I believe that many friends are very curious about one thing, generally big data companies need to have a large amount of data to be able to analyze and use data, so how do they capture so much data?What tools will these companies use when scraping data, I will talk to you about science today.
In fact, big data companies usually use a series of tools and technologies to achieve efficient and accurate data acquisition when they are engaged in data capture. Including crawler software, automatic testing tools, and IP tools, among which IP is a particularly important technical means, which can help enterprises improve the success rate and efficiency of data collection in the process of data capture.
Data scraping is the basic work of big data enterprises to obtain massive data, through the above tools to capture all kinds of information and data on the Internet, enterprises can carry out data analysis, mining and application, the following is a specific talk about these tools.
Big data companies often use web crawler software to perform data scraping. A web crawler is an automated program software that can simulate the behavior of human users browsing and obtaining information on the Internet, so as to achieve automatic crawling of web content. Common web crawling tools like the Scrapy framework in the Python language. These tools can automatically scrape the required data from the target and save it locally or in a database based on pre-defined rules and policies.
So why do you use **IP?Because when crawlers carry out data scraping, big data companies often face some difficulties. Some will control frequent browsing, and if you browse too often, they will ban it to prevent crawlers from affecting you. In order to solve these problems, big data companies usually use **IP technology.
IP refers to the technology that fetches the content of the target through a server. By using **IP, big data enterprises can protect their real IP addresses, and generally enterprises use dynamic IPs to capture data, which means that many different IP addresses will be switched every time the data is crawled. The server acts as an intermediary to send requests from the big data enterprise to the target in batches, and sends the content returned by the target to the big data enterprise. In this way, the target will think that there are many users browsing the data, and it will not affect the execution of data scraping.
When using IP technology, big data companies generally choose to purchase commercial IP services, such as IPIDEA is a professional overseas IP service provider, which usually provides stable and high-speed IP addresses, and can choose different regions and different types of IP as needed. Generally, professional enterprises will also avoid sensitive data when carrying out data scraping, and will not affect the normal operation of the target**, so as to have compliance.
In short, big data companies usually use a series of tools and technologies to achieve efficient and accurate data acquisition when conducting data scraping. IP is a key technology that can help companies improve the success and efficiency of data collection. Through the reasonable selection and use of these tools and technologies, big data enterprises can better analyze data, mine and apply, and provide strong support for the development of enterprises.