I am trying to write a query that looks for a people that have a certain code with the latest period (year) but not if they have another code with that latest period(year). I'll be explicit just so my example makes sense.
I want people who have the code A1,A2,A3,A4,A5 but not AG,AP,AQ. There are people who have an A1 code for a period (like 2014) and an AG code for a the same period. I'd like to exclude them. Not everyone has a code so the field value could be NULL.
Is there a way to express this in a different way (i.e. less characters) than the way I did?
SELECT
people.firstName
FROM
people
WHERE EXISTS (
SELECT *
FROM codes
WHERE
codes.people_id = people.id
AND period = (SELECT MAX(period) FROM codes codes2 WHERE codes2.people_id = codes.people_id)
AND code LIKE 'A[1-5]'
)
AND NOT EXISTS (
SELECT *
FROM codes
WHERE
codes.people_id = people.id
AND period = (
SELECT MAX(period)
FROM codes codes2
WHERE codes2.people_id = codes.people_id
)
AND code LIKE 'A[GPQ]'
)
Schema is as follows:
People
id (PK)
firstName
Codes
people_id (FK) many to one relation with People table
code (e.g. "A1", "A2", "AG")
period (e.g. "2013", "2014")
There are so many ways you could do that, I'm not an SQL expert but I can't see your query being too bad, if you want to try and reduce the number of sub-queries you could consider using the GROUP BY clause along with a SUM Aggregate function in a HAVING clause.
I started updating your code as follows:
SELECT
people.firstName
FROM
people
LEFT JOIN codes AS a15 ON a15.people_id = people.id AND a15.code LIKE 'A[1-5]'
LEFT JOIN codes AS agpq ON agpq.people_id = people.id AND agpq.code LIKE 'A[GPQ]'
GROUP BY
people.firstName
HAVING
SUM(CASE WHEN a15.code IS NULL THEN 0 ELSE 1 END) > 0
AND SUM(CASE WHEN agpq.code IS NULL THEN 0 ELSE 1 END) = 0
This however doesn't take into account anything to do with period specific requirements described. You could add the period to the GROUP BY clause or add it to a WHERE or one of the JOIN constraints but I'm not quite sure from your description exactly what you're after (I don't believe this is through any fault of your own, I just can't personally align the code provided to the description).
I would also like to point out that the SUM functions above will not give an accurate count of the number of matching codes. This is because if both A[GPQ] and A[1_5] return at least one row, the number returned by each constraint will be multiplied by the number returned for the other, it can however be used to determine if there are "any" returned items as if the criteria is matched it will have a SUM(...) > 0
I'm sure a more experienced SQL Developer / DBA will be able to poke many holes in my proposed query but it might give them or someone else something to work from and hopefully gives you ideas for alternatives to using sub-queries.
Related
I'm trying to calculate the rating based on a table that has 3 columns with different ratings ranging from 1 to 5.
I wanted to calculate the average of these 3 values and then be able to use this as an argument in queries, for example:
Where Rating >3.5
At this moment I have this that gives me the average for all suppliers
SELECT c.Name
,(SELECT CAST(AVG(rat) AS DECIMAL(5, 2))
FROM(
VALUES(b.Qty_Price),
(b.Quality),
(b.DeliveryTime)) A (rat)) AS Rating
FROM Order a
JOIN Evaluation b ON b.ID_Evaluation = a.ID_Evaluation
JOIN Supplier c ON c.NIF_Supplier = a.NIF_Supplier
What I would like now is, for example, to filter the providers that have more than 3 ratings, but I don't know how I can do that. If anyone can help i would be grateful
If the query works like you want it, you get the average for all entries, that is.
The WHERE rating > 3.5 cannot be added, as rating does not exist in the context of the SELECT-clause, nor the tables we JOIN.
To overcome this issue, we can keep the query that you have made, call it something different using WITH and SELECT from that sub-query WHERE rating > 3.5
It should look something like this:
WITH Averages(name, rating) AS
(SELECT c.name
,(SELECT CAST(AVG(rat) AS DECIMAL(5, 2))
FROM(
VALUES(b.qty_Price),
(b.quality),
(b.deliveryTime)) AS (rat)) AS rating
FROM Order a
JOIN Evaluation b ON b.ID_Evaluation = a.ID_Evaluation
JOIN Supplier c ON c.NIF_Supplier = a.NIF_Supplier)
SELECT name, rating FROM Averages WHERE rating > 3.5;
Now, we simply call the query you provided as Averages for example, and we SELECT from that table WHERE rating > 3.5.
