Hoping you can help. I have three tables and would like to create a conditional query to make a subset based on a row's presence in one table then excluding the row from the results, then query a final, 3rd table. I thought this would be simple enough, but I'm not well practiced in SQL and after researching/testing for 6 hours on left joins, correlated sub-queries etc, it has helped, but I still can't hit the correct result set. So here's the setup:
T1
arn_mkt_stn
A00001_177_JOHN_FM
A00001_177_BILL_FM
A00001_174_DAVE_FM
A00002_177_JOHN_FM
A00006_177_BILL_FM
A00010_177_JOHN_FM - note: the name's relationship to the 3 digit prefix (e.g. _177) and the FM part always is consistent: '_177_JOHN_FM' only the A000XX changes
T2
arn_mkt
A00001_105
A00001_177
A00001_188
A00001_246
A00002_177
A00003_177
A00004_026
A00004_135
A00004_177
A00006_177
A00010_177
Example: So if _177_JOHN_FM is a substring of arn_mkt_stn rows in T1, exclude it when getting arn_mkts with a substring of 177 from T2 - in this case, the desired result set would be:
A00003_177
A00004_177
A00006_177
Similarly, _177_BILL_FM would return:
A00002_177
A00003_177
A00004_177
A00010_177
Then I would like to use this result set to pull records from a third table based on the 'A00003' etc
T3
arn
A00001
A00002
A00003
A00004
A00005
A00006
...
I've tried a number of methods [where here $stn_code = JOHN_FM and $stn_mkt = 177]
"SELECT * FROM T2, T1 WHERE arn != SUBSTRING(T1.arn_mkt_stn, 1,6)
AND SUBSTRING(T1.arn_mkt_stn, 12,7) = '$stn_code'
AND SUBSTRING(arn_mkt, 8,3) = '$stn_mkt' (then use this result to query T3..)
Also a left join and a subquery, but I'm clearly missing something!
Any pointers gratefully received, thanks,
Rich.
[EDIT: Thanks for helping out sgeddes. I'll expand on my logic above... first, the result set desired is always in connection with one name only per query, e.g. from T1, lets use JOHN_FM. In T1, JOHN_FM is currently associated with 'arn's (within the arn_mkt_stn): A00001, A00002 & A00010'. The next step in T2 is to find all the 'arn's (within arn_mkt)' that have JOHN_FM's 3 digit prefix (177), then exclude those that are in T1. Note: A00006 remains because it is not connected to JOHN_FM in T1. The same query for BILL_FM gives slightly different results, excluding A00001 & A00006 as it has this assoc in T1.. Thanks, R]
You can use a LEFT JOIN to remove the records from T2 that match those in T1. However, I'm not sure I'm understanding your logic.
You say A00001_177_JOHN_FM should return:
A00003_177
A00004_177
A00006_177
However, wouldn't A00006_177_BILL_FM exclude A00006_177 from the above results?
This query should be close (wasn't completely sure which fields you needed returned) to what you're looking for if I'm understanding you correctly:
SELECT T2.arn_mkt, T3.arn
FROM T2
LEFT JOIN T1 ON
T1.arn_mkt_stn LIKE CONCAT(T2.arn_mkt,'%')
INNER JOIN T3 ON
T2.arn_mkt LIKE CONCAT(T3.arn,'%')
WHERE T1.arn_mkt_stn IS NULL
Sample Fiddle Demo
--EDIT--
Reviewing the comments, this should be what you're looking for:
SELECT *
FROM T2
LEFT JOIN T1 ON
T1.arn_mkt_stn LIKE CONCAT(LEFT(T2.arn_mkt,LOCATE('_',T2.arn_mkt)),'%') AND T1.arn_mkt_stn LIKE '%JOHN_FM'
INNER JOIN T3 ON
T2.arn_mkt LIKE CONCAT(T3.arn,'%')
WHERE T1.arn_mkt_stn IS NULL
And here is the updated Fiddle: http://sqlfiddle.com/#!2/3c293/13
Related
Consider the following tables:
Table A:
DOC_NUM
DOC_TYPE
RELATED_DOC_NUM
NEXT_STATUS
...
