There are many web crawlers available today, and all differ in their usability. It can be selected on the basis of our requirement. There is a big market of data crawling with different kinds of crawlers popping up every day. However easy it may seem from a top level, it is as difficult to create an efficient crawler.
Say no to plagiarism.
Get a tailor-made essay on
'Must Have Qualities of a Web Crawler'
Data crawling is no easy process, with data present in different formats, numerous codes and multiple languages. This makes the game of qualitative web crawling a complicated process. But the following ways can simplify the process:
- Well defined architecture. A well defined architecture helps a web crawler function seamlessly. With web crawlers following the Gearman model of supervisor crawlers and worker crawlers, we can speed up the page crawling process. To prevent any loss of data retrieved, it is vital to have a reliable web crawling system. A backup storage support system for all supervisor crawlers without depending on a single point of data management and crawl the web in an efficient manner.
- Smart recrawling. With various clients looking for data, web crawling is put to many uses. For lists updation across categories and genres, different websites have different frequencies. Data scraping by sending a crawler on these sites will be a waste of time. So it’s important to have a smart crawler that can analyze the frequencies with which pages get updated.
- Efficient algorithms LIFO (Last In First Out) and FIFO (First In First Out) are the different methodologies used to traverse the data, on pages and websites. Both work well, but it becomes a problem when the data to be crawled is larger or deeper than what was anticipated. This makes it important to optimize crawling, in data crawlers. By prioritising crawled pages on the basis of page rank, update frequency, reviews, etc. Your web crawling system can be enhanced by enhancing the crawling time of the pages and divide data crawlers equally so there are no bottlenecks in the process.
- Scalability. You need to test the scalability of your data crawling system before you launch it. You need to incorporate two key features?—?Storage and Extensibility in your data crawling system. A modular architectural design of the web crawler will make the crawler modifiable to accommodate any changes in the data.
- Language Independent. A web crawler needs to be language neutral and should be able to extract data in all languages. A more multilingual approach can help the users request for data in any language and make intelligent business decisions from the insights provided by your data crawling system.
