我正在尝试获取一些数据，但查询需要超过5分钟（它应该快到几毫秒）。
这是表格
CREATE TABLE IF NOT EXISTS `bookings` (
`bkid`
int(11) NOT NULL AUTO_INCREMENT,
`idBuilding`
int(11) NOT NULL,
`checkinDate`
date NOT NULL,
`baggage_checkin`
int(11) DEFAULT NULL,
`baggage_checkin_check`
tinyint(1) DEFAULT NULL,
`arrivalAtAirportTime`
time DEFAULT NULL,
`returnFlightTime`
time DEFAULT NULL,
`arrivalAtAirportTime_check`
tinyint(1) NOT NULL DEFAULT '0',
`flightNumber`
varchar(50) DEFAULT NULL,
`checkinTime`
time NOT NULL DEFAULT '15:00:00',
`checkoutDate`
date NOT NULL,
`baggage_checkout`
int(11) DEFAULT NULL,
`baggage_checkout_check`
tinyint(1) DEFAULT NULL,
`checkoutTime`
time NOT NULL DEFAULT '12:00:00',
`agency`
varchar(255) NOT NULL,
`distributor`
varchar(255) NOT NULL,
`number`
varchar(255) NOT NULL,
`arrivalby`
varchar(50) DEFAULT NULL,
`adults`
int(3) NOT NULL,
`actualAdults`
int(10) DEFAULT NULL,
`doublebeds`
int(3) DEFAULT NULL,
`children`
int(3) NOT NULL,
`singlebeds`
int(3) DEFAULT NULL,
`price`
decimal(8, 2) NOT NULL,
`received`
decimal(8, 2) NOT NULL DEFAULT '0.00',
`createdBy`
int(11) NOT NULL,
`createdTime`
int(11) NOT NULL,
`modifiedBy`
int(11) NOT NULL,
`modifiedTime`
int(11) NOT NULL,
`notes`
longblob NOT NULL,
`checkinBy`
int(11) NOT NULL,
`checkoutBy`
int(11) NOT NULL,
`keys_number`
int(11) DEFAULT NULL,
`keys_number_kept`
int(11) DEFAULT NULL,
`keys_number_back`
int(11) DEFAULT NULL,
`mobile_wifi`
int(11) DEFAULT NULL,
`mobile_wifi_back`
tinyint(1) NOT NULL DEFAULT '0',
`usb_sticks`
int(11) DEFAULT '0',
`bkstatus`
tinyint(4) NOT NULL,
`status`
int(11) NOT NULL,
`booking_fee`
decimal(8, 2) NOT NULL,
`online_guest`
decimal(10, 2) NOT NULL,
`sales`
decimal(10, 2) NOT NULL,
`sales_vat`
decimal(10, 2) DEFAULT NULL,
`distribution`
decimal(10, 2) NOT NULL,
`host_margin`
decimal(10, 2) NOT NULL,
`cleaning_fee`
decimal(8, 2) NOT NULL,
`taxi_to_office`
int(11) DEFAULT NULL,
`taxi_to_office_check`
varchar(50) DEFAULT NULL,
`taxi_apartment_to_office`
int(11) DEFAULT NULL,
`taxi_apartment_to_office_check`
varchar(50) DEFAULT NULL,
`taxi_to_apartment`
int(11) NOT NULL,
`taxi_to_apartment_check`
varchar(50) DEFAULT NULL,
`taxi_to_airport`
int(11) NOT NULL,
`taxi_to_airport_check`
varchar(50) DEFAULT NULL,
`idOrigBuilding`
int(11) NOT NULL,
`guest_satisfaction`
enum('-1', '0', '1') NOT NULL DEFAULT '0',
`guest_informed_status`
enum('1', '2', '3', '4') NOT NULL DEFAULT '1',
`channel_informed_status`
enum('1', '2', '3', '4') NOT NULL DEFAULT '1',
`mail_sent`
tinyint(1) DEFAULT '0',
`mail_sent_date`
timestamp NULL DEFAULT NULL,
`mail_sent_reminder`
tinyint(1) DEFAULT '0',
`mail_sent_reminder_date`
datetime DEFAULT NULL,
`mail_sent_lastreminder`
tinyint(1) DEFAULT '0',
`mail_sent_lastreminder_date`
datetime DEFAULT NULL,
`DELbirthDate`
date DEFAULT NULL,
`DELcity`
varchar(50) DEFAULT NULL,
`cleaning_percentage`
varchar(50) NOT NULL DEFAULT '0',
`rent_percentage`
varchar(50) NOT NULL DEFAULT '0',
`checkout_percentage`
int(3) NOT NULL DEFAULT '0',
`groupType`
varchar(50) NOT NULL,
`deposit`
double NOT NULL,
`idrefundstatustype`
int(11) NOT NULL,
`prepayment`
decimal(10, 2) NOT NULL,
`distribution_changed`