Also note that you can have multiple WITHs to make things easier for you, but remember that a comma (,) is needed to seperate them. In our case, we only have 1 use of WITH ... AS, so no need for a comma or semi-colon after ...= a.NIF_Supplier)
Looks like you typed only "A" before "(rat)", it should be "AS". Also, remember that attributes should be lowercase, it makes it easier for all of us to distinguish tables from attributes.
Cheers!
Good evening. Could someone please help me with the following. I am trying to join two tables.The first id wbr_global.gl_ap_details. This stores historic GL information. The second table sandbox.utr_fixed_mapping is where account mapping is stored. For example, ana ccount number 60820 is mapped as Employee relation. The first table needs the mapping from the second table linked on the account number. The output I am getting is not right and way to bug. Any help would be appreciated!
Output
select sandbox.utr_fixed_mapping_na.new_mapping_1,sum(wbr_global.gl_ap_details.amount)
from wbr_global.gl_ap_details
LEFT JOIN sandbox.utr_fixed_mapping_na ON wbr_global.gl_ap_details.account_number = sandbox.utr_fixed_mapping_na.account_number
Where gl_ap_details.cost_center = '1172'
and gl_ap_details.period_name = 'JUL-21'
and gl_ap_details.ledger_name = 'Amazon.com, Inc.'
Group by 1;
I tried adding the cast function but after 5000 seconds of the query running I canceled it.
The query itself appears ok, but minor changes. Learn to use table "aliases". This way you don't have to keep typing long database.table.column all over. Additionally, SQL is easier to read doing it that way anyhow.
Notice the aliases "gl" and "fm" after the tables are declared, then these aliases are used to represent the columns.. Easier to read, would you agree.
Added GL Account number as described below the query.
select
gl.account_number,
fm.new_mapping_1,
sum(gl.amount)
from
wbr_global.gl_ap_details gl
LEFT JOIN sandbox.utr_fixed_mapping_na fm
ON gl.account_number = fm.account_number
Where
gl.cost_center = '1172'
and gl.period_name = 'JUL-21'
and gl.ledger_name = 'Amazon.com, Inc.'
Group by
gl.account_number,
fm.new_mapping_1
Now, as for your query and getting null. This just means that there are records within the gl_ap_details table with an account number that is not found in the utr_fixed_mapping_na table. So, to see WHAT gl account number does NOT exist, I have added it to the query. Its possible there are MULTIPLE records in the gl_ap_details that are not found in the mapping table. So, you may get
GLAccount Description SumOfAmount
glaccount1 null $someAmount
glaccount37 null $someAmount
glaccount49 null $someAmount
glaccount72 Depreciation $someAmount
glaccount87 Real Estate $someAmount
glaccount92 Building $someAmount
glaccount99 Salaries $someAmount
I obviously made-up glaccounts just to show the purpose. You may have multiple where the null's total amount is actually masking how many different gl account numbers were NOT found.
Once you find which are missing, you can check / confirm they SHOULD be in the mapping table.
FEEDBACK.
Since you do realize the missing numbers, lets consider a Cartesian result. If there are multiple entries in the mapping table for the same G/L account number, you will get a Cartesian result thus bloating your numbers. To clarify, lets say your mapping table has
Mapping file.
GL Descr1 NewMapping
1 test Salaries
1 testView Buildings
1 Another Depreciation
And your GL_AP_Details has
GL Amount
1 $100
Your total for the query would result in $300 because the query is trying to join the AP Details GL #1 to EACH of the entries in the mapping file thus bloating the amount. You could also add a COUNT(*) as NumberOfEntries to the query to see how many transactions it THINKS it is processing. Is there some "unique ID" in the GL_AP_Details table? If so, then you could also do a count of DISTINCT ID values. If they are different (distinct is lower than # of entries), I think THAT is your culprit.
select
fm.new_mapping_1,
sum(gl.amount),
count(*) as NumberOfEntries,
count( distinct gl.UniqueIdField ) as DistinctTransactions
from
wbr_global.gl_ap_details gl
LEFT JOIN sandbox.utr_fixed_mapping_na fm
ON gl.account_number = fm.account_number
Where
gl.cost_center = '1172'
and gl.period_name = 'JUL-21'
and gl.ledger_name = 'Amazon.com, Inc.'
Group by
fm.new_mapping_1
Might you also need to limit the mapping table for a specific prophecy or mec view?
If you "think" that the result of an aggregate is wrong, then the easiest way to verify this is to select the individual rows that correlate to 1 record in the aggregate output and inspect the records, looking for duplications.
