I am trying to write subselect which will run through returned data, then checks status of all and then decides uniquity logic.
Is there any way to find out following ?
case any of data has 'Active' status first one will be marked as 1 everything else as 0
case there is no 'Active' status then first 'Expired' status will by marked as 1 and everything else as 0
case there is no 'Active' and 'Expired' status then first 'In Progress' will be marked as 1 and everything else as 0
I was trying to write it like this but i need to have it in one case statement
SELECT a.id, a.status,
,(SELECT
CASE WHEN b.STATUS = 'Active' THEN 1 ELSE 0 END
CASE WHEN b.STATUS = 'Expired' THEN 1 ELSE 0 END
FROM b.TABLE
WHERE a.id=b.id )AS unique
FROM my.TABLE
Result should look like https://i.stack.imgur.com/qCA74.png picture for expired case
Thank you in advance for any tips.
Use a window function:
select t.*,
(case when row_number() over (partition by id
order by case status when 'Active' then 1 when 'Expired' then 2 else 3 end
) = 1
then 1 else 0
end) as unique_flag
from my.table t;
If the lookup table is the same as source table, then you can use LAG function with constant and use its default value to mark the first row with 1 and others with 0. But you need to order your rows by some fields to deal with duplicates on status.
select a.id, a.status,
lag(0, 1, 1) over(
partition by a.id
order by
case a.status
when 'Active' then 0
when 'Expired' then 1
else 3
end asc,
a.some_more_columns asc /*To find that first row when there are duplicates by status*/
) as unique_flag
from MY_TABLE a
And what about object naming: never use keywords as identifiers. Calling column with date as date, table with users as users and some unknown table as table makes you design error prone.
Related
I have a table named Bank that contains a Bank_Values column. I need a calculated Bank_Value_Unique column to shows whether each Bank_Value exists somewhere else in the table (i.e. whether its count is greater than 1).
I prepared this query, but it does not work. Could anyone help me with this and/or modify this query?
SELECT
CASE
WHEN NULLIF(LTRIM(RTRIM(Bank_Value)), '') =
(SELECT Bank_Value
FROM [Bank]
GROUP BY Bank_Value
HAVING COUNT(*) = 1)
THEN '0' ELSE '1'
END AS Bank_Key_Unique
FROM [Bank]
A windowed count should work:
SELECT
*,
CASE
COUNT(*) OVER (PARTITION BY Bank_Value)
WHEN 1 THEN 1 ELSE 0
END AS Bank_Value_Unique
FROM
Bank
;
It works also, but I found solution also:
select CASE WHEN NULLIF(LTRIM(RTRIM(Bank_Value)),'') =
(select Bank_Value
from Bank
group by Bank_Value
having (count(distinct Bank_Value) > 2 )) THEN '1' ELSE '0' END AS
Bank_Value_Uniquness
from Bank
It was missing "distinct" in having part.
I'm working on SMS-Gateway that holds multiple charged SMS-services with different numbers,
each SMS sent to the customer has 4 status as below (forwarded, delivered, expired,delivery failed)
Now I have the below first_table for the charging-system with the below details (TABLE-A)
and below (TABLE-B) which contain the status of each sent SMS with its ID
Below is my expected final result to forecast the details for each sms-service :
At first I thought it was easy all I need is just to use COUNT(Case when ...)
but in my case I have thousands of SMS-numbers(services) so if I use this approach it will be like that:-
COUNT(CASE WHEN a.SMS_SHORT_CODE='1111' AND B.STATUS='forwarded' )
COUNT(CASE WHEN a.SMS_SHORT_CODE='1111' AND B.STATUS='delivered' )
COUNT(CASE WHEN a.SMS_SHORT_CODE='1111' AND B.STATUS='expired' )
COUNT(CASE WHEN a.SMS_SHORT_CODE='1111' AND B.STATUS='delivery failed' )
COUNT(CASE WHEN a.SMS_SHORT_CODE='5000' AND B.STATUS='forwarded' )
COUNT(CASE WHEN a.SMS_SHORT_CODE='5000' AND B.STATUS='delivered' )
COUNT(CASE WHEN a.SMS_SHORT_CODE='5000' AND B.STATUS='expired' )
COUNT(CASE WHEN a.SMS_SHORT_CODE='5000' AND B.STATUS='delivery failed' )
...
