【遍历集合】Java遍历List,Map,Vector，Set的几种方法

关于list,map,set的区别参考http://www.cnblogs.com/qlqwjy/p/7406573.html

1.遍历list

    @Test
    public void testList() {
        List<Integer> list = new ArrayList<Integer>();
        list.add(1);
        list.add(2);
        System.out.println("-------------------list------------------");
        System.out.println("-------增强for循环list----");
        for (int i : list) {
            System.out.println(i);
        }
        System.out.println("-------for循环list----");
        for (int i = 0; i < list.size(); i++) {
            System.out.println(list.get(i));
        }
        System.out.println("-------迭代器遍历list----");
        Iterator<Integer> iterator = list.iterator();
        while (iterator.hasNext()) {
            System.out.println(iterator.next());
        }
    }

结果:

-------------------list------------------
-------增强for循环list----
1
2
-------for循环list----
1
2
-------迭代器遍历list----
1
2

2.遍历Map

    @Test
    public void testMap() {
        Map<Integer, String> m = new HashMap<Integer, String>();
        m.put(1, "s");
        m.put(2, "s");
        m.put(3, "s");
        m.put(4, "s");
        System.out.println("-------------------map------------------");
        System.out.println("--------循环遍历键取值---------");
        for (Map.Entry<Integer, String> entry : m.entrySet()) {
            System.out.println(entry.getKey() + "   " + entry.getValue());
        }
        System.out.println("--------根据键取值(键正好为整数)---------");
        for (int i = 0; i < m.size(); i++) {
            System.out.println(m.get(i + 1));
        }
    }

-------------------map------------------
--------循环遍历键取值---------
1   s
2   s
3   s
4   s
--------根据键取值(键正好为整数)---------
s
s
s
s

 map.entrySet方法:(将键值对存到set集合中)

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" 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Map.EntrySet接口:

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" alt="" />

3.遍历Set

    @Test
    public void testSet() {
        Set<Integer> set = new HashSet();
        set.add(1);
        set.add(2);
        System.out.println("-------------------set------------------");
        System.out.println("-------增强for循环----");
        for (int i : set) {
            System.out.println(i);
        }
        System.out.println("-------迭代器遍历----");
        Iterator<Integer> iterator = set.iterator();
        while (iterator.hasNext()) {
            System.out.println(iterator.next());
        }
    }

-------------------set------------------
-------增强for循环----
1
2
-------迭代器遍历----
1
2

4.遍历vector

    @Test
    public void testVector() {
        System.out.println("-------------------vector------------------");
        Vector<String> v = new Vector<String>();
        v.add("sss");
        v.add("sssss");
        System.out.println("-------普通for循环----");
        for (int i = 0; i < v.size(); i++) {
            System.out.println(v.get(i));
        }
        System.out.println("-------增强for循环----");
        for (String x : v) {
            System.out.println(x);

        }
        System.out.println("-------迭代器遍历----");
        Iterator<String> iterator = v.iterator();
        while (iterator.hasNext()) {
            System.out.println(iterator.next());
        }
    }

-------------------vector------------------
-------普通for循环----
sss
sssss
-------增强for循环----
sss
sssss
-------迭代器遍历----
sss
sssss