Riding Redis @ask.fm
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RIDING REDIS @
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Transcript of Riding Redis @ask.fm
RIDING REDIS @
60M REGISTERED USERS
200M MONTHLY UNIQUE USERS
450M PAGEVIEWS A DAY
600 QUESTIONS / SECOND
20K REQUESTS / SECOND
50K LIKES / MINUTE
250K REGISTRATIONS / DAY
~600 SERVERS
~300 RUBY NODES
~50 JAVA NODES
~35 REDIS NODES
~90 MySQL NODES
COMPARISON
13B PAGEVIEWS 200M UNIQUE USERS 32M QUESTIONS ANSWERED
13B PAGEVIEWS* 300M UNIQUE USERS** 76.9M POSTS CREATED*
130B PAGEVIEWS*** N/A UNIQUE USERS 340M TWEETS CREATED***
_________________________________________________* http://www.tumblr.com/press** http://yahoo.tumblr.com/post/50902111638/tumblr-yahoo***http://en.wikipedia.org/wiki/Twitter
REDIS
Open-sourceKey-value databaseIn-memoryData-structure server
REDIS
Salvatore Sanfilippo@antirez
REDIS AUTHOR
TWITTERINSTAGRAMSTACK-OVERFLOWBLIZZARD
WHO IS USING REDIS?
6 SCENARIOS6 REDIS DATA-STRUCTURES
COUNTERS STRING
MESSAGES QUEUE LIST
USER ACTIVITY MATRIX HASH
FUNCTIONAL SWITCHES BIT OPERATIONS
THE WALL SORTED SET
REAL-TIME MONITORING PUB / SUB
Scenario 1 : Counters
GLOBAL COUNTERS
ACTIVE USERSQUESTIONS ASKED TODAY
LIKES TOTALLYREGISTRATIONS THIS MONTH
SELECT count(*) FROM users WHERE state='active';
NAIVE SOLUTION
REDIS STRING
MOST BASIC REDIS TYPEBINARY SAFEUP TO 512 MbOPERATIONS
INCR, DECR
@redis.incr "users/active/total"[email protected] "users/active/total"
users / active / total 61 771 480
users / inactive / total 6 943 366
EXAMPLE
USERS COUNTERS
@redis.incr "user/#{@user.id}/answers"[email protected] "user/#{@user.id}/likes"[email protected] "user/#{@user.id}/gifts"
user / :user_id/ answers 57
user / :user_id / likes 13 905
user / :user_id / gifts 27
EXAMPLE #2: USERS COUNTERS
COUNTERS CONSISTENCY
CONSISTENCY = 1 / PERFORMANCE
@redis.expire "user/#{@user.id}/inbox_questions", 1.day
SOLVED MOST CASES FOR US
REDIS TTL
SCALABILITY
@redis_shard_map = { 0 => Redis.new(:host=>"redis_host_0"), 1 => Redis.new(:host=>"redis_host_1"), ..., 7 => Redis.new(:host=>"redis_host_7")}
@redis = @redis_shard_map[@user.id % 8]@redis.incr "user/#{@user.id}/answers"
SCALABILITY (2)
Scenario 2 : Messages Queue
THIRD PARTY INTERACTION
RUBY BLOCKING MODEL
Resque to the rescue
https://github.com/resque/resque
REDIS-BACKED LIBRARY FOR● CREATING BACKGROUND JOBS
● PLACING THOSE JOBS ON MULTIPLE QUEUES● AND PROCESSING THEM LATER
RESQUE
REDIS LIST
SIMPLY LISTS OF STRINGSMAX LENGTH 232 - 1CONSTANT TIME INSERTIONOPERATIONS:
LPUSH, LPOP, RPUSH, RPOPLREM, LRANGE
WORKFLOW
Why Resque?
