I have the following basic 3 Table Structure in mariadb/mysql.
MariaDB [aix_registry]> describe nodes;
+-------+--------------+------+-----+---------+----------------+
| Field | Type | Null | Key | Default | Extra |
+-------+--------------+------+-----+---------+----------------+
| id | int(11) | NO | PRI | NULL | auto_increment |
| name | varchar(256) | NO | | NULL | |
+-------+--------------+------+-----+---------+----------------+
2 rows in set (0.036 sec)
MariaDB [aix_registry]> describe attribs;
+------------+--------------+------+-----+---------+----------------+
| Field | Type | Null | Key | Default | Extra |
+------------+--------------+------+-----+---------+----------------+
| id | int(11) | NO | PRI | NULL | auto_increment |
| name | varchar(256) | NO | | NULL | |
| persistent | int(11) | YES | | 0 | |
| parent | varchar(256) | YES | | NODE | |
+------------+--------------+------+-----+---------+----------------+
4 rows in set (0.042 sec)
MariaDB [aix_registry]> describe entries;
+-----------+--------------+------+-----+---------------------+----------------+
| Field | Type | Null | Key | Default | Extra |
+-----------+--------------+------+-----+---------------------+----------------+
| id | int(11) | NO | PRI | NULL | auto_increment |
| node_id | int(11) | NO | MUL | NULL | |
| attrib_id | int(11) | NO | MUL | NULL | |
| value | varchar(256) | NO | | NULL | |
| ts | timestamp | NO | | current_timestamp() | |
+-----------+--------------+------+-----+---------------------+----------------+
5 rows in set (0.052 sec)
This simple SELECT returns incomplete records. I reduced the output of all follwing examples to a single dataset to avoid unnecessary clutter.
SELECT nodes.id AS NODE_ID, nodes.name AS NODE ,
MAX(CASE WHEN attribs.name = 'IP_LONG' THEN value END) AS IP_LONG,
MAX(CASE WHEN attribs.name = 'IP' THEN value END) AS IP,
MAX(CASE WHEN attribs.name = 'LOCATION' THEN value END) AS LOCATION
from entries left join nodes on nodes.id = node_id left join attribs on attribs.id = attrib_id WHERE entries.ts > DATE_SUB(NOW(), INTERVAL 1 DAY) GROUP BY nodes.name ORDER BY nodes.id ;
+---------+-------------+-------------------------------------------+--------------+------------+
| NODE_ID | NODE | IP_LONG | IP | LOCATION |
+---------+-------------+-------------------------------------------+--------------+------------+
| 31 | AIXDX4-TEST | 172.17.9.196/255.255.248.0/172.17.15.255/ | 172.17.9.196 | Wienerberg |
+---------+-------------+-------------------------------------------+--------------+------------+
The IP_LONG column is missing the follwing for example...
172.16.84.74/255.255.192.0/172.16.127.255/aixdx4-test.domain.org
My guess is, it has something to do with the MAX() Function has troubles with mixed Content in the Value Column. When leaving out MAX() and GROUP BY the missing Values are shown but Output is kind of chaotic.
SELECT nodes.id AS NODE_ID, nodes.name AS NODE,
CASE WHEN attribs.name = 'IP_LONG' THEN value END AS IP_LONG,
CASE WHEN attribs.name = 'IP' THEN value END AS IP,
CASE WHEN attribs.name = 'LOCATION' THEN value END AS LOCATION
from entries left join nodes on nodes.id = node_id left join attribs on attribs.id = attrib_id
WHERE entries.ts > DATE_SUB(NOW(), INTERVAL 1 DAY) ORDER BY nodes.id;
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | 172.17.9.196 | NULL |
| 31 | AIXDX4-TEST | 172.17.9.196/255.255.248.0/172.17.15.255/ | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | 172.16.84.74 | NULL |
| 31 | AIXDX4-TEST | 172.16.84.74/255.255.192.0/172.16.127.255/aixdx4-test.domain.org | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | 172.16.13.196 | NULL |
| 31 | AIXDX4-TEST | 172.16.13.196/255.255.254.0/172.16.13.255/ | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | Wienerberg |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL | NULL | NULL |
| 31 | AIXDX4-TEST | NULL
This Query gives the right Output, but i am unclear how to integrate that in the above, but this is a Topic for another question.
SELECT nodes.id AS NODE_ID, nodes.name AS NODE, entries.value
AS IP_NETMASK_BROADCAST_DNS
FROM (entries LEFT JOIN nodes ON(nodes.id = entries.node_id))
WHERE entries.attrib_id = (SELECT attribs.id FROM attribs WHERE attribs.name = 'IP_LONG') AND CAST(entries.ts AS date) = curdate() AND nodes.id = '31' ORDER BY nodes.name;
+---------+-------------+------------------------------------------------------------------+
| NODE_ID | NODE | IP_NETMASK_BROADCAST_DNS |
+---------+-------------+------------------------------------------------------------------+
| 31 | AIXDX4-TEST | 172.17.9.196/255.255.248.0/172.17.15.255/ |
| 31 | AIXDX4-TEST | 172.16.84.74/255.255.192.0/172.16.127.255/aixdx4-test.domain.org |
| 31 | AIXDX4-TEST | 172.16.13.196/255.255.254.0/172.16.13.255/ |
+---------+-------------+------------------------------------------------------------------+
These are the 3 values you are getting a max() of
172.17.9.196/255.255.248.0/172.17.15.255/
172.16.84.74/255.255.192.0/172.16.127.255/aixdx4-test.domain.org
172.16.13.196/255.255.254.0/172.16.13.255/
These are strings -- max looks at a "alphabetical" max. Since the "9" is greater than the 8 and the 1 the first one 172.17.9.196/255.255.248.0/172.17.15.255/ is picked. These values are all different -- which do you want and why? Do you want the longest one? The longest one would require different code.
