I have a list of dates in a SQL Server table, and need to figure out a few separate themes about them:
Firstly, are the dates monthly or quarterly? The dates always start on the first of the month.
E.g. one sequence may be 01/01/13, 01/02/13, 01/03/13, 01/04/13, 01/05/13 therefore monthly (UK)
E.g. another sequence may be 01/12/12, 01/03/13, 01/06/13, 01/09/13, 01/12/13 therefore quarterly (UK)
And secondly, which may be solved by the first, are all the dates present? eg no gaps. One way I went around solving this was to say it is either monthly / quarterly or no idea, but that was in C#.
Thanks
You can use the DATEDIFF() function to compare two dates, and you can use a self-join and the ROW_NUMBER() function to compare dates from different rows:
;WITH cte AS (SELECT *, ROW_NUMBER() OVER (ORDER BY dt) RN
FROM Table1)
SELECT DATEDIFF(day,a.dt,b.dt)
FROM cte a
JOIN cte b
ON a.RN = b.RN-1
If you are using SQL 2012 you can use the LEAD() function to compare values from different rows:
SELECT DATEDIFF(day,dt,LEAD(dt,1) OVER(ORDER BY dt)) AS Days
,DATEDIFF(quarter,dt,LEAD(dt,1) OVER(ORDER BY dt)) AS Quarters
FROM Table2
Demo: SQL Fiddle
Related
Consider a time-series table that contains three fields time of type timestamptz, balance of type numeric, and is_spent_column of type text.
The following query generates a valid result for the last day of the given interval.
SELECT
MAX(DATE_TRUNC('DAY', (time))) as last_day,
SUM(balance) FILTER ( WHERE is_spent_column is NULL ) AS value_at_last_day
FROM tbl
2010-07-12 18681.800775017498741407984000
However, I am in need of an equivalent query based on window functions to report the total value of the column named balance for all the days up to and including the given date .
Here is what I've tried so far, but without any valid result:
SELECT
DATE_TRUNC('DAY', (time)) AS daily,
SUM(sum(balance) FILTER ( WHERE is_spent_column is NULL ) ) OVER ( ORDER BY DATE_TRUNC('DAY', (time)) ) AS total_value_per_day
FROM tbl
group by 1
order by 1 desc
2010-07-12 16050.496339044977568391974000
2010-07-11 13103.159119670350269890284000
2010-07-10 12594.525752964512456914454000
2010-07-09 12380.159588711091681327014000
2010-07-08 12178.119542536668113577014000
2010-07-07 11995.943973804127033140014000
EDIT:
Here is a sample dataset:
LINK REMOVED
The running total can be computed by applying the first query above on the entire dataset up to and including the desired day. For example, for day 2009-01-31, the result is 97.13522530000000000000, or for day 2009-01-15 when we filter time as time < '2009-01-16 00:00:00' it returns 24.446144000000000000.
What I need is an alternative query that computes the running total for each day in a single query.
EDIT 2:
Thank you all so very much for your participation and support.
The reason for differences in result sets of the queries was on the preceding ETL pipelines. Sorry for my ignorance!
Below I've provided a sample schema to test the queries.
https://www.db-fiddle.com/f/veUiRauLs23s3WUfXQu3WE/2
Now both queries given above and the query given in the answer below return the same result.
Consider calculating running total via window function after aggregating data to day level. And since you aggregate with a single condition, FILTER condition can be converted to basic WHERE:
SELECT daily,
SUM(total_balance) OVER (ORDER BY daily) AS total_value_per_day
FROM (
SELECT
DATE_TRUNC('DAY', (time)) AS daily,
SUM(balance) AS total_balance
FROM tbl
WHERE is_spent_column IS NULL
GROUP BY 1
) AS daily_agg
ORDER BY daily
I'm trying to get the day difference between 2 dates in Impala but I need to exclude weekends.
I know it should be something like this but I'm not sure how the weekend piece would go...
DATEDIFF(resolution_date,created_date)
Thanks!
One approach at such task is to enumerate each and every day in the range, and then filter out the week ends before counting.
Some databases have specific features to generate date series, while in others offer recursive common-table-expression. Impala does not support recursive queries, so we need to look at alternative solutions.
If you have a table wit at least as many rows as the maximum number of days in a range, you can use row_number() to offset the starting date, and then conditional aggregation to count working days.
Assuming that your table is called mytable, with column id as primary key, and that the big table is called bigtable, you would do:
select
t.id,
sum(
case when dayofweek(dateadd(t.created_date, n.rn)) between 2 and 6
then 1 else 0 end
) no_days
from mytable t
inner join (select row_number() over(order by 1) - 1 rn from bigtable) n
on t.resolution_date > dateadd(t.created_date, n.rn)
group by id
I am trying to create following logic in Alteryx and data is coming from Exasol database.
Column “Sum_Qty_28_days“ should sum up the values of “Qty ” column for same article which falls under last 28 days.
