现实业务开发中，通常为了避免超时、对方接口限制等原因需要对支持批量的接口的数据分批调用。
比如List参数的size可能为 几十个甚至上百个，但是假如对方dubbo接口比较慢，传入50个以上会超时，那么可以每次传入20个，分批执行。
通常很多人会写 for 循环或者 while 循环，非常不优雅，无法复用，而且容易出错。
下面结合 Java8 的 Stream ，Function ,Consumer 等特性实现分批调用的工具类封装和自测。
并给出 CompletableFuture 的异步改进方案。
二、实现工具类：
package com.chujianyun.common.java8.function;
import com.google.common.base.Preconditions;
import com.google.common.collect.Lists;
import org.apache.commons.collections4.CollectionUtils;
import java.util.*;
import java.util.function.Consumer;
import java.util.function.Function;
public class ExecuteUtil {
public static void partitionRun(List dataList, int size, Consumer> consumer) {
if (CollectionUtils.isEmpty(dataList)) {
return;
}
Preconditions.checkArgument(size > 0, "size must not be a minus");
Lists.partition(dataList, size).forEach(consumer);
}
public static List partitionCall2List(List dataList, int size, Function, List> function) {
if (CollectionUtils.isEmpty(dataList)) {
return new ArrayList<>(0);
}
Preconditions.checkArgument(size > 0, "size must not be a minus");
return Lists.partition(dataList, size)
.stream()
.map(function)
.filter(Objects::nonNull)
.reduce(new ArrayList<>(),
(resultList1, resultList2) -> {
resultList1.addAll(resultList2);
return resultList1;
});
}
public static Map partitionCall2Map(List dataList, int size, Function, Map> function) {
if (CollectionUtils.isEmpty(dataList)) {
return new HashMap<>(0);
}
Preconditions.checkArgument(size > 0, "size must not be a minus");
return Lists.partition(dataList, size)
.stream()
.map(function)
.filter(Objects::nonNull)
.reduce(new HashMap<>(),
(resultMap1, resultMap2) -> {
resultMap1.putAll(resultMap2);
return resultMap1;
});
}
}
待调用的服务（模拟）
package com.chujianyun.common.java8.function;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
public class SomeManager {
public void aRun(Long id, List data) {
}
public List aListMethod(Long id, List data) {
return new ArrayList<>(0);
}
public Map aMapMethod(Long id, List data) {
return new HashMap<>(0);
}
}
单元测试：
package com.chujianyun.common.java8.function;
import org.apache.commons.lang3.RandomUtils;
import org.jeasy.random.EasyRandom;
import org.junit.Assert;
import org.junit.Before;
import org.junit.Test;
import org.junit.runner.RunWith;
import org.mockito.Mock;
import org.mockito.Mockito;
import org.mockito.internal.verification.Times;
import org.powermock.api.mockito.PowerMockito;
import org.powermock.modules.junit4.PowerMockRunner;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.stream.Collectors;
import java.util.stream.Stream;
import static org.mockito.ArgumentMatchers.any;
import static org.mockito.ArgumentMatchers.anyLong;
@RunWith(PowerMockRunner.class)
public class ExecuteUtilTest {
private EasyRandom easyRandom = new EasyRandom();
@Mock
private SomeManager someManager;
// 测试数据
private List mockDataList;
private int total = 30;
@Before
public void init() {
// 构造30条数据
mockDataList = easyRandom.objects(String.class, 30).collect(Collectors.toList());
}
@Test
public void test_a_run_partition() {
// mock aRun
PowerMockito.doNothing().when(someManager).aRun(anyLong(), any());
// 每批 10 个
ExecuteUtil.partitionRun(mockDataList, 10, (eachList) -> someManager.aRun(1L, eachList));
//验证执行了 3 次
Mockito.verify(someManager, new Times(3)).aRun(anyLong(), any());
}
@Test
public void test_call_return_list_partition() {
// mock 每次调用返回条数(注意每次调用都是这2个)
int eachReturnSize = 2;
PowerMockito
.doReturn(easyRandom.objects(String.class, eachReturnSize).collect(Collectors.toList()))
.when(someManager)
.aListMethod(anyLong(), any());
// 分批执行
int size = 4;
List resultList = ExecuteUtil.partitionCall2List(mockDataList, size, (eachList) -> someManager.aListMethod(2L, eachList));
//验证执行次数
int invocations = 8;
Mockito.verify(someManager, new Times(invocations)).aListMethod(anyLong(), any());
// 正好几轮
int turns;
if (total % size == 0) {
turns = total / size;
} else {
turns = total / size + 1;
}
Assert.assertEquals(turns * eachReturnSize, resultList.size());
}
@Test
public void test_call_return_map_partition() {
// mock 每次调用返回条数
// 注意：
// 如果仅调用doReturn一次，那么每次返回都是key相同的Map，
// 如果需要不覆盖，则doReturn次数和 invocations 相同）
int eachReturnSize = 3;
PowerMockito
.doReturn(mockMap(eachReturnSize))
.doReturn(mockMap(eachReturnSize))
.when(someManager).aMapMethod(anyLong(), any());
// 每批
int size = 16;
Map resultMap = ExecuteUtil.partitionCall2Map(mockDataList, size, (eachList) -> someManager.aMapMethod(2L, eachList));
//验证执行次数
int invocations = 2;
Mockito.verify(someManager, new Times(invocations)).aMapMethod(anyLong(), any());
// 正好几轮
int turns;
if (total % size == 0) {
turns = total / size;
} else {
turns = total / size + 1;
}
Assert.assertEquals(turns * eachReturnSize, resultMap.size());
}
private Map mockMap(int size) {
Map result = new HashMap<>(size);
for (int i = 0; i < size; i++) {
// 极力保证key不重复
result.put(easyRandom.nextObject(String.class) + RandomUtils.nextInt(), easyRandom.nextInt());
}
return result;
}
}
注意：
1 判空
.filter(Objects::nonNull)
这里非常重要，避免又一次调用返回 null，而导致空指针异常。
2 实际使用时可以结合apollo配置， 灵活设置每批执行的数量，如果超时随时调整
3 用到的类库
集合工具类： commons-collections4、guava （可以不用）
这里的list划分子list也可以使用stream的 skip ,limit特性自己去做，集合判空也可以不借助collectionutils.
