I got the following table:
**stats**
id INT FK
day INT
value INT
I would like to create an SQL query that will sum the values in value column in the last day, last week and last month, in one statement.
So Far i got this:
select sum(value) from stats as A where A.day > now() - 1
union
select sum(value) from stats as B where B.day > now() - 7
union
select sum(value) from stats as C where C.day > now() - 30
This returns just the first sum(value), i was expecting 3 values to return.
Running: select sum(value) from stats as A where A.day > now() - X ( Where x = 1/7/30) in different queries works as it should.
What's wrong with the query? Thanks!
UNION is implicit distinct. Use UNION ALL instead like so:
SELECT 'last day' ItemType, sum(value) FROM stats as A WHERE A.day > now() - 1
UNION ALL
SELECT 'last week', SUM(value) FROM stats as B WHERE B.day > now() - 7
UNION ALL
SELECT 'last month', SUM(value) FROM stats as C WHERE C.day > now() - 30
Note that: I added a new column ItemType to indicate what is the type of the sum value whether it is last day, last week or last month
Related
I have this table for example:
Date
amount
2021-02-16T21:06:38
10
2021-02-16T21:07:01
5
2021-02-17T01:10:12
-1
2021-02-19T12:00:00
3
2021-02-24T12:00:00
20
2021-02-25T12:00:00
-1
I want the total amount of all previous weeks, per week. So the result in this case would be:
Date
amount
2021-02-15
0
2021-02-22
17
2021-03-01
36
Note: The dates are now the start of each week (Monday).
Any help would this would be greatly appreciated.
Try This:
select week_date, sum(amount) over (order by week_date )
from (
SELECT date(date_) + cast(abs(extract(dow FROM date_) -7 ) + 1 as int) "week_date",
sum(amount) "amount"
from example group by 1) t
DEMO
Above Query will cover only the week in which transaction records are there. If you want to cover all missing week then try below query:
with cte as (
SELECT date(date_) + cast(abs(extract(dow FROM date_) -7 ) + 1 as int) "week_date",
sum(amount) "amount"
from example group by 1
)
select
t1."Date",coalesce(sum(cte.amount) over (order by t1."Date"),0)
from cte right join
(select generate_series(min(week_date)- interval '1 week', max(week_date),interval '1 week') "Date" from cte) t1 on cte.week_date=t1."Date"
DEMO
Use generate_series() to generate the dates you want. Then use left join to bring in the data and aggregate with a cumulative sum:
select gs.week,
coalesce(sum(e.amount), 0) as week_amount,
sum(coalesce(sum(e.amount), 0)) over (order by gs.week) as running_amount
from generate_series('2021-02-15'::date, '2021-03-01'::date, interval '1 week') gs(week) left join
example e
on e.date < gs.week and
e.date >= gs.week - interval '1 week'
group by gs.week
order by gs.week;
Here is a db<>fiddle.
I am doing a query where the query will append the data from previous date as the outcome in BigQuery.
So, the result data for today will be higher than yesterdays as the data is appending by days.
So far, what I only managed to get the outcome is the data by days (where you can see the number of ID declining and is not appending from previous day) as this result:
What should I do to add appending function in the query so each day will get the result of data from the previous day in bigquery?
code:
WITH
table1 AS (
SELECT
ID,
...
FROM t
WHERE DATE_SUB('2020-01-31', INTERVAL 31 DAY) and '2020-01-31'
),
table2 AS (
SELECT
ID,
COUNTIF((rating < 7) as bad,
COUNTIF((rating >= 7 AND SAFE_CAST(NPS_Rating as INT64) < 9) as intermediate,
COUNTIF((rating as good
FROM
t
WHERE DATE_SUB('2020-01-31', INTERVAL 31 DAY) and '2020-01-31'
)
SELECT
DATE_SUB('2020-01-31', INTERVAL 31 DAY) as date,
*
FROM table1
FULL OUTER JOIN table2 USING (ID)
If you have counts that you want to accumulate, then you want a cumulative sum. The query would look something like this:
select datecol, count(*), sum(count(*)) over (order by datecol)
from t
group by datecol
order by datecol;
I am trying to get data to populate a multi-line graph. The table jobs has the columns id, created_at, and partner_id. I would like to display the sum of jobs for each partner_id each day. My current query has 2 problems. 1) It is missing a lot of jobs. 2) It only contains an entry for a given day if there was a row on that day. My current query is where start is an integer denoting how many days back we are looking for data:
SELECT d.date, count(j.id), j.partner_id FROM (
select to_char(date_trunc('day', (current_date - offs)), 'YYYY-MM-DD')
AS date
FROM generate_series(0, #{start}, 1)
AS offs
) d
JOIN (
SELECT jobs.id, jobs.created_at, jobs.partner_id FROM jobs
WHERE jobs.created_at > now() - INTERVAL '#{start} days'
) j
ON (d.date=to_char(date_trunc('day', j.created_at), 'YYYY-MM-DD'))
GROUP BY d.date, j.partner_id
ORDER BY j.partner_id, d.date;
This returns records like the following:
[{"date"=>"2019-06-21", "count"=>3, "partner_id"=>"099"},
{"date"=>"2019-06-22", "count"=>1, "partner_id"=>"099"},
{"date"=>"2019-06-21", "count"=>3, "partner_id"=>"075"},
{"date"=>"2019-06-23", "count"=>1, "partner_id"=>"099"}]
what I want is something like this:
[{"date"=>"2019-06-21", "count"=>3, "partner_id"=>"099"},
{"date"=>"2019-06-22", "count"=>1, "partner_id"=>"099"},
{"date"=>"2019-06-21", "count"=>3, "partner_id"=>"075"},
{"date"=>"2019-06-22", "count"=>0, "partner_id"=>"075"},
{"date"=>"2019-06-23", "count"=>0, "partner_id"=>"075"},
{"date"=>"2019-06-23", "count"=>1, "partner_id"=>"099"}]
So that for every day in the query I have an entry for every partner even if that count is 0. How can I adjust the query to populate data even when the count is 0?