...
...
...
...
...
...
The above approach not practical when you have many services also noting that CASE can handle only 250 conditions?
So what is the best approach to do left outer join for (Table A) on (Table B) using the SMS-ID and count each SMS-status and forecast it as below?
I would suggest conditional aggregation:
select b.SMS_SHORT_CODE,
sum(case when status = 'forwaded' then 1 else 0 end) as count_of_forwaded,
sum(case when status = 'delivered' then 1 else 0 end) as count_of_status,
sum(case when status = 'expired' then 1 else 0 end) as count_of_expired,
sum(case when status = 'delivery failed' then 1 else 0 end) as count_of_delivery_failed
from TABLEB b
group by b.SMS_SHORT_CODE ;
Note that no JOIN is necessary. All the data you want to aggregate is in TABLEB.
Please use below query,
select
A.SMS_SHORT_CODE,
case when status = 'forwaded' then count(status ) end as count_of_forwaded,
case when status = 'delivered' then count(status ) end as count_of_status,
case when status = 'expired' then count(status ) end as count_of_expired,
case when status = 'delivery failed' then count(status ) end as count_of_delivery_failed
from TABLEA A
inner join TABLEB B
on (A.SMS_ID = B.SMS_ID)
group by A.SMS_SHORT_CODE, status ;
You can use PIVOT clause (introduced in Oracle 11g version) for those status columns :
SELECT sms_short_code,
COUNT_OF_forwarded,
COUNT_OF_delivered,
COUNT_OF_expired,
COUNT_OF_delivery_failed
FROM tableB
PIVOT
(
COUNT(*) FOR status IN ( 'forwarded' AS COUNT_OF_forwarded,
'delivered' AS COUNT_OF_delivered,
'expired' AS COUNT_OF_expired,
'delivery failed' AS COUNT_OF_delivery_failed )
)
e.g. only using TableB is enough.
Demo
If i have a table like
In my table i want to compare every two consequetive row. Suppose if the employee_status is 'yes' and after it is 'pro'. Then I want to add another column and write 'problem' in both rows and 'no problem' in other rows.
Like,
1 yes problem
2 pro problem
3 pro no problem
You can use lead()/lag() -- or the Teradata equivalent -- and a case expression:
select t.*
(case when employee_status = 'yes' and
max(employee_status) over (order by employee_no rows between 1 following and 1 following) = 'pro'
then 'problem'
when employee_status = 'pro' and
max(employee_status) over (order by employee_no rows between 1 preceding and 1 preceding) = 'yes'
then 'problem'
else 'no problem'
end) as problem_col
from t;
I have a 2 column table with the columns : "user_name" and "characteristic". Each user_name may appear multiple times with a different characteristic.
The values in characteristic are:
Online
Instore
Account
Email
I want to write a sql statement that goes like this - but obviously this isn't working:
SELECT user_name,
case
when characteristic in ("online","instore") then 1
else 0
END as purchase_yn,
case
when characteristic in ("online","instore") and
characteristic in ("email",'account') then 1
else 0
END as purchaser_with_account
FROM my_table
GROUP BY user_name;
Essentially the first is a flag where I check for the presence of either value for that user_name.
The Second field is that they meet this criteria AND that they meet the criteria for having either 'email' or 'account'
An example the structure of your data would help better understand what you are trying to accomplish. But I think I get what you are trying to do.
You have to use an aggregate function in order to use a group by.
Something like SUM or AVG.
But you need first to build a pivot of your data and then you could use that pivot to check for your criterias:
This would create a table pivot that shows for each record what criterias are met:
SELECT
user_name,
case when characteristic = "online" then 1 else 0 end as online_yn,
case when characteristic = "instore" then 1 else 0 end as instore_yn,
case when characteristic = "account" then 1 else 0 end as account_yn,
case when characteristic = "email" then 1 else 0 end as email_yn,
FROM my_table
Now what you might wanted to do is to create an averaged version of these entries grouped by user_name and use those averages to create the fields you wanted. For that you need to use the same statement created earlier as an inline table :
Select
user_name,
case when avg(online_yn + instore_yn) >= 1 then 1 else 0 end as purchase_yn,
case when avg(online_yn + instore_yn) >= 1 and avg(email_yn + account_yn) >= 1 then 1 else 0 end as purchaser_with_account
From
(SELECT
user_name,
case when characteristic = "online" then 1 else 0 end as online_yn,
case when characteristic = "instore" then 1 else 0 end as instore_yn,
case when characteristic = "account" then 1 else 0 end as account_yn,
case when characteristic = "email" then 1 else 0 end as email_yn,
FROM my_table) avg_table
group by
user_name;
This should help.
