java8 stream与传统写法的性能对比简测

    以下对比了用Stream完成去重复和从list<class>中提取其中一个属性的功能与传统的写法作对比, 看性能有否差异:

   两千万记录去重,一百万取属性:

static class Class1 {public String staffId;public String getStaffId() {return staffId;}public String getStaffName() {return staffName;}public String staffName;public Class1(){}public Class1(String staffId,String staffName){this.staffId=staffId;this.staffName=staffName;}public String toString(){return "{id:"+staffId+",name:"+staffName+"}";}/*@Overridepublic int hashCode(){return staffId.hashCode()+staffName.hashCode();}*//*@Overridepublic boolean equals(Object v){Class1 a=(Class1) v;return a.staffId.equals(this.staffId)&&a.staffName.equals(this.staffName);}@Overridepublic int hashCode(){return staffId.hashCode()*staffName.hashCode();}*/}static class ResultBean{public List<Class1> result;public long consume;}public ResultBean getUnique(List<Class1> pvData,Function<List<Class1>,List<Class1>> pvFun){ResultBean lvRet=new ResultBean();long lvTmStart=System.currentTimeMillis();lvRet.result= pvFun.apply(pvData);lvRet.consume= System.currentTimeMillis()-lvTmStart;return lvRet;}static class ResultBean2{public List<String> result;public long consume;}public ResultBean2 getUnique2(List<Class1> pvData,Function<List<Class1>,List<String>> pvFun){ResultBean2 lvRet=new ResultBean2();long lvTmStart=System.currentTimeMillis();lvRet.result= pvFun.apply(pvData);lvRet.consume= System.currentTimeMillis()-lvTmStart;return lvRet;}@Testpublic void testRemoveDuplicate() {List<String> lvList1 = new ArrayList<>();lvList1.add("A");lvList1.add("B");lvList1.add("B");lvList1.add("A");lvList1.add("C");lvList1.add("C");lvList1 = lvList1.stream().distinct().collect(Collectors.toList());System.out.println(lvList1);List<Class1> lvList2 = new ArrayList<>();for (int i = 0; i < 1000000; i++) {lvList2.add(new Class1("001", "Name001"));lvList2.add(new Class1("002", "Name002"));lvList2.add(new Class1("003", "Name003"));lvList2.add(new Class1("001", "Name001"));lvList2.add(new Class1("002", "Name002"));lvList2.add(new Class1("003", "Name003"));lvList2.add(new Class1("001", "Name001"));lvList2.add(new Class1("002", "Name002"));lvList2.add(new Class1("003", "Name003"));lvList2.add(new Class1("003", "Name003"));lvList2.add(new Class1("003", "Name003"));lvList2.add(new Class1("004", "Name003"));lvList2.add(new Class1("005", "Name003"));lvList2.add(new Class1("004", "Name003"));lvList2.add(new Class1("005", "Name003"));lvList2.add(new Class1("004", "Name003"));lvList2.add(new Class1("005", "Name003"));lvList2.add(new Class1("003", "Name003"));lvList2.add(new Class1("002", "Name003"));lvList2.add(new Class1("002", "Name003"));}System.out.println(lvList2.size());//lvList2=lvList2.stream().distinct().collect(Collectors.toList());不起作用ResultBean lvLambdaResult = getUnique(lvList2, p -> {return lvList2.stream().collect(Collectors.collectingAndThen(Collectors.toCollection(() -> new TreeSet<>(Comparator.comparing(Class1::getStaffId).thenComparing(Class1::getStaffName))), ArrayList::new));//return lvList2.stream().distinct().collect(Collectors.toList());});System.out.println("Consume:" + lvLambdaResult.consume);System.out.println("result:" + lvLambdaResult.result);ResultBean lvNormalResult = getUnique(lvList2, p -> {TreeSet<Class1> lvTree = new TreeSet<Class1>(new Comparator<Class1>() {@Overridepublic int compare(Class1 class1, Class1 t1) {int lvRet = class1.staffId.compareTo(t1.staffId) * 100;return lvRet + class1.staffName.compareTo(t1.staffName);}});lvTree.addAll(p);return Arrays.asList(lvTree.toArray(new Class1[lvTree.size()]));});System.out.println("Consume:" + lvNormalResult.consume);System.out.println("result:" + lvNormalResult.result);lvList2.clear();for (int i = 0; i < 1000000; i++) {lvList2.add(new Class1(i+"", "Name00"+i));}ResultBean2 lvLambdaResult2=getUnique2(lvList2,p->{return p.stream().map(i->i.staffId).collect(Collectors.toList());});System.out.println("Consume:"+lvLambdaResult2.consume);ResultBean2 lvNormalResult2=getUnique2(lvList2,p->{List<String> lvRet=new ArrayList<>();for (Class1 rec:p){lvRet.add(rec.staffId);}return lvRet;});System.out.println("Consume:"+lvNormalResult2.consume);}

结果如下, stream函数式的写法与传统写法性能要低些, 去重慢13%, 提取慢42%. 如果是在性能要求比较高的地方就要避免了.

20000000
Consume:806
result:[{id:001,name:Name001}, {id:002,name:Name002}, {id:002,name:Name003}, {id:003,name:Name003}, {id:004,name:Name003}, {id:005,name:Name003}]
Consume:713
result:[{id:001,name:Name001}, {id:002,name:Name002}, {id:002,name:Name003}, {id:003,name:Name003}, {id:004,name:Name003}, {id:005,name:Name003}]
Consume:30
Consume:21