I have table with columns:
id month year
1 10 2011
2 1 2012
3 4 2011
4 3 2012
I Want select ids where (month=10 and year=2011) and (month=1 and year=2012), it's possible?
This is a basic SQL SELECT:
SELECT id FROM myTable WHERE (month = 10 AND year = 2011) OR (month = 1 AND year = 2012);
To search for rows between any two dates, the simplest solution may be to combine the month and year into a single number and then use numeric comparison:
SELECT id
FROM myTable
WHERE year*100 + month BETWEEN 201110 AND 201201
A misfeature of this solution is that it can't take advantage of indexes, so it will be slow on very large tables.
Related
I have this table in GBQ :
ClientID Type Month
XXX A 4
YYY C 4
FFX B 5
FFF B 6
XXX C 6
XXX A 6
YRE C 7
AAR A 7
FFF A 8
EGT B 8
FFF B 9
ETT C 9
I am counting the number of Type per ClientID and Month, with this basic query :
SELECT ClientID,
COUNT(DISTINCT Type) NbTypes,
Month
FROM Table
GROUP BY ClientID, Month
The result looks like this :
ClientID NbTypes Month
XXX 1 4
XXX 2 6
FFF 1 6
FFF 1 8
FFF 1 9
... ... ...
What I need to do is, count the number of Type per ClientID and for each Month : per the last 3 months.
For example :
For the ClientID = XXX, and Month = 8 : I want to have the count of Type where Month = 6 AND Month = 7 AND Month = 8
Is there a way to do this with GROUP BY ?
Thank you
You could use HAVING in your statement:
SELECT ClientID,
COUNT(DISTINCT Type) NbTypes,
Month
FROM Table
GROUP BY ClientID, Month
HAVING Month = EXTRACT(MONTH FROM CURRENT_DATE())
OR Month = EXTRACT(MONTH FROM DATE_SUB(DATE_TRUNC(CURRENT_DATE(), MONTH), INTERVAL 1 MONTH))
OR Month = EXTRACT(MONTH FROM DATE_SUB(DATE_TRUNC(CURRENT_DATE(), MONTH), INTERVAL 2 MONTH))
Note that in your table seems to be no column to determinate the year, so this statement will group all values with month value of the current month to current month minus two months. So for example every data from December, November and October 2021, 2020, 2019 etc. will be selected with this query.
Also note that I could not test this statement, since I don't use BigQuery.
Here is the source for the Date-Functions:
https://cloud.google.com/bigquery/docs/reference/standard-sql/date_functions
You can use a SELECT in a SELECT if that is allowed in Google Big Query
SELECT ClientID,
COUNT(DISTINCT Type) NbTypes,
Month,
MAX((select count(distinct Type)
from Table t2
where t1.ClientID=t2.ClientID
and t1.month-t2.month between 0 and 2
)
) as NbType_3_months
FROM Table t1
GROUP BY ClientID, Month
You can group rows by ClientID and Month, count the number of types and sort rows by ClientID in ascending order and by Month in descending order, and then select from each group the rows of the past three months. It is roundabout and complicated to handle such a scenario in SQL because SQL implements set-orientation only halfway up. For your case, you have to get the largest month for each ClientID, find the eligible records through a join filter, and perform grouping and count. The usual way is to fetch the original data out of the database and process it in Python or SPL. SPL, the open-source Java package, is easier to be integrated into a Java program and generate much simpler code. It gets the task done with only two lines of code:
A
1
=GBQ.query("SELECT CLIENTID, COUNT(DISTINCT TYPE) AS NBTYPES, MONTH FROM t2 GROUP BY CLIENTID, MONTH ORDER BY CLIENTID, MONTH DESC")
2
=A1.group#o(#1).run(m=~.#3-3,~=~.select(MONTH>m)).conj()
After joining two tables in google bigquery, I ended up with a table which have two sets of year and month in four separate columns. First two year and month columns should form one date and the second pair for another date. I need to convert each of those two sets of year and month in to two single dates, and then get the difference between those two dates in terms of months or days.
Example of the table is provided below:
year month year month
0 2013 12 2014 2
1 2014 5 2014 9
2 2015 6 2015 8
If anyone can help code this in bigquery, would be really helpful.
Thanks in advance.
#standardSQL
WITH `project.dataset.table` AS (
SELECT 2013 year1, 12 month1, 2014 year2, 2 month2 UNION ALL
SELECT 2014, 5, 2014, 9 UNION ALL
SELECT 2015, 6, 2015, 8
)
SELECT
DATE(year1, month1, 1) date1,
DATE(year2, month2, 1) date2,
DATE_DIFF(DATE(year2, month2, 1), DATE(year1, month1, 1), DAY) diff_in_days
FROM `project.dataset.table`
with result
Row date1 date2 diff_in_days
1 2013-12-01 2014-02-01 62
2 2014-05-01 2014-09-01 123
3 2015-06-01 2015-08-01 61
To get the difference in months, you don't need to convert to dates. Just use arithmetic:
select (year1 * 12 + month1) - (year2 * 12 + month2)
So you can use the DATE(YEAR,MONTH,DAY) function two times passing the data that you've got on both columns and passing 1 as the day since it doesn't matter, then use DATE_DIFF(date_expression, date_expression, date_part) passing the dates that you got from those functions and the DATE PART that you want to get as a return, it accepts :
DAY,WEEK, ISOWEEK,MONTH,QUARTER,YEAR and ISOYEAR.
