I have the below SQL Query
select Count(emailID) as ViewsThatMonth,
Day(entry_date) as day,
Month(entry_date) as month,
Year(entry_date) as year
from email_views
where emailID = 110197
Group By Day(entry_date), Month(entry_date), Year(entry_date)
UNION ALL
select Count(emailID) as ViewsThatMonth,
Day(Record_Entry) as day,
Month(Record_Entry) as month,
Year(Record_Entry) as year
from dbo.tblOnlineEmail_Views
where emailID = 110197
Group By Day(Record_Entry), Month(Record_Entry), Year(Record_Entry)
order by 4, 3, 2
The results are showing as below. I need the results on the same date to be combined. I.e. the total for the 23/8/2010 should be 800.
ViewsThatMonth day month year
---------------------------------
799 23 8 2010
1 23 8 2010
281 24 8 2010
88 25 8 2010
1 25 8 2010
You only need to group by once:
SELECT Count(emailID) as ViewsThatMonth,
Day(entry_date) as day,
Month(entry_date) as month,
Year(entry_date) as year
from(
select emailID, Record_Entry AS entry_date
from email_views
where emailID = 110197
UNION ALL
select emailID, entry_date
from dbo.tblOnlineEmail_Views
where emailID = 110197
) AS t
Group By Day(entry_date), Month(entry_date), Year(entry_date)
order by 4, 3, 2
Basically the easiest way is to make your union a derived table or CTE and then group them by date.
IE.
select
sum(dt.ViewsThatMonth) as ViewsThatMonth
,dt.[day]
,dt.[month]
,dt.[year]
from
(select Count(emailID) as ViewsThatMonth, Day(entry_date) as day, Month(entry_date) as month, Year(entry_date) as year from email_views
where emailID = 110197
Group By Day(entry_date), Month(entry_date), Year(entry_date)
UNION ALL
select Count(Record_Entry) as ViewsThatMonth, Day(Record_Entry) as day, Month(Record_Entry) as month, Year(Record_Entry) as year from dbo.tblOnlineEmail_Views
where emailID = 110197
Group By Day(Record_Entry), Month(Record_Entry), Year(Record_Entry)
) dt
group by [day], [month], [year]
order by dt.[year], dt.[month], dt.[day]
Keeping UNIONed code to a minimum:
select Count(emailID) as ViewsThatMonth,
Day(sort_date) as day,
Month(sort_date) as month,
Year(sort_date) as year
from (select v.*,
case c.caseid when 1 then entry_date else record_entry end sort_date
from email_views v
cross join (select 1 caseid union all select 2 caseid) c
where v.emailID = 110197) sq
Group By Day(sort_date), Month(sort_date), Year(sort_date)
EDIT: Added alias to subquery
Related
I am counting the birthdays , sales , order in all 12 months from customers table in SQL server like these
In Customers table birth_date ,sale_date, order_date are columns of the table
select 1 as ranking,'Birthdays' as Type,[MONTH],TOTAL
from ( select DATENAME(month, birth_date) AS [MONTH],count(*) TOTAL
from customers
group by DATENAME(month, birth_date)
)x
union
select 2 as ranking,'sales' as Type,[MONTH],TOTAL
from ( select DATENAME(month, sale_date) AS [MONTH],count(*) TOTAL
from customers
group by DATENAME(month, sale_date)
)x
union
select 3 as ranking,'Orders' as Type,[MONTH],TOTAL
from ( select DATENAME(month, order_date) AS [MONTH],count(*) TOTAL
from customers
group by DATENAME(month, order_date)
)x
And the output is like these(just dummy data)
ranking
Type
MONTH
TOTAL
1
Birthdays
January
12
1
Birthdays
April
6
1
Birthdays
May
10
2
Sales
Febrary
8
2
Sales
April
14
2
Sales
May
10
3
Orders
June
4
3
Orders
July
3
3
Orders
October
6
3
Orders
December
17
I want to find count of these all these three types without using UNION and UNION ALL, means I want these data by single query statement (or more optimize version of these query)
Another approach is to create a CTE with all available ranking values and use CROSS APPLY for it, as shown below.
