I have a table named Sales and a column within it named Date. I'm simply trying to find how many sales were made on a specific date. My intuition was to use something like this:
SELECT COUNT(Date) FROM Sales WHERE Date='2015-04-04'
this should count all sales that were made on that date, but that returns 0. What am I doing wrong?
While it is difficult to be precise without table definitions or an indication of what RDBMS you are using, it is likely that Date is a time/date stamp, and that the result you want would be obtained either by looking for a range from the beginning of the day to the end of the day in your WHERE clause, or by truncating Date down to a date without the time before comparing it to a date.
Try the below once.
select count(*) from <t.n> where date like '2015-04-04%';
When you want to find the count of rows based on a field (Date) You need to Group By over it like this:
SELECT Date, COUNT(*)
FROM Sales
GROUP BY Date
Now you have all count of rows for each Date.
Type and Value of Date is important in the result of the above query.
For example in SQL Server your best try is to convert a DateTime field to varchar and then check it as the result of CONVERT like this:
SELECT COUNT(*)
FROM Sales
WHERE CONVERT(VARCHAR, Date, 111) = '2015/04/04'
I hope the title of this post makes sense.
The db in question has two columns that are related to my issue, a date column that follows the format xx/xx/xxxx and price a column. What I want to do is get a sum of the prices in the price column based on the month and year in which they occurred, but that data is in the other aforementioned column. Doing so will allow me to determine the total for a given month of a given year. The problem is I have no idea how to construct a query that would do what I need. I have done some reading on the web, but I'm not really sure how to go about this. Can anyone provide some advice/tips?
Thanks for your time!
Mike
I was able to find a solution using a LIKE clause:
SELECT sum(price) FROM purchases WHERE date LIKE '11%1234%'
The "11" could be any 2-digit month and the "1234" is any 4 digit year. The % sign acts as a wildcard. This query, for example, returns the sum of any prices that were from month 11 of year 1234 in the db.
Thanks for your input!
You cannot use the built-in date functions on these date values because you have stored them formatted for displaing instead of in one of the supported date formats.
If the month and day fields always have two digits, you can use substr:
SELECT substr(MyDate, 7, 4) AS Year,
substr(MyDate, 1, 2) AS Month,
sum(Price)
FROM Purchases
GROUP BY Year,
Month
So, the goal is to get an aggregate grouping by the month?
select strftime('%m', mydate), sum(price)
from mytable
group by strftime('%m', mydate)
Look into group by
I would like to have a date and time column in my table. The main purpose of having these 2 columns is to be able to return query results like:
Number of treatments done in the period November 2011.
Number of people working in shifts between 00:01 and 08:00 hours.
I have two tables, which have the following attributes in them(among others):
Shift(day, month, year)
Treatment(start_time, date)
For the first table- Shift, query results need to return values in
terms of (ex: December 30,2012)
For the second table, start_time needs to have values like 0001 and
0800(as I mentioned above). While, date can return values like
'November 2011'.
Initially I thought using the date datatype for declaring each of the day/month/year/date variables would do the job. But this doesn't seem to work out. Should I use int, varchar and int respectively for day, month and year respectively? Also, since the date variable does not have component parts, will date datatype work here? Lastly, if I use timestamp data type for the start_time attribute, what should be the value I enter in the insert column- should it be 08:00:00?
I'm using SQL Server 2014.
Thank You for your help.
AFAIK it is better to use one column by type of DateTime instead of two columns which hold Date and Time separately.
Also you could simply query this column either by Date or Time by casting it to corresponding type :
DECLARE #ChangeDateTime AS DATETIME = '2012-12-09 16:07:43.937'
SELECT CAST(#ChangeDateTime AS DATE) AS [ChangeDate],
CAST(#ChangeDateTime AS TIME) AS [ChangeTime]
results to :
ChangeDate ChangeTime
---------- ----------------
2012-12-09 16:07:43.9370000
Long title, easy meaning:
How is it possible to extract from a date like "2014-04-04 10:47:30.000", which is stored in one column, it's components like year, month and day?
I'm not interested in the time.
For example, I have a table called "Incidents". Inside the table we got a column called "IncidentID" and a column called "ReportingDate", in which dates like the above-mentionend are stored. Let's say we have about 50k Incidents, therefore we have also 50k dates.
A year has 365 days. I want to query for the count of the Incidents, which were reported on different dates - for instance on the 5th of October 2013.
So: How can I get the components of the date and put them into another table while having own columns for the components and how can I query for the Incidents as well?
I guess at first I have to change the datatype of the date from DATETIME to DATE, but I'm not quite sure how to go further. May anyone help me while giving me a code and explains me what it does for a sql-noob? :-)
To achieve this
I want to query for the count of the Incidents, which were reported on
different dates - for instance on the 5th of October 2013.
you haven't do this:
I guess at first I have to change the datatype of the date from
DATETIME to DATE, but I'm not quite sure how to go further.