int(11) NOT NULL,
`checkinDT`
datetime NOT NULL,
`checkoutDT`
datetime NOT NULL,
PRIMARY KEY(`bkid`),
KEY `number` (`number`),
KEY `createdBy` (`createdBy`, `modifiedBy`),
KEY `idBuilding` (`idBuilding`),
KEY `checkinDate` (`checkinDate`),
KEY `checkoutDate` (`checkoutDate`),
KEY `checkinTime` (`checkinTime`),
KEY `checkoutTime` (`checkoutTime`),
KEY `checkinDT` (`checkinDT`, `checkoutDT`)
) ENGINE = MyISAM DEFAULT CHARSET = utf8 AUTO_INCREMENT = 15934;
这是查询
select
concat(bu.streetName,' ',bu.houseNumber) as address,
concat(co.firstName,' ',co.middleName,' ',co.lastName) as ownerName,
a.city as city,
a.area as area,
bu.minGuest as minGuest,
bu.maxGuest as maxGuest,
bu.bedrooms as bedrooms,
bu.bathrooms as bathrooms,
bo.checkinDate as checkinDate,
bo.checkinTime as checkinTime,
bo.checkoutDate as checkoutDate,
bo.checkoutTime as checkoutTime,
concat(ifnull(cg.firstName,''),' ',ifnull(cg.middleName,''),' ',ifnull(cg.lastName,'')) as guestName,
bo.adults as guestsCount,
bo.bkid as bkid,
bo.idBuilding as bid,
bu.price as price,
bu.percentage as isPercent,
bu.isActive as isActive,
ifnull(f.hashname,-1) as iconName,
f.ext as iconExt
from
bookings bo
left join
buildings bu
on
bu.id = bo.idBuilding
left join
items i
on
i.guid = bu.guid
left join
images im
on
im.guid = i.icon
left join
files f
on
f.hashname = im.96_hash
left join
areas a
on
a.id = bu.idArea
left join
booking_participant bp
on
bp.bookings_id = bo.bkid
and
bp.role_id = 2
left join
contacts co
on
co.id = bu.idContactOwner
left join
contacts cg
on
cg.id = bp.contacts_id
left join
bookings nextBo
on
nextBo.idBuilding = bo.idBuilding
and
nextBo.checkinDT >= bo.checkoutDT
left join
jobs nextInspection
on
nextInspection.jobtype = 2
and
nextInspection.endDT < nextBo.checkinDT
and
nextInspection.endDT > bo.checkoutDT
left join
jobs nextCleaning
on
nextCleaning.jobtype = 1
and
nextCleaning.endDT < nextBo.checkinDT
and
nextCleaning.endDT > bo.checkoutDT
where
bo.checkinDT>='2014-07-18 00:00:00'
and
bo.checkinDT<='2014-07-18 23:59:59'
group by
bo.bkid
order by
bo.checkinDate, bo.checkinTIme, bu.streetName, bu.houseNumber, bo.createdTime asc;
这是解释结果：
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: bo
type: range
possible_keys: checkinDT
key: checkinDT
key_len: 8
ref: NULL
rows: 40
Extra: Using where; Using temporary; Using filesort
*************************** 2. row ***************************
id: 1
select_type: SIMPLE
table: bu
type: eq_ref
possible_keys: PRIMARY
key: PRIMARY
key_len: 4
ref: company.bo.idBuilding
rows: 1
Extra:
*************************** 3. row ***************************
id: 1
select_type: SIMPLE
table: i
type: eq_ref
possible_keys: PRIMARY
key: PRIMARY
key_len: 8
ref: company.bu.guid
rows: 1
Extra:
*************************** 4. row ***************************
id: 1
select_type: SIMPLE
table: im
type: eq_ref
possible_keys: guid
key: guid
key_len: 8
ref: company.i.icon
rows: 1
Extra:
*************************** 5. row ***************************
id: 1
select_type: SIMPLE
table: f
type: ref
possible_keys: hash
key: hash
key_len: 42
ref: company.im.96_hash
rows: 1
Extra:
*************************** 6. row ***************************
id: 1
select_type: SIMPLE
table: a
type: eq_ref
possible_keys: PRIMARY
key: PRIMARY
key_len: 4
ref: company.bu.idArea
rows: 1
Extra:
*************************** 7. row ***************************
id: 1
select_type: SIMPLE
table: bp
type: ref
possible_keys: PRIMARY,bookings_id,bookings_id_2
key: bookings_id
key_len: 4
ref: company.bo.bkid
rows: 2
Extra: Using index
*************************** 8. row ***************************
id: 1
select_type: SIMPLE
table: co
type: eq_ref
possible_keys: PRIMARY
key: PRIMARY
key_len: 4
ref: company.bu.idContactOwner
rows: 1
Extra:
*************************** 9. row ***************************
id: 1
select_type: SIMPLE
table: cg
type: eq_ref
possible_keys: PRIMARY
key: PRIMARY
key_len: 4
ref: company.bp.contacts_id
rows: 1
Extra:
*************************** 10. row ***************************
id: 1
select_type: SIMPLE
table: nextBo
type: ref
possible_keys: idBuilding,checkinDT
key: idBuilding
key_len: 4
ref: company.bo.idBuilding
rows: 71
Extra:
*************************** 11. row ***************************
id: 1
select_type: SIMPLE
table: nextInspection
type: ref
possible_keys: endDT,jobtype
key: jobtype
key_len: 4
ref: const
rows: 2749
Extra:
*************************** 12. row ***************************
id: 1
select_type: SIMPLE
table: nextCleaning
type: ref
possible_keys: endDT,jobtype
key: jobtype
key_len: 4
ref: const
rows: 16040
Extra:
12 rows in set (0.00 sec)
您是否知道如何加快此查询？
它将用于从服务器中选择预订，因此它应该更快。对于在1天内发生的预订，查询需要超过5分钟，因此对于多天而言，情况更糟......
这个在0.01秒内执行。
完成此操作，但仍然很慢。
这是优化的输出。
mysql> OPTIMIZE TABLE bookings;
+--------------------------+----------+----------+----------+
| Table | Op | Msg_type | Msg_text |
+--------------------------+----------+----------+----------+
| company.bookings | optimize | status | OK |
+--------------------------+----------+----------+----------+
1 row in set (0.02 sec)
myisamchk的输出
Variables (--variable-name=value)
and boolean options {FALSE|TRUE} Value (after reading options)
--------------------------------- ----------------------------------------
character-sets-dir (No default value)
data-file-length 0
keys-used 18446744073709551615
max-record-length 9223372036854775807
set-auto-increment 0
set-collation (No default value)
sort-records 9
tmpdir (No default value)
key-buffer-size 520192
key-cache-block-size 1024
myisam-block-size 1024
read-buffer-size 262136
write-buffer-size 262136
sort-buffer-size 2097144
myisam-sort-buffer-size 2097144
sort-key-blocks 16
decode-bits 9
ft-min-word-len 4
ft-max-word-len 84
ft-stopword-file (No default value)
stats-method nulls_unequal
你是对的，在添加作业连接后查询开始变慢。 在加入nextBo之前，执行时间为0.01 在nextBo加入之后，它会上升到0.1 在第一次工作加入之后，它会持续几分钟
我做了你建议的改变，但它仍然没有更快。 这是新查询
select
concat(bu.streetName,' ',bu.houseNumber) as address,
concat(co.firstName,' ',co.middleName,' ',co.lastName) as ownerName,
a.city as city,
a.area as area,
bu.minGuest as minGuest,
bu.maxGuest as maxGuest,
bu.bedrooms as bedrooms,
bu.bathrooms as bathrooms,
bo.checkinDate as checkinDate,
bo.checkinTime as checkinTime,
bo.checkoutDate as checkoutDate,