It may not be efficient in terms of performance but you'll get what you want.
You just have to enclose the CASE expressions in COUNT aggregates:
SELECT user_name,
COUNT(case when characteristic in ("online","instore") then 1 END) as purchase_yn,
COUNT(case when characteristic in ("email",'account') then 1 END) as user_with_account
FROM my_table
GROUP BY user_name
If purchase_yn > 0 then you first flag is set. If purchase_yn > 0 and user_with_account > 0 then you second flag is set as well.
Note: You have to remove ELSE 0 from the CASE expressions because COUNT takes into account all not null values.
You haven't mentioned a specific RDBMS, but if SUM(DISTINCT ...) is available the following is quite nice:
SELECT
username,
SUM(DISTINCT
CASE
WHEN characteristic in ('online','instore') THEN 1
ELSE 0
END) AS purchase_yn,
CASE WHEN (
SUM(DISTINCT
CASE
WHEN characteristic in ('online','instore') THEN 1
WHEN characteristic in ('email','account') THEN 2
ELSE 0 END
)
) = 3 THEN 1 ELSE 0 END as purchaser_with_account
FROM
my_table
GROUP BY
username
If I correctly understand, if user have 'online' or 'instore', then for this user you want 1 as purchase_yn column, and if user also have 'email' or 'account', then 1 as purchaser_with_account column.
If this is correct, then one way is:
with your_table(user_name, characteristic) as(
select 1, 'online' union all
select 1, 'instore' union all
select 1, 'account' union all
select 1, 'email' union all
select 2, 'account' union all
select 2, 'email' union all
select 3, 'online'
)
-- below is actual query:
select your_table.user_name, coalesce(max(t1.purchase_yn), 0) as purchase_yn, coalesce(max(t2.purchaser_with_account), 0) as purchaser_with_account
from your_table
left join (SELECT user_name, 1 as purchase_yn from your_table where characteristic in('online','instore') ) t1
on your_table.user_name = t1.user_name
left join (SELECT user_name, 1 as purchaser_with_account from your_table where characteristic in('email', 'account') ) t2
on t1.user_name = t2.user_name
group by your_table.user_name
I've a table in my database for which I need to check if all rows have one field not null.
If there are no row or if there is at least 1 row with the field null => true
If there are rows and they are all with the field not null => False
Is there a way to do this in on simple query? Or I need to check if my table is empty first then if it's not check if I've a row with the field value empty ?
This will count how many NULL values you have in a field;
SELECT
SUM(CASE WHEN FieldName IS NULL THEN 1 ELSE 0 END) NullValues
FROM TableName
Will return 0 if there are no NULL values, and will return the number of NULLS if there are any present.
If you actually want to return a value as 'True' or 'False' then do this;
SELECT CASE
WHEN a.NullValues > 0
THEN 'True'
ELSE 'False'
END CheckField
FROM (
SELECT
SUM(CASE WHEN FieldName IS NULL
THEN 1
ELSE 0
END) NullValues
FROM TableName
) a
Use count(*) and count(field) and compare the two:
select
case when count(*) > 0 and count(*) = count(field) then 1 -- not empty and no nulls
else 0 end as isgood
from mytable;
Oracle SQL has no boolean data type , so I use 1 for true and 0 for false. You can replace this with whatever you like (e.g. 'true' instead of 1 and 'false' instead of 0).
As to turning this into a predicate (correlated to a main query), you'd use something along the lines of:
select ...
from main
where exists
(
select 1
from mytable
where mytable.colx = main.coly
having count(*) > 0 and count(*) = count(field)
);
You can do this with aggregation. However, it is difficult to understand what you are asking for. If you want to check that a field has no NULL values, you can do:
select (case when count(*) > 0 then 1 else 0 end) as HasNullValues
from t
where field is null;
Alternate way I found using max with putting null first:
select case when
max(field) keep (dense_rank first order by datfin desc nulls first) is null then 1
else 0 end as flag
from MYTABLE;