Related
In my SQL Server database, I have a table with many duplicate values and I need to fetch results with distinct columns EID and YEAR and select rows containing fewer NULL values or order the table and get a final DISTINCT column EID and YEAR rows.
For example: below the table with EID = E138442 and YEAR = 2019 occurs 21 times were in this duplicate the row containing fewer null values should be fetched
+---------+------+------+------+------+------+------+------+------+------+------+------+------+------+
| EID | YEAR | JAN | FEB | MAR | APR | MAY | JUN | JUL | AUG | SEP | OCT | NOV | DEC |
+---------+------+------+------+------+------+------+------+------+------+------+------+------+------+
| E050339 | 2019 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | 1 |
| E050339 | 2020 | NULL | 6 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL |
| E050339 | 2020 | 13 | 6 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL |
| E138348 | 2019 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | 1 | NULL |
| E138348 | 2019 | NULL | 1 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL |
| e138372 | 2019 | 1 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL |
| E138440 | 2019 | NULL | NULL | 2 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL |
| E138442 | 2019 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | 5 |
| E138442 | 2019 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | 9 | 5 |
| E138442 | 2019 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | 9 | 5 |
| E138442 | 2019 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | 4 | 9 | 5 |
| E138442 | 2019 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | 4 | 9 | 5 |
| E138442 | 2019 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | 4 | 9 | 5 |
| E138442 | 2019 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | 4 | 9 | 5 |
| E138442 | 2019 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | 4 | 9 | 5 |
| E138442 | 2019 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | 4 | 4 | 9 | 5 |
| E138442 | 2019 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | 7 | 4 | 4 | 9 | 5 |
| E138442 | 2019 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | 7 | 4 | 4 | 9 | 5 |
| E138442 | 2019 | NULL | NULL | NULL | NULL | NULL | NULL | 7 | 7 | 4 | 4 | 9 | 5 |
| E138442 | 2019 | NULL | NULL | NULL | NULL | NULL | NULL | 7 | 7 | 4 | 4 | 9 | 5 |
| E138442 | 2019 | NULL | NULL | NULL | NULL | NULL | 2 | 7 | 7 | 4 | 4 | 9 | 5 |
| E138442 | 2019 | NULL | NULL | NULL | NULL | 7 | 2 | 7 | 7 | 4 | 4 | 9 | 5 |
| E138442 | 2019 | NULL | NULL | NULL | 7 | 7 | 2 | 7 | 7 | 4 | 4 | 9 | 5 |
| E138442 | 2019 | NULL | NULL | 1 | 7 | 7 | 2 | 7 | 7 | 4 | 4 | 9 | 5 |
| E138442 | 2019 | NULL | 1 | NULL | 7 | 7 | 2 | 7 | 7 | 4 | 4 | 9 | 5 |
| E138442 | 2020 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | 1 |
| E138442 | 2020 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | 1 |
| E138442 | 2020 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | 1 |
| E138442 | 2020 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | 1 |
+---------+------+------+------+------+------+------+------+------+------+------+------+------+------+
I need a SQL query to fetch values as shown here:
+---------+------+------+------+------+------+------+------+------+------+------+------+------+------+
| EID | YEAR | JAN | FEB | MAR | APR | MAY | JUN | JUL | AUG | SEP | OCT | NOV | DEC |
+---------+------+------+------+------+------+------+------+------+------+------+------+------+------+
| E050339 | 2020 | 13 | 6 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL |
| E138348 | 2019 | NULL | 1 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL |
| e138372 | 2019 | 1 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL |
| E138440 | 2019 | NULL | NULL | 2 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL |
| E138442 | 2019 | NULL | 1 | NULL | 7 | 7 | 2 | 7 | 7 | 4 | 4 | 9 | 5 |
| E138442 | 2020 | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | 1 |
+---------+------+------+------+------+------+------+------+------+------+------+------+------+------+
The result table should have a final row with distinct columns EID and YEAR.
SELECT *
FROM TABLE_NAME C1
WHERE EXISTS (SELECT 1
FROM TABLE_NAME C2
WHERE C1.EID = C2.EID AND C1.YEAR = C2.YEAR
HAVING COUNT(*) = 1)
ORDER BY
c1.EID, c1.YEAR, c1.JAN, c1.FEB, c1.MAR, c1.APR,
c1.MAY, c1.JUN, c1.JUL, c1.AUG, c1.SEP, c1.OCT, c1.NOV, c1.DEC ASC;
I tried the above code but found irrelevant results
since you have no other way to distinguish members of a group and based on "select rows containing fewer NULL values " here is one way how you can do it by using ctes, its not clean but probably the only way:
with cte as (
SELECT *,
ISNULL(c1.JAN, 1) + ISNULL(c1.FEB,1) + ... + ISNULL(c1.DEC,1) AS NullCount
FROM
tablename
)
, cte2 as (
select EID , YEAR , min(NullCount) min_nullcount
from cte
group by EID , YEAR
)
select t.*
from
cte t
join cte2 tt
on t.EID = tt.EID
and t.YEAR = tt.YEAR
and t.NULLCount = tt.min_nullcount
If you have duplicate minimum null per group you can use query below :
select * from (
SELECT *,
ROW_NUMBER OVER (partition by EID , YEAR order by ISNULL(c1.JAN, 1) + ... + ISNULL(c1.DEC,1) AS rnk
FROM
tablename
) xx
WHERE rnk = 1
Scenario:
I am trying to build a query which has a start and end date, And the result of this query gives me the days in between and the day name. I then want to JOIN to another table which has expected pay dates and amounts. The JOINED table may have more days outside the range of the start and end date, which I want to exclude.
