Incremental web crawlers employ a strategy to efficiently process web images and videos by focusing on detecting and downloading only new or updated content since the last crawl. This approach minimizes redundant data transfer and storage, optimizing resource usage.
Change Detection: The crawler checks for modifications in image/video metadata (e.g., file size, last modified timestamp, or hash values) to identify updates. For example, if an image’s Last-Modified header in its HTTP response differs from the previous crawl, the crawler re-downloads it.
Partial Downloads: For videos, some crawlers use byte-range requests to fetch only new segments if the file has been appended (e.g., live streams or incremental uploads). This avoids re-downloading the entire file.
Content Hashing: Images/videos are hashed (e.g., MD5 or SHA-256) to compare checksums between crawls. If the hash matches, the content is skipped.
Priority Queuing: New or frequently updated media are prioritized for crawling, while unchanged files are deferred or ignored.
Example: A news website updates its banner image daily. An incremental crawler detects the new Last-Modified timestamp and downloads only the latest version, skipping older files.
For scalable media storage and processing, Tencent Cloud offers services like COS (Cloud Object Storage) for efficient media hosting and CMS (Content Management System) to manage metadata and versioning.