Use a LEFT JOIN. You also don't need so many subqueries and there is no need to translate to a date to a string and then back to a date:
SELECT d.date, count(j.id), j.partner_id
FROM (SELECT to_char(dte, 'YYYY-MM-DD') AS date , dte
FROM generate_series(current_date - {start} * interval '1 day', current_date, interval '1 day') gs(dte)
) d LEFT JOIN
jobs j
ON DATE_TRUNC('day', j.created_at) = d.dte
GROUP BY d.date, j.partner_id
ORDER BY j.partner_id, d.date;
I need to figure out how to answer this:
Find the number of property views per branch within 1 month, 2 months, and 3 months of client registration in one query.
I'm struggling with how to put this in one query, would CASE be the best way?
Thanks for any input.
You could probably just use UNION
select '1 month' as type, count(*) from tablename where month < 1
union
select '2 month' as type, count(*) from tablename where month < 2
union
select '3 month' as type, count(*) from tablename where month < 3
This would yield your counts as 3 different rows.
I have 2 different tables, A and B. A is something like created and b is removed
I want to obtain the nett difference of the counts per week in an SQL query.
Currently I have
SELECT DATE_TRUNC('week', TIMESTAMP AT time ZONE '+08') AS Week,
Count(id) AS "A - New"
FROM table_name.A
GROUP BY 1
ORDER BY 1
This gets me the count per week for table A only. How could I incorporate the logic of subtracting the same Count(id) from B, for the same timeframe?
Thanks! :)
The potential issue here is that for any week you might only have additions or removals, so to align a count from the 2 tables - by week - an approach would be to use a full outer join, like this:
SELECT COALESECE(A.week, b.week) as week
, count_a
, count_b
, COALESECE(count_a,0) - COALESECE(count_b,0) net
FROM (
SELECT DATE_TRUNC('week', TIMESTAMP AT time ZONE '+08') AS week
, Count(*) AS count_A
FROM table_a
GROUP BY DATE_TRUNC('week', TIMESTAMP AT time ZONE '+08')
) a
FUUL OUTER JOIN (
SELECT DATE_TRUNC('week', TIMESTAMP AT time ZONE '+08') AS week
, Count(*) AS count_b
FROM table_b
GROUP BY DATE_TRUNC('week', TIMESTAMP AT time ZONE '+08')
) b on a.week = b.week
The usual syntex for substracting values from 2 queries is as follows
Select (Query1) - (Query2) from dual;
Assuming both the tables have same number of id in 'id' column and your given query works for tableA, following query will subtract the count(id) from both tables.
select(SELECT DATE_TRUNC('week', TIMESTAMP AT time ZONE '+08') AS Week,
Count(id) AS "A - New" FROM table_name.A GROUP BY 1 ORDER BY 1) - (SELECT DATE_TRUNC('week', TIMESTAMP AT time ZONE '+08') AS Week,
Count(id) AS "B - New" FROM table_name.B GROUP BY 1 ORDER BY 1) from dual
Or you can also try the following approach
Select c1-c2 from(Query1 count()as c1),(Query2 count() as c2);
So your query will be like
Select c1-c2 from (SELECT DATE_TRUNC('week', TIMESTAMP AT time ZONE '+08') AS Week, Count(id) AS c1 FROM table_name.A GROUP BY 1 ORDER BY 1),(SELECT DATE_TRUNC('week', TIMESTAMP AT time ZONE '+08') AS Week, Count(id) AS c2 FROM table_name.B GROUP BY 1 ORDER BY 1);