In an attempt to create a listing of Orders (each with multiple items) that satisfy some criteria, I have attempted to create a typical LEFT JOIN statement.
The attempt looks like this
SELECT
Q1.Order_Number,
OD.Item_Num
FROM
(
SELECT
OS.Order_Number
FROM
[4-Open_Order_Summary] AS OS
WHERE
Date() >= OS.Ship_Date AND
OS.Back_Ordered > 0
)
AS Q1
LEFT JOIN [1-Open_Order_Data] AS OD
ON Q1.Order_Number = OD.Order_Number
Running this query gives me an unexplained "Invalid operation" error. Researching this error with regards to Access SQL has led me to this question on StackOverflow pertaining to multiple JOIN statements of different types, and this question on the SuperUser branch pertaining to FULL OUTER JOIN statements. However I was unable to find questions related to a single LEFT JOIN statement.
In my attempts to resolve this I have done the following;
Changing
ON Q1.Order_Number = OD.Order_Number to
ON Q1.Order_Number LIKE OD.Order_Number
crashes Access
Running
SELECT
Q1.Order_Number,
FROM
(
SELECT
OS.Order_Number
FROM
[4-Open_Order_Summary] AS OS
WHERE
Date() >= OS.Ship_Date AND
OS.Back_Ordered > 0
)
AS Q1
returns the intended order numbers.
Why not try something like the following if you're trying to get Order Numbers from one table, and related Order Details from another?
SELECT
Q1.Order_Number
OD.Item_Num
FROM
[4-Open_Order_Summary] Q1
LEFT JOIN
[1-Open_Order_Data] OD
ON
OD.Order_Number = Q1.Order_Number
WHERE
DATE() >= Q1.Ship_Date
AND Q1.Back_Ordered > 0
Related
I have the following SQL string which tries to combine an INNER JOIN with a LEFT JOIN in the FROM section.
As you can see I use table VIP_APP_VIP_SCENARIO_DETAIL_LE to perform the query. When I use it against this table, Access give me an "Invalid Operation" error.
Interestingly, when I use the EXACT same query using the VIP_APP_VIP_SCENARIO_DETAIL_BUDGET or VIP_APP_VIP_SCENARIO_DETAIL_ACTUALS table, it performs flawlessly.
So why would it work on two tables but not the other? All fields are in all tables and the data types are correct.
As a side note: on the query with the error, if I change the LEFT JOIN to an INNER JOIN, it runs with no problem! I really need a LEFT JOIN though.
SELECT
D.MATERIAL_NUMBER,
D.MATERIAL_DESCRIPTION,
D.PRODUCTION_LOT_SIZE,
D.STANDARDS_NAME,
D.WORK_CENTER,
S.OP_SHORT_TEXT,
S.OPERATION_CODE,
D.LINE_SPEED_UPM,
D.PERCENT_STD,
D.EQUIPMENT_SU,
D.EQUIPMENT_CU,
D.OPERATOR_NUM,
V.COSTING_LOT_SIZE,
V.VOL_TOTAL_ADJ
FROM
([STDS_SCENARIO: TEST] AS D INNER JOIN MASTER_SUMMARY AS S ON
D.MATERIAL_NUMBER = S.MATERIAL_NUMBER AND D.WORK_CENTER = S.WORK_CENTER)
LEFT JOIN
(SELECT ITEM_CODE, COSTING_LOT_SIZE, VOL_TOTAL_ADJ
FROM
VIP_APP_VIP_SCENARIO_DETAIL_LE
WHERE SCENARIO_ID = 16968) AS V ON D.MATERIAL_NUMBER = V.ITEM_CODE
ORDER BY D.MATERIAL_NUMBER, D.STANDARDS_NAME, S.OPERATION_CODE;
tried to mock this up in SQL server with some tables of my own, but the structure seemed to work, this follows the pattern referenced above. (hopefully no syntax errors left here)
SELECT * FROM (
select
D.MATERIAL_NUMBER,
D.MATERIAL_DESCRIPTION,
D.PRODUCTION_LOT_SIZE,
D.STANDARDS_NAME,
D.WORK_CENTER,
S.OP_SHORT_TEXT,
S.OPERATION_CODE,
D.LINE_SPEED_UPM,
D.PERCENT_STD,
D.EQUIPMENT_SU,
D.EQUIPMENT_CU,
D.OPERATOR_NUM
FROM [STDS_SCENARIO: TEST] D
INNER JOIN MASTER_SUMMARY S
ON D.MATERIAL_NUMBER = S.MATERIAL_NUMBER AND D.WORK_CENTER = S.WORK_CENTER) AS J
LEFT JOIN
(SELECT ITEM_CODE, COSTING_LOT_SIZE, VOL_TOTAL_ADJ
FROM
VIP_APP_VIP_SCENARIO_DETAIL_LE
WHERE SCENARIO_ID = 16968) AS V ON J.MATERIAL_NUMBER = V.ITEM_CODE
ORDER BY J.MATERIAL_NUMBER, J.STANDARDS_NAME, J.OPERATION_CODE;
Had help from a friend and we discovered that it was a casting problem between a linked Oracle table and the Access table. To fix the problem we casted both sides of the linked fields to a string:
CSTR(D.[MATERIAL_NUMBER]) = CSTR(V.[ITEM_CODE])
I am doing a query build in hive, the query is given below.
