Your SlideShare is downloading. ×
Redis Beyond
Upcoming SlideShare
Loading in...5

Thanks for flagging this SlideShare!

Oops! An error has occurred.


Introducing the official SlideShare app

Stunning, full-screen experience for iPhone and Android

Text the download link to your phone

Standard text messaging rates apply

Redis Beyond


Published on

Published in: Education

  • Be the first to comment

  • Be the first to like this

No Downloads
Total Views
On Slideshare
From Embeds
Number of Embeds
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

No notes for slide


  • 1. + Redis {beyond the basics} Presented by Steph ☺
  • 2. + Outline ■  Revisiting Redis ■  Keeping data safe ■  ■  Replication ■  Replacing Failed Master ■  ■  Persistence Transaction Reducing memory use ■  ■  Intlist ■  ■  Ziplist Sharding Scaling
  • 3. + Redis ■  In-memory remote database ■  Advanced key-value store ■  Data-structure server ■  Offers ■  High Performance ■  Replication ■  Unique data model
  • 4. + Snapshotting {Persistence} ■  Data is taken as it exists and is written to the disk ■  Point-in-time copy of in-memory data ■  Backup & transfer to other server ■  Written to file in “dbfilename” stored in “dir” ■  Until next snapshot is taken, last snapshot can be lost if redis crashes
  • 5. + Snapshotting {Persistence} Initiating Snapshots ■  ■  ■  ■  ■  bgsave SAVE Save lines save 60 10000 SHUTDOWN / TERM SYNC
  • 6. + Snapshotting ■  How often to perform an automatic snapshot ■  Accept writes on failure ■  Snapshot ■  What compression to name the snapshot on the disk
  • 7. + Append Only File (AOF) {Persistence} ■  Copies incoming write commands as it happens ■  Records data changes at the end of the backup file ■  Data set could be recovered with replaying AOF ■  “append only yes” ■  “appendfsyc always” ■  Limited by disk performance
  • 8. + Append Only File (AOF) ■  Option to use AOF ■  Occurrence ■  Option of sync writes to disk to sync during AOF compaction ■  Occurrence of AOF compaction
  • 9. + Replication ■  Method where other servers receive an updated copy of the data as its being written ■  Replicas can service read queries ■  Single master database sends writes out to multiple slave databases ■  Set operations can take seconds to finish
  • 10. + Replication ■  Configuring ■  On for replication master, ensure that the path and filename are writable by redis process ■  Enable slaving : slaveof host port ■  In a running system, redis can be stopped slaving or connect to a different master ■  New / Transfer connection: slaveof host port ■  Stop data update: SLAVEOF no one
  • 11. + Replication {SLAVE to MASTER Connection}
  • 12. + Replication {Redis Master-Slave Replica Tree}
  • 13. + Replacing Failed Master {Scenario and Solution} ■  What will we do in case of system failure? ■  Scenario ■  ■  ■  Machine A – Redis Master, Machine B – Redis Slave Machine A loses network connectivity Machine C has Redis, but no copy of data ■  Solution A ■  Make a fresh snapshot using Machine B using SAVE Copy snapshot to Machine C Start Redis on Machine C ■  Tell Machine B to be a slave of Machine C ■  ■ 
  • 14. + Replacing Failed Master {Sequence of Commands}
  • 15. + Replacing Failed Master {Scenario and Solution} ■  What will we do in case of system failure? ■  Solution ■  ■  ■  ■  B Use Machine B (Slave) as Master Create a new Slave (maybe Machine C) Update client configuration to read/write to proper servers (optional) update server configuration if restart is needed
  • 16. + Transactions ■  Begin transaction with MULTI ■  Execute commands with EXEC ■  Delayed execution with multi/exec can improve performance ■  ■  Holds off sending commands until all of them are known When all of the commands are known, MULTI is sent by client
  • 17. + Transactions ■  Pipelining ■  ■  ■  Send multiple commands at once Wait for all replies Reduces number of network roundtrips that the client waits for
  • 18. + Reducing Memory Use {Short Structures} ■  Method of reducing memory use ■  Ziplist – compact storage and unstructured representation of LISTs HASHes and ZSETs ■  Intset – compact representation of SET ■  As structures grow beyond limits, they are converted back to their original data structure type ■  Manipulating compact versions can become slow as they grow
  • 19. + Ziplist ■  Basic configuration for the 3 data types are similar ■  *-max-ziplist-value – max number of items to be encoded as ziplist ■  If limits are exceeded, redis will convert the list/hash/zset into nonziplist structure
  • 20. + ZIPLIST - LIST
  • 21. + Intset
  • 22. + Sharded Structures ■  Sharding – takes data, partitions it to smaller pieces and sends data to different locations depending on which partition the data is assigned to ■  Sharding ■  Sharding LISTs – uses LUA scripting ZSETs – zset operations on shards violate how quickly zsets perform, sharding is not useful on zsets
  • 23. + Sharded Structures ■  Sharding ■  ■  ■  HASHes Method of partitioning data must be chosen Hash’s keys can be used as source of info for sharding To partition keys: ■  Calculate hash function on the key ■  Calculate number of shards needed depending on number of keys we want to fit in one shard and the total number of keys ■  Resulting number of shards along with hash value will be used to find out which shard we’ll use
  • 24. + Scaling {read capacity} ■  In using small structures, make sure max ziplist is not too large ■  Use structures that offer good performance for the types of queries we want to perform ■  Compress large data sent to redis for caching to reduce network reads and writes ■  Use pipelining and connection pooling
  • 25. + Scaling {read capacity} ■  Increase total read throughput using read only slave servers ■  ■  Always remember to WRITE TO THE MASTER Writing on SLAVE will cause an error ■  Redis ■  ■  ■  Sentinel Mode where redis server binary doesn’t act like the typical one Watches behavior and health of master(s) and slave(s) Intended to offer automated failover
  • 26. + Scaling {memory capacity} ■  Make sure to check all methods to reduce read data volume ■  Make sure larger pieces of unrelated functionality are moved to different servers ■  Aggregate writes in local memory before writing to redis ■  Consider using locks or LUA when limitations such as watch/multi/exec are encountered ■  When using AOF, keep in mind that the disk needs to keep up with the volume we’re writing
  • 27. + Scaling {write capability} ■  Presharding ■  ■  for growth Run multiple redis servers on your machine (listen on diff. ports) Use multiple redis database on your database server
  • 28. + Scaling {complex queries} ■  Scenario : machines have enough memory to hold index, but we need to execute more queries that server can handle ■  Use : SUNIONSTORE, SINTERSTORE, SDIFFSTORE, ZINTERSTORE, and/or ZUNIONSTORE ■  Since we “read” from slave, set : slave-read-only no
  • 29. + Reference ■  Carlson, Josiah. (2013) Redis in Action. Shelter Island, NY: Manning Publications
  • 30. + Thank You ☺