一、mysql怎么查詢連續(xù)時間段的最大值

按儀器與時間（處理成小時）group by，計算值的數(shù)量與和，再根據(jù)結果判斷值數(shù)量是否有缺失值，以及和的最大值。首先要明確采集標準，比如說一分鐘采集一條記錄，那么可以group by 小時。

– Step1 創(chuàng)建表

CREATE TABLE monitor(

id int not null auto_increment,

seq_no int,

add_time DATETIME,

stat int,

primary key(id)

);

— Step2 初始化記錄，這里的6點和7點的數(shù)據(jù)完整，其中6點的有重復記錄。

INSERT INTO monitor(seq_no,add_time,stat)

SELECT 1,’2021-6-10 6:0′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:1′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:2′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:3′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:4′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:5′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:6′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:7′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:8′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:9′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:10′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:11′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:12′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:13′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:14′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:15′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:16′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:17′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:18′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:19′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:20′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:21′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:22′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:23′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:24′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:25′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:26′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:27′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:28′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:29′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:30′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:31′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:32′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:33′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:34′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:35′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:36′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:37′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:38′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:39′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:40′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:41′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:42′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:43′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:44′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:45′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:46′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:47′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:48′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:49′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:50′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:51′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:52′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:53′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:54′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:55′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:56′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:57′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:58′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:58′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 6:59′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:0′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:1′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:2′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:3′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:4′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:5′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:6′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:7′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:8′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:9′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:10′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:11′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:12′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:13′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:14′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:15′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:16′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:17′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:18′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:19′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:20′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:21′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:22′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:23′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:24′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:25′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:26′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:27′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:28′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:29′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:30′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:31′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:32′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:33′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:34′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:35′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:36′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:37′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:38′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:39′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:40′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:41′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:42′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:43′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:44′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:45′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:46′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:47′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:48′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:49′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:50′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:51′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:52′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:53′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:54′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:55′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:56′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:57′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:58′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 1,’2021-6-10 7:59′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:1′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:2′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:3′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:4′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:5′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:6′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:7′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:8′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:9′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:10′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:11′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:12′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:13′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:14′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:15′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:16′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:17′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:18′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:19′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:20′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:21′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:22′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:23′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:24′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:25′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:26′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:27′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:28′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:29′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:30′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:31′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:32′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:33′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:34′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:35′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:36′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:37′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:38′ ,FLOOR(1 + (RAND() * 101)) UNION ALL

SELECT 2,’2021-6-10 8:39′ ,FLOOR(1 + (RAND() * 101)) ;

— Step3 查詢

— scenario1 查詢不完整的，這里加去重是為了剔除重復記錄。

SELECT seq_no,CONCAT(DATE(add_time),’#’,HOUR(add_time))date_hour,COUNT(DISTINCT add_time) record_cnt

FROM monitor A

GROUP BY seq_no,CONCAT(DATE(add_time),’#’,HOUR(add_time))

HAVING COUNT(DISTINCT add_time)<60

/*

結果

seq_no date_hour record_cnt

2?? 2021-06-10#8? 39

*/

— scenario1，按天查詢固定小時周期內總和的最大值，如果有重復數(shù)據(jù)需加邏輯去重（當前未考慮）

SELECT SUBSTR(date_hour,1,INSTR(date_hour,’#’)-1) date_only,MAX(sum_hour) max_daily

FROM

??? (

?????? SELECT A.seq_no,B.date_hour,SUM(A.stat) sum_hour

?????? FROM monitor A

?????? JOIN(

?????????? SELECT seq_no,CONCAT(DATE(add_time),’#’,HOUR(add_time)) date_hour,COUNT(DISTINCT add_time) record_cnt

?????????? FROM monitor A

?????????? GROUP BY seq_no,CONCAT(DATE(add_time),’ ‘,HOUR(add_time))

?????????? HAVING COUNT(DISTINCT add_time)=60

?????????? )B

?????????? ON A.seq_no = B.seq_no

?????????? AND CONCAT(DATE(add_time),’#’,HOUR(add_time)) = B.date_hour

?????? GROUP BY A.seq_no,B.date_hour

??? )C

GROUP BY SUBSTR(date_hour,1,INSTR(date_hour,’#’)-1)

/*

結果

date_only max_daily

2021-06-10 3289

*/

— 3 針對任意小時的，建議通過存儲過程(定義起始時間、時間比較跨度)結合窗口函數(shù)（:= 模擬窗口函數(shù)）處理

— 補注 1 當前腳本用了隨機數(shù),關于字段state的統(tǒng)計結果不固定。

—????? 2 當前演示數(shù)據(jù)庫是mysql 5.6.14。

延伸閱讀：

二、什么是數(shù)據(jù)庫和數(shù)據(jù)庫管理系統(tǒng)

數(shù)據(jù)庫的應用非常廣泛，舉個例子，我們平時在瀏覽器上搜索內容，就要用到數(shù)據(jù)庫去檢索我們的關鍵字。以前我們可能會用數(shù)組、集合、文件等來存儲數(shù)據(jù)，但是接下來我們就會面臨一個問題，當存儲的數(shù)據(jù)或內容過多的時候，我們如何去精準的找到我們需要的東西，這時候數(shù)據(jù)庫管理系統(tǒng)就派上了用場。除此之外，數(shù)據(jù)庫管理系統(tǒng)還能永久的儲存我們的數(shù)據(jù)。

為了便于大家理解，這里先給大家講解幾個概念

DB數(shù)據(jù)庫（database)：存儲數(shù)據(jù)的“倉庫”。它保存了一系列有組織的數(shù)據(jù)。

DBMS數(shù)據(jù)庫管理系統(tǒng)（Database Management System)：數(shù)據(jù)庫是通過DBMS創(chuàng)建和操作的容器。

SQL，結構化查詢語言（Structured Query Language）用一句話概括，SQL是一種特殊目的的編程語言，一種專門用來與數(shù)據(jù)庫通信的語言。在數(shù)據(jù)庫中，數(shù)據(jù)被結構化并存儲在不同的表中，從而簡化了訪問，更新和操作數(shù)據(jù)的過程。該表由列和行組成。數(shù)據(jù)庫中的表可以在關系的幫助下進行連接。要在數(shù)據(jù)庫中執(zhí)行與數(shù)據(jù)相關的任務，可以使用SQL。SQL代表結構化查詢語言，旨在在特定RDBMS內創(chuàng)建，修改和管理數(shù)據(jù)庫中的數(shù)據(jù)。

SQL優(yōu)點：

1、不是某個特定數(shù)據(jù)庫供應商專有的語言，幾乎所有DBMS（數(shù)據(jù)庫管理系統(tǒng)）都支持SQL

2、簡單易學

3、雖然簡單，但實際上是一種強有力的語言，靈活使用其語言元素，可以進行非常復雜和高級的數(shù)據(jù)庫操作。