Comment implémenter des statistiques de groupe toutes les 10 minutes dans MYSQL

Système de gestion de bases de données relationnelles MySQL

MySQL est un petit système de gestion de bases de données relationnelles open source développé par la société suédoise MySQL AB. MySQL est largement utilisé sur les sites Web de petite et moyenne taille sur Internet. En raison de sa petite taille, de sa vitesse rapide, de son faible coût total de possession et surtout des caractéristiques de l'open source, de nombreux sites Web de petite et moyenne taille choisissent MySQL comme base de données de site Web afin de réduire le coût total de possession d'un site Web.

Cet article présente principalement comment utiliser MYSQL pour implémenter des statistiques de groupe toutes les 10 minutes. L'article donne un exemple de code détaillé. Je pense qu'il sera utile à tout le monde pour comprendre et apprendre. a une certaine valeur de référence. Les amis dans le besoin peuvent jeter un œil ci-dessous.

Avant-propos

Le contenu de cet article présente principalement la méthode de mise en œuvre des statistiques de groupe MYSQL toutes les 10 minutes. Lors de l'élaboration du graphique de distribution de l'état de connexion et de fonctionnement des utilisateurs au cours d'une journée, il sera très utile. Avant, je ne savais utiliser que la "procédure stockée" (bien que la vitesse d'exécution soit rapide, elle est vraiment trop rigide). Plus tard, j'ai appris à utiliser la méthode "group by" plus avancée pour implémenter de manière flexible une méthode similaire. fonctions.

Texte :

-- time_str '2016-11-20 04:31:11'
-- date_str 20161120

select concat(left(date_format(time_str, '%y-%m-%d %h:%i'),15),'0') as time_flag, count(*) as count from `security`.`cmd_info` where `date_str`=20161120 
group by time_flag order by time_flag; -- 127 rows

select round(unix_timestamp(time_str)/(10 * 60)) as timekey, count(*) from `security`.`cmd_info` where `date_str`=20161120 group by timekey 
order by timekey; -- 126 rows

-- 以上2个SQL语句的思路类似——使用「group by」进行区分，但是方法有所不同，前者只能针对10分钟(或1小时)级别，后者可以动态调整间隔大小，两者效率差不多，
可以根据实际情况选用

select concat(date(time_str),' ',hour(time_str),':',round(minute(time_str)/10,0)*10), count(*) from `security`.`cmd_info` where `date_str`=20161120 
group by date(time_str), hour(time_str), round(minute(time_str)/10,0)*10; -- 145 rows

select concat(date(time_str),' ',hour(time_str),':',floor(minute(time_str)/10)*10), count(*) from `security`.`cmd_info` where `date_str`=20161120 
group by date(time_str), hour(time_str), floor(minute(time_str)/10)*10; -- 127 rows (和 date_format 那个等价)

select concat(date(time_str),' ',hour(time_str),':',ceil(minute(time_str)/10)*10), count(*) from `security`.`cmd_info` where `date_str`=20161120 
group by date(time_str), hour(time_str), ceil(minute(time_str)/10)*10; -- 151 rows

&

DELIMITER //

DROP PROCEDURE IF EXISTS `usp_cmd_info`;