For instance, pick 'Building Management':
SELECT fixed.new_mapping_1,details.amount,*
FROM wbr_global.gl_ap_details details
LEFT JOIN sandbox.utr_fixed_mapping_na fixed ON details.account_number = fixed.account_number
WHERE details.cost_center = '1172'
AND details.period_name = 'JUL-21'
AND details.ledger_name = 'Amazon.com, Inc.'
AND details.account_number = 'Building Management'
Notice that we tack on a ,* to the end of the projection, this will show you everything that the query has access to, you should look for repeating sections of data that you were not expecting, then depending on which table they originate from your might add additional criteria to the JOIN, or to the WHERE or you might need to group by additional columns.
This type of issue is really hard to comment on in a forum like this because it is highly specific to your schema, and the data contained within it, making solutions highly subjective to criteria you are not likely to publish online.
Generally if you think a calculation is wrong, you need to manually compute it to verify, this above advice helps you to inspect the data your query is using, you should either construct your own query or use other tools to build the data set that helps you to manually compute the correct values, then work them back into or replace your original query.
The speed issues are out of scope here, we can comment on the poor schema design but I suspect you don't have a choice. In the utr_fixed_mapping_na table you should make the account_number have the same column type as the source data, or add a new column that has the data in the original type, then you can setup indexes on the columns to improve the speed of the join.
Schema
Question: List all paying customers with users who had 4 or 5 activities during the week of February 15, 2021; also include how many of the activities sent were paid, organic and/or app store. (i.e. include a column for each of the three source types).
My attempt so far:
SELECT source_type, COUNT(*)
FROM activities
WHERE activity_time BETWEEN '02-15-21' AND '02-19-21'
GROUP BY source_type
I would like to get a second opinion on it. I didn't include the accounts table because I don't believe that I need it for this query, but I could be wrong.
Have you tried to run this? It doesn't satisfy the brief on FOUR counts:
List all the ... customers (that match criteria)
There is no customer information included in the results at all, so this is an outright fail.
paying customers
This is the top level criteria, only customers that are not free should be included in the results.
Criteria: users who had 4 or 5 activities
There has been no attempt to evaluate this user criteria in the query, and the results do not provide enough information to deduce it.
there is further ambiguity in this requirement, does it mean that it should only include results if the account has individual users that have 4 or 5 acitvities, or is it simply that the account should have 4 or 5 activities overall.
If this is a test question (clearly this is contrived, if it is not please ask for help on how to design a better schema) then the use of the term User is usually very specific and would suggest that you need to group by or otherwise make specific use of this facet in your query.
Bonus: (i.e. include a column for each of the three source types).
This is the only element that was attempted, as the data is grouped by source_type but the information cannot be correlated back to any specific user or customer.
Next time please include example data and the expected outcome with your post. In preparing the data for this post you would have come across these issues yourself and may have been inspired to ask a different question, or through the process of writing the post up you may have resolved the issue yourself.
without further clarification, we can still start to evolve this query, a good place to start is to exclude the criteria and focus on the format of the output. the requirement mentions the following output requirements:
List Customers
Include a column for each of the source types.
Firstly, even though you don't think you need to, the request clearly states that Customer is an important facet in the output, and in your schema account holds the customer information, so although we do not need to, it makes the data readable by humans if we do include information from the account table.
This is a standard PIVOT style response then, we want a row for each customer, presenting a count that aggregates each of the values for source_type. Most RDBMS will support some variant of a PIVOT operator or function, however we can achieve the same thing with simple CASE expressions to conditionally put a value into projected columns in the result set that match the values we want to aggregate, then we can use GROUP BY to evaluate the aggregation, in this case a COUNT
The following syntax is for MS SQL, however you can achieve something similar easily enough in other RBDMS
OP please tag this question with your preferred database engine...
NOTE: there is NO filtering in this query... yet
SELECT accounts.company_id
, accounts.company_name
, paid = COUNT(st_paid)
, organic = COUNT(st_organic)
, app_store = COUNT(st_app_store)
FROM activities
INNER JOIN accounts ON activities.company_id = accounts.company_id
-- PIVOT the source_type
CROSS APPLY (SELECT st_paid = CASE source_type WHEN 'paid' THEN 1 END
,st_organic = CASE source_type WHEN 'organic' THEN 1 END
,st_app_store = CASE source_type WHEN 'app store' THEN 1 END
) as PVT
GROUP BY accounts.company_id, accounts.company_name
This results in the following shape of result:
company_id
company_name
paid
organic
app_store
apl01
apples
4
8
0
ora01
oranges
6
12
0
Criteria
When you are happy with the shpe of the results and that all the relevant information is available, it is time to apply the criteria to filter this data.