Progress:
I sort-of have what I want, but not in the correct output, I have created the following thus far:
DECLARE
#startDate DATETIME,
#endDate DATETIME
SET #startDate = CONVERT(VARCHAR(4), DATEPART(YEAR, DATEADD(MONTH, -1, GETDATE())))+'-'+CONVERT(VARCHAR(2), DATEPART(MONTH, DATEADD(MONTH, -1, GETDATE())))+'-21'
SET #endDate = CONVERT(VARCHAR(4), DATEPART(YEAR, DATEADD(MONTH, -1, GETDATE())))+'-'+CONVERT(VARCHAR(2), DATEPART(MONTH, DATEADD(MONTH, -0, GETDATE())))+'-20'
;WITH dates AS
(
SELECT #startdate as Date,DATENAME(Dw,#startdate) As DayName
UNION ALL
SELECT DATEADD(d,1,[Date]),DATENAME(Dw,DATEADD(d,1,[Date])) as DayName
FROM dates
WHERE DATE < #enddate
)
SELECT LEFT(CONVERT(VARCHAR(30),Date, 106), 2) + '-' + LEFT(CONVERT(VARCHAR(30),Date, 10), 2) Date,DayName, SUM(ExpectedAmount), ExpectedDate FROM dates
FULL JOIN Commissions.dbo.ThreeMonthPayment on CONVERT(VARCHAR(30),Date) = Commissions.dbo.ThreeMonthPayment.ExpectedDate
GROUP BY Date, DayName, ExpectedDate
Order by ExpectedDate
Which results in this table (Sorry so long):
+-------+-----------+------------------+--------------+
| Date | DayName | (No column name) | ExpectedDate |
+-------+-----------+------------------+--------------+
| NULL | NULL | 0 | NULL |
| 21-03 | Friday | NULL | NULL |
| 22-03 | Saturday | NULL | NULL |
| 23-03 | Sunday | NULL | NULL |
| 24-03 | Monday | NULL | NULL |
| 25-03 | Tuesday | NULL | NULL |
| 26-03 | Wednesday | NULL | NULL |
| 27-03 | Thursday | NULL | NULL |
| 28-03 | Friday | NULL | NULL |
| 29-03 | Saturday | NULL | NULL |
| 30-03 | Sunday | NULL | NULL |
| 31-03 | Monday | NULL | NULL |
| 01-04 | Tuesday | NULL | NULL |
| 02-04 | Wednesday | NULL | NULL |
| 03-04 | Thursday | NULL | NULL |
| 04-04 | Friday | NULL | NULL |
| 05-04 | Saturday | NULL | NULL |
| 06-04 | Sunday | NULL | NULL |
| 07-04 | Monday | NULL | NULL |
| 08-04 | Tuesday | NULL | NULL |
| 09-04 | Wednesday | NULL | NULL |
| 10-04 | Thursday | NULL | NULL |
| 11-04 | Friday | NULL | NULL |
| 12-04 | Saturday | NULL | NULL |
| 13-04 | Sunday | NULL | NULL |
| 14-04 | Monday | NULL | NULL |
| 15-04 | Tuesday | NULL | NULL |
| 16-04 | Wednesday | NULL | NULL |
| 17-04 | Thursday | NULL | NULL |
| 18-04 | Friday | NULL | NULL |
| 19-04 | Saturday | NULL | NULL |
| 20-04 | Sunday | NULL | NULL |
| NULL | NULL | 89466 | 01-03 |
| NULL | NULL | 86058 | 01-04 |
| NULL | NULL | 23356 | 01-05 |
| NULL | NULL | 1858 | 01-06 |
| NULL | NULL | 13597 | 02-03 |
| NULL | NULL | 55587 | 02-04 |
| NULL | NULL | 7857 | 02-05 |
| NULL | NULL | 1377 | 02-06 |
| NULL | NULL | 6947 | 03-03 |
| NULL | NULL | 49626 | 03-04 |
| NULL | NULL | 0 | 03-05 |
| NULL | NULL | 0 | 03-06 |
| NULL | NULL | 6054 | 04-03 |
| NULL | NULL | 31639 | 04-04 |
| NULL | NULL | 0 | 04-05 |
| NULL | NULL | 0 | 04-06 |
| NULL | NULL | 26421 | 05-03 |
| NULL | NULL | 28154 | 05-04 |
| NULL | NULL | 15036 | 05-05 |
| NULL | NULL | 634 | 05-06 |
| NULL | NULL | 0 | 05-07 |
| NULL | NULL | 20832 | 06-03 |
| NULL | NULL | 0 | 06-04 |
| NULL | NULL | 0 | 06-05 |
| NULL | NULL | 0 | 06-06 |
| NULL | NULL | 5406 | 07-03 |
| NULL | NULL | 12864 | 07-04 |
| NULL | NULL | 4257 | 07-05 |
| NULL | NULL | 537 | 07-06 |
| NULL | NULL | 0 | 08-03 |
| NULL | NULL | 363 | 08-04 |
| NULL | NULL | 426 | 08-05 |
| NULL | NULL | 0 | 08-06 |
| NULL | NULL | 0 | 09-03 |
| NULL | NULL | 23240 | 09-04 |
| NULL | NULL | 0 | 09-05 |
| NULL | NULL | 0 | 09-06 |
| NULL | NULL | 12670 | 10-03 |
| NULL | NULL | 6790 | 10-04 |
| NULL | NULL | 0 | 10-05 |
| NULL | NULL | 0 | 10-06 |
| NULL | NULL | 2914 | 11-03 |
| NULL | NULL | 19053 | 11-04 |
| NULL | NULL | 0 | 11-05 |
| NULL | NULL | 0 | 11-06 |
| NULL | NULL | 6402 | 12-03 |
| NULL | NULL | 0 | 12-04 |
