I have a table called LAB and it has these important field:
DATA, CODE, STRUTT.
DATA contains dates, code string and strutt integer as well
What I need is to query this table and get back something like:
-----------------------
| DAYS | YEAR | YEAR2 |
-----------------------
| | STRUTT |
-----------------------
| | | |
They suggest me to use pivot. But I don't know how to group years.
My first try was:
SELECT * FROM
(
SELECT STRUTT, CODe, DATA
FROM LAB
WHERE DATA >= DATE '2016-05-01' AND DATA <= DATE '2016-05-31'
)
PIVOT
(
count(DISTINCT CODE)
FOR STRUTT IN (21,22,23,24,25,26)
)
This is a start for my use of Pivot. But then i tried to change the for statement and put:
FOR DATA IN ('2016-05-01','2016-05-21')
but this gave me errors. Some ideas for solve the entire problem? Or at least to solve the last one of dates? SOLVED BUT NOT NEEDED AT THE END TO SOLVE THE PROBLEM
It looks like you are using Oracle. I might suggest trying:
FOR DATA IN (DATE '2016-05-01', DATE '2016-05-21')
Otherwise, the string values are interpreted as strings, not dates.
I solve the problem by having a look somewhere... I still don't know which version of Oracle I'm using. By the way this work for me:
select strutt
, to_char(data,'dd-MON') AS dayMonth
, count(DISTINCT (case extract(year from data) when 2015 then code end)) numutenze_2015
, count(DISTINCT (case extract(year from data) when 2016 then code end)) numutenze_2016
from lab
where data >= DATE '2015-01-01' and data <= DATE '2016-06-08'
group by strutt, to_char(data,'dd-MON')
order by strutt, to_char(data,'dd-MON') asc
The only problem I have, I don't know how to order the Dates... it start from April, then August... ecc
Related
I would like to get one row with the maximum date. I cannot use group by as I need to retrieve all data in that row.
I have this:
ID Date Country
1 05/05/2019 US
2 05/06/2019 UK
I want to get this:
ID Date Country
2 05/06/2019 UK
I've tried the below but it didn't work for me
select TOP 1 ID, Date, country
from table
order by Date desc
I don't believe you. Here is a db<>fiddle that shows three different interpretations of the date in your sample data:
as a string
as mm/dd/yyyy
as dd/mm/yyyy
All three of them produce the same result.
I suspect that your actual data is more complicated and you have oversimplified the example for the question. Further, my suspicion is that the date column is stored as a string rather than a date.
As a string, you might have some hidden characters that affect the sorting (such as leading spaces).
If this is the case, fix the data type and your code will work.
This depends on what DB system you are using.
In Microsoft SQL server, you can use row_number() function:
select top 1 *
from facts
order by ROW_NUMBER() over (order by dateKey)
Can you try this?
select Top 1 ID,Date, country from table where date = max(date)
First set the DATE or DATETIME Datatype in your [Date] column
then try this code:
SELECT TOP 1 ID, [Date] , country FROM TableName ORDER BY Date DESC
SELECT ID,Date,Country from TableName Where Date = MAX(Date) AND Rownum <= 1
The gem we have installed (Blazer) on our site limits us to one query.
We are trying to write a query to show how many hours each employee has for the past 10 days. The first column would have employee names and the rest would have hours with the column header being each date. I'm having trouble figuring out how to make the column headers dynamic based on the day. The following is an example of what we have working without dynamic column headers and only using 3 days.
SELECT
pivot_table.*
FROM
crosstab(
E'SELECT
"User",
"Date",
"Hours"
FROM
(SELECT
"q"."qdb_users"."name" AS "User",
to_char("qdb_works"."date", \'YYYY-MM-DD\') AS "Date",
sum("qdb_works"."hours") AS "Hours"
FROM
"q"."qdb_works"
LEFT OUTER JOIN
"q"."qdb_users" ON
"q"."qdb_users"."id" = "q"."qdb_works"."qdb_user_id"
WHERE
"qdb_works"."date" > current_date - 20
GROUP BY
"User",
"Date"
ORDER BY
"Date" DESC,
"User" DESC) "x"
ORDER BY 1, 2')
AS
pivot_table (
"User" VARCHAR,
"2017-10-06" FLOAT,
"2017-10-05" FLOAT,
"2017-10-04" FLOAT
);
This results in
| User | 2017-10-05 | 2017-10-04 | 2017-10-03 |
|------|------------|------------|------------|
| John | 1.5 | 3.25 | 2.25 |
| Jill | 6.25 | 6.25 | 6 |
| Bill | 2.75 | 3 | 4 |
This is correct, but tomorrow, the column headers will be off unless we update the query every day. I know we could pivot this table with date on the left and names on the top, but that will still need updating with each new employee – and we get new ones often.
