如何同时优化大型递归任务

i have a chron task to perform the best way in Golang.

1. I need to store big data from web service in JSON in sellers
2. After saving these sellers in a database, i need to browse another large JSON webservice with sellersID parameter to save to another table named customers.
3. Each customer has an initial state, if this state has changed from the data of the webservice (n°2) i need to store the difference in another table changes to have a history of changes.
4. Finally, if the change is equal to our conditions I perform another task.

My current operation

var wg sync.WaitGroup
action.FetchSellers() // fetch large JSON and stort in sellers table ~2min

sellers := action.ListSellers()
for _, s := range sellers {
    wg.Add(1)
    go action.FetchCustomers(&wg, s) // fetch multiple large JSON and stort in customers table and store notify... ~20sec
}
wg.Wait()

• The first difficulty with this code is that I do not control the number of calls to the webservice.
• The second is that the action.FetchCustomers function does a lot of work that I think can be done in a concurrency way.
• The third difficulty is that I can not resume where an error has occurred in case of errors.

I need to run this code every hour so it needs to be well built, currently it works but not in the best way. I think that considering the use of Worker Pools in Go like this example Go by Example: Worker Pools But I have trouble conceiving it

Not to be a jerk! But I would use a queue for this kind of things. I have already created a library and using this. github.com/AnikHasibul/queue

// Limit the max
maximumJobLimit := 50
// Open a new queue with the limit
q := queue.New(maximumJobLimit)
defer q.Close()

// simulate a large amount of jobs
for i := 0; i != 1000; i++ {
    // Add a job to queue
    q.Add()

    // Run your long long long job here in a goroutine
    go func(c int) {
        // Must call Done() after finishing the job
        defer q.Done()
        time.Sleep(time.Second)
        fmt.Println(c)
    }(i)

}

//wait for the end of the all jobs
q.Wait()
// Done!