I have a data-set (using SQL Server Management Studio) that is used for Sales Analysis. For this example, when an agent fufills a Sales Call or Account Review, they list (via a drop-down) what topics they discussed in the call/review. Then there is a corresponding column of the products that client purchased after-the fact (in this example, I'm using automobiles). I'm thinking maybe a case statement is the way to do but in esscence I need to figure out if any of the makers the person suggested exists in the products column:
So in this example, in line 1, they had suggested Mazda and a Toyota (seperate by ";") and Mazda appears in the products line so that would then be marked as effective. Line 3, they suggested Honda but the person ended up getting a Jeep, so that not effective. So on and so forth.
I'd like for it to be dynamic (maybe an EXISTS??) that way I don't have to write/maintain something like 'Effective'=CASE WHEN Topic like '%Mazada%' and Products like '%Mazada%', "Yes", "No" WHEN.....
Thoughts?
If you have a Product table, then you might be able to get away with something like this:
select RowId, Topic, Products,
(case when exists (select 1
from Products p
where t.Topic like '%'+p.brand+'%' and
t.Products like '%'+p.brand+'%'
)
then 'Yes' else 'No'
end) as Effective
from t;
This is based on the fact that the "brand" seems to be mentioned in both the topic and products fields. If you don't have such a table, you could do something like:
with products as (
select 'Mercedes' as brand union all
select 'Mazda' union all
select 'Toyota' . . .
)
select RowId, Topic, Products,
(case when exists (select 1
from Products p
where t.Topic like '%'+p.brand+'%' and
t.Products like '%'+p.brand+'%'
)
then 'Yes' else 'No'
end) as Effective
from t;
However, this may not work, because in the real world, text is more complicated. It has misspellings, abbreviations, and synonyms. There is no guarantee that there is even a matching word on both lists, and so on. But, if your text is clean enough, this approach might be helpful.
Related
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 am learning MySQL(Beginner). And I am trying to solve one question in which I got stuck.
From the above database ORDER_TABLE, I am trying to extract out the ORDER_ID when user inputs the various fruits, stationary items and drinks. Name of respective items (Apple, Book, Tea) will be provided us. We need to check whether the database contains the items provided by the user and if exists we need to return ORDER_ID of it, if not a message saying "No such order yet".
How to check and extract it? Do we need to use loop here? If yes, let us suppose, there is quantity of items provided to us. But how to use loop here? I am totally confused. Beginners tutorials does not teach this kind of question and its solution.
Or, can we break this data in several tables and then get the ORDER_ID??
One simple approach uses aggregation. For example, to find all orders which have (Apple, Book, Tea), we can try:
SELECT Order_ID
FROM yourTable
GROUP BY Order_ID
HAVING
COUNT(CASE WHEN Fruits = 'Apple' THEN 1 END) > 0 AND
COUNT(CASE WHEN Stationary = 'Book' THEN 1 END) > 0 AND
COUNT(CASE WHEN Drinks = 'Teat' THEN 1 END) > 0;
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.
I have a column which stores data like this:
Product:
product1,product2,product5
product5,product7
product1
What I would like to do is count the number of occurrences there are of product1, product2, etc. but where the record contains multiple products I want it to double count them.
So for the above example the totals would be:
product1: 2
product2: 1
product5: 2
product7: 1
How can I achieve this?
I was trying something like this:
select count(case when prodcolumn like '%product1%' then 'product1' end) from myTable
This gets me the count for product1 appears but how do I extend this to go through each product?
I also tried something like this:
select new_productvalue, count(new_productvalue) from OpportunityExtensionBase
group by new_ProductValue
But that lists all different combinations of the products which were found and how many times they were found...
These products don't change so hard coding it is ok...
EDIT: here is what worked for me.
WITH Product_CTE (prod) AS
(SELECT
n.q.value('.', 'varchar(50)')
FROM (SELECT cast('<r>'+replace(new_productvalue, ';', '</r><r>')+'</r>' AS xml) FROM table) AS s(XMLCol)
CROSS APPLY s.XMLCol.nodes('r') AS n(q)
WHERE n.q.value('.', 'varchar(50)') <> '')
SELECT prod, count(*) AS [Num of Opps.] FROM Product_CTE GROUP BY prod
You have a lousy, lousy data structure, but sometimes one must make do with that. You should have a separate table storing each pair product/whatever pair -- that is the relational way.
with prodref as (
select 'product1' as prod union all
select 'product2' as prod union all
select 'product5' as prod union all
select 'product7' as prod
)
select p.prod, count(*)
from prodref pr left outer join
product p
on ','+p.col+',' like '%,'+pr.prod+',%'
group by p.prod;
This will be quite slow on a large table. And, the query cannot make use of standard indexes. But, it should work. If you can restructure the data, then you should.
Nevermind all you need if one split function
SQL query to split column data into rows
hope after this you can manage .
Hello: I want to do a "weighted search" on product that are tagged with keywords.
(So: not fulltext search, but n-to-m-relation). So here it is:
Table 'product':
sku - the primary key
name
Table 'keywords':
kid - keyword idea
keyword_de - German language String (e.g. 'Hund','Katze','Maus')
keyword_en - English language String (e.g. 'Dog','Cat','Mouse')
Table 'product_keyword' (the cross-table)
sku \__ combined primary key
kid /
What I want is to get a score for all products that at least "contain" one relevant keyword. If I search for ('Dog','Elephant','Maus') I want that
Dog credits a score of 1.003,
Elephant of 1.002
Maus of 1.001
So least important search term starts at 1.001, everything else 0.001++. That way, a lower score limit of 3.0 would equal "AND" query (all three keywords must be found), a lower score limit of 1.0 would equal an "OR". Anything in between something more or less matching. In particular by sorting according to this score, most relevant search results would be first (regardless of lower limit)...
I guess I will have to do something with
IF( keyword1 == 'dog', 1.001, 0) + IF...
maybe inside a SUM() and probably with a GROUP BY at the end of a JOIN over the cross table, eh? But I am fairly clueless how to tackle this.
What would be feasible, is to get the keyword id's from the keywords beforehand. That's a cheap query. So the keywords table can be left ignored and it's all about the other of the cross and product table...
I have PHP at hand to automatically prepare a fairly lengthy PHP statement, but I would like to avoid further multiple SQL statements. In particular since I will limit the query outcome (most often to "LIMIT 0, 20") for paging mode results, so looping a very large number of in between results through a script would be no good...
DANKESCHÖN, if you can help me on this :-)
I think a lot of this is in the Lucene engine (http://lucene.apache.org/java/docs/index.html), which is available for PHP in the Zend Framework: http://framework.zend.com/manual/en/zend.search.lucene.html.
EDIT:
If you want to do the weighted thing you are talking about, I guess you could use something like this:
select p.sku, sum(case k.keyword_en when 'Dog' then 1001 when 'Cat' then 1002 when 'Mouse' then 1003 else 0 end) as totalscore
from products p
left join product_keyword pk on p.sku = pk.sku
inner join keywords k on k.kid = pk.kid
where k.keyword_en in ('Dog', 'Cat', 'Mouse')
group by p.sku
(Edit 2: forgot the group by clause.)