👀 Views: 50 💬 Answers: 1 📅 Created: 2025-06-14

go sorting performance Go

I'm converting an old project and I've been working on this all day and I'm upgrading from an older version and I'm currently working on a Go application where I need to sort a large dataset of transaction records by their date fields. The dataset can be quite large, sometimes exceeding a million records, and I'm working with important performance optimization when using the standard sorting functions. Here's an example of how my transaction struct looks: ```go type Transaction struct { ID int Amount float64 Date time.Time } ``` I'm using the `sort.Slice` function to sort the transactions: ```go sort.Slice(transactions, func(i, j int) bool { return transactions[i].Date.Before(transactions[j].Date) }) ``` This approach works, but for datasets over 100,000 records, it takes several seconds to complete. I've tried optimizing by ensuring that I'm not inadvertently holding references to large data structures, and I’ve also tried sorting using parallel processing with goroutines, but the complexity of merging the results has made this approach cumbersome and behavior-prone. Additionally, I’ve noticed that when sorting by date, transactions with the same date seem to have an inconsistent order. I want to ensure that if two transactions have the same date, they maintain the order they were originally in (stable sort). Is there a more efficient way to sort large slices of structs in Go, especially while ensuring stability? Should I consider moving to a different sorting algorithm, or is there a library that provides better performance for such cases? Any advice or code examples would be greatly appreciated! I'm developing on CentOS with Go. Any examples would be super helpful. Thanks for any help you can provide!