一、Stream
Map
[1] list 转 map，避免重复key， 重复时，使用第一个value
list.stream().collect(Collectors.toMap(People::getName, Function.identity(), (k, v) -> k));
[2] list 转 map，避免null value，null value会出错
systems.stream().collect(Collectors.toMap(ThingInfo::getId,
system -> StringUtils.isBlank(system.getProjectName()) ? "" : system.getProjectName(),
(k, v) -> k));
【3】 遍历
for (Map.Entry<Integer, Integer> entry : map.entrySet()) { System.out.println("key = " + entry.getKey() + ", value = " + entry.getValue()); }
过滤
[1]
templates.stream().filter(template -> template.getColumnName().equals(column)).findFirst()
.map(ReportHeadTemplate::getColumnType).orElse("")
Option
1、判断map结果不为空，再给对象set 属性值
Optional.ofNullable(userIdInfoMap.get(name))
.ifPresent(userInfo -> evaluationInfo.setEvaluatorUser(userInfo.getName()));
2、集合判断 为空返回空集合
List<String> list = null;
List<String> newList = Optional.ofNullable(list).orElse(new ArrayList());
newList.forEach(x -> System.out.println(x));
分组
1. 分组成map<key，bean>
Map<Long, List<OtaTaskVehicle>> vehicleListMap = vehicleList.stream()
.collect(Collectors.groupingBy(veh -> veh.getTaskId()));
2. 分组后提取对象中某个属性
Map<Long, Set<Long>> nodeIdMap = topologyNodes.stream()
.collect(Collectors.groupingBy(
TopologyNodeInfoSync::getThingId, // 1. 按 thingId 分组
Collectors.mapping( // 2. 对每个分组内的元素进行映射
TopologyNodeInfoSync::getId, // 2.1 提取 id
Collectors.toSet() // 2.2 收集到 Set 中
)
));
三、运算
日期转换
DatePattern.NORM_DATE_PATTERN = "yyyy-MM-dd";
DatePattern.NORM_DATETIME_PATTERN = "yyyy-MM-dd HH:mm:ss";
[1] 日期转字符串
当前时间 Date date = DateUtil.date();
// 结果 2020/01/24
String format = DateUtil.format(date, "yyyy/MM/dd");
//常用格式的格式化，结果：2020-01-24
String formatDate = DateUtil.formatDate(date);
//结果：2020-01-24 17:25:02
String formatDateTime = DateUtil.formatDateTime(date);
[2] 字符串转日期
String dateStr = "2017-03-01";
Date date = DateUtil.parse(dateStr, "yyyy-MM-dd");
日期计算
DatePattern.NORM_DATE_PATTERN = "yyyy-MM-dd";
DatePattern.NORM_DATETIME_PATTERN = "yyyy-MM-dd HH:mm:ss";
[1] 日期转字符串
当前时间 Date date = DateUtil.date();
//常用格式的格式化，结果：2020-01-24
String formatDate = DateUtil.formatDate(date);
//结果：2020-01-24 17:25:02
String formatDateTime = DateUtil.formatDateTime(date);
[2] 字符串转日期
String dateStr = "2017-03-01";
Date date = DateUtil.parse(dateStr, "yyyy-MM-dd");
-- 获取一天开始的时间 00:00
LocalDateTime cleanTaskEndTime.truncatedTo(ChronoUnit.DAYS)
日期加减
LocalDateTime cleanTaskEndTime.plusDays(1)
两日期 之间天数
long daysBetween = Duration.between(cleanTaskEndTime.truncatedTo(ChronoUnit.DAYS), now).toDays();
两日期之间的每一天
private List<DateTime> between(DateTime start, DateTime end) {
List<DateTime> dateTimes = new ArrayList<>();
for (DateTime dateTime = start; dateTime.isBefore(end); dateTime = dateTime.offset(DateField.DAY_OF_MONTH, 1)) {
dateTimes.add(dateTime);
}
// 添加结束日期（可选，取决于是否需要包含结束日期）
dateTimes.add(end);
return dateTimes;
}
数字类
[1] 对 list 某个字段求和
BigDecimal eForecastTotal = sumBigDecimalField(reportTags, CleaningReportTag::getEForecast);;
public static <T> BigDecimal sumBigDecimalField(List<T> list, Function<T, BigDecimal> fieldExtractor) {
// 1. 处理列表为 null 或空的情况
if (list == null || list.isEmpty()) {
return BigDecimal.ZERO;
}
// 2. 通用累加逻辑：提取字段 → 处理 null → 累加
return list.stream()
// 提取字段，null 则替换为 0 .map(item -> Optional.ofNullable(fieldExtractor.apply(item)).orElse(BigDecimal.ZERO))
// 累加所有值
.reduce(BigDecimal.ZERO, BigDecimal::add);
}
对象
[1] 根据id填充List中name属性，map中取值
waterDevices.stream().filter(waterDevice -> stationIdNameMap.containsKey(waterDevice.getProjectId()))
.forEach(waterDevice -> {
String projectName = stationIdNameMap.get(waterDevice.getProjectId());
waterDevice.setProjectName(projectName);
});
json
1. json转成javabean
List<String> columns =
JacksonUtils.getJsonConvert().fromJsonList(userSelectionInfo.getInfoJson(), String.class);
集合
[1] 将List 拆成子list数量固定的多个 list ， 每一个子List size是NUMBER_TWO
import com.google.common.collect.Lists; List<List<String>> partition = Lists.partition(initNumA(), NUMBER_TWO);
[2] 将List 拆成固定数量 子List
public static <T> List<List<T>> splitListByNum(List<T> list, int parts) {
List<List<T>> result = new ArrayList<>();
int totalSize = list.size();
// 每个子列表的平均大小
int baseSize = totalSize / parts;
// 计算多余的元素
int remainder = totalSize % parts;
int index = 0;
for (int i = 0; i < parts; i++) {
// 计算每个子列表的实际大小
int currentSize = baseSize + (i < remainder ? 1 : 0); // 前 remainder 个子列表多一个元素
List<T> sublist = new ArrayList<>();
// 把当前子列表的元素放入
for (int j = 0; j < currentSize; j++) {
sublist.add(list.get(index++));
}
result.add(sublist);
}
return result;
}
[3] 取两个字段组成新对象
List<CarDTO> carDTOS = cars.stream().map (e -> new CarDTO(e.getCountry(), e.getName())).collect(Collectors.toList());
redis
private SystemCleaningReportQueryResp queryCleanReportByTaskId(Long taskId) {
String taskDate = taskId + "-" + DateUtil.format(new Date(), "yyyy-MM-dd");
String key = formatTempRedisKey(taskDate);
if (redisTemplate.opsForValue().get(key) != null) {
log.warn("queryCleanReportByTaskId-key:{} queryByCate", key);
return JacksonUtils.getJsonConvert().fromJsonString((String)redisTemplate.opsForValue().get(key),
SystemCleaningReportQueryResp.class);
} else {
log.warn("queryCleanReportByTaskId-key:{} queryByInterface", key);
SystemCleaningReportQueryResp systemCleaningReport = querySystemCleaningReport(taskId);
redisTemplate.opsForValue().set(key, JacksonUtils.getJsonConvert().toJsonString(systemCleaningReport), 1,
TimeUnit.DAYS);
return systemCleaningReport;
}
}
private String formatTempRedisKey(String tempId) {
return String.format(TEMP_FILTER_REDIS_KEY, tempId);
}
private static final String TEMP_FILTER_REDIS_KEY = "clean:report:%s";