We have tried using functions and queries in the "AS" section with no luck. For example:
AS
pivot_table (
"User" VARCHAR,
current_date - 0 FLOAT,
current_date - 1 FLOAT,
current_date - 2 FLOAT
);
Is there any way to pull this off with one query?
You could select a row for each user, and then per column sum the hours for one day:
with user_work as
(
select u.name as user
, to_char(w.date, 'YYYY-MM-DD') as dt_str
, w.hours
from qdb_works w
join qdb_users u
on u.id = w.qdb_user_id
where w.date >= current_date - interval '2 days'
)
select User
, sum(case when dt_str = to_char(current_date,
'YYYY-MM-DD') then hours end) as Today
, sum(case when dt_str = to_char(current_date - 'interval 1 day',
'YYYY-MM-DD') then hours end) as Yesterday
, sum(case when dt_str = to_char(current_date - 'interval 2 days',
'YYYY-MM-DD') then hours end) as DayBeforeYesterday
from user_work
group by
user
, dt_str
It's often easier to return a list and pivot it client side. That also allows you to generate column names with a date.
Is there any way to pull this off with one query?
No, because a fixed SQL query cannot have any variability in its output columns. The SQL engine determines the number, types and names of every column of a query before executing it, without reading any data except in the catalog (for the structure of tables and other objects), execution being just the last of 5 stages.
A single-query dynamic pivot, if such a thing existed, couldn't be prepared, since a prepared query always have the same results structure, whereas by definition a dynamic pivot doesn't, as the rows that pivot into columns can change between executions. That would be at odds again with the Prepare-Bind-Execute model.
You may find some limited workarounds and additional explanations in other questions, for example: Execute a dynamic crosstab query, but since you mentioned specifically:
The gem we have installed (Blazer) on our site limits us to one
query
I'm afraid you're out of luck. Whatever the workaround, it always need at best one step with a query to figure out the columns and generate a dynamic query from them, and a second step executing the query generated at the previous step.
I am writing a query and am having trouble filtering data as I would like. In the table, there is a date field and an ItemCode field. I would like to return one record per ItemCode with the earliest date that is after today.
If today is 6/6/2017 and my data looks like:
ItemCode Date
1 6/1/2017
1 6/7/2017
1 6/10/2017
2 6/2/2017
2 6/8/2017
2 6/15/2017
I would want the result to be
ItemCode Date
1 6/7/2017
2 6/8/2017
My query so far is:
SELECT PO_PurchaseOrderDetail.ItemCode, Min(PO_PurchaseOrderDetail.RequiredDate) AS NextPO
FROM PO_PurchaseOrderDetail
GROUP BY PO_PurchaseOrderDetail.ItemCode
HAVING (((Min(PO_PurchaseOrderDetail.RequiredDate))>=Now()));
The problem is that the Min function fires first and grabs the earliest dates per ItemCode, which are before today. Then the >=Now() is evaluated and because the min dates are before today, the query returns nothing.
I've tried putting the >=Now() inside the min function in the HAVING part of the query but it does not change the result.
My structure is wrong and I would appreciate any advice. Thanks!
I would approach like this for standard SQL, Access approach may vary
select PO_PurchaseOrderDetail.ItemCode,
min(PO_PurchaseOrderDetail.RequiredDate) as NextPO
from PO_PurchaseOrderDetail
where PO_PurchaseOrderDetail.RequiredDate >= Now()
group by PO_PurchaseOrderDetail.ItemCode;
Put the date condition in the where clause (not the having clause):
select ItemCode, min(Date) as NextPO
from PO_PurchaseOrderDetail
where Date > '6/6/2017'
group by ItemCode
It's quite a hard one to explain but probably (hopefully) an easy one to solve so I'll just explain what it is I'm trying to achieve.
I have a table where multiple logs can be entered for a day each as a seperate row, I then have a decimal as another column, I'm trying to create a summary for each day which would be something like
01/01/1900 | | 5.5
When there's one entry for the 01/01/1900 with 2.5, one with 3 in the main table so adding the values together for the day?
My only issue is adding the dates together if the dates the same, I was thinking something like
Select distinct date and joining it with a table that gets the sum of the decimal column where date is... and that's where im not too sure?
Any help would be great! thanks
If your table is named logs with data like
log_date | value
1900-01-01 | 2.5
1900-01-01 | 3
then your query is
SELECT sum(value) FROM logs GROUP BY log_date
What you're looking for is probably a GROUP BY clause.
SELECT [ yourdatecol, ] sum(yourdecimalcol) FROM yourtable
[ WHERE yourdatecol = .. ]
GROUP BY [ get_ymd_from_date(yourdatecol) | yourdatecol ] ;
With such syntax you'll get sum of row sets, selected by the same datecol value. You may also want to approximate date ( e.g. taking only Y/M/D part from it ), if date contains H/M/ss and what you want is per-day sums. Optional parts I enclosed in square brackets.