WITH ranks(ranking) AS (
SELECT * FROM (VALUES (1), (2), (3)) v(r)
)
SELECT
r.ranking,
CASE WHEN r.ranking = 1 THEN 'Birthdays'
WHEN r.ranking = 2 THEN 'Sales'
WHEN r.ranking = 3 THEN 'Orders'
END AS Type,
DATENAME(month, CASE WHEN r.ranking = 1 THEN c.birth_date
WHEN r.ranking = 2 THEN c.sale_date
WHEN r.ranking = 3 THEN c.order_date
END) AS MONTH,
COUNT(*) AS TOTAL
FROM customers c
CROSS APPLY ranks r
GROUP BY r.ranking,
DATENAME(month, CASE WHEN r.ranking = 1 THEN c.birth_date
WHEN r.ranking = 2 THEN c.sale_date
WHEN r.ranking = 3 THEN c.order_date
END)
ORDER BY r.ranking, MONTH
I have a transactions table for a single year with the amount indicating the debit transaction if the value is negative or credit transaction values are positive.
Now in a given month if the number of debit records is less than 3 or if the sum of debits for a month is less than 100 then I want to charge a fee of 5.
I want to build and sql query for this in postgre:
select sum(amount), count(1), date_part('month', date) as month from transactions where amount < 0 group by month;
I am able get records per month level, I am stuck on how to proceed further and get the result.
You can start by generating the series of month with generate_series(). Then join that with an aggregate query on transactions, and finally implement the business logic in the outer query:
select sum(t.balance)
- 5 * count(*) filter(where coalesce(t.cnt, 0) < 3 or coalesce(t.debit, 0) < 100) as balance
from generate_series(date '2020-01-01', date '2020-12-01', '1 month') as d(dt)
left join (
select date_trunc('month', date) as dt, count(*) cnt, sum(amount) as balance,
sum(-amount) filter(where amount < 0) as debit
from transactions t
group by date_trunc('month', date)
) t on t.dt = d.dt
Demo on DB Fiddle:
| balance |
| ------: |
| 2746 |
How about this approach?
SELECT
SUM(
CASE
WHEN usage.amount_s > 100
OR usage.event_c > 3
THEN 0
ELSE 5
END
) AS YEAR_FEE
FROM (SELECT 1 AS month UNION
SELECT 2 UNION
SELECT 3 UNION
SELECT 4 UNION
SELECT 5 UNION
SELECT 6 UNION
SELECT 7 UNION
SELECT 8 UNION
SELECT 9 UNION
SELECT 10 UNION
SELECT 11 UNION
SELECT 12
) months
LEFT OUTER JOIN
(
SELECT
sum(amount) AS amount_s,
count(1) event_c,
date_part('month', date) AS month
FROM transactions
WHERE amount < 0
GROUP BY month
) usage ON months.month = usage.month;
First you must use a resultset that returns all the months (1-12) and join it with a LEFT join to your table.
Then aggregate to get the the sum of each month's amount and with conditional aggregation subtract 5 from the months that meet your conditions.
Finally use SUM() window function to sum the result of each month:
SELECT DISTINCT SUM(
COALESCE(SUM(t.Amount), 0) -
CASE
WHEN SUM((t.Amount < 0)::int) < 3
OR SUM(CASE WHEN t.Amount < 0 THEN -t.Amount ELSE 0 END) < 100 THEN 5
ELSE 0
END
) OVER () total
FROM generate_series(1, 12, 1) m(month) LEFT JOIN transactions t
ON m.month = date_part('month', t.date) AND date_part('year', t.date) = 2020
GROUP BY m.month
See the demo.
Results:
> | total |
> | ----: |
> | 2746 |
I think you can use the hanving clause.
