Version 0.7
Copyright © 2009 - 2011 Lars Vogel
09.04.2011
| Revision History | ||
|---|---|---|
| Revision 0.1 | 15.09.2009 | Lars Vogel |
| Created | ||
| Revision 0.2 - 0.7 | 21.09.2009 - 09.04.2011 | Lars Vogel |
| bugfixes and enhancements | ||
Table of Contents
Google uses an amazing set of technologies. I use this article to keep information about this technology and to keep pointers to publicly available information about these technologies.
Pagerank is the weight of importance for a webpage calculated by Google.
The calculation process is not known and contains many factors but the principle is simple. A web page is more important if other web pages link to it. The more importance a web pages has (by inbound links from other sites) the more important are outbound links from this webpage.
Please find a good description of the pagerank calculation in the following article http://www.ams.org/featurecolumn/archive/pagerank.html .
Please see MapReduce .
Google has the GFS, a distributed, multi-gigabyte files. This file system is described Google File System Whitepaper .
GFS does not handle the replication between different data centers.
Please see Bigtable .
Google provides on the Google App Engine memcache as a caching mechanism.
Memcache is a high-performance, distributed memory object caching system, primarily intended for fast access to cached results of datastore queries.
Similar to Bigtable it works similar to a map with key and objects. If the memory consumption of memcache is to big then memory will automatically released based on a Last-Recently-Used (LRU) strategy.
Google provides an API to put something into memcache and to remove something again from memcache.
Before posting questions, please see the vogella FAQ. If you have questions or find an error in this article please use the www.vogella.de Google Group. I have created a short list how to create good questions which might also help you.