| NULL | NULL | 0 | 12-05 |
| NULL | NULL | 0 | 12-06 |
| NULL | NULL | 4166 | 13-03 |
| NULL | NULL | 0 | 13-04 |
| NULL | NULL | 0 | 13-05 |
| NULL | NULL | 0 | 13-06 |
| NULL | NULL | 50534 | 14-03 |
| NULL | NULL | 23854 | 14-04 |
| NULL | NULL | 15435 | 14-05 |
| NULL | NULL | 4003 | 14-06 |
| NULL | NULL | 475330 | 15-03 |
| NULL | NULL | 451014 | 15-04 |
| NULL | NULL | 103210 | 15-05 |
| NULL | NULL | 19947 | 15-06 |
| NULL | NULL | 12084 | 16-03 |
| NULL | NULL | 22203 | 16-04 |
| NULL | NULL | 517 | 16-05 |
| NULL | NULL | 0 | 16-06 |
| NULL | NULL | 31423 | 17-03 |
| NULL | NULL | 32150 | 17-04 |
| NULL | NULL | 0 | 17-05 |
| NULL | NULL | 0 | 17-06 |
| NULL | NULL | 33402 | 18-03 |
| NULL | NULL | 900 | 18-04 |
| NULL | NULL | 289 | 18-05 |
| NULL | NULL | 0 | 18-06 |
| NULL | NULL | 33929 | 19-03 |
| NULL | NULL | 6942 | 19-04 |
| NULL | NULL | 0 | 19-05 |
| NULL | NULL | 0 | 19-06 |
| NULL | NULL | 161806 | 20-03 |
| NULL | NULL | 141319 | 20-04 |
| NULL | NULL | 26659 | 20-05 |
| NULL | NULL | 4695 | 20-06 |
| NULL | NULL | 21074 | 21-03 |
| NULL | NULL | 15579 | 21-04 |
| NULL | NULL | 2693 | 21-05 |
| NULL | NULL | 0 | 21-06 |
| NULL | NULL | 28401 | 22-03 |
| NULL | NULL | 46258 | 22-04 |
| NULL | NULL | 11409 | 22-05 |
| NULL | NULL | 1672 | 22-06 |
| NULL | NULL | 76562 | 23-03 |
| NULL | NULL | 66804 | 23-04 |
| NULL | NULL | 32853 | 23-05 |
| NULL | NULL | 3168 | 23-06 |
| NULL | NULL | 47008 | 24-03 |
| NULL | NULL | 35888 | 24-04 |
| NULL | NULL | 4528 | 24-05 |
| NULL | NULL | 459 | 24-06 |
| NULL | NULL | 1108747 | 25-03 |
| NULL | NULL | 543351 | 25-04 |
| NULL | NULL | 152852 | 25-05 |
| NULL | NULL | 15712 | 25-06 |
| NULL | NULL | 343379 | 26-03 |
| NULL | NULL | 117657 | 26-04 |
| NULL | NULL | 41793 | 26-05 |
| NULL | NULL | 5645 | 26-06 |
| NULL | NULL | 0 | 27-02 |
| NULL | NULL | 401110 | 27-03 |
| NULL | NULL | 87571 | 27-04 |
| NULL | NULL | 39192 | 27-05 |
| NULL | NULL | 2801 | 27-06 |
| NULL | NULL | 313274 | 28-03 |
| NULL | NULL | 92607 | 28-04 |
| NULL | NULL | 21901 | 28-05 |
| NULL | NULL | 1852 | 28-06 |
| NULL | NULL | 77999 | 29-03 |
| NULL | NULL | 27693 | 29-04 |
| NULL | NULL | 3341 | 29-05 |
| NULL | NULL | 0 | 29-06 |
| NULL | NULL | 229556 | 30-03 |
| NULL | NULL | 261036 | 30-04 |
| NULL | NULL | 9109 | 30-05 |
| NULL | NULL | 545 | 30-06 |
| NULL | NULL | 460871 | 31-03 |
| NULL | NULL | 28710 | 31-05 |
+-------+-----------+------------------+--------------+
Out of the above results, I am trying to match the ExpectedDate to the date column , so instead of seeing the above results, I would have something that looks like this: (to keep it short, i haven't created all of the days I receive from my start and end date)
+-------+-----------+------------------+--------------+
| Date | DayName | (No column name) | ExpectedDate |
+-------+-----------+------------------+--------------+
| NULL | NULL | 0 | NULL |
| 21-03 | Friday | 21074 | 21-03 |
| 22-03 | Saturday | 28401 | 22-03 |
| 23-03 | Sunday | 76562 | 23-03 |
| 24-03 | Monday | 47008 | 24-03 |
+-------+-----------+------------------+--------------+
But you can see above that the expectedDate and date column are grouped / joined nicely together. And the expectedDates that are not in the date range are not displayed.
I have been struggling with this the entire morning :( is this possible ??
Any help or links to threads that I may have missed would be great!
I am using SQL SERVER 2008
Thanks so much.
first of all the full join includes everything. from both tables. if you only want the dates from the dates cte, use left join.
secondly, the CONVERT(VARCHAR(30),Date) = Commissions.dbo.ThreeMonthPayment.ExpectedDate seems to not work. are you sure you need to convert?
