How does the AWS SDK for Go handle memory management during large file uploads

1. Streaming: The SDK uses streaming to upload large files, which means that it breaks the file into smaller chunks and uploads each chunk separately. This approach helps to reduce memory usage by only loading a small portion of the file into memory at a time[4].

2. Multipart Uploads: The SDK also supports multipart uploads, which allow you to upload large files by dividing them into smaller parts and uploading each part separately. This approach helps to manage memory usage by only loading a small portion of the file into memory at a time[3].

3. Chunking: The SDK uses chunking to manage memory usage during large file uploads. It divides the file into smaller chunks and uploads each chunk separately. This approach helps to reduce memory usage by only loading a small portion of the file into memory at a time[3].

4. Concurrency: The SDK supports concurrency, which means that it can upload multiple chunks of the file simultaneously. This approach helps to improve upload performance and reduce memory usage by spreading the load across multiple goroutines[1].

5. Buffering: The SDK uses buffering to manage memory usage during large file uploads. It buffers the file data in memory and then uploads it in chunks. This approach helps to reduce memory usage by only loading a small portion of the file into memory at a time[1].

By using these techniques, the AWS SDK for Go can efficiently handle large file uploads while managing memory usage effectively.