Beyond relational database - Building high performance websites using Redis and PHP

Hanoi PHP Day 2009December 19, 2009

Beyond relational database Building high performance websites using Redis and PHP

Pham Cong DinhSoftware DeveloperVega Corporation

Go beyond relational database

What I am talking about

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Relational database in our worldHigh performance web apps: new challengesRedis: A data structure storeIntroduction to some Redis's PHP clients


QuestionHow can we store our data?

AnswerRelational database

ACID is our loveAtomicity - all parts of a transaction succeed or none of then

succeed. Integrity.

Consistency - Nothing in your transaction will violate the rules of the database. Integrity.

Isolation - Each transaction operates independently of every other transaction.

Durability - Once the database says that data is committed there is no opportunity for that to be undone.

Part 1

Relational database in our world


Brewer's (CAP) TheoremC: Consistency - The client perceives that a set of

operations has occurred all at once.Strong consistency: ACID

A: Availability - Every operation must terminate in an intended response. Requests are to be served even when there is a partition in the cluster.

P: Partition tolerance - Operations will complete, even if individual components are unavailable.



BASE: An ACID Alternative Basically AvailableSoft stateEventually consistent.

Data partitioning and decision between Consistency and Availability.



Relational database in high performance environments

Google

Facebook

Wikipedia

Live Journal

Yahoo

FAILED?… but most companies does not need more

than a single database server

… but modern web apps today is facing a but modern web apps today is facing a real challengereal challenge



High performance web apps: new challenges

Web server is bottleneck

Part 2


Database is bottleneck



CPU is bottleneck



More requests: going distributed is easyApachePHP

Database scalability is hardStruggling with SMP: MySQLReplication is hard: replication is single threaded:

MySQLMost relational databases find hard to scale

WRITEsSchema constraintsDisk I/OMemory constraintsGlobal lockComplicated data types



Scaling for READ is easier for scaling for WRITE

E.x: Records inserted in 14h


mysql> select count(1) from setacc;

+----------+

| count(1) |

+----------+

| 3982438 |

+----------+

1 row in set (0.00 sec)

mysql> select count(1) from setacc_del;

+----------+

| count(1) |

+----------+

| 4003793 |

+----------+

1 row in set (0.00 sec)


Relational databases is SLOW in some speical cases

Alternatives but not drop-in solutionsDocument oriented databasesColumn-based databasesKey-value datastoresGraph databases



REDIS: A data structure datastore

Redis (REmote DIctionary Server)One of the hottest technologies in 2009

(Github)Network interface to language dependent

client library: Python, Java, Ruby, Erlang, C# …

Written in C, single process, single thread, event-based

Latest version: 1.1Can be found at http://code.google.com/p/redis/

Part 3


Redis is fast



In a most basic form, it is a key – value storeNot yet another Memcached

Not memory onlyNot immediately durableRedis VM (upcoming)Supports set of complicated data structureBuilt-in replication



Data can be partitioned using database conceptSELECT index



Key => ValueSET mykey myvalueGET mykeySETNX (atomic operation)More: MGET, MSET

Key or Value is binary safe



Redis supports manipulation on a list of values via LIST

Think of an ordered list with the operations you would expect: appending, indexed access, and access to a range of values

CommandRPUSH mylistkey stringLPUSH mylistkey stringLLEN mylistkeyLPOP mylistkeyRPOP mylistkeyMore: LGET/LSET ...



SET in Redis is an unordered collection with no duplicate membersSET commands

SADD mysetkey member

SREM mysetkey memberSMEMBERS mysetkey

Sorted SET: similar to SET but every member is attached with a score (floating number score)Sorted Set commands

ZADD key score member ZREM key memberZRANGE key start end



Use casesOperational dataPre-computed dataLoggingCacheMessage queue

Immediate data layer

Job server



Redis PHP clients

Owlient's phpredisCan be found at

http://github.com/owlient/phpredisC extensionSample

Class: RedisKey-value

$redis->get('key');$redis->set('key', 'value');$redis->incr('key1');

List$redis->lpush('key1', 'C');

Set$redis->sadd('key1' , 'set1');

Part 4

http://github.com/owlient/phpredis


Rediska: http://rediska.geometria-lab.net/Full Zend Framework integrationSample

Redis PHP clients

require_once 'Rediska/Key.php';

$key = new Rediska_Key('keyName');

// Set value

$key->setValue('hello');

// Get value

$key = new Rediska_Key('keyName');

$key->getValue(); #=> hello

http://rediska.geometria-lab.net/


Predis: http://github.com/nrk/predisPHP 5.3+ onlySupport PHP 5.3 namespace and functorSupport multiple Redis instances and

pipelining

Redis PHP clients

$redis = Predis\Client::create(

array('host' => '10.0.0.1', 'port' => 6379),

array('host' => '10.0.0.2', 'port' => 6379)

);

$replies = $redis->pipeline(function($pipe) {

for ($i = 0; $i < 1000; $i++) {

$pipe->set("key:$i", str_pad($i, 4, '0', 0));

$pipe->get("key:$i");

}

});

http://github.com/nrk/predis


Any question?

Phần 5

Beyond relational database - Building high performance websites using Redis and PHP

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