i suggest you try this:
DECLARE
#startDate DATETIME,
#endDate DATETIME
SET #startDate = CONVERT(VARCHAR(4), DATEPART(YEAR, DATEADD(MONTH, -1, GETDATE())))+'-'+CONVERT(VARCHAR(2), DATEPART(MONTH, DATEADD(MONTH, -1, GETDATE())))+'-21'
SET #endDate = CONVERT(VARCHAR(4), DATEPART(YEAR, DATEADD(MONTH, -1, GETDATE())))+'-'+CONVERT(VARCHAR(2), DATEPART(MONTH, DATEADD(MONTH, -0, GETDATE())))+'-20'
;WITH dates AS
(
SELECT #startdate as Date,DATENAME(Dw,#startdate) As DayName
UNION ALL
SELECT DATEADD(d,1,[Date]),DATENAME(Dw,DATEADD(d,1,[Date])) as DayName
FROM dates
WHERE DATE < #enddate
)
SELECT LEFT(CONVERT(VARCHAR(30),Date, 106), 2) + '-' + LEFT(CONVERT(VARCHAR(30),Date, 10), 2) Date
, DayName, SUM(ExpectedAmount), ExpectedDate
FROM dates
LEFT JOIN Commissions.dbo.ThreeMonthPayment
on Date = Commissions.dbo.ThreeMonthPayment.ExpectedDate
GROUP BY
Date
, DayName
, ExpectedDate
Order by
ExpectedDate
I'm trying to get the total count of a table from a left join where there's a multiple of the same id. Here's my example below -
Table 1:
+-------------+--------------+------+-----+---------+----------------+
| Field | Type | Null | Key | Default | Extra |
+-------------+--------------+------+-----+---------+----------------+
| id | int(11) | NO | PRI | NULL | auto_increment |
| project_id | int(11) | NO | | NULL | |
| token | varchar(32) | NO | | NULL | |
| email | varchar(255) | NO | | NULL | |
| status | char(1) | NO | | 0 | |
| permissions | varchar(255) | YES | | NULL | |
| created | datetime | NO | | NULL | |
| modified | datetime | NO | | NULL | |
+-------------+--------------+------+-----+---------+----------------+
Table 2:
+------------+-------------+------+-----+---------+----------------+
| Field | Type | Null | Key | Default | Extra |
+------------+-------------+------+-----+---------+----------------+
| id | int(11) | NO | PRI | NULL | auto_increment |
| name | varchar(32) | NO | | NULL | |
| account_id | int(11) | NO | | NULL | |
| created | datetime | NO | | NULL | |
| modified | datetime | NO | | NULL | |
| active | tinyint(1) | YES | | 1 | |
+------------+-------------+------+-----+---------+----------------+
I have this statement so far -
SELECT account_id, (SELECT COUNT(invitations.id)
FROM invitations WHERE invitations.project_id = projects.id) AS inv_count
FROM projects order by account_id;
And here's a sample of the results:
+------------+-----------+
| account_id | inv_count |
+------------+-----------+
| 1 | 0 |
| 2 | 2 |
| 2 | 0 |
| 3 | 4 |
| 3 | 0 |
| 3 | 4 |
| 3 | 0 |
| 4 | 6 |
| 4 | 3 |
| 4 | 3 |
| 4 | 5 |
| 4 | 3 |
| 4 | 9 |
| 5 | 6 |
| 5 | 0 |
| 5 | 4 |
| 5 | 2 |
| 5 | 2 |
How do I get account_id to show once and the sum of inv_count to show as 1 line? So I should see -
+------------+-----------+
| account_id | inv_count |
+------------+-----------+
| 1 | 0 |
| 2 | 2 |
| 3 | 8 |
You only need to put your query in a derived table (and name it, say tmp) and then group by the account_id:
SELECT account_id,
SUM(inv_count) AS inv_count
FROM
( SELECT account_id,
(SELECT COUNT(invitations.id)
FROM invitations
WHERE invitations.project_id = projects.id
) AS inv_count
FROM projects
) AS tmp
GROUP BY account_id
ORDER BY account_id ;
To simplify it farther, you can convert the inline subquery to a LEFT join. This way, no derived table is needed. I've also added aliases and removed the ORDER BY. MySQL does an implicit ORDER BY when you have GROUP BY so it's not needed here (unless you want to order by some other expression, different from the one you group by):
SELECT
p.account_id,
COUNT(i.id) AS inv_count
FROM
projects AS p
LEFT JOIN
invitations AS i
ON i.project_id = p.id
GROUP BY
p.account_id ;
I have the following SQL generated from my Rails app, it is trying to get a list of all auto models that have live adverts in a marketplace app & from mysql:
SELECT `models`.* FROM `models`
INNER JOIN `autos` ON autos.model_id = models.id
INNER JOIN `ads` ON `ads`.id = `autos`.ad_id
WHERE (ads.ad_status_id = 4 AND pub_start_date < NOW() AND pub_end_date > NOW() AND models.manufacturer_id = 50 )
GROUP BY models.id ORDER BY models.name;
When I run an explain, this is what I get:
Id 1 1 1
Select Type SIMPLE SIMPLE SIMPLE
Table models autos ads
Type ref ref eq_ref
Possible Keys PRIMARY,manufacturer_id model_id,ad_id PRIMARY,quick_search,ad_status_id
Key manufacturer_id model_id PRIMARY
Key Length 5 4 4
Ref const concept_development.models.id concept_development.autos.ad_id
Rows 70 205 1
Extra Using where; Using temporary; Using filesort Using where Using where
I cannot understand why the query is generating a temporary table / using file-sort - all of the referenced keys are indexes. Been trying to figure this out for a few days now and getting nowhere.
Any help is very much appreciated!