Resque.enqueue(PostToFacebookJob, "Hello world")
ADDING A NEW JOB
@redis.lpush 'queue:facebook', '{ "class":"PostToFacebookJob", "args":["Hello world"] }'
O(1)
COMPLEXITY
@redis.rpop "queue:facebook"O(1)
GETTING A JOB FROM QUEUE
Scenario 3 :User activity matrix
ROBOTSCRAWLERS
SPAM
TIME-BASED RESTRICTIONS
POSTASK A QUESTION
LOGINLIKE
GETPROFILE VIEW
USER ACTIONS
LIMIT ACTIVITYPER MINUTEPER HOURPER DAY
REQUIREMENTS
REDIS HASH
MAPS BETWEEN
STRING FIELDS AND VALUES
MAX PAIRS 232 - 1
OPERATIONS:HGET, HGETALLHSET, HDEL
LIKES QUESTIONS REQUESTS
user/:uid/date/:today/minute/:minute 12 3 27
user/:uid/date/:today/hour/:hour 34 15 113
user/:uid/date/:today/day/:day 158 22 529
STRUCTURE
def register_users_like!(user_id)minute = @redis.hincrby minute_key, 'like', 1hour = @redis.hincrby hour_key, 'like', 1day = @redis.hincrby day_key, 'like', 1
end
EXAMPLE: REGISTER ACTIVITY
def allowed_to_like_questions?(user_id)minute = @redis.hget minute_key, "likes"hour = @redis.hget hour_key, "likes"day = @redis.hget day_key, "likes"
return per_minute < LIKES_PER_MINUTE_THRESHOLD && per_hour < LIKES_PER_HOUR_THRESHOLD && per_day < LIKES_PER_DATE_THRESHOLD
end
EXAMPLE: ALLOWED?
@redis.expire per_minute_key, [email protected] per_hour_key, [email protected] per_day_key, 1.day
CLEANUP
SCALABILITY
SCALE BY USER_ID
DATEPHASE OF THE MOON
CONSISTENT HASHING
Scenario 4 :Functional switches
TURN ON/OFF ANY FEATURE ON SITE
REQUIREMENTS
PHOTO ANSWERSVIDEO ANSWERS
WALLSTREAM
DATABASE SHARDSSET POSTS PER PAGE
FUNCTIONALITY
BIT OPERATIONS
BIT OPERATIONSSETBIT, GETBITBITCOUNT
@redis.setbit common_settings_key, WALL_ENABLED, true
EXAMPLE
MASTER / SLAVE REPLICATION
SCALABILITY
Scenario 5 : The Wall
THE WALL
THE WALL
SHOW FRIENDS POSTS
INITIAL REQUIREMENT
SELECT * FROM questions q LEFT JOIN followships f ON (q.user_id = f.friend_id) WHERE f.user_id = :my_user_id ORDER BY q.answered_at LIMIT 0,25
SOLUTION
LATER REQUIREMENTS
LIKES INTRODUCEDSHOW RETWEETS
UNIQUENESS OF ANSWERSORDERED BY FIRST OCCURRENCE
PAGINATION NEEDEDDO NOT SHOW OWN POSTS
SHOW RETWEETS SINCE STARTED FOLLOWING A FRIENDS
MORE REQUIREMENTS
DO NOT SHOW RETWEETS IF ANSWERER OR RETWEETER IS DISABLED
SHOW LATEST FRIENDS WHO LIKED A QUESTION
OUR SOLUTION
IDEA
STORE SEPARATE SET OF QUESTIONS FOR EVERY USER
NON REPEATING COLLECTIONS OF STRINGS
EACH MEMBER ASSOCIATED WITH SCORE
QUICKLY ACCESSELEMENTS IN ORDERFAST EXISTENCE TESTFAST ACCESS TO ELEMENTS IN THE
MIDDLE
REDIS SORTED SET
user/:user_id/wallscore_1 score_2 ... score_N
question_id_1 question_id_2 ... question_id_N
score - timestamp, when the question_id first occurred in a set
STRUCTURE
● GET USERS WALL○ ZREVRANGEBYSCORE - O(log(N)+M)
● USER ANSWERED A QUESTION○ ZADD - O(log(N))
● LIKE○ ZRANK - O(log(N)) ○ ZADD - O(log(N))
● REMOVE ANSWER○ ZREM - O(M*log(N)
OPERATIONS
GUARANTEED 1000-1500 POSTS ON WALLPERIODICALLY CALL
ZCARDZREMRANGEBYRANK
CLEANUP
USER_ID
SHARDING
Scenario 6 :Real time monitoring
PATTERN DETECTION
REQUIREMENT
HUMAN vs MACHINE
MySQL TABLE PULL
INITIAL SOLUTION
PUBLISH / SUBSCRIBE MESSAGING PARADIGM
ALLOW PATTERN-MATCHING SUBSCRIPTIONS
OPERATIONS:SUBSCRIBE, UNSUBSCRIBEPUBLISH
REDIS PUB/SUB
SCHEMA
MODERATORS PANEL
Time complexity: O(N+M) where N is the number of clients subscribed to the receiving channel and M is the total number of subscribed patterns (by any client).
SCALING
So, why Redis?
SIMPLEFAST
FLEXIBLEROBUST
FREE
WHY REDIS?
CLUSTERING
WHAT'S MISSING
Not covered?
SETSLUA SCRIPTINGTRANSACTIONS
PIPELINED
NOT COVERED
JAVA
Questions
