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How to Scrape Websites at Large Scale

Wednesday, January 20, 2021

As your business scales up, it is necessary to take the data extraction process to the next level and scrape data at a large scale. However, scraping a large amount of data from websites isn't an easy task. You may encounter a few challenges that would hold you up from getting a significant amount of data from various sources automatically. 


Table of Content:


Roadblocks while undergoing web scraping at scale:



1. Dynamic website structure:

It is easy to scrape HTML web pages. However, many websites now rely heavily on Javascript/Ajax techniques for dynamic content loading. Both of them require all sort of complex libraries that cumbersome web scrapers from obtaining data from such websites


2. Anti-scraping technologies:

Such as Captcha and behind-the-log-in serve as surveillance to keep spam away. However, they also pose a great challenge for a basic web scraper to get passed. As such anti-scraping technologies apply complex coding algorithms, it takes a lot of effort to come up with a technical solution to workaround. Some may even need a middleware like 2Captcha to solve.


3. Slow loading speed:

The more web pages a scraper needs to go through, the longer it takes to complete. It is obvious that scraping at a large scale will take up a lot of resources on a local machine. A heavier workload on the local machine might lead to a breakdown. 


4. Data warehousing: 

A Large scale extraction generates a huge volume of data. This requires a strong infrastructure on data warehousing to be able to store the data securely. It will take a lot of money and time to maintain such a database. 


Although these are some common challenges of scraping at large scale,  Octoparse already helped many companies overcome such issues. Octoparse’s cloud extraction is engineered for large-scale extraction. 



Cloud extraction to scrape websites at scale

Cloud extraction allows you to extract data from your target websites 24/7 and stream into your database, all automatically. The one obvious advantage? You don’t need to sit by your computer and wait for the task to get completed. 


But...there are actually more important things you can achieve with cloud extraction. Let me break them down into details:


1. Speediness

In Octoparse, we call a scraping project a “task”. With cloud extraction, you can scrape as many as 6 to 20 times faster than a local run. 


This is how Cloud extraction works. When a task is created and set to run on the cloud, Octoparse sends the task to multiple cloud servers that then go on to perform the scraping tasks concurrently. For example, if you are trying to scrape product information for 10 different pillows on Amazon, Instead of extracting the 10 pillows one by one, Octoparse initiates the task and send it to 10 cloud servers, each goes on to extract data for one of the ten pillows. In the end, you would get 10 pillows data extracted in 1/10th of the time if you were to extract the data locally. 


This is apparently an over-simplified version of the Octoparse algorithm, but you get the idea. 


2. Scrape more websites simultaneously

Cloud extraction also makes it possible to scrape up to 20 websites simultaneously. Following the same idea, each website is scraped on a single cloud server that then sends back the extracted to your account. 

You can set up different tasks with various priorities to make sure the websites will be scraped in the order preferred. 


3. Unlimited cloud storage 

During a cloud extraction, Octoparse removes duplicated data and stored the clean data in the cloud such that you can easily access the data at any time, anywhere and there’s no limit to the amount of data you can store. For an even more seamless scraping experience, integrate Octoparse with your own program or database via API for managing your tasks and data.  

4. Schedule runs for regular data extraction 

If you're gonna need regular data feeds from any websites,  this is the feature for you. With Octoparse, you can easily set your tasks to run on schedule, daily, weekly, monthly or even at any specific time of each day.  Once you finish scheduling, click "Save and Start". The task will run as scheduled.


5. Less blocking 

Cloud extraction reduces the chance of being blacklisted/blocked. You can use IP proxies, switch user-agents, clear cookies, adjust scraping speed.etc. 


Tracking web data at a large volume such as social media, news, and e-commerce websites will elevate your business performance with data-driven practices. It’s time to ditch old-fashion web surfing and use web scraping technology to gain a competitive edge now. 



Author: Ashley

Ashley is a data enthusiast and passionate blogger with hands-on experience in web scraping. She focuses on capturing web data and analyzing in a way that empowers companies and businesses with actionable insights. Read her blog here to discover practical tips and applications on web data extraction

Artículo en español: Cómo scrape sitio web a gran escala (guía 2020)
También puede leer artículos de web scraping en El Website Oficial



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