Table B:
DOC_NUM
DOC_TYPE
RELATED_DOC_NUM
NEXT_STATUS
...
The DOC_TYPE and NEXT_STATUS columns have different meanings between the two tables, although a NEXT_STATUS = 999 means "closed" in both. Also, under certain conditions, there will be a record in each table, with a reference to a corresponding entry in the other table (i.e. the RELATED_DOC_NUM columns).
I am trying to create a query that will get data from both tables that meet the following conditions:
A.RELATED_DOC_NUM = B.DOC_NUM
A.DOC_TYPE = "ST"
B.DOC_TYPE = "OT"
A.NEXT_STATUS < 999 OR B.NEXT_STATUS < 999
A.DOC_TYPE = "ST" represents a transfer order to transfer inventory from one plant to another. B.DOC_TYPE = "OT" represents a corresponding receipt of the transferred inventory at the receiving plant.
We want to get records from either table where there is an ST/OT pair where either or both entries are not closed (i.e. NEXT_STATUS < 999).
I am assuming that I need to use a FULL OUTER join to accomplish this. If this is the wrong assumption, please let me know what I should be doing instead.
UPDATE (11/30/2021):
I believe that #Caius Jard is correct in that this does not need to be an outer join. There should always be an ST/OT pair.
With that I have written my query as follows:
SELECT <columns>
FROM A LEFT JOIN B
ON
A.RELATED_DOC_NUM = B.DOC_NUM
WHERE
A.DOC_TYPE IN ('ST') AND
B.DOC_TYPE IN ('OT') AND
(A.NEXT_STATUS < 999 OR B.NEXT_STATUS < 999)
Does this make sense?
UPDATE 2 (11/30/2021):
The reality is that these are DB2 database tables being used by the JD Edwards ERP application. The only way I know of to see the table definitions is by using the web site http://www.jdetables.com/, entering the table ID and hitting return to run the search. It comes back with a ton of information about the table and its columns.
Table A is really F4211 and table B is really F4311.
Right now, I've simplified the query to keep it simple and keep variables to a minimum. This is what I have currently:
SELECT CAST(F4211.SDDOCO AS VARCHAR(8)) AS SO_NUM,
F4211.SDRORN AS RELATED_PO,
F4211.SDDCTO AS SO_DOC_TYPE,
F4211.SDNXTR AS SO_NEXT_STATUS,
CAST(F4311.PDDOCO AS VARCHAR(8)) AS PO_NUM,
F4311.PDRORN AS RELATED_SO,
F4311.PDDCTO AS PO_DOC_TYPE,
F4311.PDNXTR AS PO_NEXT_STATUS
FROM PROD2DTA.F4211 AS F4211
INNER JOIN PROD2DTA.F4311 AS F4311
ON F4211.SDRORN = CAST(F4311.PDDOCO AS VARCHAR(8))
WHERE F4211.SDDCTO IN ( 'ST' )
AND F4311.PDDCTO IN ( 'OT' )
The other part of the story is that I'm using a reporting package that allows you to define "virtual" views of the data. Virtual views allow the report developer to specify the SQL to use. This is the application where I am using the SQL. When I set up the SQL, there is a validation step that must be performed. It will return a limited set of results if the SQL is validated.
When I enter the query above and validate it, it says that there are no results, which makes no sense. I'm guessing the data casting is causing the issue, but not sure.
UPDATE 3 (11/30/2021):
One more twist to the story. The related doc number is not only defined as a string value, but it contains leading zeros. This is true in both tables. The main doc number (in both tables) is defined as a numeric value and therefore has no leading zeros. I have no idea why those who developed JDE would have done this, but that is what is there.
So, there are matching records between the two tables that meet the criteria, but I think I'm getting no results because when I convert the numeric to a string, it does not match, because one value is, say "12345", while the other is "00012345".
Can I pad the numeric -> string value with zeros before doing the equals check?
UPDATE 4 (12/2/2021):
Was able to finally get the query to work by converting the numeric doc num to a left zero padded string.