From the requirement, the following criteria can be identified:
paying customers
The spec doesn't mention paying specifically, but it does include a note that (free customers have current_mrr = 0)
Now aren't we glad we did join on the account table :)
users who had 4 or 5 activities
This is very specific about explicitly 4 or 5 activities, no more, no less.
For the sake of simplicity, lets assume that the user facet of this requirement is not important and that is is simply a reference to all users on an account, not just users who have individually logged 4 or 5 activities on their own - this would require more demo data than I care to manufacture right now to prove.
during the week of February 15, 2021.
This one was correctly identified in the original post, but we need to call it out just the same.
OP has used Monday to Friday of that week, there is no mention that weeks start on a Monday or that they end on Friday but we'll go along, it's only the syntax we need to explore today.
In the real world the actual values specified in the criteria should be parameterised, mainly because you don't want to manually re-construct the entire query every time, but also to sanitise input and prevent SQL injection attacks.
Even though it seems overkill for this post, using parameters even in simple queries helps to identify the variable elements, so I will use parameters for the 2nd criteria to demonstrate the concept.
DECLARE #from DateTime = '2021-02-15' -- Date in ISO format
DECLARE #to DateTime = (SELECT DateAdd(d, 5, #from)) -- will match Friday: 2021-02-19
/* NOTE: requirement only mentioned the start date, not the end
so your code should also only rely on the single fixed start date */
SELECT accounts.company_id, accounts.company_name
, paid = COUNT(st_paid), organic = COUNT(st_organic), app_store = COUNT(st_app_store)
FROM activities
INNER JOIN accounts ON activities.company_id = accounts.company_id
-- PIVOT the source_type
CROSS APPLY (SELECT st_paid = CASE source_type WHEN 'paid' THEN 1 END
,st_organic = CASE source_type WHEN 'organic' THEN 1 END
,st_app_store = CASE source_type WHEN 'app store' THEN 1 END
) as PVT
WHERE -- paid accounts = exclude 'free' accounts
accounts.current_mrr > 0
-- Date range filter
AND activity_time BETWEEN #from AND #to
GROUP BY accounts.company_id, accounts.company_name
-- The fun bit, we use HAVING to apply a filter AFTER the grouping is evaluated
-- Wording was explicitly 4 OR 5, not BETWEEN so we use IN for that
HAVING COUNT(source_type) IN (4,5)
I believe you are missing some information there.
without more information on the tables, I can only guess that you also have a customer table. i am going to assume there is a customer_id key that serves as key between both tables
i would take your query and do something like:
SELECT customer_id,
COUNT() AS Total,
MAX(CASE WHEN source_type = "app" THEN "numoperations" END) "app_totals"),
MAX(CASE WHEN source_type = "paid" THEN "numoperations" END) "paid_totals"),
MAX(CASE WHEN source_type = "organic" THEN "numoperations" END) "organic_totals"),
FROM (
SELECT source_type, COUNT() AS num_operations
FROM activities
WHERE activity_time BETWEEN '02-15-21' AND '02-19-21'
GROUP BY source_type
) tb1 GROUP BY customer_id
This is the most generic case i can think of, but does not scale very well. If you get new source types, you need to modify the query, and the structure of the output table also changes. Depending on the sql engine you are using (i.e. mysql vs microsoft sql) you could also use a pivot function.
The previous query is a little bit rough, but it will give you a general idea. You can add "ELSE" statements to the clause, to zero the fields when they have no values, and join with the customer table if you want only active customers, etc.
I've got an aggregated query that checks if I have more than one record matching certain conditions.
SELECT RegardingObjectId, COUNT(*) FROM [CRM_MSCRM].[dbo].[AsyncOperationBase] a
where WorkflowActivationId IN ('55D9A3CF-4BB7-E311-B56B-0050569512FE',
'1BF5B3B9-0CAE-E211-AEB5-0050569512FE',
'EB231B79-84A4-E211-97E9-0050569512FE',
'F0DDF5AE-83A3-E211-97E9-0050569512FE',
'9C34F416-F99A-464E-8309-D3B56686FE58')
and StatusCode = 10
group by RegardingObjectId
having COUNT(*) > 1
That's nice, but then there is one field in AsyncOperationBase that will be unique. Say count(*) = 3, well, AsyncOperationBaseId in AsyncOperationBase will have 3 different values since AsyncOperationBase is the table's primary key.
To be honest, I would not even know what terms and expressions to Google to find a solution.
If anyone has a solution and also, is there any words to describe what I'm looking for ? Perhaps BI people are often faced with such a requirement or something...
