I have a table, consisting of 3 columns (Person, Year and Count), so for each person, there are several rows with different years and counts and the final row with total count. I want to keep the table ordered by Name, but also order it by the total count.
So the rows should be ordered by sum, but also grouped by the Person and ordered by year. When I am trying to order by sum, of course, both person and years are messed up. Is there a way to sort like this?
You've stored those "total" rows as well? Gosh! Why did you do that?
Anyway: if you
compute rank for rows whose year column is equal to 'total' and
add case expression into the order by clause,
you might get what you want:
SQL> with sorter as
2 (select name, cnt,
3 rank() over (order by cnt) rnk
4 from test
5 where year = 'total'
6 )
7 select t.*
8 from test t join sorter s on s.name = t.name
9 order by s.rnk, case when year = 'total' then '9'
10 else year
11 end;
NAME YEAR CNT
---- ----- ----------
John 2018 3
John 2019 2
John total 5
Bob 2017 2
Bob 2019 4
Bob total 6
6 rows selected.
SQL>
I have a table which contain _id, underSubheadId, wefDate, price.
Whenever a product is created or price is edited an entry is made in this table also.
What I want is if I enter a date, I get the latest price of all distinct UnderSubheadIds before the date (or on that date if no entry found)
_id underHeadId wefDate price
1 1 2016-11-01 5
2 2 2016-11-01 50
3 1 2016-11-25 500
4 3 2016-11-01 20
5 4 2016-11-11 30
6 5 2016-11-01 40
7 3 2016-11-20 25
8 5 2016-11-15 52
If I enter 2016-11-20 as date I should get
1 5
2 50
3 25
4 30
5 52
I have achieved the result using ROW NUMBER function in SQL SERVER, but I want this result in Sqlite which don't have such function.
Also if a date like 2016-10-25(which have no entries) is entered I want the price of the date which is first.
Like for 1 we will get price as 5 as the nearest and the 1st entry is 2016-11-01.
This is the query for SQL SERVER which is working fine. But I want it for Sqlite which don't have ROW_NUMBER function.
select underSubHeadId,price from(
select underSubHeadId,price, ROW_NUMBER() OVER (Partition By underSubHeadId order by wefDate desc) rn from rates
where wefDate<='2016-11-19') newTable
where newTable.rn=1
Thank You
This is a little tricky, but here is one way:
select t.*
from t
where t.wefDate = (select max(t2.wefDate)
from t t2
where t2.underSubHeadId = t.underSubHeadId and
t2.wefdate <= '2016-11-20'
);
select underHeadId, max(price)
from t
where wefDate <= "2016-11-20"
group by underHead;
I have a raw table recording customer ids coming to a store over a particular time period. Using Impala, I would like to calculate the number of distinct customer IDs coming to the store until each day. (e.g., on day 3, 5 distinct customers visited so far)
Here is a simple example of the raw table I have:
Day ID
1 1234
1 5631
1 1234
2 1234
2 4456
2 5631
3 3482
3 3452
3 1234
3 5631
3 1234
Here is what I would like to get:
Day Count(distinct ID) until that day
1 2
2 3
3 5
Is there way to easily do this in a single query?
Not 100% sure if will work on impala
But if you have a table days. Or if you have a way of create a derivated table on the fly on impala.
CREATE TABLE days ("DayC" int);
INSERT INTO days
("DayC")
VALUES (1), (2), (3);
OR
CREATE TABLE days AS
SELECT DISTINCT "Day"
FROM sales
You can use this query
SqlFiddleDemo in Postgresql
SELECT "DayC", COUNT(DISTINCT "ID")
FROM sales
cross JOIN days
WHERE "Day" <= "DayC"
GROUP BY "DayC"
OUTPUT
| DayC | count |
|------|-------|
| 1 | 2 |
| 2 | 3 |
| 3 | 5 |
UPDATE VERSION
SELECT T."DayC", COUNT(DISTINCT "ID")
FROM sales
cross JOIN (SELECT DISTINCT "Day" as "DayC" FROM sales) T
WHERE "Day" <= T."DayC"
GROUP BY T."DayC"
try this one:
select day, count(distinct(id)) from yourtable group by day
I would like to find the percent of repeat visitors to my site. Currently I am selecting users for one month and dividing that month by the following month. to calculate those that have returned. Is this the best way to write that query?
it is yielding results that seem to be accurate, but wondering if there is a more elegant solution.
SELECT (
SELECT COUNT(table.user) as Total
FROM table
WHERE table.event IN ('event1','event2','event3')
AND table.month IN ('october')
) /
(
SELECT COUNT(table.user) as newTotal
FROM table
WHERE table.event IN ('event1','event2','event3')
AND (table.month IN ('october') OR table.month IN ('november'))
) AS percent_return
table structure looks like this, you have the same user purchasing multiple events for the same month or the same time period.
order_number user month event gross
1 jack october event2 30
2 jack november event3 20
3 jack november event3 20
4 jack november event2 30
5 sam november event2 30
6 john october event3 20
7 john october non_event 20
You don't need two subqueries to do what you want. Just use conditional aggregation:
SELECT (SUM(s.month IN (october)) / SUM(s.month IN (october, november))
) as percent_return
FROM sales s
WHERE s.event IN ('event1', 'event2', 'event3') AND
s.gross > 0;
Also, there is no need for single quotes around numeric constants.
