kind of data
that you are storing and performance trade-off must be understood
• Good for write-heavy, frequently changing and non-relational data
• Polyglot-persistence isa smartchoice
• Start by using Redis to augment, and then replace

36. Some Adopters
36
Digg
• Stackoverflow
• Craiglist
• Github
•
•
•
Instagram
Blizzard Entertainment

37. Learning Resources
37
• http://redis.io/commands
•
•
http://try.redis-db.org
Redis CLI

38. Advanced Features
38
Pub /Sub
Transactions
Using multiple databases
Commands pipelining
Clustering / Sharding
• Master-slave replication
•
•
•
•
•
• LUA scripting

39. What is Redis
39
• Simple &Easytouse(Key / Value, data-types map toprogramming
Fast(100 Kops / second)
Powerful(data-types, operations on data-types)
Safe(persistence)
Easytouse(various client libraries)
languages)
• Flexible (Supports commonly used data-types
•
•
•
•
• Widely adopted (Digg, Craiglist, Github …)

40. Discussion
40
Now that you understand Redis and its capabilities, what use-cases do
come to your mind?
What are your concerns around usage of Redis?

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