bo.checkoutTime as checkoutTime,
concat(ifnull(cg.firstName,''),' ',ifnull(cg.middleName,''),' ',ifnull(cg.lastName,'')) as guestName,
bo.adults as guestsCount,
bo.bkid as bkid,
bo.idBuilding as bid,
bu.price as price,
bu.percentage as isPercent,
bu.isActive as isActive,
ifnull(f.hashname,-1) as iconName,
f.ext as iconExt,
(
select
clnid
from
jobs nextInspection
where
nextInspection.jobtype = 2
and
nextInspection.endDT < nextBo.checkinDT
and
nextInspection.endDT > bo.checkoutDT
order by
nextInspection.endDT asc
limit 1
) as nextInspect,
(
select
clnid
from
jobs nextInspection
where
nextInspection.jobtype = 2
and
nextInspection.endDT < nextBo.checkinDT
and
nextInspection.endDT > bo.checkoutDT
order by
nextInspection.endDT asc
limit 1
) as nextClean
from
bookings bo
left join
buildings bu
on
bu.id = bo.idBuilding
left join
items i
on
i.guid = bu.guid
left join
images im
on
im.guid = i.icon
left join
files f
on
f.hashname = im.96_hash
left join
areas a
on
a.id = bu.idArea
left join
booking_participant bp
on
bp.bookings_id = bo.bkid
and
bp.role_id = 2
left join
contacts co
on
co.id = bu.idContactOwner
left join
contacts cg
on
cg.id = bp.contacts_id
left join
bookings nextBo
on
nextBo.idBuilding = bo.idBuilding
and
nextBo.checkinDT >= bo.checkoutDT
where
bo.checkinDT>='2014-07-18 00:00:00'
and
bo.checkinDT<='2014-07-18 23:59:59'
group by
bo.bkid
order by
bo.checkinDate, bo.checkinTIme, bu.streetName, bu.houseNumber, bo.createdTime asc;
解释现在说
*************************** 1. row ***************************
id: 1
select_type: PRIMARY
table: bo
type: range
possible_keys: checkinDT
key: checkinDT
key_len: 8
ref: NULL
rows: 74
Extra: Using where; Using temporary; Using filesort
*************************** 2. row ***************************
id: 1
select_type: PRIMARY
table: bu
type: eq_ref
possible_keys: PRIMARY
key: PRIMARY
key_len: 4
ref: company.bo.idBuilding
rows: 1
Extra:
*************************** 3. row ***************************
id: 1
select_type: PRIMARY
table: i
type: eq_ref
possible_keys: PRIMARY
key: PRIMARY
key_len: 8
ref: company.bu.guid
rows: 1
Extra:
*************************** 4. row ***************************
id: 1
select_type: PRIMARY
table: im
type: eq_ref
possible_keys: guid
key: guid
key_len: 8
ref: company.i.icon
rows: 1
Extra:
*************************** 5. row ***************************
id: 1
select_type: PRIMARY
table: f
type: ref
possible_keys: hash
key: hash
key_len: 42
ref: company.im.96_hash
rows: 1
Extra:
*************************** 6. row ***************************
id: 1
select_type: PRIMARY
table: a
type: eq_ref
possible_keys: PRIMARY
key: PRIMARY
key_len: 4
ref: company.bu.idArea
rows: 1
Extra:
*************************** 7. row ***************************
id: 1
select_type: PRIMARY
table: bp
type: ref
possible_keys: PRIMARY,bookings_id,bookings_id_2
key: bookings_id
key_len: 4
ref: company.bo.bkid
rows: 2
Extra: Using index
*************************** 8. row ***************************
id: 1
select_type: PRIMARY
table: co
type: eq_ref
possible_keys: PRIMARY
key: PRIMARY
key_len: 4
ref: company.bu.idContactOwner
rows: 1
Extra:
*************************** 9. row ***************************
id: 1
select_type: PRIMARY
table: cg
type: eq_ref
possible_keys: PRIMARY
key: PRIMARY
key_len: 4
ref: company.bp.contacts_id
rows: 1
Extra:
*************************** 10. row ***************************
id: 1
select_type: PRIMARY
table: nextBo
type: ref
possible_keys: idBuilding,checkinDT
key: idBuilding
key_len: 4
ref: company.bo.idBuilding
rows: 70
Extra:
*************************** 11. row ***************************
id: 3
select_type: DEPENDENT SUBQUERY
table: nextInspection
type: index
possible_keys: endDT,jobtype
key: endDT
key_len: 8
ref: NULL
rows: 10
Extra: Using where
*************************** 12. row ***************************
id: 2
select_type: DEPENDENT SUBQUERY
table: nextInspection
type: index
possible_keys: endDT,jobtype
key: endDT
key_len: 8
ref: NULL
rows: 10
Extra: Using where
12 rows in set (0.00 sec)
实际上我刚刚发现我忘了加入idBuilding上的工作表，所以它只是为了当前的工作而获得了所有建筑的工作。无论如何，执行现在是1秒而不是5分钟，但应用程序应该响应更快（每天大约0.01秒是可以接受的，所以如果搜索是整年，那么总共大约需要3秒像现在这样的5分钟..）
这是最新的查询
select
concat(bu.streetName,' ',bu.houseNumber) as address,
concat(co.firstName,' ',co.middleName,' ',co.lastName) as ownerName,
a.city as city,
a.area as area,
bu.minGuest as minGuest,
bu.maxGuest as maxGuest,
bu.bedrooms as bedrooms,
bu.bathrooms as bathrooms,
bo.checkinDate as checkinDate,
bo.checkinTime as checkinTime,
bo.checkoutDate as checkoutDate,
bo.checkoutTime as checkoutTime,
concat(ifnull(cg.firstName,''),' ',ifnull(cg.middleName,''),' ',ifnull(cg.lastName,'')) as guestName,
bo.adults as guestsCount,
bo.bkid as bkid,
bo.idBuilding as bid,
bu.price as price,
bu.percentage as isPercent,
bu.isActive as isActive,
ifnull(f.hashname,-1) as iconName,
f.ext as iconExt,
( select
clnid
from
jobs nextInspection
where
nextInspection.idBuilding = bo.idBuilding
and
nextInspection.jobtype = 2
and
nextInspection.endDT < nextBo.checkinDT
and
nextInspection.endDT > bo.checkoutDT
) as inspectionClnid,
( select
clnid
from
jobs nextCleaning
where
nextCleaning.idBuilding = bo.idBuilding
and
nextCleaning.jobtype = 1
and
nextCleaning.endDT < nextBo.checkinDT
and
nextCleaning.endDT > bo.checkoutDT
) as cleaningClnid
from
bookings bo
left join
buildings bu
on
bu.id = bo.idBuilding
left join
items i
on
i.guid = bu.guid
left join
images im
on
im.guid = i.icon
left join
files f
on
f.hashname = im.96_hash
left join
areas a
on
a.id = bu.idArea
left join
booking_participant bp
on
bp.bookings_id = bo.bkid
and
bp.role_id = 2
left join
contacts co
on
co.id = bu.idContactOwner
left join
contacts cg
on
cg.id = bp.contacts_id
left join
bookings nextBo
on
nextBo.idBuilding = bo.idBuilding
and
nextBo.checkinDT >= bo.checkoutDT
where
bo.checkinDT>='2014-07-18 00:00:00'
and
bo.checkinDT<='2014-07-18 23:59:59'
group by
bo.bkid
order by
bo.checkinDate, bo.checkinTIme, bu.streetName, bu.houseNumber, bo.createdTime asc;
这是解释结果
*************************** 1. row ***************************
id: 1
select_type: PRIMARY
table: bo
type: range
possible_keys: checkinDT
key: checkinDT
key_len: 8
ref: NULL
rows: 73
Extra: Using where; Using temporary; Using filesort