构造数据：easy-random
单元测试框架： Junit4 、 powermockito、mockito
4 大家可以加一些更强大的功能，如允许设置每次调用的时间间隔、并行或并发调用等。
三、改进以上面的List接口为例，将其改为异步版本：
public static List partitionCall2ListAsync(List dataList,
int size,
ExecutorService executorService,
Function, List> function) {
if (CollectionUtils.isEmpty(dataList)) {
return new ArrayList<>(0);
}
Preconditions.checkArgument(size > 0, "size must not be a minus");
List>> completableFutures = Lists.partition(dataList, size)
.stream()
.map(eachList -> {
if (executorService == null) {
return CompletableFuture.supplyAsync(() -> function.apply(eachList));
} else {
return CompletableFuture.supplyAsync(() -> function.apply(eachList), executorService);
}
})
.collect(Collectors.toList());
CompletableFuture allFinished = CompletableFuture.allOf(completableFutures.toArray(new CompletableFuture[0]));
try {
allFinished.get();
} catch (Exception e) {
throw new RuntimeException(e);
}
return completableFutures.stream()
.map(CompletableFuture::join)
.filter(CollectionUtils::isNotEmpty)
.reduce(new ArrayList(), ((list1, list2) -> {
List resultList = new ArrayList<>();
if(CollectionUtils.isNotEmpty(list1)){
resultList.addAll(list1);
}
if(CollectionUtils.isNotEmpty(list2)){
resultList.addAll(list2);
}
return resultList;
}));
}
测试代码：
// 测试数据
private List mockDataList;
private int total = 300;
private AtomicInteger atomicInteger;
@Before
public void init() {
// 构造total条数据
mockDataList = easyRandom.objects(String.class, total).collect(Collectors.toList());
}
@Test
public void test_call_return_list_partition_async() {
ExecutorService executorService = Executors.newFixedThreadPool(10);
atomicInteger = new AtomicInteger(0);
Stopwatch stopwatch = Stopwatch.createStarted();
// 分批执行
int size = 2;
List resultList = ExecuteUtil.partitionCall2ListAsync(mockDataList, size, executorService, (eachList) -> someCall(2L, eachList));
Stopwatch stop = stopwatch.stop();
log.info("执行时间: {} 秒", stop.elapsed(TimeUnit.SECONDS));
Assert.assertEquals(total, resultList.size());
// 正好几轮
int turns;
if (total % size == 0) {
turns = total / size;
} else {
turns = total / size + 1;
}
log.info("共调用了{}次", turns);
Assert.assertEquals(turns, atomicInteger.get());
// 顺序也一致
for(int i =0; i< mockDataList.size();i++){
Assert.assertEquals((Integer) mockDataList.get(i).length(), resultList.get(i));
}
}
private List someCall(Long id, List strList) {
log.info("当前-->{}，strList.size：{}", atomicInteger.incrementAndGet(), strList.size());
try {
TimeUnit.SECONDS.sleep(2L);
} catch (InterruptedException e) {
e.printStackTrace();
}
return strList.stream()
.map(String::length)
.collect(Collectors.toList());
}
通过异步可以尽可能快得拿到执行结果。
四、总结1 要灵活运用Java 8 的 特性简化代码
2 要注意代码的封装来使代码更加优雅,复用性更强
3 要利用来构造单元测试的数据框架如 java-faker和easy-random来提高构造数据的效率
4 要了解性能改进的常见思路：合并请求、并发、并行、缓存等。