CREATE PROCEDURE `usp_cmd_info`(IN dates VARCHAR(12))
BEGIN
 SELECT count(*) from `cmd_info` where `time_str` BETWEEN CONCAT(dates, " 00:00:00") AND CONCAT(dates, " 00:10:00") 
 INTO @count_0;
 SELECT count(*) from `cmd_info` where `time_str` BETWEEN CONCAT(dates, " 00:10:00") AND CONCAT(dates, " 00:20:00") 
 INTO @count_1;
 ...
 SELECT count(*) from `cmd_info` where `time_str` BETWEEN CONCAT(dates, " 23:40:00") AND CONCAT(dates, " 23:50:00") 
 INTO @count_142;
 SELECT count(*) from `cmd_info` where `time_str` BETWEEN CONCAT(dates, " 23:50:00") AND CONCAT(dates, " 23:59:59") 
 INTO @count_143;
 select @count_0, @count_1, @count_2, @count_3, @count_4, @count_5, @count_6, @count_7, @count_8, @count_9, @count_10, 
 @count_11, @count_12, @count_13, @count_14, @count_15, @count_16, @count_17, @count_18, @count_19, @count_20, @count_21, 
 @count_22, @count_23, @count_24, @count_25, @count_26, @count_27, @count_28, @count_29, @count_30, @count_31, @count_32, 
 @count_33, @count_34, @count_35, @count_36, @count_37, @count_38, @count_39, @count_40, @count_41, @count_42, @count_43, 
 @count_44, @count_45, @count_46, @count_47, @count_48, @count_49, @count_50, @count_51, @count_52, @count_53, @count_54, 
 @count_55, @count_56, @count_57, @count_58, @count_59, @count_60, @count_61, @count_62, @count_63, @count_64, @count_65, 
 @count_66, @count_67, @count_68, @count_69, @count_70, @count_71, @count_72, @count_73, @count_74, @count_75, @count_76, 
 @count_77, @count_78, @count_79, @count_80, @count_81, @count_82, @count_83, @count_84, @count_85, @count_86, @count_87,
  @count_88, @count_89, @count_90, @count_91, @count_92, @count_93, @count_94, @count_95, @count_96, @count_97, @count_98, 
  @count_99, @count_100, @count_101, @count_102, @count_103, @count_104, @count_105, @count_106, @count_107, @count_108, 
  @count_109, @count_110, @count_111, @count_112, @count_113, @count_114, @count_115, @count_116, @count_117, @count_118, 
  @count_119, @count_120, @count_121, @count_122, @count_123, @count_124, @count_125, @count_126, @count_127, @count_128, 
  @count_129, @count_130, @count_131, @count_132, @count_133, @count_134, @count_135, @count_136, @count_137, @count_138, 
  @count_139, @count_140, @count_141, @count_142, @count_143;
END //

DELIMITER ;

show PROCEDURE status\G

CALL usp_cmd_info("2016-10-20");
上面的这段MySQL存储过程的语句非常长，不可能用手工输入，可以用下面的这段Python代码按所需的时间间隔自动生成：
import datetime

today = datetime.date.today()
# 或 由给定格式字符串转换成
# today = datetime.datetime.strptime('2016-11-21', '%Y-%m-%d')

min_today_time = datetime.datetime.combine(today, datetime.time.min) # 2016-11-21 00:00:00
max_today_time = datetime.datetime.combine(today, datetime.time.max) # 2016-11-21 23:59:59

sql_procedure_arr = []
sql_procedure_arr2 = []
for x in xrange(0, 60*24/5, 1):
  start_datetime = min_today_time + datetime.timedelta(minutes = 5*x)
  end_datetime = min_today_time + datetime.timedelta(minutes = 5*(x+1))
  # print x, start_datetime.strftime("%Y-%m-%d %H:%M:%S"), end_datetime.strftime("%Y-%m-%d %H:%M:%S")
  select_str = 'SELECT count(*) from `cmd_info` where `time_str` BETWEEN "{0}" AND "{1}" INTO @count_{2};'.format(start_datetime, end_datetime, x)
  # print select_str
  sql_procedure_arr.append(select_str)
  sql_procedure_arr2.append('@count_{0}'.format(x))
print '\n'.join(sql_procedure_arr)
print 'select {0};'.format(', '.join(sql_procedure_arr2))

Résumé

Ce qui précède est l'intégralité du contenu de la méthode d'implémentation de MYSQL effectuant des statistiques de groupe tous les 10 minutes Pour plus de contenu connexe, veuillez faire attention au site Web PHP chinois (www.php.cn) !