*************************** 2. row ***************************
id: 1
select_type: PRIMARY
table: bu
type: eq_ref
possible_keys: PRIMARY
key: PRIMARY
key_len: 4
ref: company.bo.idBuilding
rows: 1
Extra:
*************************** 3. row ***************************
id: 1
select_type: PRIMARY
table: i
type: eq_ref
possible_keys: PRIMARY
key: PRIMARY
key_len: 8
ref: company.bu.guid
rows: 1
Extra:
*************************** 4. row ***************************
id: 1
select_type: PRIMARY
table: im
type: eq_ref
possible_keys: guid
key: guid
key_len: 8
ref: company.i.icon
rows: 1
Extra:
*************************** 5. row ***************************
id: 1
select_type: PRIMARY
table: f
type: ref
possible_keys: hash
key: hash
key_len: 42
ref: company.im.96_hash
rows: 1
Extra:
*************************** 6. row ***************************
id: 1
select_type: PRIMARY
table: a
type: eq_ref
possible_keys: PRIMARY
key: PRIMARY
key_len: 4
ref: company.bu.idArea
rows: 1
Extra:
*************************** 7. row ***************************
id: 1
select_type: PRIMARY
table: bp
type: ref
possible_keys: PRIMARY,bookings_id,bookings_id_2
key: bookings_id
key_len: 4
ref: company.bo.bkid
rows: 2
Extra: Using index
*************************** 8. row ***************************
id: 1
select_type: PRIMARY
table: co
type: eq_ref
possible_keys: PRIMARY
key: PRIMARY
key_len: 4
ref: company.bu.idContactOwner
rows: 1
Extra:
*************************** 9. row ***************************
id: 1
select_type: PRIMARY
table: cg
type: eq_ref
possible_keys: PRIMARY
key: PRIMARY
key_len: 4
ref: company.bp.contacts_id
rows: 1
Extra:
*************************** 10. row ***************************
id: 1
select_type: PRIMARY
table: nextBo
type: ref
possible_keys: idBuilding,checkinDT
key: idBuilding
key_len: 4
ref: company.bo.idBuilding
rows: 70
Extra:
*************************** 11. row ***************************
id: 3
select_type: DEPENDENT SUBQUERY
table: nextCleaning
type: ref
possible_keys: idBuilding,endDT,jobtype
key: idBuilding
key_len: 4
ref: func
rows: 128
Extra: Using where
*************************** 12. row ***************************
id: 2
select_type: DEPENDENT SUBQUERY
table: nextInspection
type: ref
possible_keys: idBuilding,endDT,jobtype
key: idBuilding
key_len: 4
ref: func
rows: 128
Extra: Using where
12 rows in set (0.00 sec)
答案 0 :(得分：1)
有趣。实际上，你的查询看起来很不错，索引看起来很好，你唯一的WHERE子句变量是bo.checkinDT，它被索引（虽然只是一个更大的索引的一部分，但它是左边的部分.. ）。
GROUP BY的目的是什么？您没有使用任何分组功能。你是DISTINCT的短缺吗？
你可以尝试：
SELECT * FROM bookings bo where bo.checkinDT>='2014-07-18 00:00:00' and bo.checkinDT<='2014-07-18 23:59:59'）的情况下运行相同的查询。这样慢吗？如果没有，它可能是通过播放加入/组合。bookings.checkinDT上创建单独的索引？OPTIMIZE TABLE bookings一次？myisamchk --sort-index --sort-records=9（如果9是checkinDT索引）？（我会在您提供详细信息时更新我的答案）。
好的，由于基本查询（仅限预订）很快，因此连接速度会降低。你能为基表做一个SELECT *，并逐个添加LEFT JOIN吗？
jobs表（2749行）和（16040行）导致问题。我看错了，或者你（目前）甚至没有使用该表吗？
如果你需要的只是两者的下一个日期，子查询可能会更快，你可以尝试将它放在你的select语句中：
(SELECT * FROM jobs nextInspection
WHERE nextInspection.jobtype = 2
and nextInspection.endDT < nextBo.checkinDT
and nextInspection.endDT > bo.checkoutDT
ORDER BY nextInspection.endDT ASC
LIMIT 1)
获取当前结帐后但下次登记前的第一次“检查”。