Parallelizing file operations in large GCS or S3 buckets can significantly improve performance. By using the rill concurrency toolkit in Go, tasks like listing, filtering, and deleting files can be made concurrent. This involves creating split points within the bucket to distribute the workload more evenly and efficiently using goroutines. The strategy minimizes bottlenecks and maintains cost efficiency. The provided examples demonstrate implementation for both GCS and S3.
Table of contents
Why Listing is Slow?Can We Make the Listing Operation Concurrent?Dynamic Split Points and FlatMapPutting it All TogetherMy Bucket Has Different StructureHow to Do the Same Thing for the Amazon S3?What About the Costs?Performance and ConclusionSort: