I want a query that can give result with sum of last 7 day look back.
I want output date and sum of last 7 day look back impressions for each date
e.g. I have a table tblFactImps with below data:
dateFact impressions id
2015-07-01 4022 30
2015-07-02 4021 33
2015-07-03 4011 34
2015-07-04 4029 35
2015-07-05 1023 39
2015-07-06 3023 92
2015-07-07 8027 66
2015-07-08 2024 89
I need output with 2 columns:
dateFact impressions_last_7
query I got:
select dateFact, sum(if(datediff(curdate(), dateFact)<=7, impressions,0)) impressions_last_7 from tblFactImps group by dateFact;
Thanks!
If your fact table is not too big, then a correlated subquery is a simple way to do what you want:
select i.dateFact,
(select sum(i2.impressions)
from tblFactImps i2
where i2.dateFact >= i.dateFact - interval 6 day
) as impressions_last_7
from tblFactImps i;
You can achieve this by LEFT OUTER JOINing the table with itself on a date range, and summing the impressions grouped by date, as follows:
SELECT
t1.dateFact,
SUM(t2.impressions) AS impressions_last_7
FROM
tblFactImps t1
LEFT OUTER JOIN
tblFactImps t2
ON
t2.dateFact BETWEEN
DATE_SUB(t1.dateFact, INTERVAL 6 DAY)
AND t1.dateFact
GROUP BY
t1.dateFact;
This should give you a sliding 7-day sum for each date in your table.
Assuming your dateFact column is indexed, this query should also be relatively fast.
Related
update: this can be done with python. here
i have a table like this:
event_id vendor_id start_date end_date
1 100 2021-01-01 2021-01-31
2 101 2021-01-15 2021-02-15
3 102 2021-02-01 2021-02-31
4 103 2021-02-01 2021-03-31
5 104 2021-03-01 2021-03-31
6 105 2021-03-01 2021-04-31
7 100 2021-04-01 2021-04-31
i would like an output like this: number of events based on month. but if the event between two or more months, it must be included in the count for each month. For example, The event in the second row (event_id=2) takes place in both January and February. Therefore, this event should be included in the total both in January and February.
output:
month total_event
2021-01 2 ---->> event_id=(1,2)
2021-02 3 ---->> event_id=(2,3,4)
2021-03 3 ---->> event_id=(4,5,6)
2021-04 2 ---->> event_id=(6,7)
Note: I wrote it to make the " --->> event_id= : " part better understood. i dont needed. i just need the month and the total_event.
i tried this query:
select date_format(start_date,'%Y-%m') as month,count(event_id) as total_event
group by date_format(start_date,'%Y-%m')
month total_event
2021-01 2
2021-02 2
2021-03 2
2021-04 1
but it counts only by start_date, so the numbers are missing.
Idea
To get the valid months list from the table
To calculate the event counts by event table's joining with the months
MySQL 8.0+
We can get the valid months list by Recursive.
Here is a full SQL. Assumed that your event table is c!
WITH RECURSIVE all_dates(dt) AS (
-- anchor
SELECT MIN(c.`start_date`) AS dt FROM c
UNION ALL
-- recursion with stop condition
SELECT dt + INTERVAL 1 MONTH
FROM all_dates WHERE dt + INTERVAL 1 MONTH <= (SELECT MAX(c.end_date) FROM c)
)
SELECT LEFT(dt, 7) AS `month`, COUNT(d.dt) AS total_event, GROUP_CONCAT(DISTINCT c.`event_id`) AS event_ids FROM all_dates d
INNER JOIN c ON LEFT(d.dt, 7) >= LEFT(c.start_date, 7) AND LEFT(d.dt, 7) <= LEFT(c.end_date, 7)
GROUP BY LEFT(dt, 7);
I have a dataset like this:
team date score
A 2011-05-01 50
A 2011-05-02 54
A 2011-05-03 51
A 2011-05-04 49
A 2011-05-05 59
B 2011-05-03 30
B 2011-05-04 35
B 2011-05-05 39
B 2011-05-06 47
B 2011-05-07 50