I could do it with an SSRS report where the report would visually do the grouping then I could expand each grouped row to get the AsyncOperationBaseId value, but simply through SQL, I can't seem to find a way out...
Thanks.
select * from [CRM_MSCRM].[dbo].[AsyncOperationBase]
where RegardingObjectId in
(
SELECT RegardingObjectId
FROM [CRM_MSCRM].[dbo].[AsyncOperationBase] a
where WorkflowActivationId IN
(
'55D9A3CF-4BB7-E311-B56B-0050569512FE',
'1BF5B3B9-0CAE-E211-AEB5-0050569512FE',
'EB231B79-84A4-E211-97E9-0050569512FE',
'F0DDF5AE-83A3-E211-97E9-0050569512FE',
'9C34F416-F99A-464E-8309-D3B56686FE58'
)
and StatusCode = 10
group by RegardingObjectId
having COUNT(*) > 1
)
Edited
I am running into an error and I know what is happening but I can't see what is causing it. Below is the sql code I am using. Basically I am getting the general results I want, however I am not accurately giving the query the correct 'where' clause.
If this is of any assistance. The count is coming out as this:
Total Tier
1 High
2 Low
There are 4 records in the Enrollment table. 3 are active, and 1 is not. Only 2 of the records should be displayed. 1 for High, and 1 for low. The second Low record that is in the total was flagged as 'inactive' on 12/30/2010 and reflagged again on 1/12/2011 so it should not be in the results. I changed the initial '<=' to '=' and the results stayed the same.
I need to exclude any record from Enrollments_Status_Change that where the "active_status" was changed to 0 before the date.
SELECT COUNT(dbo.Enrollments.Customer_ID) AS Total,
dbo.Phone_Tier.Tier
FROM dbo.Phone_Tier as p
JOIN dbo.Enrollments as eON p.Phone_Model = e.Phone_Model
WHERE (e.Customer_ID NOT IN
(Select Customer_ID
From dbo.Enrollment_Status_Change as Status
Where (Change_Date >'12/31/2010')))
GROUP BY dbo.Phone_Tier.Tier
Thanks for any assistance and I apologize for any confusion. This is my first time here and i'm trying to correct my etiquette on the fly.
If you don't want any of the fields from that table dbo.Enrollment_Status_Change, and you don't seem to use it in any way — why even include it in the JOINs? Just leave it out.
Plus: start using table aliases. This is very hard to read if you use the full table name in each JOIN condition and WHERE clause.
Your code should be:
SELECT
COUNT(e.Customer_ID) AS Total, p.Tier
FROM
dbo.Phone_Tier p
INNER JOIN
dbo.Enrollments e ON p.Phone_Model = e.Phone_Model
WHERE
e.Active_Status = 1
AND EXISTS (SELECT DISTINCT Customer_ID
FROM dbo.Enrollment_Status_Change AS Status
WHERE (Change_Date <= '12/31/2010'))
GROUP BY
p.Tier
Also: most likely, your EXISTS check is wrong — since you didn't post your table structures, I can only guess — but my guess would be:
AND EXISTS (SELECT * FROM dbo.Enrollment_Status_Change
WHERE Change_Date <= '12/31/2010' AND CustomerID = e.CustomerID)
Check for existence of any entries in dbo.Enrollment_Status_Change for the customer defined by e.CustomerID, with a Change_Date before that cut-off date. Right?
Assuming you want to:
exclude all customers whose latest enrollment_status_change record was since the start of 2011
but
include all customers whose latest enrollment_status_change record was earlier than the end of 2010 (why else would you have put that EXISTS clause in?)
Then this should do it:
SELECT COUNT(e.Customer_ID) AS Total,
p.Tier
FROM dbo.Phone_Tier p
JOIN dbo.Enrollments e ON p.Phone_Model = e.Phone_Model
WHERE dbo.Enrollments.Active_Status = 1
AND e.Customer_ID NOT IN (
SELECT Customer_ID
FROM dbo.Enrollment_Status_Change status
WHERE (Change_Date >= '2011-01-01')
)
GROUP BY p.Tier
Basically, the problem with your code is that joining a one-to-many table will always increase the row count. If you wanted to exclude all the records that had a matching row in the other table this would be fine -- you could just use a LEFT JOIN and then set a WHERE clause like Customer_ID IS NULL.
But because you want to exclude a subset of the enrollment_status_change table, you must use a subquery.
Your intention is not clear from the example given, but if you wanted to exclude anyone who's enrollment_status_change as before 2011, but include those who's status change was since 2011, you'd just swap the date comparator for <.
Is this any help?