*
Select * from CSS407
LEFT OUTER JOIN PROD_CORE.SERV_ACCT_ISVC_LINK SASP
ON CSS407.TABLE_ABBRV_CODE = 'SACT'
AND CSS407.EVENT_ITEM_REF_NUM = SASP.Serv_Acct_Id
AND to_date(CSS407.EVENT_RTS_VAL) >= SASP.Acct_Serv_Pnt_Strt_Dt
AND to_date(CSS407.EVENT_RTS_VAL) < SASP.Acct_Serv_Pnt_End_Dt
LEFT OUTER JOIN PROD_CORE.CUST_ACCT_SA_LINK ASA
ON CSS407.TABLE_ABBRV_CODE = 'SACT'
AND CSS407.EVENT_ITEM_REF_NUM = ASA.Serv_Acct_Id
AND CSS407.EVENT_RTS_VAL_UTC_DTTM >= ASA.Acct_Relt_Strt_Dttm
AND CSS407.EVENT_RTS_VAL_UTC_DTTM < ASA.Acct_Relt_End_Dttm
LEFT OUTER JOIN PROD_CORE.CUST_SA_LINK ASAT
ON CSS407.TABLE_ABBRV_CODE = 'TACT'
AND CSS407.EVENT_ITEM_REF_NUM = ASAT.Serv_Acct_Id
AND CSS407.EVENT_RTS_VAL_UTC_DTTM >= ASAT.Acct_Relt_Strt_Dttm
AND CSS407.EVENT_RTS_VAL_UTC_DTTM < ASAT.Acct_Relt_End_Dttm
*
When I am executing the above table in hive I am getting the below error
"Both left and right aliases encountered in JOIN 'SASP'"
On further investigation I founded that we cannot use date between filter in the join on condition. In every post everyone is asking to insert that filter in where condition.
But in our case if we are moving that date between filter to where condition then we are not getting any data since left outer join is not satisfying.
I am getting this issue while executing in HIVE, it is working fine in Teradata and oracle
Please help.
Only equality(=) works in join condition in Hive.Move <= to where clause.
I have the similar issue earlier.Please check below thread.
Hive Select MAX() in Join Condition
Hope this helps.
There might be some common column between CSS407 and SERV_ACCT_ISVC_LINK which might be creating this error.
Hey All i am using sum iff to return a count based on multiple criteria.
i am basically running a report on calls recieved per site, however i need sites with 0 calls included in the result set, with the value of 0 or even Null, if they have no calls for that week.
only issue is that my where cluase has only included sites that have had calls in the week
Any ideas.
Code:
SELECT
d.sitename,
count(c.Chargeablecalls) AS All_Calls,
SUM(IIf(c.ChargeableCalls Like "Chargeable",1,0)) AS Chargeable_calls,
d.sitetype
FROM
(Callstatus AS s LEFT JOIN statusconversion AS c ON s.description=c.reportheading)
INNER JOIN sitedetails AS d ON s.zone=d.zone
WHERE s.date_loaded BETWEEN
(SELECT reportdate FROM reportMonth) AND (SELECT priorweek FROM reportMonth)
GROUP BY d.sitename, d.sitetype;
You need a RIGHT JOIN for sitedetails in order to get all the sites even those with no calls.
You may need to do the first half of query separately and then use that query in the main query.
create a new query - qryCallStatus:
SELECT DISTINCT zone, description
FROM Callstatus, reportMonth
WHERE
Callstatus.date_loaded BETWEEN reportMonth.reportdate AND reportMonth.priorweek;
Then change your output query to:
SELECT
d.sitename,
count(c.Chargeablecalls) AS All_Calls,
SUM(IIf(c.ChargeableCalls Like "Chargeable",1,0)) AS Chargeable_calls,
d.sitetype
FROM
(sitedetails AS d LEFT JOIN qryCallStatus AS s ON d.zone=s.zone)
LEFT JOIN statusconversion AS c ON s.description=c.reportheading
GROUP BY d.sitename, d.sitetype;
I know this is an older issue with Google BigQuery, but it seems the problem had been fixed # mid 2013. I wanted to know if there has been any recent workarounds/fixes to this issue in the recent months. Here is my query from the google sample data.
SELECT publicdata:samples.natality.mother_age, publicdata:samples.gsod.station_number
FROM [publicdata:samples.natality]
INNER JOIN [publicdata:samples.gsod]
ON publicdata:samples.gsod.year = publicdata:samples.natality.year
LIMIT 100
Query Failed
Error: Unexpected. Please try again.
Job ID: deft-grammar-553:job_eUkW4EhgNvlJPuWPoP1bLL7Ra_w
Thanks for the report! That error message should be improved.
In the meantime: The same query using table aliases works well (though I had to change the JOIN to JOIN EACH to deal with the size of both tables).
Instead of:
SELECT publicdata:samples.natality.mother_age, publicdata:samples.gsod.station_number
FROM [publicdata:samples.natality]
INNER JOIN [publicdata:samples.gsod]
ON publicdata:samples.gsod.year = publicdata:samples.natality.year
LIMIT 100
Do:
SELECT a.mother_age, b.station_number
FROM [publicdata:samples.natality] a
INNER JOIN EACH [publicdata:samples.gsod] b
ON a.year = b.year
LIMIT 100
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)