I want to add another column called MA3 where I can calculate the moving average of scores for the last 3 days. The point that made it tricky is to calculate the MA for each team. The end result should be like this:
team date score MA3
A 2011-05-01 50 null
A 2011-05-02 54 null
A 2011-05-03 51 null
A 2011-05-04 49 51.66
A 2011-05-05 59 51.33
B 2011-05-03 30 null
B 2011-05-04 35 null
B 2011-05-05 39 null
B 2011-05-06 47 34.66
B 2011-05-07 50 40.33
If that would be a single team, I would go on and do:
SELECT team,
year,
AVG(score) OVER (ORDER BY date ASC ROWS 3 PRECEDING) AS MA3
FROM table
You're missing the PARTITION BY clause:
SELECT team,
date,
AVG(score) OVER (
PARTITION BY team
ORDER BY date ASC ROWS 3 PRECEDING
) AS MA3
FROM table
Note that there will always be an average calculation, regardless of the window size. If you want the average to be null if your window size is smaller than 3, you could do it like this:
SELECT team,
date,
CASE
WHEN count(*) OVER w <= 3 THEN null
ELSE AVG(score) OVER w
END AS MA3
FROM table
WINDOW w AS (PARTITION BY team ORDER BY date ASC ROWS 3 PRECEDING)
dbfiddle
Side note
Your next question might be about logical windowing, because often, you don't actually want to calculate the average over 3 rows, but over some interval,
like e.g. 3 days. Luckily, MySQL implements this. You could then write:
WINDOW w AS (PARTITION BY team ORDER BY date ASC RANGE INTERVAL 3 DAY PRECEDING)
I´m trying to do some analysis in the following data
WeekDay Date Count
5 06/09/2018 20
6 07/09/2018 Null
7 08/09/2018 19
1 09/09/2018 16
2 10/09/2018 17
3 11/09/2018 24
4 12/09/2018 25
5 13/09/2018 24
6 14/09/2018 23
7 15/09/2018 23
1 16/09/2018 9
2 17/09/2018 23
3 18/09/2018 33
4 19/09/2018 22
5 20/09/2018 31
6 21/09/2018 17
7 22/09/2018 10
1 23/09/2018 12
2 24/09/2018 26
3 25/09/2018 29
4 26/09/2018 27
5 27/09/2018 24
6 28/09/2018 29
7 29/09/2018 27
1 30/09/2018 19
2 01/10/2018 26
3 02/10/2018 39
4 03/10/2018 32
5 04/10/2018 37
6 05/10/2018 Null
7 06/10/2018 26
1 07/10/2018 11
2 08/10/2018 32
3 09/10/2018 41
4 10/10/2018 37
5 11/10/2018 25
6 12/10/2018 20
The problem that I want to solve is: I want to create a table with the average of the 3 last same weekdays related to the day. But, when there is a NULL in the weekday, I want to ignore and do the average only with the remain numbers, not count NULL as an 0. I will give you an example here:
The date in this table is day/month/year :)
Ex: On day 12/10/2018, I need the average from
the days 05/10/2018; 28/09/2018; 21/09/2018. These are the last 3 same weekday(six) as 12/10/2018.
. Their values are Null; 29; 17. Then the result of this average must be 23, because I need to ignore the NULL, and not be 15,333.
How can I do this?
The count() function ignores nulls (i.e. does NOT increment if it encounters null) so I suggest you simply count the values then may contain the nulls you wish to ignore.
dow datecol value
6 21/09/2018 17
6 28/09/2018 29
6 05/10/2018 Null
e.g. sum(value) above = 46, and the count(value) = 2 so the average is 23.0 (and avg(value) will also return 23.0 as it also ignores nulls)
select
weekday
, `date`
, `count`
, (select (sum(`count`) * 1.0) / (count(`count`) * 1.0)
from atable as t2
where t2.weekday = t1.weekday
and t2.`date` < t1.`date
order by t2.`date` DESC
limit 3
) as average
from atable as t1
You could just use avg(count) in the query above, and get the same result.
ps. I do hope you do NOT use count as a column name! I also would suggest you do NOT use date as a column name either. i.e. Avoid using SQL terms as names.