Just query
SELECT
IncidentID
FROM incidents
WHERE ReportingDate >= '20131005'
AND ReportingDate < '20131006'
I've been given a stack of data where a particular value has been collected sometimes as a date (YYYY-MM-DD) and sometimes as just a year.
Depending on how you look at it, this is either a variance in type or margin of error.
This is a subprime situation, but I can't afford to recover or discard any data.
What's the optimal (eg. least worst :) ) SQL table design that will accept either form while avoiding monstrous queries and allowing maximum use of database features like constraints and keys*?
*i.e. Entity-Attribute-Value is out.
You could store the year, month and day components in separate columns. That way, you only need to populate the columns for which you have data.
if it comes in as just a year make it default to 01 for month and date, YYYY-01-01
This way you can still use a date/datetime datatype and don't have to worry about invalid dates
Either bring it in as a string unmolested, and modify it so it's consistent in another step, or modify the year-only values during the import like SQLMenace recommends.
I'd store the value in a DATETIME type and another value (just an integer will do, or some kind of enumerated type) that signifies its precision.
It would be easier to give more information if you mentioned what kind of queries you will be doing on the data.
Either fix it, then store it (OK, not an option)
Or store it broken with a fixed computed columns
Something like this
CREATE TABLE ...
...
Broken varchar(20),
Fixed AS CAST(CASE WHEN Broken LIKE '[12][0-9][0-9][0-9]' THEN Broken + '0101' ELSE Broken END AS datetime)
This also allows you to detect good from bad source data
If you don't always have a full date, what sort of keys and constraints would you need? Perhaps store two columns of data; a full date, and a year. For data that has only year, the year is stored and date is null. For items with full info, both are populated.
I'd put three columns in the table:
The provided value (YYYY-MM-DD or YYYY)
A date column, Date or DateTime data type, which is nullable
A year column, as an integer or char(4) depending upon your needs.
I'd always populate the year column, populate the date column only when the provided value is a date.
And, because you've kept the provided value, you can always re-process down the road if needs change.
An alternative solution would be to that of a date mask (like in IP). Store the date in a regular datetime field, and insert an additional field of type smallint or something, where you could indicate which is present (could go even binary here):
If you have YYYY-MM-DD, you would have 3 bits of data, which will have the values 1 if data is present and 0 if not.
Example:
Date Mask
2009-12-05 7 (111)
2009-12-01 6 (110, only year and month are know, and day is set to default 1)
2009-01-20 5 (101, for some strange reason, only the year and the date is known. January has 31 days, so it will never generate an error)
Which solution is better depends on what you will do with it.
This is better when you want to select those with full dates, which are between a certain period (less to write). Also this way it's easier to compare any dates which have masks like 7,6,4. It may also take up less memory (date + smallint may be smaller than int+int+int, and only if datetime uses 64 bit, and smallint uses up as much as int, it will be the same).
I was going to suggest the same solution as #ninesided did above. Additionally, you could have a date field and a field that quantitatively represents your uncertainty. This offers the advantage of being able to represent things like "on or about Sept 23, 2010". The problem is that to represent the case where you only know the year, you'd have to set your date to be the middle of the year, with 182.5 days' uncertainty (assuming non-leap year), which seems ugly.
You could use a similar but distinct approach with a mask that represents what date parts you're confident about - that's what SQLMenace offered in his answer above.
+1 each to recommendations from ninesided, Nikki9696 and Jeff Siver - I support all those answers though none was exactly what I decided upon.
My solution:
a date column used only for complete dates
an int column used for years
a constraint to ensure integrity between the two
a trigger to populate the year if only date is supplied
Advantages:
can run simple (one-column) queries on the date column with missing data ignored (by using NULL for what it was designed for)
can run simple (one-column) queries on the year column for any row with a date (because year is automatically populated)
insert either year or date or both (provided they agree)
no fear of disagreement between columns
self explanatory, intuitive
I would argue that methods using YYYY-01-01 to signify missing data (when flagged as such with a second explanatory column) fail seriously on points 1 and 5.
Example code for Sqlite 3:
create table events
(
rowid integer primary key,
event_year integer,
event_date date,
check (event_year = cast(strftime("%Y", event_date) as integer))
);
create trigger year_trigger after insert on events
begin
update events set event_year = cast(strftime("%Y", event_date) as integer)
where rowid = new.rowid and event_date is not null;
end;
-- various methods to insert
insert into events (event_year, event_date) values (2008, "2008-02-23");
insert into events (event_year) values (2009);
insert into events (event_date) values ("2010-01-19");
-- select events in January without expressions on supplementary columns
select rowid, event_date from events where strftime("%m", event_date) = "01";