Select ( sum(a.total) - (12- count(b.cnt ))*5 ) as result From
(Select sum(amount) as total , 'A' as name from transactions ) as a left join
(Select count(amount) as cnt , 'A' as name
From transactions
where amount <0
group by month(date)
having not(count(amount) <3 or sum(amount) >-100) ) as b
on a.name = b.name
select
sum(amount) - 5*(12-(
select count(*)
from(select month, count(amount),sum(amount)
from transactions
where amount<0
group by month
having Count(amount)>=3 And Sum(amount)<=-100))) as balance
from transactions ;
I have a table as follows
user_id date month year visiting_id
123 11-04-2017 APRIL 2017 4500
123 12-05-2017 MAY 2017 4567
123 13-05-2017 MAY 2017 4568
123 17-05-2017 MAY 2017 4569
123 22-05-2017 MAY 2017 4570
123 11-06-2017 JUNE 2017 4571
123 12-06-2017 JUNE 2017 4572
I want to calculate the visiting count for the current month and last month at the monthly level as follows:
user_id month year visit_count_this_month visit_count_last_month
123 APRIL 2017 1 0
123 MAY 2017 4 1
123 JUNE 2017 2 4
I was able to calculate visit_count_this_month using the following query
SELECT v.user_id, v.month, v.year,
SUM(is_visit_this_month) as visit_count_this_month
FROM
(SELECT user_id, date, month, year,
CASE WHEN TO_CHAR(date, 'MM/YYYY') = TO_CHAR(date, 'MM/YYYY')
THEN 1 ELSE 0
END as is_visit_this_month
FROM visits
GROUP BY user_id, date, month, year
HAVING user_id = 123) v
GROUP BY v.user_id, v.month, v.year
However, I'm stuck with calculating visit_count_last_month. Similar to this, I also want to calculate visit_count_last_2months.
Can somebody help?
You can use a LATERAL JOIN like this:
SELECT user_id, month, year, COUNT(*) as visit_count_this_month, visit_count_last_month
FROM visits v
CROSS JOIN LATERAL (
SELECT COUNT(*) as visit_count_last_month
FROM visits
WHERE user_id = v.user_id
AND date = (CAST(v.date AS date) - interval '1 month')
) l
GROUP BY user_id, month, year, visit_count_last_month;
SQLFiddle - http://sqlfiddle.com/#!15/393c8/2
Assuming there are values for every month, you can get the counts per month first and use lag to get the previous month's values per user.
SELECT T.*
,COALESCE(LAG(visits,1) OVER(PARTITION BY USER_ID ORDER BY year,mth),0) as last_month_visits
,COALESCE(LAG(visits,2) OVER(PARTITION BY USER_ID ORDER BY year,mth),0) as last_2_month_visits
FROM (
SELECT user_id, extract(month from date) as mth, year, COUNT(*) as visits
FROM visits
GROUP BY user_id, extract(month from date), year
) T
If there can be missing months, it is best to generate all months within a specified timeframe and left join ing the table on to that. (This example shows it for all the months in 2017).
select user_id,yr,mth,visits
,coalesce(lag(visits,1) over(PARTITION BY USER_ID ORDER BY yr,mth),0) as last_month_visits
,coalesce(lag(visits,2) OVER(PARTITION BY USER_ID ORDER BY yr,mth),0) as last_2_month_visits
from (select u.user_id,extract(year from d.dt) as yr, extract(month from d.dt) as mth,count(v.visiting_id) as visits
from generate_series(date '2017-01-01', date '2017-12-31',interval '1 month') d(dt)
cross join (select distinct user_id from visits) u
left join visits v on extract(month from v.dt)=extract(month from d.dt) and extract(year from v.dt)=extract(year from d.dt) and u.user_id=v.user_id
group by u.user_id,extract(year from d.dt), extract(month from d.dt)
) t
I want to get a "totals" report for business XYZ. They want the season,term,distinct count of employees, and total employee's dropped hours, only when dropped hours of anemployee != any adds that equal the drops.