EXPLAIN models:
+---------------------+-------------+------+-----+---------+----------------+
| Field | Type | Null | Key | Default | Extra |
+---------------------+-------------+------+-----+---------+----------------+
| id | int(11) | NO | PRI | NULL | auto_increment |
| name | varchar(32) | YES | | NULL | |
| manufacturer_id | int(11) | YES | MUL | NULL | |
| vehicle_category_id | int(11) | NO | MUL | 1 | |
| synonym_names | longtext | YES | | NULL | |
+---------------------+-------------+------+-----+---------+----------------+
SHOW INDEXES FROM models:
+--------+------------+---------------------+--------------+---------------------+-----------+-------------+----------+--------+------+------------+---------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment |
+--------+------------+---------------------+--------------+---------------------+-----------+-------------+----------+--------+------+------------+---------+
| models | 0 | PRIMARY | 1 | id | A | 2261 | NULL | NULL | | BTREE | |
| models | 1 | manufacturer_id | 1 | manufacturer_id | A | 205 | NULL | NULL | YES | BTREE | |
| models | 1 | vehicle_category_id | 1 | vehicle_category_id | A | 7 | NULL | NULL | | BTREE | |
+--------+------------+---------------------+--------------+---------------------+-----------+-------------+----------+--------+------+------------+---------+
MODEL TABLE STATUS:
+--------+--------+---------+------------+------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+---------------------+---------------------+-------------------+----------+----------------+---------+
| Name | Engine | Version | Row_format | Rows | Avg_row_length | Data_length | Max_data_length | Index_length | Data_free | Auto_increment | Create_time | Update_time | Check_time | Collation | Checksum | Create_options | Comment |
+--------+--------+---------+------------+------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+---------------------+---------------------+-------------------+----------+----------------+---------+
| models | MyISAM | 10 | Dynamic | 2261 | 26 | 61000 | 281474976710655 | 84992 | 0 | 2751 | 2010-09-28 18:42:45 | 2010-09-28 18:42:45 | 2010-09-28 18:44:00 | latin1_swedish_ci | NULL | | |
+--------+--------+---------+------------+------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+---------------------+---------------------+-------------------+----------+----------------+---------+
EXPLAIN ADS
+------------------+--------------------------+------+-----+---------------------+----------------+
| Field | Type | Null | Key | Default | Extra |
+------------------+--------------------------+------+-----+---------------------+----------------+
| id | int(10) | NO | PRI | NULL | auto_increment |
| fp_urn | int(10) | NO | MUL | 0 | |
| user_id | int(10) | NO | MUL | 0 | |
| ad_status_id | int(3) unsigned | NO | MUL | 1 | |
| style_id | int(10) | NO | | 3 | |
| search_tags | varchar(255) | YES | | NULL | |
| title | varchar(255) | NO | | | |
| description | text | YES | | NULL | |
| currency | enum('EUR','GBP') | NO | | EUR | |
| price | decimal(8,2) | NO | MUL | 0.00 | |
| proposal_type | enum('Offered','Wanted') | NO | | Offered | |
| category_id | int(10) | YES | | 0 | |
| contact | varchar(50) | NO | MUL | | |
| area_id | int(10) | NO | | 0 | |
| origin_id | int(10) | NO | | 0 | |
| reject_reason_id | int(3) | NO | | 0 | |
| date_created | timestamp | NO | | 0000-00-00 00:00:00 | |
| last_modified | timestamp | NO | | CURRENT_TIMESTAMP | |
| pub_start_date | datetime | YES | | 0000-00-00 00:00:00 | |
| pub_end_date | datetime | YES | | 0000-00-00 00:00:00 | |
| bumped_up_date | datetime | YES | | 0000-00-00 00:00:00 | |
| state | smallint(6) | YES | | NULL | |
| eproofed | tinyint(1) | NO | | 0 | |
| is_featured | int(1) | NO | | 0 | |
| num_featured_imp | int(10) | YES | | 0 | |
| num_direct_imp | int(10) | YES | | 0 | |
| is_top_listed | int(1) | NO | | 0 | |
| delta | tinyint(1) | NO | | 0 | |
| ext_ref_id | varchar(50) | YES | | NULL | |
| email_seller | tinyint(1) | YES | | 1 | |
| sort_by | int(10) | YES | | 8 | |
| permalink | varchar(500) | YES | | NULL | |
| external_url | varchar(255) | YES | | NULL | |
+------------------+--------------------------+------+-----+---------------------+----------------+
SHOW TABLE STATUS FROM concept_development WHERE NAME LIKE 'ads';
+------+--------+---------+------------+--------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+-------------+------------+-----------------+----------+-------------------------------------------------+---------+
| Name | Engine | Version | Row_format | Rows | Avg_row_length | Data_length | Max_data_length | Index_length | Data_free | Auto_increment | Create_time | Update_time | Check_time | Collation | Checksum | Create_options | Comment |
+------+--------+---------+------------+--------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+-------------+------------+-----------------+----------+-------------------------------------------------+---------+
| ads | InnoDB | 10 | Compact | 656350 | 232 | 152748032 | 0 | 87736320 | 340787200 | 1148382 | 2010-09-29 09:55:46 | NULL | NULL | utf8_general_ci | NULL | checksum=1 delay_key_write=1 row_format=DYNAMIC | |
+------+--------+---------+------------+--------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+-------------+------------+-----------------+----------+-------------------------------------------------+---------+
SHOW INDEXES FROM ADS
+-------+------------+-----------+--------------+--------------+-----------+-------------+----------+--------+------+------------+---------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment |
+-------+------------+-----------+--------------+--------------+-----------+-------------+----------+--------+------+------------+---------+
| ads | 0 | PRIMARY | 1 | id | A | 521391 | NULL | NULL | | BTREE | |
| ads | 1 | NewIndex1 | 1 | ad_status_id | A | 15 | NULL | NULL | | BTREE | |
| ads | 1 | NewIndex1 | 2 | pub_end_date | A | 260695 | NULL | NULL | YES | BTREE | |
| ads | 1 | NewIndex1 | 3 | category_id | A | 521391 | NULL | NULL | YES | BTREE | |
| ads | 1 | NewIndex1 | 4 | style_id | A | 521391 | NULL | NULL | | BTREE | |
| ads | 1 | NewIndex2 | 1 | user_id | A | 130347 | NULL | NULL | | BTREE | |
| ads | 1 | NewIndex3 | 1 | price | A | 7667 | NULL | NULL | | BTREE | |
