Java 8：功能性VS传统

业务逻辑是相同的：

给定一个由访问次数/时间组成的String表达式，例如：“ 1 / 24h，1..3 / 3h，5 / *”

然后，结果应为以下字符串列表：

“ 1 / 24h”，
“ 1 / 3h”，“ 2 / 3h”，“ 3 / 3h”，
“ 5 / 1h”，“ 5 / 2h”，“ 5 / 3h”，“ 5 / 4h”，“ 5 / 5h”，直到“ 24 / 1h”

因此，需要解决2件事，即访问点和时间点和星星。

我将使用Java 8，但我将向您展示使用Functional实现此逻辑与使用循环和ifs以传统方式实现此逻辑之间的区别。 

package com.marco;
import java.util.ArrayList;
import java.util.List;
import java.util.function.Function;
import java.util.stream.Collectors;
import com.google.common.collect.ImmutableList;
import com.google.common.collect.Lists;
public class ExpressionConverter {private static final String COMMA = ",";private static final String SEPARATOR = "/";private final ImmutableList<Function<String, List<String>>> visitFunctions;private final ImmutableList<Function<String, List<String>>> timeFunctions;public ExpressionConverter(DotsVisitFunction dotsVisitFunction, StarVisitFunction starVisitFunction, StandardFunction standardFunction,StarTimeFunction starTimeFunction) {this.visitFunctions = ImmutableList.of(dotsVisitFunction, starVisitFunction, standardFunction);this.timeFunctions = ImmutableList.of(starTimeFunction, standardFunction);}public List<String> convertVisitTimeExpressionFunctional(String visitTimeExpression) {return Lists.newArrayList(visitTimeExpression.split(COMMA)).parallelStream().filter(it -> !it.isEmpty()).map(it -> interpretSingleExpressionFunctional(it)).flatMap(it -> it.parallelStream()).collect(Collectors.toList());}public List<String> convertVisitTimeExpressionTraditional(String visitTimeExpression) {List<String> result = new ArrayList<String>();for (String singleVisitTime : visitTimeExpression.split(COMMA)) {if (!singleVisitTime.isEmpty()) {result.addAll(interpretSingleVisitTimeExpressionTraditional(singleVisitTime));}}return result;}private List<String> interpretSingleExpressionFunctional(String singleExpression) {String visit = singleExpression.split(SEPARATOR)[0];String time = singleExpression.split(SEPARATOR)[1];List<String> result = Lists.newArrayList();visitFunctions.stream().map(it -> it.apply(visit)).flatMap(it -> it.stream()).forEach(visitIt -> {timeFunctions.stream().map(it -> it.apply(time)).flatMap(it -> it.stream()).forEach(timeIt -> {result.add(visitIt + SEPARATOR + timeIt);});});return result;}private List<String> interpretSingleVisitTimeExpressionTraditional(String singleExpression) {String visit = singleExpression.split(SEPARATOR)[0];String time = singleExpression.split(SEPARATOR)[1];List<String> result = Lists.newArrayList();List<String> visists = Lists.newArrayList();List<String> times = Lists.newArrayList();for (Function<String, List<String>> visitFunction : visitFunctions) {visists.addAll(visitFunction.apply(visit));}for (Function<String, List<String>> timeFunction : timeFunctions) {times.addAll(timeFunction.apply(time));}for (String visitIt : visists) {for (String timeIt : times) {result.add(visitIt + SEPARATOR + timeIt);}}return result;}
}

如您所见，我们有2种公共方法和2种私有方法（功能方法和传统方法）。

这是一个针对这两种样式的性能的简单测试： 

package com.marco;
import static org.mockito.Matchers.any;
import static org.mockito.Matchers.anyInt;
import static org.mockito.Matchers.anyLong;
import static org.mockito.Mockito.mock;
import static org.mockito.Mockito.when;
import java.math.BigDecimal;
import java.util.Set;
import org.junit.Before;
import org.junit.Test;
import com.google.common.collect.ImmutableSet;
import com.google.common.collect.Sets;
public class ExpressionConverterTest {private static final String EXPRESSIONS = 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7400,9/65h,6/7400,9/65h,6/7400,9/65h,6/7400,9/65h,6/7400,9/65h,6/7400,9/65h,6/7400,9/65h,6/7400,9/65h,6/7400,9/65h,6/7400,9/65h,55..57/14400";private Cache cache;private ExpressionConverter expressionConverter;@Beforepublic void init() {cache = mock(Cache.class);expressionConverter = new ExpressionConverter(new DotsVisitFunction(cache), new StarVisitFunction(cache), new StandardFunction(),new StarTimeFunction(cache));Set<Integer> totVisists = Sets.newHashSet();for (int i = 1; i <= 100; i++) {totVisists.add(i);}when(cache.getVisits(anyLong(), (BigDecimal) any(), anyInt())).thenReturn(ImmutableSet.copyOf(totVisists));}@Testpublic void testPerf() {long averageTraditional = 0l;long averageFuntional = 0l;for (int a = 0; a < 10; a++) {long start = System.currentTimeMillis();for (int i = 0; i < 1000; i++) {expressionConverter.convertVisitTimeExpressionTraditional(EXPRESSIONS);}System.out.println("Traditional java " + (System.currentTimeMillis() - start) + " ms");averageTraditional += (System.currentTimeMillis() - start);long start2 = System.currentTimeMillis();for (int i = 0; i < 1000; i++) {expressionConverter.convertVisitTimeExpressionFunctional(EXPRESSIONS);}System.out.println("Functional java " + (System.currentTimeMillis() - start2) + " ms");averageFuntional += (System.currentTimeMillis() - start2);}System.out.println("Average Traditional java : " + (averageTraditional / 10) + " ms");System.out.println("Average Functional java : " + (averageFuntional / 10) + " ms");}
}

这是输出： 

Traditional java 1274 msFunctional java 773 msTraditional java 1054 msFunctional java 531 msTraditional java 961 msFunctional java 493 msTraditional java 948 msFunctional java 492 msTraditional java 949 msFunctional java 491 msTraditional java 958 msFunctional java 481 msTraditional java 1004 msFunctional java 474 msTraditional java 949 msFunctional java 471 msTraditional java 947 msFunctional java 475 msTraditional java 942 msFunctional java 472 msAverage Traditional java : 998 msAverage Functional java : 515 ms

功能是传统的2倍。 为什么？

因此：parallelStream（）

Parallel Stream将利用您的多核系统将工作分解为多个任务。

因此，您可以将parallelStream（）放在任何地方，并用parallelStream（）替换所有stream（）方法吗？

没有！

如果在错误的地方使用parallelStream（）实际上会导致性能大大降低。

在使用此功能之前，应阅读有关此参数的大量文章，但请记住，如果要使用parallelStream（），请确保在测量前后的性能！！！！

翻译自: https://www.javacodegeeks.com/2014/08/java-8-functional-vs-traditional.html

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