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MySQL多个发送数据状态

explain entity-attribute-value profiling mysql php
  •  1
  • Влад Чачиев  · 技术社区  · 7 年前

    我的查询太长了。当我分析它时,我会看到这样的情况: 

        Sending data    0.039324
    executing   0.000011
    Sending data    0.039662
    executing   0.000012
    Sending data    0.040380
    executing   0.000015
    Sending data    0.035879
    executing   0.000012
    Sending data    0.035426
    executing   0.000012
    Sending data    0.038107
    executing   0.000011
    Sending data    0.035247
    executing   0.000011
    Sending data    0.050108
    executing   0.000014
    Sending data    0.045458
    executing   0.000012
    Sending data    0.034700
    executing   0.000012
    Sending data    0.036205
    executing   0.000012
    Sending data    0.034602
    executing   0.000015
    Sending data    0.034580
    executing   0.000012
    Sending data    0.034477
    executing   0.000010
    Sending data    0.034382
    executing   0.000010
    Sending data    0.034416
    executing   0.000011
    Sending data    0.034335
    executing   0.000010
    Sending data    0.034474
    executing   0.000010
    Sending data    0.034405
    executing   0.000010
    Sending data    0.034433
    executing   0.000011
    Sending data    0.034544
    executing   0.000010
    Sending data    0.034525
    executing   0.000011
    Sending data    0.034459
    executing   0.000010
    Sending data    0.034766
    executing   0.000011
    Sending data    0.034633
    executing   0.000010
    Sending data    0.034574
    executing   0.000011
    Sending data    0.034607
    executing   0.000010
    Sending data    0.034613
    executing   0.000011
    Sending data    0.034394
    executing   0.000010
    Sending data    0.034606
    executing   0.000011
    Sending data    0.034790
    executing   0.000011
    Sending data    0.034614
    executing   0.000011
    Sending data    0.034497
    executing   0.000010
    Sending data    0.034756
    executing   0.000010
    Sending data    0.034440
    executing   0.000010
    Sending data    0.034414
    executing   0.000011
    Sending data    0.034484
    executing   0.000011
    Sending data    0.034490
    executing   0.000011
    Sending data    0.034672
    executing   0.000011
    Sending data    0.034455
    executing   0.000011
    Sending data    0.034430
    executing   0.000011
    Sending data    0.034509
    executing   0.000012
    Sending data    0.034432
    executing   0.000012
    Sending data    0.034348
    executing   0.000011
    Sending data    0.034378
    executing   0.000011
    Sending data    0.034356
    executing   0.000011
    Sending data    0.034631
    end 0.000014
    query end   0.000007
    closing tables  0.000010
    freeing items   0.000025
    logging slow query  0.000003
    logging slow query  0.000004
    cleaning up 0.000004

    发送数据太多了。

    我运行的查询: 

    SELECT COUNT(*) as count from OrdersArchive where ID>0 and PId IN ('2564') and 
   (
   ID like '17000106864' 
   OR `OrderID` like '17000106864' 
   OR `ID` IN
   (
       SELECT `transferID`
       FROM `custom_fields`
       WHERE `fieldName` = 'invoiceNumber'
       AND `value` like '%17000106864%'
   )
   OR `tpb` LIKE '17000106864' 

   )

    解释节目 

    id  select_type table   type    possible_keys   key key_len ref rows    Extra
1   PRIMARY OrdersArchive   range   PRIMARY,ID_UNIQUE   PRIMARY 4   NULL    41609   Using where
2   DEPENDENT SUBQUERY  custom_fields   ALL NULL    NULL    NULL    NULL    93141   Using where



