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I wondered whether the simplicity of My SQL would be a liability when it came to trying to squeeze the last bit of performance out of the database. There are a like 4 thumbnails for each video so there are a lot more thumbnails than videos. - For more information on Big Table take a look at Google Architecture, Google Talk Architecture, and Big Table. The Early Years - Use My SQL to store meta data like users, tags, and descriptions. And that puts him in the position of being able to get more CPU immediately when and if the time comes. All outbound Data is Gzipped at a cost of only 30% CPU usage. A way around this would be to store session state in a database or in a shared file system. - If you call the database 20 times per page view you are screwed no matter what you do. If you don't have a lot of RAM and you do reads and writes you get paging involved which can hang your system for seconds. - One day it will work, but when your database doubles in size it won't work anymore. This architecture originated with the Digital Equipment Corporation VAXcluster in the early 1980s, and has been widely used by Sun Microsystems and Hewlett-Packard.

After doing some research, I found that by using a combination of Apache 2’s worker threads, Fast CGI, and a PHP accelerator, this was no longer a problem. Just have an agent that watches for changes, precalculates, and sends. Costs include bandwidth, hardware, and power consumption. Plenty Of Fish Architecture (983) Update: by Facebook standards Read/Write Web says POF is worth a cool one billion dollars. But that's not the most interesting part of the story. How are all these love connections made using so few resources? Unless the whole fact table fits in the aggregate memory of the cluster, sequential scans do not typically benefit from large amounts of cache.

The enterprise Java applications I had worked on were powered by expensive database software like Oracle, Informix, and DB2. Saw problems associated with serving a lot of small objects: - Lots of disk seeks and problems with inode caches and page caches at OS level. - With so many images setting up a new machine took over 24 hours. - Lower latency because it uses a distributed multilevel cache. You can't control hardware or make favorable networking agreements. Friendster Architecture (341) Friendster is one of the largest social network sites on the web. His learning curve of creating the system is what was most interesting. And using Server Iron allowed advanced functionality like bot blocking and load balancing based on passed on cookies, session data, and IP data. Because POF doesn't use the library it's relatively easy to track down performance problems. - If you are maxing the CPU you've either done something wrong or it's really really optimized. In a shared-disk architecture, there are a number of independent processor nodes, each with its own memory.