| ads | 1 | contact | 1 | contact | A | 260695 | NULL | NULL | | BTREE | |
| ads | 1 | fp_urn | 1 | fp_urn | A | 521391 | NULL | NULL | | BTREE | |
+-------+------------+-----------+--------------+--------------+-----------+-------------+----------+--------+------+------------+---------+
EXPLAIN autos
+-------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+------+-----+-------------+----------------+
| Field | Type | Null | Key | Default | Extra |
+-------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+------+-----+-------------+----------------+
| id | int(10) | NO | PRI | NULL | auto_increment |
| ad_id | int(10) | YES | MUL | NULL | |
| style_id | int(10) | YES | MUL | NULL | |
| manufacturer_id | int(10) | NO | MUL | NULL | |
| model_id | int(10) | NO | MUL | NULL | |
| registration | varchar(10) | YES | | NULL | |
| year | int(4) | YES | | NULL | |
| fuel_type | enum('Petrol','Diesel') | NO | | Petrol | |
| colour | varchar(75) | YES | | NULL | |
| mileage | varchar(25) | NO | | Not Entered | |
| mileage_units | enum('mls','kms') | NO | | mls | |
| num_doors | varchar(25) | NO | | Not Entered | |
| num_owners | int(2) | YES | | NULL | |
| engine_size | varchar(10) | YES | | NULL | |
| transmission_type | enum('Manual','Automatic') | NO | | Manual | |
| body_type | enum('Saloon','Hatchback') | NO | | Saloon | |
| condition | varchar(75) | NO | | NA | |
| extra_features | text | YES | | NULL | |
| tax_expiry | varchar(7) | YES | | NULL | |
| nct_expiry | varchar(7) | YES | | NULL | |
| variation | text | YES | | NULL | |
| tax_class | enum('Agricultural','Bus') | NO | | Private | |
| co2 | int(9) | YES | | NULL | |
+-------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+------+-----+-------------+----------------+
SHOW TABLE STATUS FROM concept_development WHERE NAME LIKE 'autos'
+-------+--------+---------+------------+--------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+-------------+------------+-----------------+----------+-------------------------------------------------+---------+
| Name | Engine | Version | Row_format | Rows | Avg_row_length | Data_length | Max_data_length | Index_length | Data_free | Auto_increment | Create_time | Update_time | Check_time | Collation | Checksum | Create_options | Comment |
+-------+--------+---------+------------+--------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+-------------+------------+-----------------+----------+-------------------------------------------------+---------+
| autos | InnoDB | 10 | Compact | 196168 | 136 | 26804224 | 0 | 26279936 | 340787200 | 485405 | 2010-09-17 22:09:45 | NULL | NULL | utf8_general_ci | NULL | checksum=1 delay_key_write=1 row_format=DYNAMIC | |
+-------+--------+---------+------------+--------+----------------+-------------+-----------------+--------------+-----------+----------------+---------------------+-------------+------------+-----------------+----------+-------------------------------------------------+---------+
show indexes from autos;
+-------+------------+-----------------+--------------+-----------------+-----------+-------------+----------+--------+------+------------+---------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment |
+-------+------------+-----------------+--------------+-----------------+-----------+-------------+----------+--------+------+------------+---------+
| autos | 0 | PRIMARY | 1 | id | A | 294937 | NULL | NULL | | BTREE | |
| autos | 1 | ad_id | 1 | ad_id | A | 294937 | NULL | NULL | YES | BTREE | |
| autos | 1 | style_id | 1 | style_id | A | 10 | NULL | NULL | YES | BTREE | |
| autos | 1 | manufacturer_id | 1 | manufacturer_id | A | 194 | NULL | NULL | | BTREE | |
| autos | 1 | model_id | 1 | model_id | A | 830 | NULL | NULL | | BTREE | |
+-------+------------+-----------------+--------------+-----------------+-----------+-------------+----------+--------+------+------------+---------+
From the MySQL documentation:
Temporary tables can be created under conditions such as these:
* If there is an ORDER BY clause and a different GROUP BY clause, or if the ORDER BY or GROUP BY contains columns from tables other than the first table in the join queue, a temporary table is created.
http://dev.mysql.com/doc/refman/5.1/en/internal-temporary-tables.html
Change all the text columns to varchar. If you need to maintain them as "text", you'll need to snowflake the schema and exclude the description tables from this query.
If any of the columns in any of the tables are text or blob, MySQL automatically creates an on-disk temporary table, rather than an in-memory temporary table. The temporary table itself isn't killing you, it's the fact that it's writing it to the disk.
http://dev.mysql.com/doc/refman/5.1/en/internal-temporary-tables.html
Some conditions prevent the use of an in-memory temporary table, in which case the server uses an on-disk table instead:
Presence of a BLOB or TEXT column in the table
You have a index on pub_end_date, but not on pub_start_date and your WHERE clause references both.
It looks like it is not using the pub_end_date index, but this could be because it needs to check pub_start_date as well.
This isn't explaining why but how about you rewrite your query to not use a group by? I think you're just joining on those tables to ensure there exists an ad of interest. So how about:
SELECT `models`.*
FROM `models`
WHERE models.manufacturer_id = 50
AND EXISTS ( SELECT * FROM `autos`
INNER JOIN `ads` ON `ads`.id = `autos`.ad_id
WHERE autos.model_id = models.id
AND ads.ad_status_id = 4
AND ads.pub_start_date < NOW()
AND ads.pub_end_date > NOW()
)
ORDER BY models.name;
The performance issues might be related to the group by, in which case this would improve performance.
Maybe it'd look a bit nicer with and NOW() between ads.pub_start_date and ads.pub_end_date, if you're allowed to do that in mysql (and if it works how you want with the edge cases).
EDIT: Updated with suggestions from Bill Karwin below. Still very slow.
I'm trying to write a query that will find all items on an order that are entered to a warehouse that doesn't have a record for that item in that warehouse. As an example, if item XYZ is entered for warehouse A, but warehouse A doesn't actually carry item XYZ, I want the order item to show up in my report.
