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Introduction Typical Implementation Tools
◦ Memcache, Redis◦ Varnish◦ HTML 5
Challenges
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A cache is a component that transparently stores data so that future requests for that data can be served faster
Speeds up the data lookups Wikipedia serves 75% content from Cache
Cache
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Hardware◦ CPU (L1, L2)◦ HDD (Read/Write Buffers)
Applications Database Proxies Web Servers Browsers
It is everywhere
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Cache Levels
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Populating the cache◦ Upfront Population◦ Lazy Population
Keeping the cache and source in sync◦ Time based Expiry◦ Active Expiry◦ Write through Cache
Managing cache size◦ Removing data
Consideration
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Populating the Cache
Upfront Population Lazy Population
No one-off cache read delay
The initial build of the cache takes time
Data cached may not be read at all
First request is not found in cache
Only caches data that is actually read
Has no cache build delay
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Time Based Expiry◦ Data is removed from cache after some time◦ Most commonly used◦ Short expiry time can be a problem
Active Expiry◦ Source tells cache to remove data when updated
or removed Write-through cache
◦ Allow read and write to cache◦ Data is added/written to source when written to
cache
Keeping in Sync
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Cache storage is smaller then original data Have to manage space smartly To make space for new data:
◦ Time based eviction◦ First in, first out (FIFO)◦ Least accessed◦ Least time between access◦ Many others (http://en.wikipedia.org/wiki/Cache_algorithms#Examples)
Managing Size
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Without Cache
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With Cache
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Update Cache
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Application◦ Objects◦ Arrays / Query results◦ String/HTML/ Full Page
Database◦ Query cache
Web Server◦ Static resources◦ Full page cache
Browser◦ Headers◦ HTML5
Cache Levels
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It is Free & Open Source Distributed memory based cache Key value store Easy to deploy Client libraries available in most of the
languages
Memcached
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Since 2003 Written in C Works on Linux, Windows Fast by default Security can be an issue
◦ Expose only to trusted network◦ Optional authentication
Memcached
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Memcached in Application
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Memcached Internals
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Issues with large implementations.◦ Large works are fine by default
No communication between Servers◦ No Data replication
Capacity issue of single Server No warm-up on startup Solution
◦ Mick-Router
Issues with Memcached
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Tool by Facebook Provides failover, Load balance, warm-up
server, replication of server How it works:
◦ https://code.facebook.com/posts/296442737213493/introducing-mcrouter-a-memcached-protocol-router-for-scaling-memcached-deployments/
Memcached Router
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Admin Interface
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Key-value cache Optionally a permanent Store
◦ Snapshotting◦ Log Based
Support a lot of Data Structures.◦ String, Lists (arrays), Sets (Unique), Hashes (Objects),
Sorted Sets, BitMaps, HyperLogLogs etc◦ http://redis.io/topics/data-types-intro
Lot more than just SET, GET and DEL◦ Increment, Append, LPUSH, RPOP, LRANGE◦ Pipelining (Send multiple commands in one go)◦ http://redis.io/commands
Redis
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Replication Client libraries available in most of the languages
◦ C, C#, PHP, Objective-C, Node.Js, Python, Ruby and more◦ http://redis.io/clients
Works on Windows◦ Windows port developed/maintained by Microsoft Open
Tech group Available on cloud
◦ AWS, Morpheus, RedisToGo, RackSpace, Microsoft Azure◦ Comes with a lot of preset like backup, monitoring, high
availability, ACL etc ◦ http://en.wikipedia.org/wiki/Redis#Cloud_deployment
Redis
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Performance◦ Has built-in benchmark, easy to run◦ It is easy to run test and find out real picture
◦ http://redis.io/topics/benchmarks Since 2009 Written in C
Redis
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Redis Memcached
Stores data in a variety of formats Complex to configure (Default
configuration can work) Pipelining! Multiple commands at
once Locking reads - will wait until
another process writes data to the cache
Mass insertion of data to prime a cache
Partitions data across multiple redis instances
Can back data to disk Pub/Sub feature
Doesn't do anything besides being an in-memory key/value store
Low complexity Simple to configure Few command macros
making it simple to master Runs like a rock Many years in production Every programming
language has a memcached library.
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A lot of bench marks available◦ http://oldblog.antirez.com/post/redis-memcached-
benchmark.html◦ http://dormando.livejournal.com/525147.html◦ http://oldblog.antirez.com/post/update-on-memca
ched-redis-benchmark.html
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NCache: Distributed Cache for .NET CouchDB: Can be used as replacement of
Memcache MemSQL: The Database for Speed, Scale &
Simplicity And a lot more
Other Tools
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Sits in front of web server(s)
Varnish
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Page cache Static File Cache Load Balancing Rewriting and redirecting URLs Varnish Configuration Language
◦ Powerful, Can manage rules, Modify headers Community/Enterprise Editions Becoming the default for specialized cloud
hosting◦ WP, Magento, Joom, Drupal etc
Varnish
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ESI◦ Useful for user customized dynamic content◦ Help increase TTL for pages◦ <esi:include src="/news/hot_news.html"/>
Works for Windows via CYGWIN◦ Can have IIS on backend
Stores cache in memory or file Paid edition has admin interface
◦ Real-time Statistics◦ Cache group management◦ Invalidations of cache etc
Varnish
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LiteSpeed: Provides cache, replacement for apache httpd, Load balancer etc
Apache Httpd: Mod Cache, Mod Mem Cache Nginx Cache
Others
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If cached properly:◦ Resources are not downloaded on next requests
Set “Expires” Header for Static Resources “304 Not Modified” Requests
◦ Involves http round trip but file is not downloaded
Browser
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Easy to implement Very effective Headers can be set on
◦ Application◦ Web Server
Browser
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Application Cache◦ manifest="demo.appcache“◦ Define files which are to be cached
CACHE MANIFEST NETWORK: Not to be cached FALLBACK: If page not available then fallback to
these◦ http://diveintohtml5.info/offline.html
HTML 5
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Which Data to Cache◦ Can’t cache every thing◦ Space is limited
Expiry Time◦ Have to be selective, too short or too long can be a problem
Multiple Cache backend◦ Use frame works so it is easy to Switch
Full Page / Parts◦ Based on needs and usage
Logged/Logged Out Users◦ ESI, Logged in user still has part which can be cached
Removing Data form cache◦ There must be a way to remove individual item
Key Scheme Monitor Hit/Miss
Challenges
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