Database Cost Next I was worried about database costs. - A high number of requests/sec as web pages can display 60 thumbnails on page. Run into problems with multiprocesses mode because they would each keep a separate cache. Now they can customize everything and negotiate their own contracts. On a blog, for example, one might display entry titles in many places (e.g., a list of recent posts) but only ever display teasers or the full post bodies once on a given page. bookmarks uses symfony 8/2/2007 Slides Getting Rich with PHP 5 8/2/2007 Audio Getting Rich with PHP 5 8/2/2007 Blog Scaling Fast and Cheap - How We Built Flickr 8/2/2007 News Open source helps Flickr share photos 8/2/2007 Slides 41 Flickr and PHP 8/2/2007 Slides 30 Wikipedia: Cheap and explosive scaling with LAMP 8/2/2007 Blog You Tube Scalability Talk 8/2/2007 High Order Bit: Architecture for Humanity 8/2/2007 PDF Mysql and Web2.0 companies 8/3/2007 36 Building Highly Scalable Web Applications 8/3/2007 Introduction to hadoop 8/3/2007 webpage The Hadoop Distributed File System: Architecture and Design 8/3/2007 Interpreting the Data: Parallel Analysis with Sawzall 8/3/2007 PDF ODISSEA: A Peer-to-Peer Architecture for Scalable Web Search and Information Retrieval 8/3/2007 PDF SEDA: An Architecture for well conditioned scalable internet services 8/3/2007 PDF A scalable architecuture for Global web service hosting service 8/3/2007 Meed Hadoop 8/3/2007 Blog Yahoo’s Hadoop Support 8/3/2007 Blog Running Hadoop Map Reduce on Amazon EC2 and Amazon S3 8/3/2007 53m LH*RSP2P : A Scalable Distributed Data Structure for P2P Environment 8/3/2007 90m Scaling the Internet routing table with Locator/ID Separation Protocol (LISP) 8/3/2007 Hadoop Map/Reduce 8/3/2007 Slides Hadoop distributed file system 8/3/2007 Video 45m Brad Fitzpatrick - Behind the Scenes at Live Journal: Scaling Storytime 8/3/2007 Slides Inside Live Journal’s Backend (April 2004) 8/3/2007 Slides 25 How to scale 8/3/2007 36m Testing Oracle 10g RAC Scalability 8/3/2007 Slides 107 PHP & Performance 8/3/2007 Blog 1217 8/3/2007 45m SQL Performance Optimization 8/3/2007 80m Building_a_Scalable_Software_Security_Practice 8/3/2007 59m Building Large Systems at Google 8/3/2007 Scalable computing with Hadoop 8/3/2007 Slides 37 The Ebay architecture 8/3/2007 PDF Bigtable: A Distributed Storage System for Structured Data 8/3/2007 PDF Fault-Tolerant and scalable TCP splice and web server architecture 8/3/2007 Video Big Table: A Distributed Structured Storage System 8/3/2007 PDF Map Reduce: Simplified Data Processing on Large Clusters 8/3/2007 PDF Google Cluster architecture 8/3/2007 PDF Google File System 8/3/2007 Doc Implementing a Scalable Architecture 8/3/2007 News How linux saved Millions for Amazon 8/3/2007 Yahoo experience with hadoop 8/3/2007 Slides Scalable web application using Mysql and Java 8/3/2007 Slides Friendster: scalaing for 1 Billion Queries per day 8/3/2007 Blog Lightweight web servers 8/3/2007 PDF Mysql Scale out by application partitioning 8/3/2007 PDF Replication under scalable hashing: A family of algorithms for Scalable decentralized data distribution 8/3/2007 Product Clustered storage revolution 8/3/2007 Blog Early Amazon Series 8/3/2007 Web Wikimedia Server info 8/3/2007 Slides 32 Wikimedia Architecture 8/3/2007 Slides 21 My Space presentation 8/3/2007 PDF A scalable and fault-tolerant architecture for distributed web resource discovery 8/4/2007 PDF The Chubby Lock Service for Loosely-Coupled Distributed Systems 8/5/2007 Slides 47 Real world Mysql tuning 8/5/2007 Slides 100 Real world Mysql performance tuning 8/5/2007 Slides 63 Learning Mogile FS: Buliding scalable storage system 8/5/2007 Slides Reverse Proxy and Webserver 8/5/2007 PDF Case for Shared Nothing 8/5/2007 Slides 27 A scalable stateless proxy for DBI 8/5/2007 Slides 91 Real world scalability web builder 2006 8/5/2007 Slides 52 Real world web scalability Friendster Architecture Thu, 07/12/2007 - — Todd Hoff ? Hopefully the new grid model will allow a lot of people to keep writing their stories. Nothing is more complex than a simple if then and for loops. Adding a second IP address and then using a round robin DNS was considered, but the load balancer was considered more redundant and allowed easier swap in of more web servers. Shared-disk systems don't scale well either Shared-disk systems suffer from similar scalability limitations.

However, these issues are decidedly not PHP related, and are being addressed in future versions of My SQL. They use most tools build into Linux and layer on top of those. - Updates cause cache misses which goes to disk where slow I/O causes slow replication. Rebooting will persist data, but a true "crash" or termination of your instance will discard everything. If you have 8 images and each takes 100 msecs you are talking a second load just for the images. - NLB has an affinity option so a user always maps to a certain server, thus no external storage is used for session state and if the server fails the user loses their state and must relogin. Went nuts in Canada, spread to UK, Australia, and then to the US. To set locks, one must either centralize the lock manager on one processor or resort to a complex distributed locking protocol.