MySQL查询优化。 太慢了

Question

I am trying to get some data, but the query takes more then 5 minutes (it should be as fast as few milliseconds).

This is the table

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;

Here is the query

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;

This is the explain result:

*************************** 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)

Do you maybe have an idea how can I speed up this query?

It will be used for selecting bookings from a server, so it should be much faster. For bookings that happened in a period of 1 day the query takes more then 5 minutes, so for multiple days it is even worse..

---

This one executed in 0.01 seconds.

Done this, but still slow.

Here is output of optimize.

  mysql> OPTIMIZE TABLE bookings;

 +--------------------------+----------+----------+----------+
 | Table                    | Op       | Msg_type | Msg_text |
 +--------------------------+----------+----------+----------+
 | company.bookings | optimize | status   | OK       |
 +--------------------------+----------+----------+----------+
 1 row in set (0.02 sec)

Output of myisamchk

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

---

You are correct, the query starts slowing down after adding the jobs join. Before joining nextBo, execution time is 0.01 After nextBo join, it goes up to 0.1 After the first jobs join it goes up to few minutes

I made the change you suggested, but it is still not faster. Here is the new query

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;

The explain now says

*************************** 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)

Actually I just found out that I forgot to join the jobs table on idBuilding, so it was getting jobs of all buildings instead for the current one only. Anyways, the execution is now 1 seconds instead of 5 minutes, but the application should be much more responsive than that (around 0.01 seconds per day is acceptable, so if the search is for whole year then it would be around 3 seconds in total instead of 5 minutes like it is now..)

Here is the latest query

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;

And this is the explain result

*************************** 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)

Answer 1

Interesting. Actually, your query looks pretty good , the indexes look fine, your only WHERE clause variable is bo.checkinDT, which is indexed (although just part of a bigger index, but it' sa left part...).

What is the purpose of the GROUP BY ? You are not using any grouping functions. Are you shorthanding DISTINCT?

Can you try:

• Running the same query without the joins ( SELECT * FROM bookings bo where bo.checkinDT>='2014-07-18 00:00:00' and bo.checkinDT<='2014-07-18 23:59:59' ). Is that slow too? If not, it might be the joins/group by playing.
• Creating a seperate index on bookings.checkinDT ?
• Running an OPTIMIZE TABLE bookings once?
• Running myisamchk --sort-index --sort-records=9 (if 9 is the checkinDT index)?

(I'll update my answer as you provide details).

Ok, since the base query (only on bookings) is fast, the joins are slowing it down. Can you do a SELECT * for the base table, and one by one add a LEFT JOIN?

I'm guessing the jobs table (2749 rows) and (16040 rows) are causing the problem.

Am I seeing things wrong, or are you (currently) not even using the table?

If all you need is the next date for both, a subquery might be faster, you could try putting this in your select statement:

(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)

Gets the first "inspection" after the current checkout but before the next checkin.