    CREATE TABLE IF NOT EXISTS `OrdersArchive` (
  `ID` int(11) NOT NULL,
  `ids` int(11) NOT NULL DEFAULT '0',
  `OrderID` varchar(11) NOT NULL DEFAULT '0',
  `PricePosition` int(11) NOT NULL DEFAULT '0',
  `Reverse` tinyint(1) DEFAULT NULL,
  `DataOrder` timestamp NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
  `DataFlightTrain` timestamp NOT NULL DEFAULT '0000-00-00 00:00:00',
  `Customer` varchar(255) DEFAULT NULL,
  `PhoneCustomer` varchar(255) DEFAULT NULL,
  `EmailCustomer` varchar(255) DEFAULT NULL,
  `Provider` int(11) DEFAULT NULL,
  `DeliveryTime` timestamp NULL DEFAULT NULL,
  `Address1` varchar(255) DEFAULT NULL,
  `Address2` varchar(255) NOT NULL,
  `Passangers` varchar(1024) DEFAULT NULL,
  `PassangersPhones` varchar(255) NOT NULL,
  `PassangersEmailes` varchar(255) NOT NULL,
  `FlightTrain` varchar(255) DEFAULT NULL,
  `QuantityPassangers` int(11) DEFAULT '1',
  `NamePlate` varchar(255) DEFAULT NULL,
  `PhoneDriver` varchar(255) DEFAULT NULL,
  `PhoneDriverNeed` tinyint(1) DEFAULT '0',
  `Status` int(11) DEFAULT NULL,
  `Operator` int(11) DEFAULT NULL,
  `userId` int(11) NOT NULL,
  `usn` varchar(256) NOT NULL,
  `ArendaNeed` varchar(255) DEFAULT '',
  `ArendaHour` int(11) DEFAULT NULL,
  `ArendaMinutes` varchar(255) DEFAULT '',
  `Cost` double DEFAULT NULL,
  `Notes` text NOT NULL,
  `notes2` varchar(256) NOT NULL DEFAULT '',
  `PId` int(11) NOT NULL DEFAULT '0',
  `Voucher` varchar(256) NOT NULL,
  `Invoice` varchar(256) NOT NULL,
  `Meet` varchar(255) NOT NULL,
  `Toward` varchar(255) NOT NULL,
  `techStatus` int(2) NOT NULL DEFAULT '0',
  `City` varchar(55) NOT NULL,
  `City2` varchar(55) NOT NULL,
  `Auto` varchar(30) NOT NULL,
  `department` varchar(255) NOT NULL DEFAULT '',
  `nsktime` timestamp NOT NULL DEFAULT '0000-00-00 00:00:00',
  `tpb` varchar(255) NOT NULL DEFAULT '',
  `ban_add_races` int(1) NOT NULL DEFAULT '0',
  `paid` int(10) NOT NULL DEFAULT '0',
  `taxi` varchar(255) NOT NULL DEFAULT '',
  `price_client` int(11) DEFAULT NULL,
  `comission_from_client` int(11) DEFAULT NULL,
  `primechanie` varchar(1000) DEFAULT NULL,
  PRIMARY KEY (`ID`),
  UNIQUE KEY `ID_UNIQUE` (`ID`),
  KEY `fk_Orders_Users1_idx` (`Operator`),
  KEY `fk_Orders_Providers1_idx` (`Provider`),
  KEY `fk_Orders_OrderStatus1_idx` (`Status`),
  KEY `ids` (`ids`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

## and other table

CREATE TABLE IF NOT EXISTS `custom_fields` (
  `ID` int(11) NOT NULL AUTO_INCREMENT,
  `pid` int(11) NOT NULL,
  `transferID` int(11) NOT NULL,
  `fieldName` varchar(255) NOT NULL,
  `value` varchar(1024) NOT NULL,
  PRIMARY KEY (`ID`)
) ENGINE=InnoDB  DEFAULT CHARSET=utf8 AUTO_INCREMENT=325452 ;
    3 回复  |  直到 7 年前
        1
  •  0
  •   SpacemanSpiff    7 年前

    虽然当前的SELECT查询可能会在某种程度上得到改进,但我认为如果您能够以更高效的方式存储数据,尤其是如果您可以消除对

    和 value

    如果您为invoiceNumber创建一个单独的字段,并在插入数据时填充该字段,则可以对其进行索引,并按如下方式选择/连接:

    其中发票编号=17000106864

        2
  •  0
  •   Влад Чачиев    7 年前

    嗯,我是通过内部连接完成的。运行0.34秒

    最终查询是: 

    SELECT COUNT(`OrdersArchive`.ID) as count, `OrdersArchive`.ID
FROM `OrdersArchive`
INNER JOIN `custom_fields` on `OrdersArchive`.ID = `custom_fields`.`transferID`
WHERE `OrdersArchive`.ID>0 
AND `custom_fields`.`fieldName` = 'invoiceNumber'
AND 
`OrdersArchive`.PId IN ('2564') AND
(
   `OrdersArchive`.ID LIKE '17000106864' 
   OR `OrdersArchive`.`OrderID` LIKE '17000106864' 
   OR `OrdersArchive`.`tpb` LIKE '17000106864' 
   OR (
 `custom_fields`.`value` like '%17000106864%'
   )
)
        3
  •  0
  •   Rick James    7 年前

    IN(SELECT ...) 通常效率很低。在您的例子中,它被重复执行,从而为每个调用“执行”和“发送数据”。

    其他答案通过将该构造转换为 JOIN

    其他问题; 

    PRIMARY KEY (`ID`),   -- This is UNIQUE and an INDEX
UNIQUE KEY `ID_UNIQUE` (`ID`),  -- totally redundant; DROP it

    由于模式是“EAV”(实体属性值),并且需要基于某个键值(“invoiceNumber”)进行过滤,因此您可能会受到性能问题的困扰。考虑将其从键值表中拉出( custom_fields )把它放在主桌上( OrdersArchive

    但我看到了 OrdersArchive公司 有相当多的列。但我没有任何具体的建议。

    自定义_字段 my tips

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