How did you optimize search scenarios?

To optimize search scenarios in Go, I employed several approaches:

• Using indexes and data structures suitable for the type of search (e.g., hash tables, B-trees, trigrams).
• Caching results of frequent queries with built-in or third-party caches (e.g., groupcache).
• Parallel processing of requests using goroutines to speed up searches over large data volumes.
• Optimizing database queries: minimizing the number of queries, using prepared statements, proper schema design.
• Profiling code with pprof to identify bottlenecks and eliminate them.

Example of a simple parallel search over a slice of strings:

func parallelSearch(data []string, query string) []string {
    var wg sync.WaitGroup
    results := make(chan string)

    for _, item := range data {
        wg.Add(1)
        go func(s string) {
            defer wg.Done()
            if strings.Contains(s, query) {
                results <- s
            }
        }(item)
    }

    go func() {
        wg.Wait()
        close(results)
    }()

    var found []string
    for r := range results {
        found = append(found, r)
    }
    return found
}