标签:ogr 包含 指定 pwa ++ tostring 性能 pac play
今天看到一篇关于java8的文章,发现有些特性在日常没用到,所以也完全不了解,然后学习了一波:
(主要包含:Map, FlatMap, reduce, groupingBy, joining, reducing, parallelStream, peek 等)
package cn.miaoying.test; import lombok.extern.slf4j.Slf4j; import org.apache.commons.lang.time.StopWatch; import org.junit.Before; import org.junit.Test; import org.junit.runner.RunWith; import org.springframework.test.context.junit4.SpringRunner; import java.util.*; import java.util.stream.Collectors; import java.util.stream.Stream; @RunWith(SpringRunner.class) @Slf4j public class Test { List<Student> studentList = new ArrayList<>(); @Before public void init() { Student student1 = new Student(); student1.setAge(1); student1.setName("name1name"); studentList.add(student1); Student student2 = new Student(); student2.setAge(2); student2.setName("name2name"); studentList.add(student2); Student student3 = new Student(); student3.setAge(3); student3.setName("name3name"); studentList.add(student3); } @Test public void testMap01() { List<String> res = studentList.stream() .map(Student::getName) .collect(Collectors.toList()); res.forEach(r -> { log.info(r); // 分别输出: // name1name // name2name // name3name }); } @Test public void testFlatMap01() { List<String> collect = studentList.stream() .flatMap(p -> Arrays.stream(p.getName().split("nam"))) .collect(Collectors.toList()); collect.forEach(c -> { log.info(c); // 分别输出: // 空 // e1 // e // 空 // e2 // e // 空 // e3 // e }); log.info(String.valueOf(collect.size())); // 分别输出: // 9 } @Test public void testReduce01() { Integer reduce = Stream.of(1, 2, 3, 4).reduce(10, (count, item) -> { log.info("count = " + count); log.info("item = " + item); return count + item; }); log.info(reduce.toString()); // 分别输出: // count = 10 // item = 1 // count = 11 // item = 2 // count = 13 // item = 3 // count = 16 // item = 4 // 20 } @Test public void toListTest() { List<String> collect = studentList.stream() .map(Student::getName) .collect(Collectors.toList()); collect.forEach(c -> { log.info(c); }); // 分别输出: // name1name // name2name // name3name } @Test public void toSetTest() { Set<Integer> collect = studentList.stream() .map(Student::getAge) .collect(Collectors.toSet()); collect.forEach(c -> { log.info(c.toString()); }); // 分别输出: // 1 // 2 // 3 } @Test public void toMapTest() { Map<String, Integer> map = studentList.stream() .collect( Collectors.toMap(Student::getName, Student::getAge) ); map.forEach((k, v) -> { log.info(k + " : " + v); }); // 分别输出: // name1name : 1 // name2name : 2 // name3name : 3 } /** * 指定类型 */ @Test public void toTreeSetTest() { TreeSet<String> collect = studentList.stream() .map(Student::getName) .collect(Collectors.toCollection(TreeSet::new)); collect.forEach(c -> { log.info(c); }); // 分别输出: // name1name // name2name // name3name } /** * 分组 */ @Test public void toGroupTest() { Map<Boolean, List<Student>> collect = studentList.stream() .collect( Collectors.groupingBy( c -> "name2name".equals(c.getName()) ) ); collect.forEach((b, l) -> { log.info(b + " : " + l.toString()); }); // 分别输出: // false : [Student{name=‘name1name‘, age=1}, Student{name=‘name3name‘, age=3}] // true : [Student{name=‘name2name‘, age=2}] } /** * 分隔 */ @Test public void testJoiningTest() { String collect = studentList.stream() .map(s -> s.getName()) .collect(Collectors.joining(" | ", " { ", " } ")); log.info(collect); // 分别输出: // { name1name | name2name | name3name } } /** * 自定义 */ @Test public void reduce() { List<String> collect = Stream.of("1", "2", "3").collect( Collectors.reducing( new ArrayList<String>(), c -> Arrays.asList(c), (x, y) -> { x.addAll(y); return x; } ) ); collect.forEach(c -> { log.info(c); }); // 分别输出: // 1 // 2 // 3 } @Test public void streamTest() { // 输入流的大小并不是决定并行化是否会带来速度提升的唯一因素,性能还会受到编码方式和核的数量的影响 // 影响性能的五要素是:数据大小、源数据结构、值是否可装箱、可用的CPU核数量、处理每个元素所花的时间 int size = 1000_0000; List<Integer> list = new ArrayList<>(size); for (Integer i = 0; i < size; i++) { list.add(new Integer(i)); } List<Integer> temp1 = new ArrayList<>(size); // old StopWatch stopWatch1 = new StopWatch(); stopWatch1.start(); for (Integer i : list) { temp1.add(i); } stopWatch1.stop(); log.info("old time = " + stopWatch1.getTime()); // synchronized StopWatch stopWatch2 = new StopWatch(); stopWatch2.start(); list.stream().collect(Collectors.toList()); stopWatch2.stop(); log.info("synchronized time = " + stopWatch2.getTime()); // concurrent StopWatch stopWatch3 = new StopWatch(); stopWatch3.start(); list.parallelStream().collect(Collectors.toList()); stopWatch3.stop(); log.info("concurrent time = " + stopWatch3.getTime()); } @Test public void peekTest() { // 通过 peek 可以查看每个值,并且继续流操作 studentList.stream().map(s -> s.getName()).peek(p -> { log.info(p); }).collect(Collectors.toList()); } class Student { public String name; public Integer age; public String getName() { return name; } public void setName(String name) { this.name = name; } public Integer getAge() { return age; } public void setAge(Integer age) { this.age = age; } @Override public String toString() { return "Student{" + "name=‘" + name + ‘\‘‘ + ", age=" + age + ‘}‘; } } }
标签:ogr 包含 指定 pwa ++ tostring 性能 pac play
原文地址:https://www.cnblogs.com/miaoying/p/11972501.html