I was trying to aggregate a 7 days data for FY13 (starts on 10/1/2012 and ends on 9/30/2013) in SQL Server but so far no luck yet. Could someone please take a look. Below is my example data.
DATE BREAD MILK
10/1/12 1 3
10/2/12 2 4
10/3/12 2 3
10/4/12 0 4
10/5/12 4 0
10/6/12 2 1
10/7/12 1 3
10/8/12 2 4
10/9/12 2 3
10/10/12 0 4
10/11/12 4 0
10/12/12 2 1
10/13/12 2 1
So, my desired output would be like:
DATE BREAD MILK
10/1/12 1 3
10/2/12 2 4
10/3/12 2 3
10/4/12 0 4
10/5/12 4 0
10/6/12 2 1
Total 11 15
10/7/12 1 3
10/8/12 2 4
10/9/12 2 3
10/10/12 0 4
10/11/12 4 0
10/12/12 2 1
10/13/12 2 1
Total 13 16
--------through 9/30/2013
Please note, since FY13 starts on 10/1/2012 and ends on 9/30/2012, the first week of FY13 is 6 days instead of 7 days.
I am using SQL server 2008.
You could add a new computed column for the date values to group them by week and sum the other columns, something like this:
SELECT DATEPART(ww, DATEADD(d,-2,[DATE])) AS WEEK_NO,
SUM(Bread) AS Bread_Total, SUM(Milk) as Milk_Total
FROM YOUR_TABLE
GROUP BY DATEPART(ww, DATEADD(d,-2,[DATE]))
Note: I used DATEADD and subtracted 2 days to set the first day of the week to Monday based on your dates. You can modify this if required.
Use option with GROUP BY ROLLUP operator
SELECT CASE WHEN DATE IS NULL THEN 'Total' ELSE CONVERT(nvarchar(10), DATE, 101) END AS DATE,
SUM(BREAD) AS BREAD, SUM(MILK) AS MILK
FROM dbo.test54
GROUP BY ROLLUP(DATE),(DATENAME(week, DATE))
Demo on SQLFiddle
Result:
DATE BREAD MILK
10/01/2012 1 3
10/02/2012 2 4
10/03/2012 2 3
10/04/2012 0 4
10/05/2012 4 0
10/06/2012 2 1
Total 11 15
10/07/2012 1 3
10/08/2012 4 7
10/10/2012 0 4
10/11/2012 4 0
10/12/2012 2 1
10/13/2012 2 1
Total 13 16
You are looking for a rollup. In this case, you will need at least one more column to group by to do your rollup on, the easiest way to do that is to add a computed column that groups them into weeks by date.
Take a lookg at: Summarizing Data Using ROLLUP
Here is the general idea of how it could be done:
You need a derived column for each row to determine which fiscal week that record belongs to. In general you could subtract that record's date from 10/1, get the number of days that have elapsed, divide by 7, and floor the result.
Then you can GROUP BY that derived column and use the SUM aggregate function.
The biggest wrinkle is that 6 day week you start with. You may have to add some logic to make sure that the weeks start on Sunday or whatever day you use but this should get you started.
The WITH ROLLUP suggestions above can help; you'll need to save the data and transform it as you need.
The biggest thing you'll need to be able to do is identify your weeks properly. If you don't have those loaded into tables already so you can identify them, you can build them on the fly. Here's one way to do that:
CREATE TABLE #fy (fyear int, fstart datetime, fend datetime);
CREATE TABLE #fylist(fyyear int, fydate DATETIME, fyweek int);
INSERT INTO #fy
SELECT 2012, '2011-10-01', '2012-09-30'
UNION ALL
SELECT 2013, '2012-10-01', '2013-09-30';
INSERT INTO #fylist
( fyyear, fydate )
SELECT fyear, DATEADD(DAY, Number, DATEADD(DAY, -1, fy.fstart)) AS fydate
FROM Common.NUMBERS
CROSS APPLY (SELECT * FROM #fy WHERE fyear = 2013) fy
WHERE fy.fend >= DATEADD(DAY, Number, DATEADD(DAY, -1, fy.fstart));
WITH weekcalc AS
(
SELECT DISTINCT DATEPART(YEAR, fydate) yr, DATEPART(week, fydate) dt
FROM #fylist
),
ridcalc AS
(
SELECT
ROW_NUMBER() OVER (ORDER BY yr, dt) AS rid, yr, dt
FROM weekcalc
)
UPDATE #fylist
SET fyweek = rid
FROM #fylist
JOIN ridcalc
ON DATEPART(YEAR, fydate) = yr
AND DATEPART(week, fydate) = dt;
SELECT list.fyyear, list.fyweek, p.[date], COUNT(bread) AS Bread, COUNT(Milk) AS Milk
FROM products p
JOIN #fylist list
ON p.[date] = list.fydate
GROUP BY list.fyyear, list.fyweek, p.[date] WITH ROLLUP;
The Common.Numbers reference above is a simple numbers table that I use for this sort of thing (goes from 1 to 1M). You could also build that on the fly as needed.