trying to do something like this:
select year,
season,
(select count(distinct empID)
from tableA
where a.season = season
and a.year = year) "Employees",
(select sum(hours)
from(
select distinct year,season,empID,hours
from tableA
where code like 'Drop%'
)
where a.season = season
and a.year = year) "Dropped"
from tableA a
-- need help below
where (select sum(hours)
from(
select distinct year,season,empID,hours
from tableA
where code like 'Drop%'
)
where a.season = season
and a.year = year
and a.emplID = emplID)
!=
(select sum(hours)
from(
select distinct year,season,empID,hours
from tableA
where code like 'Add%'
)
where a.season = season
and a.year = year
and a.emplID = emplID)
group by year,season
It appears I am not correctly doing my where clause correctly. I dont believe I am joining the emplID to each emplID correctly to exlude those whos "drops" <> "adds"
EDIT:
sample data:
year,season,EmplID,hours,code
2015, FALL, 001,10,Drop
20150 FALL, 001,10,Add
2015,FALL,002,5,Drop
2015,FALL,003,10,Drop
The total hours should be 15. EmplyID 001 should be removed from the totaling because he has drops that are exactly equal to adds.
I managed to work it out with a bit of analytics .. ;)
with tableA as (
select 2015 year, 1 season, 1234 empID, 2 hours , 'Add' code from dual union all
select 2015 year, 1 season, 1234 empID, 3 hours , 'Add' code from dual union all
select 2015 year, 1 season, 1234 empID, 4 hours , 'Add' code from dual union all
select 2015 year, 1 season, 1234 empID, 2 hours , 'Drop' code from dual union all
select 2015 year, 1 season, 2345 empID, 5 hours , 'Add' code from dual union all
select 2015 year, 1 season, 2345 empID, 3.5 hours, 'Add' code from dual union all
select 2015 year, 2 season, 1234 empID, 7 hours , 'Add' code from dual union all
select 2015 year, 2 season, 1234 empID, 5 hours , 'Add' code from dual union all
select 2015 year, 2 season, 2345 empID, 5 hours , 'Add' code from dual union all
select 2015 year, 2 season, 7890 empID, 3 hours , 'Add' code from dual union all
select 2014 year, 1 season, 1234 empID, 1 hours , 'Add' code from dual union all
select 2014 year, 1 season, 1234 empID, 2 hours , 'Add' code from dual union all
select 2014 year, 1 season, 1234 empID, 4 hours , 'Add' code from dual
),
w_group as (
select year, season, empID, hours, code,
lead(hours) over (partition by year, season, empID, hours
order by case when code like 'Drop%' then 'DROP'
when code like 'Add%' then 'ADD'
else NULL end ) new_hours
from tableA
)
select year, season, count(distinct empID),
sum(hours-nvl(new_hours,0)) total_hours
from w_group
where code like 'Add%'
group by year, season
/
YEAR SEASON COUNT(DISTINCTEMPID) TOTAL_HOURS
---------- ---------- -------------------- -----------
2015 1 2 15.5
2014 1 1 7
2015 2 3 20
(the first part "with tableA" is just faking some data, since you didn't provide any) :)
[edit]
corrected based on your data, and your explanation - in short, you're counting the DROPs, (minus the ADDs), I was doing the reverse
[edit2] replaced below query with minor tweak based on comment/feedback: don't count an empID if their DROP-ADD zero out)
with tableA as (
select 2015 year, 'FALL' season, '001' empID, 10 hours, 'Drop' code from dual union all
select 2015 year, 'FALL' season, '001' empID, 10 hours, 'Add' code from dual union all
select 2015 year, 'FALL' season, '002' empID, 5 hours, 'Drop' code from dual union all
select 2015 year, 'FALL' season, '003' empID, 10 hours, 'Drop' code from dual
),
w_group as (
select year, season, empID, hours, code,
lag(hours) over (partition by year, season, empID, hours
order by case when code like 'Drop%' then 'DROP'
when code like 'Add%' then 'ADD'
else NULL end ) new_hours
from tableA
)
select year, season, count(distinct empID),
sum(hours-nvl(new_hours,0)) total_hours
from w_group
where code like 'Drop%'
and hours - nvl(new_hours,0) > 0
group by year, season
/
YEAR SEAS COUNT(DISTINCTEMPID) TOTAL_HOURS
---------- ---- -------------------- -----------
2015 FALL 2 15
[/edit]
I think you can do what you want with just conditional aggregation. Something like this:
select year, season, count(distinct empID) as Employees,
sum(case when code like 'Drop%' then hours end) as Dropped
from tableA
group by year, season;
It is hard to tell exactly what you want, because you do not have sample data and desired results (or better yet, a SQL Fiddle). You might also want a having clause:
having (sum(case when code like 'Drop%' then hours end) <>
sum(case when code like 'Add%' then hours end)
)
Are you wanting the result of something like this?