SELECT <columns>
FROM PROD2DTA.F4211 AS F4211
INNER JOIN PROD2DTA.F4311 AS F4311
ON F4211.SDRORN = RIGHT(CONCAT('00000000', CAST(F4311.PDDOCO AS VARCHAR(8))), 8)
WHERE F4211.SDDCTO IN ( 'ST' )
AND F4311.PDDCTO IN ( 'OT' )
AND ( F4211.SDNXTR < 999
OR F4311.PDNXTR < 999 )
You should write your query as follows:
SELECT <columns>
FROM A INNER JOIN B
ON
A.RELATED_DOC_NUM = B.DOC_NUM
WHERE
A.DOC_TYPE IN ('ST') AND
B.DOC_TYPE IN ('OT') AND
(A.NEXT_STATUS < 999 OR B.NEXT_STATUS < 999)
LEFT join is a type of OUTER join; LEFT JOIN is typically a contraction of LEFT OUTER JOIN). OUTER means "one side might have nulls in every column because there was no match". Most critically, the code as posted in the question (with a LEFT JOIN, but then has WHERE some_column_from_the_right_table = some_value) runs as an INNER join, because any NULLs inserted by the LEFT OUTER process, are then quashed by the WHERE clause
See Update 4 for details of how I resolved the "data conversion or mapping" error.
I'm trying to find a way to find a way to compare two queries that use a combine sent of criteria. In this case we have Prefixes (Two letter code like DA) and Pack number 1234567. In the query I've created a field that combines these two things so it appears 1234567DA this is done with each of the queries from the separate tables they are pulled from. The idea is that if this is in one table and not the other it would show up as "False". I tried to use an Unmatched query but that doesn't seem to work. What I have currently is as follows:
SELECT
[1LagoTest].Prefix,
[1BigPicPackPref].BigPicPP,
IIf([BigPicPP]=[LagoPP],"True","False") AS Compare,
[1LagoTest].RETAIL,
[1LagoTest].MEDIA
FROM 1LagoTest
LEFT JOIN 1BigPicPackPref
ON [1LagoTest].[Prefix] = [1BigPicPackPref].[BigPicPP]
WHERE (((IIf([BigPicPP]=[LagoPP],"True","False")) Like "False")
AND (([1LagoTest].MEDIA) Not Like "*2019 FL*"))
ORDER BY [1LagoTest].RETAIL;
Right now it will show whats missing from LagoPP but doesn't give me anything from missing packs in BigPicPP. Any help in the right direction would be greatly appreciated.
Thanks!!
This gets a little tricky in Access without FULL OUTER JOIN, but the general idea to is replicate a FULL OUTER JOIN using UNION ALL, then filter from that.
Something like this:
SELECT I.Prefix,
I.BigPicPP,
I.Compare,
I.Retail,
I.Media
FROM (SELECT L.Prefix,
B.BigPicPP,
IIf([BigPicPP]=[LagoPP],"True","False") as Compare,
L.Retail,
L.Media
FROM 1LagoTest L
JOIN 1BigPicPackPref B ON L.Prefix = B.BigPicPP
WHERE L.Media NOT LIKE "*2019 FL*"
UNION ALL
SELECT L.Prefix,
B.BigPicPP,
"False", --Missing records from 1BigPicPackPref
L.Retail,
L.Media
FROM 1LagoTest L
LEFT JOIN 1BigPicPackPref B ON L.Prefix = B.BigPicPP
AND L.Media NOT LIKE "*2019 FL*"
WHERE B.Prefix IS NULL
UNION ALL
SELECT B.Prefix,
B.BigPicPP,
"False", --Missing records from 1LagoTest
L.Retail,
L.Media
FROM 1LagoTest L
RIGHT JOIN 1BigPicPackPref B ON L.Prefix = B.BigPicPP
AND L.Media NOT LIKE "*2019 FL*"
WHERE L.Prefix IS NULL
) AS I
You only need IFF in the first part of the union because in the second two parts one side will always be NULL, so we know the compare will always fail and be False.
You shouldn't need this part of your current WHERE clause at all (((IIf([BigPicPP]=[LagoPP],"True","False")) Like "False"). But if you only want to see False records, just add WHERE I.Compare = "False" to the bottom of the outer select.