My sample data looks like:
and I want following output:
E.g. “Sum_Qty_28_days” value for “article” = ‘A’ and date = ‘’2019-10-8” is 8 because it is summing up the “Qty” values associated with dates (coming within previous 28 days) Which are:
2019-09-15
2019-10-05
2019-10-08
for “article” = ‘A’.
Is this possible using SQL window function?
I tried myself with following code:
SUM("Qty") OVER (PARTITION BY "article", date_trunc('month',"Date")
ORDER BY "Date")
But, it is far from what I need. It is summing up the Qty for dates falling in same month. However, I need to sum of Qty for last 28 days.
Thanks in advance.
Yes, this is possible using standard SQL and in many databases. However, this will not work in all databases:
select t.*,
sum(qty) over (partition by article
order by date
range between interval '27 day' preceding and current row
) as sum_qty_28_days
from t;
If your RDBMS does not support the range frame, an alternative solution is to use an inline subquery:
select
t.*,
(
select sum(t1.qty)
from mytable t1
where
t1.article = t.article
and t1.date between t.date - interval 28 days and t.date
) sum_qty_28_days
from mytable t
I need to form a report which provides some information per each date within dates interval.
I need to have it within a single query (can't create any functions or supporting tables).
How can I achieve that in PrestoDB?
Note: There are lots of vendor specific solution here, here and even here. But none of them satisfies my need as they either don't work in Presto or use tables/functions.
To be more precise here is an example of query:
WITH ( query to select all dates between 2017.01.01 and 2018.01.01 ) AS dates
SELECT
date date,
count(*) number_of_orders
FROM dates dates
LEFT JOIN order order
ON order.created_at = dates.date
You can use the Presto SEQUENCE() function to generate a sequence of days as an array, and then use UNNEST to explode that array as a result set.
Something like this should work for you:
SELECT date_array AS DAY
FROM UNNEST(
SEQUENCE(
cast('2017-01-01' AS date),
cast('2018-01-01' AS date),
INTERVAL '1' DAY
)
) AS t1(date_array)
There are questions like this all over the place so let me specify where I specifically need help.
I have seen moving averages in SQL with Oracle Analytic functions, MSSQL apply, or a variety of other methods. I have also seen this done with self joins (one join for each day of the average, such as here How do you create a Moving Average Method in SQL? ).
I am curious as to if there is a way (only using self joins) to do this in SQL (preferably oracle, but since my question is geared towards joins alone this should be possible for any RDBMS). The way would have to be scalable (for a 20 or 100 day moving average, in contrast to the link I researched above, which required a join for each day in the moving average).
My thoughts are
select customer, a.tradedate, a.shares, avg(b.shares)
from trades a, trades b
where b.tradedate between a.tradedate-20 and a.tradedate
group by customer, a.tradedate
But when I tried it in the past it hadn't worked. To be more specific, I am trying a smaller but similar exmaple (5 day avg instead of 20 day) with this fiddle demo and cant find out where I am going wrong. http://sqlfiddle.com/#!6/ed008/41
select a.ticker, a.dt_date, a.volume, avg(b.volume)
from yourtable a, yourtable b
where b.dt_date between a.dt_date-5 and a.dt_date
and a.ticker=b.ticker
group by a.ticker, a.dt_date, a.volume
I don't see anything wrong with your second query, I think the only reason it's not what you're expecting is because the volume field is an integer data type so when you calculate the average the resulting output will also be an integer data type. For an average you have to cast it, because the result won't necessarily be an integer (whole number):
select a.ticker, a.dt_date, a.volume, avg(cast(b.volume as float))
from yourtable a
join yourtable b
on a.ticker = b.ticker
where b.dt_date between a.dt_date - 5 and a.dt_date
group by a.ticker, a.dt_date, a.volume
Fiddle:
http://sqlfiddle.com/#!6/ed008/48/0 (thanks to #DaleM for DDL)
I don't know why you would ever do this vs. an analytic function though, especially since you mention wanting to do this in Oracle (which has analytic functions). It would be different if your preferred database were MySQL or a database without analytic functions.
Just to add to the answer, this is how you would achieve the same result in Oracle using analytic functions. Notice how the PARTITION BY acts as the join you're using on ticker. That splits up the results so that the same date shared across multiple tickers don't interfere.
select ticker,
dt_date,
volume,
avg(cast(volume as decimal)) over( partition by ticker
order by dt_date
rows between 5 preceding
and current row ) as mov_avg
from yourtable
order by ticker, dt_date, volume
Fiddle:
http://sqlfiddle.com/#!4/0d06b/4/0
Analytic functions will likely run much faster.
http://sqlfiddle.com/#!6/ed008/45 would appear to be what you need.
select a.ticker,
a.dt_date,
a.volume,
(select avg(cast(b.volume as float))
from yourtable b
where b.dt_date between a.dt_date-5 and a.dt_date
and a.ticker=b.ticker)
from yourtable a
order by a.ticker, a.dt_date
not a join but a subquery