Crawling and Indexing the Web

Maintaining the webcrawler is a tuff challenging task which involves tricky and reliablity issues. crawling is the thing that it interacts with hundreds of servers world wide.In order to crawl millions of web pages google has quick and fast distributed crawling system. A single URL server will list number of URL'S list to crawle where both crawlers and URL server are implemented by Python

.The system can crawl over 100 web pages per second using four crawlers.Systems which access large parts of the Internet need to be designed to be very robust and carefully tested. Since large complex systems such as crawlers will invariably cause problems, there needs to be significant resources devoted to reading the email and solving these problems as they come up. 

Parsing -- Any parser which is designed to run on the entire Web must handle a huge array of possible errors. These range from typos in HTML tags to kilobytes of zeros in the middle of a tag, non-ASCII characters, HTML tags nested hundreds deep, and a great variety of other errors that challenge anyone's imagination to come up with equally creative ones.

Indexing Documents into Barrels -- After each document is parsed, it is encoded into a number of barrels. Every word is converted into a wordID by using an in-memory hash table -- the lexicon. New additions to the lexicon hash table are logged to a file. 

Sorting -- In order to generate the inverted index, the sorter takes each of the forward barrels and sorts it by wordID to produce an inverted barrel for title and anchor hits and a full text inverted barrel.

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