The reason the "Unmatched" query (assuming through the Wizard) does not work, is because you are attempting to see the values of two separate tables / queries that do not match either table / query. This is not how the "Unmatched" works. All that will give you is a single table / query that does not match another single table / query.
This can most likely be done any number of ways, but this would probably get you where you want to be (or close to it):
SELECT
a.Prefix,
b.BigPicPP,
IIf([BigPicPP]=[LagoPP],"True","False") AS Compare,
a.RETAIL,
a.MEDIA
FROM [1LagoTest] a
LEFT JOIN [1BigPicPackPref] b ON a.Prefix = b.BigPicPP
WHERE a.MEDIA Not Like "*2019 FL*"
AND b.BigPicPP IS NULL
ORDER BY a.RETAIL
UNION
SELECT
a.Prefix,
b.BigPicPP,
IIf([BigPicPP]=[LagoPP],"True","False") AS Compare,
a.RETAIL,
a.MEDIA
FROM [1LagoTest] a
RIGHT JOIN [1BigPicPackPref] b ON a.Prefix = b.BigPicPP
WHERE a.MEDIA Not Like "*2019 FL*"
AND a.Prefix IS NULL
ORDER BY a.RETAIL
NOTE: Depending on the data structure, the ORDER BY may cause some issues.
So the way I got this to finally work was to build two separate queries. One looking at what was missing from Lago and One that was looking at what was missing from BigPic. It was the only way I could get it to give me both sets of missing data. If I can find a better way to do it through one query I will report back as I'm still gonna play around with it.
My query here has a sub-query in it but it returns no output, but in reality it has to give some output because I manually checked and output exists.I have posted the query below.
select mac.mac_id,mac.mac1,mac.mac_type,record.soc_id
from mso_charter.mac
join record on mac.record_id = record.record_id
where mac.mac_type='ethB' and record.soc_id IN (select soc from d);
Sample data is below
mac_id mac1 mac_type record_id--- for table mac
1 6142 ethA 1
2 6412 ethB 1
3 2313 ethC 1
record_id soc_id ---- for table record
1 Qu132
1 as432
1 342aq
soc --- for table d
a12w2
23we
qw12
mso_charter is the schema name mac,d and record is the table name.
Note that your subquery is actually still a join and can be written that way:
select mac.mac_id,mac.mac1,mac.mac_type,record.soc_id
from mso_charter.mac
join record using(record_id)
join d on record.soc_id = d.soc
where mac.mac_type='ethB';
As per the comment we still need a data set to reproduce and help.
Should be select soc_id from d instead of select select soc from d
According to your sample data, d has a column soc_id. That should be used for the comparison:
select m.mac_id, m.mac1, m.mac_type, r.soc_id
from mso_charter.mac m join
record r
on m.record_id = r.record_id
where m.mac_type = 'ethB' and
r.soc_id in (select d.soc_id from d);
It is possible that ids look the same but are not, because of international characters, hidden characters, spaces in the wrong place, and so on.
If this doesn't work then try the following:
Remove the soc_id condition and see if any rows match the first condition and join.
If that still returns nothing, remove the entire where clause to see if anything matches the join.
None of your record.soc_id match any of your d.soc_id. So you get no row.
Also, you write select soc from d. soc, not soc_id. Typo or error?
So, thanks to all who tried helping me in this situation. I actually had did a very silly mistake.The reason I am posting the right answer is probably because if someone else in future get stuck in such a issue or something similar it would be helpful to them.
select m.mac_id,m.mac,m.mac_type,r.soc_id
from mso_charter.mac m
join mso_charter.record r on m.record_id = r.record_id
where m.mac_type = 'ethB' and r.soc_id IN (select d.soc_id from d);
Mistake was I had not mentioned the schema name while performing join and there were multiple tables named record in other schema's, it was just out of frustration we tend to forget small things which costed me few hours to work over.
