Speed up your Symfony2 application and build awesome features with Redis

SPEED UP YOUR SYMFONY2 APPLICATION AND BUILD AWESOME FEATURES WITH REDIS

HELLO WORLD • Ricard Clau, born and grown up in Barcelona • Server engineer at Another Place Productions • Symfony2 lover and PHP believer (sometimes…) • Open-source contributor, sometimes I give talks • Twitter @ricardclau / Gmail ricard.clau@gmail.com

AGENDA • REDIS introduction, data types and commands • Getting started with Redis in PHP / Symfony2 • Options out of the box in SncRedisBundle • Cookbooks implemented in Real World Applications • Sharding data and the new Redis Cluster

INTRODUCTION TO REDIS And some demystifications

WHAT IS REDIS? • REmote DIctionary Server • Created in 2009 by Salvatore Sanfilipo (@antirez) • Open source (https://github.com/antirez/redis) • Advanced in-memory key-value data-structure server • Part of the NoSQL movement, think back to structures!

ONLY IN-MEMORY? • Your data needs to fit in your memory • It has configurable persistence: RDB snapshots, AOF persistence logs, combine both or no persistence at all • Think like memcached on steroids with persistence • http://redis.io/topics/persistence • “Memory is the new disk, disk is the new tape”

INTERESTING FEATURES • Master-slave replication • Pipelining to improve performance • Transactions (kind of with MULTI ... EXEC) • Scripting with LUA (~stored procedures) • Iterators for Keyspaces and SETS and HASHES (>= 2.8) !

COMMANDS http://redis.io/commands

NO QUERIES •We communicate with Redis via commands • No indexes, no schemas, just structures under a key • Very good documentation and sandbox • All commands have their complexity documented

DATA TYPES • Strings (binary-safe) up to 512 Mb • Lists of elements sorted by insertion order (max 2^32 - 1) • Sets supporting unions, intersections and diffs (max 2^32 - 1) • Hashes key-value pairs (max 2^32 - 1) • Sorted sets automatically ordered by score (max 2^32 - 1) • HyperLogLog to compute cardinality of BIG sets (2^64)

STRINGS COMMANDS • GET, SET, STRLEN, APPEND • GETRANGE, SETRANGE • Bitmap operations: GETBIT, SETBIT, BITCOUNT • Counter operations: INCR, DECR, INCRBY, DECRBY • If the value is a number, Redis tries to store it efficiently

LISTS COMMANDS Key S1 S2 S3 … SN • Order of insertion matters • Easy to implement Queues and Stacks • RPUSH, LPUSH, RPOP, LPOP • Blocking versions BLPOP, BRPOP, BRPOPLPUSH with timeout

SETS COMMANDS Key S1 S5 S3 S2 S4 • Collection of unique unordered elements • SCARD (Size), SADD, SREM, SISMEMBER, SMEMBERS • Intersections, Unions and Diffs: SINTER, SUNION, SDIFF, SINTERSTORE, SUNIONSTORE, SDIFFSTORE • Iterators with SSCAN (Redis >= 2.8)

HASHES COMMANDS Key K1 V1 K2 V2 K3 V3 K4 V4 • Many key-value pairs under the same key • HSET, HGET, HGETALL, HLEN, HEXISTS • Counters HINCR, HINCRBY, HINCRBYFLOAT • Iterators with HSCAN (Redis >= 2.8)

SORTED SETS COMMANDS S4 - 1000 Key S2 - 20 S3 - 15 S1 - 0 • Collection of unique elements ordered by score • ZCARD (Size), ZADD, ZREM, ZSCORE • Ranking: ZRANGE, ZREVRANGE (optional WITHSCORES) • Iterators with ZSCAN (Redis >= 2.8)

HYPERLOGLOG COMMANDS • Counting unique things in massive data sets using a very small amount of memory • PFADD, PFCOUNT, PFMERGE • HyperLogLog has an standard error of 0.81% • PF prefix in honor of Philippe Flajolet

PHP CLIENTS • Predis (PHP) vs phpredis (PHP extension) • Predis is very mature, actively maintained, feature complete, extendable, composer friendly and supports all Redis versions • Phpredis is faster, but not always backwards compatible • Network latency is the biggest performance killer • http://redis.io/clients

EASY STEPS (I) $ composer require snc/redis-bundle 1.1.* $ composer require predis/predis 0.8.* or install the phpredis extension https://github.com/nicolasff/phpredis

EASY STEPS (II) Add the bundle to the Symfony2 kernel

EASY STEPS (III) Add some magic to your config.yml

EASY STEPS (IV) You can now use Redis as a Symfony2 service! ! In your controller extending SymfonyBundleFrameworkBundleControllerController.php

EASY STEPS (V) Or inject it to your services via your services.xml

REDIS-CLI AND MONITOR • Redis-cli to connect to a Redis instance • Experiment with http://redis.io/commands •With Monitor we can watch live activity!

SNCREDISBUNDLE So many options out of the box!

PHP SESSION SUPPORT ! TTL is the session lifetime, Redis expires it for you Session Locking implementation (not optimal) Added not so many months ago

LOCKING PROBLEM • Problem in heavy-write applications: 2 almost concurrent requests trying to update same records • Concurrent AJAX requests for the same user timeline R1read R1 R2 R2save R2read R1save R1 updates are lost!!!!!

