用10个一次拉2吨的卡车代替1个一次拉10吨的卡车。前提是有资源折腾,比如线程池,多核cpu,也要考虑线程的切换代价。把java服务器和数据库服务器综合利用起来,传统的方式是java服务器发送一条指令给数据库就坐等喝茶拿结果,数据库累个半死才出结果,而且出力不讨好,嫌干活慢,现在也要让java服务器也要干点事,这样大家都心里比较平衡点。


List<CompletableFuture<List<TimesAndAmount>>>  allStationsTimesAmount =
        inputParamArrayList.stream()
                .map(inputParam -> CompletableFuture.supplyAsync(() ->nonOilSalesAndPerCustomerTransactionDao.getTimesHoursInterval(inputParam), executorService))
                .collect(Collectors.toList());

List<List<TimesAndAmount>>  timesAmount = allStationsTimesAmount.stream()
        .map(CompletableFuture::join)
        .collect(Collectors.toList());
private List<String> getBarcodeList(String[] deptIds, String[] ids) {

    List<String> list = new ArrayList<>();
    List<String> list1 = new ArrayList<>();
    if (deptIds != null){
        list = Arrays.asList(deptIds);

        List<CompletableFuture<List<String>>>  allBarcodes =
                list.stream()
                        .map(inputParam -> CompletableFuture.supplyAsync(() ->nonOilSalesAndPerCustomerTransactionDao.getBarcodesBydeptid(inputParam), executorService))
                        .collect(Collectors.toList());

        List<List<String>>  listList = allBarcodes.stream()
                .map(CompletableFuture::join)
                .collect(Collectors.toList());
//List<List<String>> 转换为List<String> ,使用flatMap
list1 =
                listList.stream()
                        .flatMap(inner -> inner.stream()).collect(Collectors.toList());


    }

    if (ids != null){
        list1.addAll(Arrays.asList(ids));
    }

    return list1;

}