I pop into a problem recently, and Im sure its because of how I Join them.
this is my code:
select LP_Pending_Info.Service_Order,
LP_Pending_Info.Pending_Days,
LP_Pending_Info.Service_Type,
LP_Pending_Info.ASC_Code,
LP_Pending_Info.Model,
LP_Pending_Info.IN_OUT_WTY,
LP_Part_Codes.PartCode,
LP_PS_Codes.PS,
LP_Confirmation_Codes.SO_NO,
LP_Pending_Info.Engineer_Code
from LP_Pending_Info
join LP_Part_Codes
on LP_Pending_Info.Service_order = LP_Part_Codes.Service_order
join LP_PS_Codes
on LP_Pending_Info.Service_Order = LP_PS_Codes.Service_Order
join LP_Confirmation_Codes
on LP_Pending_Info.Service_Order = LP_Confirmation_Codes.Service_Order
order by LP_Pending_Info.Service_order, LP_Part_Codes.PartCode;
For every service order I have 5 part code maximum.
If the service order have only one value it show the result correctly but when it have more than one Part code the problem begin.
for example: this service order"4182134076" has only 2 part code, first'GH81-13601A' and second 'GH96-09938A' so it should show the data 2 time but it repeat it for 8 time. what seems to be the problem?
If your records were exactly the same the distinct keyword would have solved it.
However in rows 2 and 3 which have the same Service_Order and Part_Code if you check the SO_NO you see it is different - that is why distinct won't work here - the rows are not identical.
I say you have some problem in one of the conditions in your joins. The different data is in the SO_NO column so check the raw data in the LP_Confirmation_Codes table for that Service_Order:
select * from LP_Confirmation_Codes where Service_Order = 4182134076
I assume you are missing an and with the value from the LP_Part_Codes or LP_PS_Codes (but can't be sure without seeing those tables and data myself).
By this sentence If the service order have only one value it show the result correctly but when it have more than one Part code the problem begin. - probably you are missing and and with the LP_Part_Codes table
Based on your output result, here are the following data that caused multiple output.
Service Order: 4182134076 has :
2 PartCode which are GH81-13601A and GH96-09938A
2 PS which are U and P
2 SO_NO which are 1.00024e+09 and 1.00022e+09
Therefore 2^3 returns 8 rows. I believe that you need to check where you should join your tables.
Use DINTINCT
select distinct LP_Pending_Info.Service_Order,LP_Pending_Info.Pending_Days,
LP_Pending_Info.Service_Type,LP_Pending_Info.ASC_Code,LP_Pending_Info.Model,
LP_Pending_Info.IN_OUT_WTY, LP_Part_Codes.PartCode,LP_PS_Codes.PS,
LP_Confirmation_Codes.SO_NO,LP_Pending_Info.Engineer_Code
from LP_Pending_Info
join LP_Part_Codes on LP_Pending_Info.Service_order = LP_Part_Codes.Service_order
join LP_PS_Codes on LP_Part_Codes.Service_Order = LP_PS_Codes.Service_Order
join LP_Confirmation_Codes on LP_PS_Codes.Service_Order = LP_Confirmation_Codes.Service_Order
order by LP_Pending_Info.Service_order, LP_Part_Codes.PartCode;
distinct will not return duplicates based on your select. So if a row is same, it will only return once.
I'm trying to using the aggregation features of the django ORM to run a query on a MSSQL 2008R2 database, but I keep getting a timeout error. The query (generated by django) which fails is below. I've tried running it directs the SQL management studio and it works, but takes 3.5 min
It does look it's aggregating over a bunch of fields which it doesn't need to, but I wouldn't have though that should really cause it to take that long. The database isn't that big either, auth_user has 9 records, ticket_ticket has 1210, and ticket_watchers has 1876. Is there something I'm missing?
SELECT
[auth_user].[id],
[auth_user].[password],
[auth_user].[last_login],
[auth_user].[is_superuser],
[auth_user].[username],
[auth_user].[first_name],
[auth_user].[last_name],
[auth_user].[email],
[auth_user].[is_staff],
[auth_user].[is_active],
[auth_user].[date_joined],
COUNT([tickets_ticket].[id]) AS [tickets_captured__count],
COUNT(T3.[id]) AS [assigned_tickets__count],
COUNT([tickets_ticket_watchers].[ticket_id]) AS [tickets_watched__count]
FROM
[auth_user]
LEFT OUTER JOIN [tickets_ticket] ON ([auth_user].[id] = [tickets_ticket].[capturer_id])
LEFT OUTER JOIN [tickets_ticket] T3 ON ([auth_user].[id] = T3.[responsible_id])
LEFT OUTER JOIN [tickets_ticket_watchers] ON ([auth_user].[id] = [tickets_ticket_watchers].[user_id])
GROUP BY
[auth_user].[id],
[auth_user].[password],
[auth_user].[last_login],
[auth_user].[is_superuser],
[auth_user].[username],
[auth_user].[first_name],
[auth_user].[last_name],
[auth_user].[email],
[auth_user].[is_staff],
[auth_user].[is_active],
[auth_user].[date_joined]
HAVING
(COUNT([tickets_ticket].[id]) > 0 OR COUNT(T3.[id]) > 0 )
EDIT:
Here are the relevant indexes (excluding those not used in the query):
auth_user.id (PK)
auth_user.username (Unique)
tickets_ticket.id (PK)
tickets_ticket.capturer_id
tickets_ticket.responsible_id
tickets_ticket_watchers.id (PK)
tickets_ticket_watchers.user_id
tickets_ticket_watchers.ticket_id
EDIT 2:
After a bit of experimentation, I've found that the following query is the smallest that results in the slow execution:
SELECT
COUNT([tickets_ticket].[id]) AS [tickets_captured__count],
COUNT(T3.[id]) AS [assigned_tickets__count],
COUNT([tickets_ticket_watchers].[ticket_id]) AS [tickets_watched__count]
FROM
[auth_user]
LEFT OUTER JOIN [tickets_ticket] ON ([auth_user].[id] = [tickets_ticket].[capturer_id])
LEFT OUTER JOIN [tickets_ticket] T3 ON ([auth_user].[id] = T3.[responsible_id])
LEFT OUTER JOIN [tickets_ticket_watchers] ON ([auth_user].[id] = [tickets_ticket_watchers].[user_id])
GROUP BY
[auth_user].[id]
The weird thing is that if I comment out any two lines in the above, it runs in less that 1s, but it doesn't seem to matter which lines I remove (although obviously I can't remove a join without also removing the relevant SELECT line).
EDIT 3:
The python code which generated this is:
User.objects.annotate(
Count('tickets_captured'),
Count('assigned_tickets'),
Count('tickets_watched')
)
A look at the execution plan shows that SQL Server is first doing a cross-join on all the table, resulting in about 280 million rows, and 6Gb of data. I assume that this is where the problem lies, but why is it happening?
SQL Server is doing exactly what it was asked to do. Unfortunately, Django is not generating the right query for what you want. It looks like you need to count distinct, instead of just count: Django annotate() multiple times causes wrong answers
As for why the query works that way: The query says to join the four tables together. So say an author has 2 captured tickets, 3 assigned tickets, and 4 watched tickets, the join will return 2*3*4 tickets, one for each combination of tickets. The distinct part will remove all the duplicates.
what about this?
SELECT auth_user.*,
C1.tickets_captured__count
C2.assigned_tickets__count
C3.tickets_watched__count
FROM
auth_user
LEFT JOIN
( SELECT capturer_id, COUNT(*) AS tickets_captured__count
FROM tickets_ticket GROUP BY capturer_id ) AS C1 ON auth_user.id = C1.capturer_id
LEFT JOIN
( SELECT responsible_id, COUNT(*) AS assigned_tickets__count
FROM tickets_ticket GROUP BY responsible_id ) AS C2 ON auth_user.id = C2.responsible_id
LEFT JOIN
( SELECT user_id, COUNT(*) AS tickets_watched__count
FROM tickets_ticket_watchers GROUP BY user_id ) AS C3 ON auth_user.id = C3.user_id
WHERE C1.tickets_captured__count > 0 OR C2.assigned_tickets__count > 0
--WHERE C1.tickets_captured__count is not null OR C2.assigned_tickets__count is not null -- also works (I think with beter performance)