sql优化：数据量过大查询优化

    public List<Map> getCiServiceBadEvaNumStatistic(SAASIndexQuery saasIndexQuery) throws InvocationTargetException, IllegalAccessException {
        String startDate = saasIndexQuery.getStartDate();
        String endDate = saasIndexQuery.getEndDate();
        int days = DateUtil.getDatebetweenOfDayNum(DateUtil.parseDate(startDate,DateUtil.dateFormatPattern),DateUtil.parseDate(endDate,DateUtil.dateFormatPattern));

        CompletionService<List<CiOrderStatisticSection>> completionService = new ExecutorCompletionService<List<CiOrderStatisticSection>>(executorService);

        List<CiOrderStatisticSection> allList = new ArrayList<>();

        long start = System.currentTimeMillis();
        logger.info("测试异步时间start:" + System.currentTimeMillis());
        //CountDownLatch countDownLatch = new CountDownLatch(days);
        SAASIndexQuery everyDaySaas = new SAASIndexQuery();
        BeanUtils.copyProperties(everyDaySaas,saasIndexQuery);
        for(int i = 0;i<days;i++){
            everyDaySaas.setStartDate(DateUtil.afterNDay(saasIndexQuery.getStartDate(),i,DateUtil.dateFormatPattern));
            everyDaySaas.setEndDate(DateUtil.afterNDay(everyDaySaas.getStartDate(),1,DateUtil.dateFormatPattern));
            //countDownLatch.countDown();
            int finalI = i;
            completionService.submit(new Callable<List<CiOrderStatisticSection>>() {
                @Override
                public List<CiOrderStatisticSection> call() throws Exception {
                    //allList.addAll(biSaasCiDeviceDayExMapper.getCiServiceNegativeRate(saasIndexQuery));
                    //countDownLatch.countDown();
                    System.out.println("====="+ finalI +"=====");
                    return biSaasCiDeviceDayExMapper.getCiServiceNegativeRate(saasIndexQuery);
                }
            });
        }
        System.out.println("==============" + (System.currentTimeMillis()-start) + "毫秒");
        long t = System.currentTimeMillis();
        for (int i = 0;i<days;i++){
            System.out.println("for循环耗时==============+"+i + (System.currentTimeMillis()-t) + "毫秒");

            try {
                Future<List<CiOrderStatisticSection>> future = completionService.take();
                List<CiOrderStatisticSection>  ciList = future.get();
                allList.addAll(ciList);
            } catch (InterruptedException e) {
                e.printStackTrace();
            } catch (ExecutionException e) {
                e.printStackTrace();
            }
        }
        long end = System.currentTimeMillis();
        logger.info("测试异步时间end:" + (end-start) + "毫秒");
        System.out.println("测试异步时间end:" + (end-start) + "毫秒");

}

测试后发现不对，使用多线程的take方式 每次都会有阻塞，这个阻塞一直没明白是哪里阻塞了？ 是线程池、LinkedBlockingDeque 还是for循环 take时候 阻塞了 一直没明白，观察的结果就是每次for循环都要差不多200多毫秒，30个循环要6s多。。。。额，算了 ，还没有原来快呢

2.昨天换了种思路：直接从数据库查询时候做好控制。每次查询先根据月份和年份，查询出来id的最大值和最小值，之后sql里面查询时候加上id在这个最大值和最小是区间内。大概思路是这样：嗯，结果竟然可以。

sql优化：数据量过大查询优化

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