SELECT
year
,season
,COUNT(DISTINCT empID) AS Employees
,SUM(CASE WHEN code LIKE 'Drop%' THEN hours ELSE 0 END) AS Dropped
FROM
TableA
GROUP BY
year
,season
HAVING
(
SUM(CASE WHEN code LIKE 'Drop%' THEN hours ELSE 0 END)
- SUM(CASE WHEN code LIKE 'Add%' THEN hours ELSE 0 END)
) <> 0
I am using PostgreSQL and my data looks something like this:
UserID TimeStamp
1 2014-02-03
2 2014-02-03
3 2014-02-03
1 2014-03-03
2 2014-03-03
6 2014-03-03
7 2014-03-03
This is just dummy data for 2 days in which some UserID is getting repeated on both the days. I would like to find out the number of repeated UserId every month. For this example the final result set should look like:
Count Year Month
0 2014 2
2 2014 3
In the above table, March 3014 has 2 repeat UserID and Feb 2014 has none.
I can find out the distinct UserID for each month but not the repeated UserID. Any help in this regard would be much appreciated.
select
count(distinct userid) as "Count",
extract(year from t0.timestamp) as "Year",
extract(month from t0.timestamp) as "Month"
from
t t1
inner join
t t0 using (userid)
where t0.timestamp < date_trunc('month', t1.timestamp)
group by 2, 3
or may be faster
select
count(distinct userid) as "Count",
extract(year from t0.timestamp) as "Year",
extract(month from t0.timestamp) as "Month"
from t t1
where exists (
select 1
from t
where
userid = t1.userid
and
timestamp < date_trunc('month', t1.timestamp)
)
group by 2, 3
This might work, have not tested it out yet.
SELECT
COUNT(DISTINCT(UserId))
, EXTRACT(YEAR FROM TIMESTAMP TimeStamp) AS Year
, EXTRACT(MONTH FROM TIMESTAMP Timestamp) AS Month
FROM TABLE
GROUP BY TimeStamp
To rephrase your question:
How many users are not new (i.e. already visited the shop/website/whatever in a previous month) for each month?
SELECT
yr, mon,
COUNT(*) AS all_users,
COUNT(*) - SUM(repeated) AS new_users,
SUM(repeated) AS existing_users
FROM
(
SELECT UserId,
EXTRACT(YEAR FROM TimeStamp) AS yr,
EXTRACT(MONTH FROM TimeStamp) AS mon,
CASE WHEN ROW_NUMBER() -- 1st time users get 0
OVER (PARTITION BY UserId
ORDER BY EXTRACT(YEAR FROM TimeStamp) ,
EXTRACT(MONTH FROM TimeStamp)) = 1
THEN 0
ELSE 1
END AS repeated
FROM vt
GROUP BY UserId,
EXTRACT(YEAR FROM TimeStamp),
EXTRACT(MONTH FROM TimeStamp)
) AS dt
GROUP BY yr,mon
ORDER BY 1,2
The inner GROUP BY is needed if there are multiple rows for a user within the same month.
Is this what you want?
select yyyymm, sum(case when cnt > 1 then 1 else 0 end) as dupcnt
from (select to_char(timestamp, 'YYYY-MM') as yyyymm, userid, count(*) as cnt
from table t
group by to_char(timestamp, 'YYYY-MM'), userid
) t
group by yyyymm
order by yyyymm;