SELECT WeekDay, AVG(Count)
FROM myTable
WHERE Count IS NOT NULL
GROUP BY WeekDay
Use IsNULL(Count,0) in your Select
SELECT WeekDay, AVG(IsNULL(Count,0))
FROM myTable
GROUP BY WeekDay
First off, you need to get the number of instances of that weekday in the data since you just need the last 3 same week days
create table table2
as
select
row_number() over(partition by weekday order by date desc) as rn
,weekday
,date
,count
from table
From here, you can get what you want. With you explanation, you don't need to filter out the NULL values for count. Just doing the avg() aggregation will simply ignore it.
select
weekday
,avg(count)
from table2
where rn in (1,2,3)
group by weekday
I'm stuck on this query. I need to do a group by date, card_id and only show the highest hits. I have this data:
date card_name card_id hits
29/02/2016 Paul Stanley 1345 12
29/02/2016 Phil Anselmo 1347 16
25/02/2016 Dave Mustaine 1349 10
25/02/2016 Ozzy 1351 17
23/02/2016 Jhonny Cash 1353 13
23/02/2016 Elvis 1355 15
20/02/2016 James Hethfield 1357 9
20/02/2016 Max Cavalera 1359 12
My query at the moment
SELECT DATE(card.create_date) `day`, `name`,card_model_id, count(1) hits
FROM card
Join card_model ON card.card_model_id = card_model.id
WHERE DATE(card.create_date) >= DATE(DATE_SUB(NOW(), INTERVAL 1 MONTH)) AND card_model.preview = 0
GROUP BY `day`, card_model_id
;
I want to group by date, card_id and filter the higher hits result showing only one row per date. As if I run a max(hits) with group by but I won't work
Like:
date card_name card_id hits
29/02/2016 Phil Anselmo 1347 16
25/02/2016 Ozzy 1351 17
23/02/2016 Elvis 1355 15
20/02/2016 Max Cavalera 1359 12
Any light on that will be appreciated. Thanks for reading.
Here is one way to do this. Based on your sample data (not the query):
select s.*
from sample s
where s.hits = (select max(s2.hits)
from sample s2
where date(s2.date) = date(s.date)
);
Your attempted query seems to have no relationship to the sample data, so it is unclear how to incorporate those tables (the attempted query has different columns and two tables).
I am having an issue with a SELECT command in MySQL. I have a database of securities exchanged daily with maturity from 1 to 1000 days (>1 mio rows). I would like to get the outstanding amount per day (and possibly per category). To give an example, suppose this is my initial dataset:
DATE VALUE MATURITY
1 10 3
1 15 2
2 10 1
3 5 1
I would like to get the following output
DATE OUTSTANDING_AMOUNT
1 25
2 35
3 15
Outstanding amount is calculated as the total of securities exchanged still 'alive'. That means, in day 2 there is a new exchange for 10 and two old exchanges (10 and 15) still outstanding as their maturity is longer than one day, for a total outstanding amount of 35 on day 2. In day 3 instead there is a new exchange for 5 and an old exchange from day 1 of 10. That is, 15 of outstanding amount.
Here's a more visual explanation:
Monday Tuesday Wednesday
10 10 10 (Day 1, Value 10, matures in 3 days)
15 15 (Day 1, 15, 2 days)
10 (Day 2, 10, 1 day)
5 (Day 3, 5, 3 days with remainder not shown)
-------------------------------------
25 35 15 (Outstanding amount on each day)
Is there a simple way to get this result?
First of all in the main subquery we find SUM of all Values for current date. Then add to them values from previous dates according their MATURITY (the second subquery).
SQLFiddle demo
select T1.Date,T1.SumValue+
IFNULL((select SUM(VALUE)
from T
where
T1.Date between
T.Date+1 and T.Date+Maturity-1 )
,0)
FROM
(
select Date,
sum(Value) as SumValue
from T
group by Date
) T1
order by DATE
I'm not sure if this is what you are looking for, perhaps if you give more detail
select
DATE
,sum(VALUE) as OUTSTANDING_AMOUNT
from
NameOfYourTable
group by
DATE
Order by
DATE
I hope this helps
Each date considers each row for inclusion in the summation of value
SELECT d.DATE, SUM(m.VALUE) AS OUTSTANDING_AMOUNT
FROM yourTable AS d JOIN yourtable AS m ON d.DATE >= m.MATURITY
GROUP BY d.DATE
ORDER BY d.DATE
A possible solution with a tally (numbers) table
SELECT date, SUM(value) outstanding_amount
FROM
(
SELECT date + maturity - n.n date, value, maturity
FROM table1 t JOIN
(
SELECT 1 n UNION ALL
SELECT 2 UNION ALL
SELECT 3 UNION ALL
SELECT 4 UNION ALL
SELECT 5
) n ON n.n <= maturity
) q
GROUP BY date
Output:
| DATE | OUTSTANDING_AMOUNT |
-----------------------------
| 1 | 25 |
| 2 | 35 |
| 3 | 15 |
Here is SQLFiddle demo