SELECT log_date,sum(value) FROM logs GROUP BY log_date
CREATE VIEW Summary
AS
SELECT
DateValue,
SUM(DecimalValue) DayTotal
FROM
EventTable
GROUP BY
DateValue;
Then
SELECT
*
FROM
Summary
WHERE
DateValue = '1900-01-01'
Try this :
SELECT CONVERT(VARCHAR, DateColumn, 103) AS OutputDate, SUM(ValueColumn) AS TotalValue
FROM YourTable
GROUP BY CONVERT(VARCHAR, DateColumn, 103)
I'm presuming a DateTime is used, lets call it logdate. I'm also presuming the other one is a decimal, lets call it logdecimal.
Using SQL server 2008 you can do (the is a type called date which is without the time-part):
SELECT
CAST(logdate as date) as TheDay,
SUM(logdecimal) as TheSum
FROM logTable
GROUP BY CAST(logdatetime as date)
Using a SQL server without the type date, maybe something like:
SELECT
CONVERT(varchar(10), logdate, 101) as TheDay,
SUM(logdecimal) as TheSum
FROM logTable
GROUP BY CONVERT(varchar(10), logdate , 101)
Regards, Olle
Edit: This one will work if it is a DateTime (including time part) you want to group as a date (not including time part). Looks like this was not the case in this question.
I've seen a lot of questions on SO concerning how to group data by a range in a SQL query.
The exact scenarios vary, but the general underlying problem in each is to group by a range of values rather than each discrete value in the GROUP BY column. In other words, to group by a less precise granularity than you're storing in the database table.
This crops up often in the real world when producing things like histograms, calendar representations, pivot tables and other bespoke reporting outputs.
Some example data (tables unrelated):
| OrderHistory | | Staff |
--------------------------- ------------------------
| Date | Quantity | | Age | Name |
--------------------------- ------------------------
|01-Jul-2012 | 2 | | 19 | Barry |
|02-Jul-2012 | 5 | | 53 | Nigel |
|08-Jul-2012 | 1 | | 29 | Donna |
|10-Jul-2012 | 3 | | 26 | James |
|14-Jul-2012 | 4 | | 44 | Helen |
|17-Jul-2012 | 2 | | 49 | Wendy |
|28-Jul-2012 | 6 | | 62 | Terry |
--------------------------- ------------------------
Now let's say we want to use the Date column of the OrderHistory table to group by weeks, i.e. 7-day ranges. Or perhaps group the Staff into 10-year age ranges:
| Week | QtyCount | | AgeGroup | NameCount |
-------------------------------- -------------------------
|01-Jul to 07-Jul | 7 | | 10-19 | 1 |
|08-Jul to 14-Jul | 8 | | 20-29 | 2 |
|15-Jul to 21-Jul | 2 | | 30-39 | 0 |
|22-Jul to 28-Jul | 6 | | 40-49 | 2 |
-------------------------------- | 50-59 | 1 |
| 60-69 | 1 |
-------------------------
GROUP BY Date and GROUP BY Age on their own won't do it.
The most common answers I see (none of which are consistently voted "correct") are to use one or more of:
a bunch of CASE statements, one per grouping
a bunch of UNION queries, with a different WHERE clause per grouping
as I'm working with SQL Server, PIVOT() and UNPIVOT()
a two-stage query using a sub-select, temp table or View construct
Is there an established generic pattern for dealing with such queries?
You can use some of the dimensional modeling techniques, such as fact tables and dimension tables. Order History can act as a fact table with DateKey foreign key relation to a Date dimension.
Date dimension can have a schema such as below:
Note that Date table is pre-filled with data up-to N number of years.
Using an example above, here is a sample query to get the result:
select CalendarWeek, sum(Quantity)
from OrderHistory a
join DimDate b
on a.DateKey = b.DateKey
group by CalendarWeek
For Staff table, you can store Birthday Key instead of age and let the query calculate the age and ranges.
Here is SQL Fiddle
Date dimension population script was taken from here.
As is often the case this SQL problem requires using more than one pattern in composition.
In this case the two you can use are
NTILE
Numbers Table
You can use NTITLE to create a set number of groups. However since you don't have each member of the groups represented you also need to use a numbers table Since you're using SQL Server you have it easy as you don't have to simulate either.