DOCTRINE CACHING Implemented with SET / SETEX / GET Be careful with expirations! No expiring Possibly better use APC entities data (annotations / xml / yaml) RecordSets Setting TTL explicitly DQL parsing

MONOLOG (I) Implemented with LISTS using RPUSH Be careful with memory!

MONOLOG (II) And add a new monolog handler using the service Level recommended at least warning

SWIFTMAILER SPOOL Implemented with LISTS using RPUSH Serialized Swift_Mime_Messages in the list

COOKBOOKS From Real World applications

REDIS AS A QUEUE • Using Lists and LPUSH / RPOP instructions •We can have different languages accessing data • I used this to send OpenGraph requests to Facebook (REALLY slow API) with Python daemons • If you need some advanced message queuing features check RabbitMQ (@cakper last month´s talk) and others

REAL-TIME DASHBOARDS •We can use hashes to group many stats under one key • Most of the times we have counters: HINCRBY “stats" <key> <increment> • HMGET “stats” <key1> <key2> ... to retrieve values and HMSET “stats” “stat1” <value1> “stat2” <value2> to set them • HGETALL to get the full hash

LEADERBOARDS • Super-easy with Redis, heavy consuming with other systems • Each board with a single key, using sorted sets • ZINCRBY “rankXXX” <increment> <userId> • Top N ZREVRANGE “rankXXX” 0 N [WITHSCORES] • You can store several millions of members under 1 key

WHO IS ONLINE? (I) •We can use SETS to achieve it! • One set for every minute, SADD <minute> <userId> Time +1m +2m +3m 2 2 7 4 1 2 3 1 1 5 3 1 SUNION 1 2 3 5 7 4

WHO IS ONLINE? (II) • Online users == everyone active in the last N minutes • SUNION <now> <now-1> <now-2> ... • SUNIONSTORE “online” <now> <now-1> <now-2> ... • Number of users: SCARD “online” • Obtain online users with SMEMBERS “online”

FRIENDS ONLINE? • If we store user´s friends in a SET with key friends-<user-id> • Friends online: SINTERSTORE “friends-<userid>-online” “online” “friends-<userid>” ! ! 1 7 3 5 2 4 15 1 ! • Imagine how you would do it without Redis! 9 3 10 7 ONLINE FRIENDS-12 SINTER FRIENDS-12-ONLINE

SHARDING / CLUSTERING This is when it gets tricky…

NEEDS TO FIT IN MEMORY • Redis Cluster will be available in 3.0 (currently RC1) • Proxy servers: Twemproxy (also for memcached) • Client-side partitioning (supported in many clients) • Sharding strategies (range vs hash partitioning) • Presharding can help scaling horizontally

CONFIGS WARNING! ! The default behaviour is RandomDistributionStrategy! PHPRedis has a RedisArray class for client-side sharding but this is not supported yet in the bundle!

1-99999 100000-199999 200000-299999 300000-399999 id % 4 == 0 id % 4 == 1 id % 4 == 2 id % 4 == 3 Easy to predict scale Load not properly distributed Load distributed ok Fairly easy to reshard RANGE PARTITIONING May work in some cases, not a silver bullet

hash(key) % 4 == 0 hash(key) % 4 == 1 hash(key) % 4 == 2 hash(key) % 4 == 3 Distribution also depending on hash algorithm Complicated resharding HASH PARTITIONING Better distribution... but still issues If few keys, it also becomes useless HASH CRC16 CRC32 MD5 SHA1 MURMUR3 ! DIST MODULUS KETAMA

Many Redis instances in one PRESHARDING Maybe overengineered initial server ! When needed, just split it into more servers and you don´t need resharding!!! ! Be careful configuring memory limits

REDIS CLUSTER • Shards the dataset among N nodes • Has a responsive failover in order to survive certain failures (this was partially covered already with Sentinel) • Ability to reshard keys internally • Neither CP nor AP, eventually consistent, not very resistant to network partitions in some scenarios • Many disagree with some of the decisions and tradeoffs

FINAL THOUGHTS When and when not to consider Redis

REDIS IS PERFECT FOR... • Intensive read-write data applications • Temporary stored data • Data that fits in memory • Problems that fit Redis built-in data types • Predictability in performance needed

BUT IS NOT SUITABLE WHEN.. • Big data sets, archive data • Relational data (RDBMS are absolutely fine to scale) •We don´t know how we will access data • Reporting applications (no where clauses) • It gets tricky for distributed applications (replication, clustering) • ALWAYS choose the right tool for the job!

SPECIAL THANKS • Ronny López (@ronnylt) & Alonso Vidales (@alonsovidales) • Salvatore Sanfilippo (@antirez) • Henrik Westphal (https://github.com/snc) • Danielle Alessandri (https://github.com/nrk) • Nicolas Favre-Felix (https://github.com/nicolasff) • Of course, to all of you for being here today!

QUESTIONS? • Twitter: @ricardclau • E-mail: ricard.clau@gmail.com • Github: https://github.com/ricardclau • Blog about PHP and Symfony2: http://www.ricardclau.com

Speed up your Symfony2 application and build awesome features with Redis

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