I'm able to run the query just fine, but it seems to take forever (50 seconds). It seems to be hanging mainly on the "is null" condition I have in the where clause. If I remove the condition with the "is null" and run it, it executes in about 4.8s. Here's my query:
SELECT
saw_order.Wo,
saw_orderitem.Item,
saw_orderitem.Stock,
saw_order.`Status`,
saw_order.`Date`,
saw_orderitem.Warehouse,
saw_stockbalance.Balno,
saw_stockbalance.Stock
FROM
saw_order
Inner Join saw_orderitem ON saw_order.Wo = saw_orderitem.Wo
Inner Join saw_stock ON saw_orderitem.Stock = saw_stock.Stock
Left Join saw_stockbalance ON saw_orderitem.Stock = saw_stockbalance.Stock
AND saw_orderitem.Warehouse = saw_stockbalance.Warehouse
WHERE
saw_order.`Status` Between 3 and 81 and
saw_stockbalance.Stock Is Null
When I explain the query above, I see:
+----+-------------+------------------+--------+------------------------------+---------+---------+-------------------------------------------------------+-------+-------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+------------------+--------+------------------------------+---------+---------+-------------------------------------------------------+-------+-------------------------+
| 1 | SIMPLE | saw_stock | index | PRIMARY | PRIMARY | 17 | NULL | 32793 | Using index |
| 1 | SIMPLE | saw_orderitem | ref | PRIMARY,Stock,StockWarehouse | Stock | 17 | saws.saw_stock.Stock | 68 | |
| 1 | SIMPLE | saw_order | eq_ref | PRIMARY,Status | PRIMARY | 4 | saws.saw_orderitem.Wo | 1 | Using where |
| 1 | SIMPLE | saw_stockbalance | ref | Stock,Warehouse | Stock | 20 | saws.saw_orderitem.Stock,saws.saw_orderitem.Warehouse | 1 | Using where; Not exists |
+----+-------------+------------------+--------+------------------------------+---------+---------+-------------------------------------------------------+-------+-------------------------+
I'm pretty sure I have indexes for all of the fields of the respective tables in my joins, but can't figure out how to rewrite the query to make it go faster.
EDIT: Here are the indexes I have set up on my tables:
mysql> show index from saw_order;
+-----------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment |
+-----------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
| saw_order | 0 | PRIMARY | 1 | Wo | A | 553425 | NULL | NULL | | BTREE | |
| saw_order | 1 | Customer | 1 | Customer | A | 14957 | NULL | NULL | | BTREE | |
| saw_order | 1 | Other | 1 | Other | A | 218 | NULL | NULL | | BTREE | |
| saw_order | 1 | Site | 1 | Site | A | 8 | NULL | NULL | | BTREE | |
| saw_order | 1 | Date | 1 | Date | A | 1594 | NULL | NULL | | BTREE | |
| saw_order | 1 | Status | 1 | Status | A | 15 | NULL | NULL | | BTREE | |
+-----------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
6 rows in set
mysql> show index from saw_orderitem;
+---------------+------------+----------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment |
+---------------+------------+----------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
| saw_orderitem | 0 | PRIMARY | 1 | Wo | A | NULL | NULL | NULL | | BTREE | |
| saw_orderitem | 0 | PRIMARY | 2 | Item | A | 1842359 | NULL | NULL | | BTREE | |
| saw_orderitem | 1 | Stock | 1 | Stock | A | 27093 | NULL | NULL | | BTREE | |
| saw_orderitem | 1 | Product | 1 | Product | A | 803 | NULL | NULL | | BTREE | |
| saw_orderitem | 1 | GGroup | 1 | GGroup | A | 114 | NULL | NULL | | BTREE | |
| saw_orderitem | 1 | ShipVia | 1 | ShipVia | A | 218 | NULL | NULL | | BTREE | |
| saw_orderitem | 1 | Warehouse | 1 | Warehouse | A | 9 | NULL | NULL | | BTREE | |
| saw_orderitem | 1 | StockWarehouse | 1 | Stock | A | 27093 | NULL | NULL | | BTREE | |
| saw_orderitem | 1 | StockWarehouse | 2 | Warehouse | A | 49793 | NULL | NULL | | BTREE | |
+---------------+------------+----------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
9 rows in set
mysql> show index from saw_stock;
+-----------+------------+-------------------+--------------+-------------------+-----------+-------------+----------+--------+------+------------+---------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment |
+-----------+------------+-------------------+--------------+-------------------+-----------+-------------+----------+--------+------+------------+---------+
| saw_stock | 0 | PRIMARY | 1 | Stock | A | 32793 | NULL | NULL | | BTREE | |
| saw_stock | 1 | Class | 1 | Class | A | 655 | NULL | NULL | YES | BTREE | |
| saw_stock | 1 | DateFirstReceived | 1 | DateFirstReceived | A | 2732 | NULL | NULL | | BTREE | |
+-----------+------------+-------------------+--------------+-------------------+-----------+-------------+----------+--------+------+------------+---------+
3 rows in set
mysql> show index from saw_stockbalance;
+------------------+------------+-----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment |
+------------------+------------+-----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
| saw_stockbalance | 0 | PRIMARY | 1 | Balno | A | 146315 | NULL | NULL | | BTREE | |
| saw_stockbalance | 1 | Stock | 1 | Stock | A | 36578 | NULL | NULL | | BTREE | |
| saw_stockbalance | 1 | Stock | 2 | Warehouse | A | 146315 | NULL | NULL | | BTREE | |
| saw_stockbalance | 1 | Warehouse | 1 | Warehouse | A | 11 | NULL | NULL | | BTREE | |
+------------------+------------+-----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
4 rows in set
Any ideas?
I'd try to make it use a covering index. That is, instead of testing if Balno is null, test if one of the columns in your left outer join conditions is null. E.g. Stock or Warehouse.
You should also define an index over the two columns (Stock, Warehouse) in both tables saw_orderitem and saw_stockbalance.
Try:
SELECT t.wo,
soi.item,
soi.stock,
t.Status,
t.Date,
soi.warehouse,
NULL 'balno', --ssb.Balno,
NULL 'stock', --ssb.Stock
FROM SAW_ORDER t
JOIN SAW_ORDERITEM soi ON soi.wo = t.wo
JOIN SAW_STOCK ss ON ss.stock = soi.stock
WHERE t.status BETWEEN 3 AND 81
AND NOT EXISTS (SELECT NULL
FROM SAW_STOCKBALANCE ssb
WHERE ssb.stock != soi.stock
AND ssb.warehouse = soi.warehouse)
The problem with the query is that you are checking for nulls on a LEFT JOIN...