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: Technology

  • Be the first to comment

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 compression ■ What 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 of sync writes to disk ■ Option 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 for replication On 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 loses network connectivity ■ ■ Machine A – Redis Master, Machine B – Redis Slave 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 non-ziplist 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 LISTs – uses LUA scripting ■ Sharding 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 ☺