Here's an example for the Staff problem
WITH g as (
SELECT
NTILE(6) OVER (ORDER BY number) grp,
NUMBER
FROM
master..spt_values
WHERE
TYPE = 'P'
and number >=10 and number <=69
)
SELECT
CAST(min(g.number) as varchar) + ' - ' +
CAST(max(g.number) as varchar) AgeGroup ,
COUNT(s.age) NameCount
FROM
g
LEFT JOIN Staff s
ON g.NUMBER = s.Age
GROUP BY
grp
DEMO
You can apply this to dates as well it just requires some date to day maniplulation
Take a look at the OVER clause and its associated clauses: PARTITION BY, ROW, RANGE...
Determines the partitioning and ordering of a rowset before the
associated window function is applied. That is, the OVER clause
defines a window or user-specified set of rows within a query result
set. A window function then computes a value for each row in the
window. You can use the OVER clause with functions to compute
aggregated values such as moving averages, cumulative aggregates,
running totals, or a top N per group results.
My favorite case in this genre is where transactions must be grouped by fiscal quarter or fiscal year. The fiscal quarter or fiscal year boundaries of various enterprises can border on the bizarre.
My favorite way to implement this is to create a separate table for the attributes of a date. Let's call the table "Almanac". One of the columns in this table is the fiscal quarter, and another one is the fiscal year. The key to this table is of course the date. Ten years worth of data fill up 3,650 rows, plus a few for leap years. You then need a program that can populate this table from scratch. All the enterprise calendar rules are built into this one program.
When you need to group transaction data by fiscal quarter, you just join with this table over date, and then group by fiscal quarter.
I figure this pattern could be extended to groupings by other kinds of ranges, but I've never done it myself.
In your first example your intervals are regular so you can achieve the desired result simply by using functions. Below is an example that gets the data as you require it. The first query keeps the first column in date format (how I would preferably deal with it doing any formatting outside of SQL), the second does the string conversion for you.
DECLARE #OrderHistory TABLE (Date DATE, Quantity INT)
INSERT #OrderHistory VALUES
('20120701', 2), ('20120702', 5), ('20120708', 1), ('20120710', 3),
('20120714', 4), ('20120717', 2), ('20120728', 6)
SET DATEFIRST 7
SELECT DATEADD(DAY, 1 - DATEPART(WEEKDAY, Date), Date) AS WeekStart,
SUM(Quantity) AS Quantity
FROM #OrderHistory
GROUP BY DATEADD(DAY, 1 - DATEPART(WEEKDAY, Date), Date)
SELECT WeekStart,
SUM(Quantity) AS Quantity
FROM #OrderHistory
CROSS APPLY
( SELECT CONVERT(VARCHAR(6), DATEADD(DAY, 1 - DATEPART(WEEKDAY, Date), Date), 6) + ' to ' +
CONVERT(VARCHAR(6), DATEADD(DAY, 7 - DATEPART(WEEKDAY, Date), Date), 6) AS WeekStart
) ws
GROUP BY WeekStart
Something similar can be done for your age grouping using:
SELECT CAST(FLOOR(Age / 10.0) * 10 AS INT)
However this fails for 30-39 because there is no data for this group.
My stance on the matter would be, if you are doing the query as a one off, using a temp table, cte or case statement should work just fine, this should also extend to reusing the same query on small sets of data.
If you are likely to reuse the group however, or you are referring to significant amounts of data then create a permanent table with the ranges defined and indices applied to any columns required. This is the basis of creating dimensions in OLAP.
Couldn't you treat the age (or date) as a foreign key in a new, tiny table that is just ages (or dates) and their corresponding ranges? A join statement could provide a new table with a column that contains AgeGroups. With the new table you could use the standard group-by method.
It does seem reckless to make a new table for grouping, but it would be easy to make programatically and I think it would be easier to maintain (or drop and recreate) than a case statement or a where clause. If the result of this query is a one-off, a throwaway sql statement would probably work best, but I think my method makes the most sense for long-term use.
Well, some years ago with Oracle DB we did it the following way:
We had two tables: Sessions and Ranges. Ranges had foreign key that referenced Session.
When we needed to perform SQL, we created a new record in Sessions and several new records in Ranges that referred to that session.
Our SQL joined Ranges with filter by Session:
select sum(t.Value), r.Name
from DataTable t
join Ranges r on (r.Session = ? and r.Start t.MyDate)
group by r.Name
After we got results we deleted that record from Sessions and records from Ranges where deleted by cascade.
We had daemon job that purged Sessions from junk records that were leaked in case of extraordinary situation (killed processes, etc).
This worked perfectly. Since that time Oracle added new SQL clauses, and maybe they could be used instead. But on other RDBMSes this is still a valid way.
Another approach is to create a number of functions such as GET_YEAR_BY_DATE or GET_QUARTER_BY_DATE or GET_WEEK_BY_DATE (they would return start date of corresponding
period, for example, for any date return start date of year). And then group by them:
select sum(Value), GET_YEAR_BY_DATE(MyDate) from DataTable
group by GET_YEAR_BY_DATE(MyDate)