I want to write a query to always select the same number of rows, even if the data is not there. If the data is not there, I would still like to select something in its place.
For example, if I want to select the amount in my bank account for the last 5 years, but I only have data for the last 3 years, could I still select 5 rows and just have 0's for the two missing years?
| Year | Balance |
| 2014 | $5 |
| 2013 | $10 |
| 2012 | $31 |
| 2011 | $0 | << Doesn't exist
| 2010 | $0 | << Doesn't exist
Is this possible? Thanks for any help.
Using mssql, this will work. There are other similar functions for other DBs.
SELECT TOP 5 year, ISNULL(balance,0) FROM yourtable
The key to solving this is using an outer join. It is tempting to think of your actual table of data as the "main" table, but what you really want is a table of all possible years. I didn't have a table of years, so I made one up on the fly:
select 2010 as Year
union select 2011 as Year
union select 2012 as Year
union select 2013 as Year
union select 2014 as Year
This gives me a list of all the years I care about.
Then I use an outer join to join it to my table with real data. The outer join will just return NULL values for the stuff that isn't there. But I don't want NULLs, I want zeroes, so I use the isnull function to make them zeros if they are null. And then I end up with this:
select YearList.Year, isnull(Bals.Balance, 0) as theBalance
from
(select 2010 as Year
union select 2011 as Year
union select 2012 as Year
union select 2013 as Year
union select 2014 as Year) as YearList
left join (select Year, Balance from Balances) as Bals
on YearList.Year = Bals.Year
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.
This question already has answers here:
Closed 11 years ago.
Possible Duplicate:
Running total by grouped records in table
I am trying to put together an SQL statement that returns the SUM of a value by month, but on a year to date basis. In other words, for the month of March, I am looking to get the sum of a value for the months of January, February, and March.
I can easily do a group by to get a total for each month by itself, and potentially calculate the year to date value I need in my application from this data by looping through the results set. However, I was hoping to have some of this work handled with my SQL statement.
Has anyone ever tackled this type of problem with an SQL statement, and if so, what is the trick that I am missing?
My current sql statement for monthly data is similar to the following:
Select month, year, sum(value) from mytable group by month, year
If I include a where clause on the month, and only group by the year, I can get the result for a single month that I am looking for:
select year, sum(value) from mytable where month <= selectedMonth group by year
However, this requires me to have a particular month pre-selected or to utilize 12 different SQL statements to generate one clean result set.
Any guidance that can be provided would be greatly appreciated!
Update: The data is stored on an IBM iSeries.
declare #Q as table
(
mmonth INT,
value int
)
insert into #Q
values
(1,10),
(1,12),
(2,45),
(3,23)
select sum(January) as UpToJanuary,
sum(February)as UpToFebruary,
sum(March) as UpToMarch from (
select
case when mmonth<=1 then sum(value) end as [January] ,
case when mmonth<=2 then sum(value) end as [February],
case when mmonth<=3 then sum(value) end as [March]
from #Q
group by mmonth
) t
Produces:
UpToJanuary UpToFebruary UpToMarch
22 67 90
You get the idea, right?
NOTE: This could be done easier with PIVOT tables but I don't know if you are using SQL Server or not.
As far as I know DB2 does support windowing functions although I don't know if this is also supported on the iSeries version.
If windowing functions are supported (I believe IBM calls them OLAP functions) then the following should return what you want (provided I understood your question correctly)
select month,
year,
value,
sum(value) over (partition by year order by month asc) as sum_to_date
from mytable
order by year, month
create table mon
(
[y] int not null,
[m] int not null,
[value] int not null,
primary key (y,m))
select a.y, a.m, a.value, sum(b.value)
from mon a, mon b
where a.y = b.y and a.m >= b.m
group by a.y, a.m, a.value
2011 1 120 120
2011 2 130 250
2011 3 500 750
2011 4 10 760
2011 5 140 900
2011 6 100 1000
2011 7 110 1110
2011 8 90 1200
2011 9 70 1270
2011 10 150 1420
2011 11 170 1590
2011 12 600 2190
You should try to join the table to itself by month-behind-a-month condition and generate a synthetic month-group code to group by as follows:
select
sum(value),
year,
up_to_month
from (
select a.value,
a.year,
b.month as up_to_month
from table as a join table as b on a.year = b.year and b.month => a.month
)
group by up_to_month, year
gives that:
db2 => select * from my.rep
VALUE YEAR MONTH
----------- ----------- -----------
100 2011 1
200 2011 2
300 2011 3
400 2011 4
db2 -t -f rep.sql
1 YEAR UP_TO_MONTH
----------- ----------- -----------
100 2011 1
300 2011 2
600 2011 3
1000 2011 4