Java8-实践

• Map的双重循环

      //对map的entry对象来做stream操作，使用两次forEach    Map<String, Long> map = new HashMap<>();    crowdMap.entrySet().stream()            .map(Map.Entry::getValue)            .forEach(x -> x.entrySet().forEach(y -> {                if (map.containsKey(y.getKey()))                    map.put(y.getKey(), map.get(y.getKey()) + y.getValue());                else map.put(y.getKey(), y.getValue());            }));    //对map的entry对象来做stream操作，使用flatMap将stream合并    Map<String, Long> map = new HashMap<>();    crowdMap.entrySet().stream()            .map(Map.Entry::getValue)            .flatMap(x -> x.entrySet().stream())            .forEach(y -> {                if (map.containsKey(y.getKey()))                    map.put(y.getKey(), map.get(y.getKey()) + y.getValue());                else map.put(y.getKey(), y.getValue());            });    //使用map本身的foreach语句                Map<String, Long> map = new HashMap<>();    crowdMap.forEach((key, value) -> value.forEach((x, y) -> {        if (map.containsKey(x))            map.put(x, map.get(x) + y);        map.put(x, y);    }));

• List的多次分组

      //使用groupingBy将ApproveRuleDetail对象分别按照item和detail分组，并计次    Map<String, Map<String, Long>> detailMap = approveRuleDetailList.stream()            .collect(Collectors                    .groupingBy(ApproveRuleDetail::getItem, Collectors.                            groupingBy(ApproveRuleDetail::getDetail, Collectors.counting())));

• List按照自定义条件分组

      //使用自定义的Function函数，将年龄按照每10岁分组    Function<Integer, Integer> ageGroup = x -> x / 10;    Map<Integer, List<StatisticsPipeline>> ageMap = statisticsPipelineList            .stream()            .collect(Collectors.groupingBy(y -> ageGroup.apply(y.getAge())));

      //将年龄按不同方式分组    Function<Integer, Integer> ageCredit = x -> {        if (x <= 18)            return 18;        else if (x >= 40)            return 40;        else return x;    };    //将StatisticsPipeline转化为suggestion    ToDoubleFunction<StatisticsPipeline> mapper = StatisticsPipeline::getSuggestion;    //将人群按照不同年龄分组，并计算每个年龄段的suggestion的平均值    Map<Integer, Double> ageCreditMap = statisticsPipelineList            .stream()            .collect(Collectors.groupingBy(y -> ageCredit.apply(y.getAge()), Collectors.averagingDouble(mapper)));

• 多个数据求集合

      //合并数据    private BiFunction<Integer[], ApprovePipeline, Integer[]> accumulator = (x, y) -> new Integer[]{            x[0] + y.getAuth(), x[1] + y.getAntiFraud(), x[2] + y.getCreditRule(), x[3] + y.getModelReject(), x[4] + y.getSuggestion()    };    //合并集合    private BinaryOperator<Integer[]> combiner = (x, y) -> new Integer[]{x[0] + y[0], x[1] + y[1], x[2] + y[2], x[3] + y[3], x[4] + y[4]};    //将ApprovePipeline对象的不同数据相加    Integer[] detail = approvePipelineList.stream().reduce(new Integer[]{0, 0, 0, 0, 0}, accumulator, combiner);

• 多个数据求集合-多重合并

      private BiFunction<Integer[], ApprovePipeline, Integer[]> accumulator = (x, y) -> new Integer[]{        x[0] += y.getAuth(), x[1] += y.getAntiFraud(), x[2] += y.getCreditRule(), x[3] += y.getModelReject(), x[4] += y.getSuggestion()    };    //合并数据    BiFunction<Integer[], Map.Entry<String, List<ApprovePipeline>>, Integer[]> newAccumulator = (x, y) -> {        List<ApprovePipeline> pipelineList = y.getValue();        Integer[] data = pipelineList.stream().reduce(new Integer[]{0, 0, 0, 0, 0}, accumulator, combiner);        return new Integer[]{                x[0] += data[0], x[1] += data[1], x[2] += data[2], x[3] += data[3], x[4] += data[4]        };    };    //最终reduce    Integer[] total = channelMap.entrySet().stream().reduce(new Integer[]{0, 0, 0, 0, 0}, newAccumulator, combiner);

• map最大多项和

  Long hourC3 = hourMap.entrySet().stream().mapToLong(Map.Entry::getValue).sorted().limit(3).sum();

  项目地址：https://github.com/MyHerux/java-java8-learning