使用foreach将arrayList与自身进行比较，不包括重复项

Question

I'm comparing an arrayList to itself using foreach. I have an arrayList containing tips for waiters, each object has a date "dd-MM-yyy" and an amount (double), Now i want to add all transactions for the same day, so i get a total for the day that can be divided between the waiters. Without duplicates. I've looked all over especially here, but I can't seem to find a solution. I really hope you guys can help, I know it's a bit embarrassing, seeing as the problem being so simple, but I've been working on it for a couple of days now and I'm stuck.

I had a longer algorithm but it wouldn't work and I couldn't find any solutions online, so i broke it all down to it's most basic components and checked for each step and pretty early on this problem occured: I'm using a local arrayList to make sure that I'm not comparing the same days to eachother over and over again. The if(!alreadyMade.contains(tips1.getTime()) followed by alreadyMade.add(tips1.getTime()) seems to be producing duplicates, which in my mind makes no sense. All I want is to add all the transactions for the same day from the same arrayList.

public void dist(){

    double day = 0;
    List<String> alreadyMade = new ArrayList<>();
    for (Tips tips : data.getTips()) {
        for (Tips tips1 : data.getTips()) {
            if(tips.getTime().equals(tips1.getTime())) {
                if (!alreadyMade.contains(tips1.getTime())){
                    alreadyMade.add(tips1.getTime());
                    day += tips.getTips();
                }
            }
        }
        System.out.println(day);
        day = 0;
    }
}

I wanted the print to be for a single day, but it is printing a lot of numbers that doesn't make sense

Answer 1

I think you're trying to do something like this:

        Map<String,Double> alreadyMade = new HashMap<>();
    for (Tips tips : new ArrayList<Tips>()) {
        // If this time doesn't exist in the map then add it to the map with the
        // value tips.getTips().  If this time does exist in the map then add 
        // the value of tips.getTips() to the value that is already in the map.
        alreadyMade.merge(tips.getTime(), tips.getTips(), (Double a, Double b) -> a + b);
    }
    // go through each map entry.  The keys are the times and the values are the tip totals for that time.
    for (Map.Entry<String, Double> entry : alreadyMade.entrySet()) {
        System.out.println("Time: " + entry.getKey() + " Tips: " + entry.getValue());
    }

Note: I couldn't test this because I'm running Java 7 and this map function isn't available until java 8.

Answer 2

In Java 8+ you can use the stream API to group by the time:

Map<Date, Integer> alreadyMade = data.getTips().stream()
  .collect(groupingBy(Tip::getTime, summingInt(Tip::getTips)));

Answer 3

I would do it like the following:

This is your Tip class(I think)

public class Tip{
    Date date;
    float tip;
    public Tip(Date date, float tip){
        this.date = date;
        this.tip = tip;
    }
}

And this is the ("Algorithm")

//To Format the Dates
SimpleDateFormat ft = new SimpleDateFormat("dd-MM-yyyy");

//Input
ArrayList<Tip> tips = new ArrayList<Tip>();

//Just some Data for testing
tips.add(new Tip(ft.parse("11-04-2019"), 2.40F));
tips.add(new Tip(ft.parse("25-04-2019"), 3.30F));
tips.add(new Tip(ft.parse("25-04-2019"), 0.90F));



//Output
ArrayList<Date> dates = new ArrayList<Date>();
ArrayList<Float> sum = new ArrayList<Float>();

for(Tip tip : tips){  //Go through each Tip
  int match = dates.indexOf(tip.date);  //Look if the date is already in the array (if not -> -1)

  if(match == -1){  //If not add it
    dates.add(tip.date);
    sum.add(tip.tip);
  }else {  //If yes set it
    sum.set(match, sum.get(match) + tip.tip);
  }

}

//Output to console
for(int i = 0; i < dates.size(); i++){
  System.out.println(ft.format(dates.get(i)).toString() + " " + String.valueOf(sum.get(i)));
}

There is also a solution with maps or pairs but I never worked with them (not a professional coder). Also make sure to try-catch the ParseException. I Hope thats what you meant. :)