I need to a value associated to a month and a user in a table. And I want to perform queries on it. I don't know if there is a column data type for this type of need. If not, should I:
Create a string field and build year-month concatenation (2017-01)
Create a int field and build year-month concatenation (201701)
Create two columns (one year and one month)
Create a date column at the beginning of the month (2017-01-01 00:00:00)
Something else?
The objective is to run queries like (pseudo-SQL):
SELECT val FROM t WHERE year_month = THIS_YEAR_MONTH and user_id='adc1-23...';
I would suggest not thinking too hard about the problem and just using the first date/time of the month. Postgres has plenty of date-specific functions -- from date_trunc() to age() to + interval -- to support dates.
You can readily convert them to the format you want, get the difference between two values, and so on.
If you phrase your query as:
where year_month = date_trunc('month', now()) and user_id = 'adc1-23...'
Then it can readily take advantage of an index on (user_id, year_month) or (year_month, user_id).
If you are interested in display values in YYYY-MM formt you can use to_char(your_datatime_colum,'YYYY-MM')
example:
SELECT to_char(now(),'YYYY-MM') as year_month
Related
I was wondering, in SQL/dbt is there a way to set all dates to be >= another date?
Say I have a 'createdat' date field and a 'updatedat' date field. I use it multiple times in my query (multiple CTEs) as well as other dates. I want to make sure all dates used are less then the last day of last month (i.e. <= last_day(current_date()-30, month)).
Is there a way to set that in the beginning of the query?
This can definitely be done. You'll want to compare the greatest() of a number of columns with whatever date cut-off you want.
Effectively, it would be:
select *
from {{ ref('some_table') }}
where greatest(created_at,updated_at) < date_trunc('month', current_date)
You can obviously add as many columns to that query as you'd like.
N.B.: On some warehouses, greatest returns null if any of the columns in it are null. In that situation, you'll need to coalesce each date with some date placeholder, like '1970-01-01'.
I have a table containing the following columns:
stats_date (YYYY-MM-DD)
registered (INT)
opened_form (INT)
Compose a query that will return the total registered, and opened_form by month for the last 3 months. Also a calculated column called conversion_rate which is the registered column divided by the opened_form.
Are you just looking for aggregation? Date/time functions differ significantly among databases, but the idea is:
select year(stats_date), month(stats_date),
sum(registered), sum(opened_form),
sum(registered) * 1.0 / sum(opened_form) as ratio
from t
group by year(stats_date), month(stats_date)
order by min(stats_date);
Of course, your database might have a different way of extracting the year and month from a date.
You can see the ANSI SQL at page 187 to understand how agregation works. To know how to group your column by Month you need to check the documentation of your db, usually is MONTH(COLUMN_NAME).
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 have a date of birth DATE column in a customer table with ~13 million rows. I would like to query this table to find all customers who were born on a certain month and day of that month, but any year.
Can I do this by casting the date into a char and doing a subscript query on the cast, or should I create an aditional char column, update it to hold just the month and day, or create three new integer columns to hold month, day and year, respectively?
This will be a very frequently used query criteria...
EDIT:... and the table has ~13 million rows.
Can you please provide an example of your best solution?
If it will be frequently used, consider a 'functional index'. Searching on that term at the Informix 11.70 InfoCentre produces a number of relevant hits.
You can use:
WHERE MONTH(date_col) = 12 AND DAY(date_col) = 25;
You can also play games such as:
WHERE MONTH(date_col) * 100 + DAY(date_col) = 1225;
This might be more suitable for a functional index, but isn't as clear for everyday use. You could easily write a stored procedure too:
Note that in the absence of a functional index, invoking functions on a column in the criterion means that an index is unlikely to be used.
CREATE FUNCTION mmdd(date_val DATE DEFAULT TODAY) RETURNING SMALLINT AS mmdd;
RETURN MONTH(date_val) * 100 + DAY(date_val);
END FUNCTION;
And use it as:
WHERE mmdd(date_col) = 1225;
Depending on how frequently you do this and how fast it needs to run you might think about splitting the date column into day, month and year columns. This would make search faster but cause all sorts of other problems when you want to retrieve a whole date (and also problems in validating that it is a date) - not a great idea.
Assuming speed isn't a probem I would do something like:
select *
FROM Table
WHERE Month(*DateOfBirthColumn*) = *SomeMonth* AND DAY(*DateOfBirthColumn*) = *SomeDay*
I don't have informix in front of me at the moment but I think the syntax is right.
I've got a table with purchase orders stored in it. Each row has a timestamp indicating when the order was placed. I'd like to be able to create a report indicating the number of purchases each day, month, or year. I figured I would do a simple SELECT COUNT(xxx) FROM tbl_orders GROUP BY tbl_orders.purchase_time and get the value, but it turns out I can't GROUP BY a timestamp column.
Is there another way to accomplish this? I'd ideally like a flexible solution so I could use whatever timeframe I needed (hourly, monthly, weekly, etc.) Thanks for any suggestions you can give!
This does the trick without the date_trunc function (easier to read).
// 2014
select created_on::DATE from users group by created_on::DATE
// updated September 2018 (thanks to #wegry)
select created_on::DATE as co from users group by co
What we're doing here is casting the original value into a DATE rendering the time data in this value inconsequential.
Grouping by a timestamp column works fine for me here, keeping in mind that even a 1-microsecond difference will prevent two rows from being grouped together.
To group by larger time periods, group by an expression on the timestamp column that returns an appropriately truncated value. date_trunc can be useful here, as can to_char.