java list和map切割分段的实现及多线程应用案例
更新时间:2023年12月24日 15:08:04 作者:蚕1蚕2
这篇文章主要为大家介绍了java list和map切割分段的实现及多线程应用案例,有需要的朋友可以借鉴参考下,希望能够有所帮助,祝大家多多进步,早日升职加薪
map工具类
/** * @author chengxianwei * @title map工具类 * @date 2023/08/03 **/ public class MapUtil { /** * List拆分 (指定分组大小) * * @param chunkList 被分隔的数组 * @param chunkNum 每段的大小 * @param <T> List中的类型 * @return */ public static <T> List<List<T>> listChunk(List<T> chunkList, int chunkNum) { if (chunkList == null || chunkNum <= 0) { List<List<T>> t = new ArrayList<>(); t.add(chunkList); return t; } Iterator<T> iterator = chunkList.iterator(); int i = 1; List<List<T>> total = new ArrayList<>(); List<T> tem = new ArrayList<>(); while (iterator.hasNext()) { T next = iterator.next(); tem.add(next); if (i == chunkNum) { total.add(tem); tem = new ArrayList<>(); i = 0; } i++; } if (!ChargeEmptyUtil.isEmpty(tem)) { total.add(tem); } return total; } /** * Map拆分 (指定分组大小) * * @param chunkMap 被切段的map * @param chunkNum 每段的大小 * @param <k> map的key类型 * @param <v> map的value类型 如果是自定义类型,则必须实现equals和hashCode方法 * @return */ public static <k, v> List<Map<k, v>> mapChunk(Map<k, v> chunkMap, int chunkNum) { if (chunkMap == null || chunkNum <= 0) { List<Map<k, v>> list = new ArrayList<>(); list.add(chunkMap); return list; } Set<k> keySet = chunkMap.keySet(); Iterator<k> iterator = keySet.iterator(); int i = 1; List<Map<k, v>> total = new ArrayList<>(); Map<k, v> tem = new HashMap<>(); while (iterator.hasNext()) { k next = iterator.next(); tem.put(next, chunkMap.get(next)); if (i == chunkNum) { total.add(tem); tem = new HashMap<>(); i = 0; } i++; } if (!ChargeEmptyUtil.isEmpty(tem)) { total.add(tem); } return total; } /** * Map拆分 (指定分组大小) * * @param map Map * @param chunkSize 每个分组的大小 (>=1) * @param <K> Key * @param <V> Value * @return 子Map列表 */ public static <K, V> List<Map<K, V>> splitByChunkSize(Map<K, V> map, int chunkSize) { if (Objects.isNull(map) || map.isEmpty() || chunkSize < 1) { //空map或者分组大小<1,无法拆分 return Collections.emptyList(); } int mapSize = map.size(); //键值对总数 int groupSize = mapSize / chunkSize + (mapSize % chunkSize == 0 ? 0 : 1); //计算分组个数 List<Map<K, V>> list = Lists.newArrayListWithCapacity(groupSize); //子Map列表 if (chunkSize >= mapSize) { //只能分1组的情况 list.add(map); return list; } int count = 0; //每个分组的组内计数 Map<K, V> subMap = Maps.newHashMapWithExpectedSize(chunkSize); //子Map for (Map.Entry<K, V> entry : map.entrySet()) { if (count < chunkSize) { //给每个分组放chunkSize个键值对,最后一个分组可能会装不满 subMap.put(entry.getKey(), entry.getValue()); count++; //组内计数+1 } else { //结束上一个分组 list.add(subMap); //当前分组装满了->加入列表 //开始下一个分组 subMap = Maps.newHashMapWithExpectedSize(chunkSize); //新的分组 subMap.put(entry.getKey(), entry.getValue()); //添加当前键值对 count = 1; //组内计数重置为1 } } list.add(subMap); //添加最后一个分组 return list; } /** * Map拆分(指定分组个数) * * @param map Map * @param groupSize 分组个数 (>=1) * @param <K> Key * @param <V> Value * @return 子Map列表 */ public static <K, V> List<Map<K, V>> splitByGroupSize(Map<K, V> map, int groupSize) { if (Objects.isNull(map) || map.isEmpty() || groupSize < 1) { //空map或者分组数<1,无法拆分 return Collections.emptyList(); } List<Map<K, V>> list = Lists.newArrayListWithCapacity(groupSize); if (groupSize == 1) { //只有1个分组的情况 list.add(map); return list; } int mapSize = map.size(); //键值对总数 int chunkIndex = 0; //当前分组的下标,[0, groupSize-1] int restCount = mapSize % groupSize; //平均后剩余的键值对数 int chunkSize0 = mapSize / groupSize; //每个分组键值对数量 int chunkSize1 = chunkSize0 + 1; //多分一个 int chunkSize = chunkIndex < restCount ? chunkSize1 : chunkSize0; //实际每组的大小(前面的部分分组可能会多分1个) int count = 0; //每个分组的组内计数 Map<K, V> subMap = Maps.newHashMapWithExpectedSize(chunkSize);//子Map for (Map.Entry<K, V> entry : map.entrySet()) { if (count < chunkSize) { //每个分组按实际分组大小(chunkSize)加入键值对 subMap.put(entry.getKey(), entry.getValue()); count++; //组内计数+1 } else { //结束上一个分组 list.add(subMap); //当前分组装满了->加入列表 chunkIndex++; //分组个数+1 //开始下一个分组 chunkSize = chunkIndex < restCount ? chunkSize1 : chunkSize0; //重新计算分组大小 subMap = Maps.newHashMapWithExpectedSize(chunkSize); //新的分组 subMap.put(entry.getKey(), entry.getValue()); //添加当前键值对 count = 1; //组内计数重置为1 } } list.add(subMap); //添加最后一个分组 return list; } //测试 public static void main(String[] args) { Map<String, String> map = new HashMap<>(); map.put("a", "1"); map.put("b", "2"); map.put("c", "3"); map.put("d", "4"); map.put("e", "5"); map.put("f", "6"); map.put("g", "7"); System.out.println("splitByChunkSize: " + splitByChunkSize(map, 3)); System.out.println("splitByGroupSize: " + splitByGroupSize(map, 3)); } }
应用案例
List分段
{ // 导出动态标题 List<String> titleList = new ArrayList<>(); // 上网电量和发电量 String[] monthKeyArr = {"powernetday", "powerday"}; // 获取导出电站基础数据 List<XczxPoverPhotovolSourceVO>[0] = new ArrayList<>(); // 保存成<consNo, <日电量数据列表>> 形式 ConcurrentHashMap<String, List<XczxPoverPhotovolSourceDayEleVO>> xczxPovertyPowerDayListMap = new ConcurrentHashMap<>(); ... ... ... // 多线程分段批量处理List列表 int threadSize = 2000;//每2000条开启一个任务 int dataSize = xczxPoverPhotovolSourceVOList[0].size(); int threadNum = dataSize / threadSize + 1;// 开启的任务数 boolean special = dataSize % threadSize ==0;// 表计整除 (threadNum多算了一次) Callable<Integer> task = null; List<XczxPoverPhotovolSourceVO> curList = null; List<Callable<Integer>> tasks = new ArrayList<>(); ExecutorService exec = Executors.newCachedThreadPool(); CountDownLatch countDownLatch = new CountDownLatch(threadNum); // 使用Collections将线程不安全的集合转成线程安全的集合 List<Map<String, Object>> dataList = Collections.synchronizedList(new ArrayList<>(dataSize)); for (int i = 0; i < threadNum; i++) { if (i == threadNum - 1) { if(special){ countDownLatch.countDown(); break; } curList = xczxPoverPhotovolSourceVOList[0].subList(threadSize * i, dataSize); } else { curList = xczxPoverPhotovolSourceVOList[0].subList(threadSize * i, threadSize * (i + 1)); } final List<XczxPoverPhotovolSourceVO> list2 = curList; task = new Callable<Integer>() { @Override public synchronized Integer call() throws Exception { try { XczxPoverPhotovolSourceVO next = null; Date parallelInTime = null; Map<String, Object> map = null; List<Map<String, Object>> totalList = null; Map<String, Object> totalMap = null; List<Map<String, Object>> povertyList = null; Map<String, Object> entityMap = null; XczxPoverPhotovolSourceDayEleVO next2 = null; XczxPoverPhotovolSourceDayEleVO curDayEle = null; List<XczxPoverPhotovolSourceDayEleVO> list = null; List<XczxPoverPhotovolSourceDayEleVO> listDay = new ArrayList<>(); // 迭代导出电站基础数据 Iterator<XczxPoverPhotovolSourceVO> iterator = list2.iterator(); while (iterator.hasNext()) { next = iterator.next(); map = CommonUtils.transClassToMapLowCase(next); // 合计 集合 totalList = new ArrayList<>(); totalMap = new HashMap<>(); // 合计 BigDecimal powerNetTotal = new BigDecimal(BigInteger.ZERO); BigDecimal powerTotal = new BigDecimal(BigInteger.ZERO); // 指定日期的 户号列表 17123 listDay = xczxPovertyPowerDayListMap.get(""+next.getId()); if (listDay != null && listDay.size() > 0) { // 遍历一个户号 所有日期 for (int i = 0; i < titleList.size() - 1; i++) { String date = titleList.get(i).substring(0, 4) + titleList.get(i).substring(5, 7) + titleList.get(i).substring(8, 10); list = listDay.stream().filter(x -> date.equals(x.getPovertyDay())).collect(Collectors.toList()); povertyList = new ArrayList<>(); entityMap = new HashMap<>(); if (list != null && list.size() > 0) { for (XczxPoverPhotovolSourceDayEleVO vo : list) { entityMap.put(monthKeyArr[0] + titleList.get(i), new BigDecimal(vo.getPowerNetDay())); entityMap.put(monthKeyArr[1] + titleList.get(i), new BigDecimal(vo.getPowerDay())); powerNetTotal = powerNetTotal.add(new BigDecimal(vo.getPowerNetDay())); powerTotal = powerTotal.add(new BigDecimal(vo.getPowerDay())); povertyList.add(entityMap); } } else { // 如果为空,填充0 entityMap.put(monthKeyArr[0] + titleList.get(i), "0"); entityMap.put(monthKeyArr[1] + titleList.get(i), "0"); povertyList.add(entityMap); } map.put(day + titleList.get(i), povertyList); } } else { // 遍历一个户号 所有日期 for (int i = 0; i < titleList.size() - 1; i++) { povertyList = new ArrayList<>(); entityMap = new HashMap<>(); // 如果为空,填充0 entityMap.put(monthKeyArr[0] + titleList.get(i), "0"); entityMap.put(monthKeyArr[1] + titleList.get(i), "0"); povertyList.add(entityMap); povertyList.add(entityMap); map.put(day + titleList.get(i), povertyList); } } // 合计模型 totalMap.put(monthKeyArr[0] + "合计", powerNetTotal); totalMap.put(monthKeyArr[1] + "合计", powerTotal); totalList.add(totalMap); map.put(day + "合计", totalList); dataList.add(map); map.put("xh", dataList.size()); } } catch (Exception e) { log.error("catch error",e); } finally { countDownLatch.countDown(); return 1; } } }; tasks.add(task); } // 多线程并发 List<Future<Integer>> futureList = null; try { futureList = exec.invokeAll(tasks); for(Future<Integer> future : futureList){ if(future!=null) { while (!future.isDone()); } } countDownLatch.await(); } catch (Exception e) { log.error("catch error",e); } finally { exec.shutdown(); } ... ... ... }
Map分段
{ ... ... ... // <户主身份证号, List<户主成员(含户主)>> 集合档案信息 Map<String, List<XczxArchives>> impListMap = new HashMap<>(); ... ... ... // 多线程分段批量处理Map集合 int threadSize = 2000;// 每2000条开启一个任务 int dataSize = impListMap.size();// map数据条数 int threadNum = dataSize / threadSize + 1;// 开启的任务数 List<Callable<Integer>> tasks = new ArrayList<>(); ExecutorService exec = Executors.newCachedThreadPool(); List<Map<String, List<XczxArchives>>> splitGroup = MapUtil.splitByChunkSize(impListMap, threadSize); for (int i = 0; i < threadNum; i++) { Map<String, List<XczxArchives>> curLists = splitGroup.get(i); // 新建一个并发任务 Callable<Integer> task = new Callable<Integer>() { @Override public Integer call() throws Exception { int count = 0; // iterator遍历分段Map Iterator<Map.Entry<String, List<XczxArchives>>> entryIterator = curLists.entrySet().iterator(); while (entryIterator.hasNext()) { XczxArchives head = null; Map.Entry<String, List<XczxArchives>> entry = entryIterator.next(); String key = entry.getKey();// 户主身份证号 List<XczxArchives> list = entry.getValue();// 户主及成员列表 Iterator<XczxArchives> dataIterator = list.iterator(); while (dataIterator.hasNext()) { XczxArchives next = dataIterator.next(); if (key.equals(next.getIdCard())) { head = next; dataIterator.remove(); } } if (head != null) { // 插入户主 head.setHeadName(null); head.setHeadIdCard(null); head.setHeadMobile(null); head.setCreateTime(date); head.setUpdateTime(date); int result = xczxArchivesMapper.insert(head); if (result == 1) { count++; if (list != null && list.size() > 0) { for (XczxArchives next : list) { next.setCreateTime(date); next.setUpdateTime(date); next.setHeadId(head.getArchivesId()); } // 插入成员 int result2 = xczxArchivesMapper.batchInsert(list); if (result2 > 0) { count = count + result2; } } } } } return count; } }; tasks.add(task); } // 多线程并发 List<Future<Integer>> futureList = null; try { futureList = exec.invokeAll(tasks); for (Future<Integer> future : futureList) { if (future != null) { while (!future.isDone()); successCount = successCount + future.get(); } } } catch (Exception e) { log.error("catch error",e); } finally { exec.shutdown(); } ... ... ... }
以上就是java list和map切割分段的实现及多线程应用案例的详细内容,更多关于java list map多线程切割分段的资料请关注脚本之家其它相关文章!
相关文章
Java OpenSSL生成的RSA公私钥进行数据加解密详细介绍
这篇文章主要介绍了Java OpenSSL生成的RSA公私钥进行数据加解密详细介绍的相关资料,这里提供实例代码及说明具体如何实现,需要的朋友可以参考下2016-12-12SpringBoot整合PageHelper实现分页查询功能详解
PageHelper是mybatis框架的一个插件,用于支持在mybatis执行分页操作。本文将通过SpringBoot整合PageHelper实现分页查询功能,需要的可以参考一下2022-03-03
最新评论