I am not very good with Queries and Database.
I have the the following data table
Date ID Value
20160601 1 300
20160607 1 301
20160601 2 600
20160607 2 601
20160501 1 250
20160507 1 240
20160501 2 800
20160507 2 801
my requirement is to select the last date of a given month for each ID and show the value.
for example, If I choose month 5 the result would be:
Date ID Value
20160507 1 240
20160507 2 801
and so on based on the month the user will enter.
I know it may look simple but I am really stuck and I would appreciate some help. Thanks.
Assuming date is an actual date column (as it should be), you can use extract to compare the month value, and then the row_number() over ... analytic function to get the latest row per id value:
select date, id, value
from (select date, id, value,
row_number() over (partition by id order by date desc) as rn
from tbl
where extract(month from date) = 5)
where rn = 1
Of course, I assume that your actual date column is called something else, as date is a reserved word.
Find the maximum date then select all rows with that date.
select *
from table
where date = (select max(date) from table where date like '201605%')
Related
Have a requirement where I would need to rope the calculated value of the previous row for calculation in the current row.
The following is a sample of how the data currently looks :-
ID
Date
Days
1
2022-01-15
30
2
2022-02-18
30
3
2022-03-15
90
4
2022-05-15
30
The following is the output What I am expecting :-
ID
Date
Days
CalVal
1
2022-01-15
30
2022-02-14
2
2022-02-18
30
2022-03-16
3
2022-03-15
90
2022-06-14
4
2022-05-15
30
2022-07-14
The value of CalVal for the first row is Date + Days
From the second row onwards it should take the CalVal value of the previous row and add it with the current row Days
Essentially, what I am looking for is means to access the previous rows calculated value for use in the current row.
Is there anyway we can achieve the above via Postgres SQL? I have been tinkering with window functions and even recursive CTEs but have had no luck :(
Would appreciate any direction!
Thanks in advance!
select
id,
date,
coalesce(
days - (lag(days, 1) over (order by date, days))
, days) as days,
first_date + cast(days as integer) as newdate
from
(
select
-- get a running sum of days
id,
first_date,
date,
sum(days) over (order by date, days) as days
from
(
select
-- get the first date
id,
(select min(date) from table1) as first_date,
date,
days
from
table1
) A
) B
This query get the exact output you described. I'm not at all ready to say it is the best solution but the strategy employed is to essential create a running total of the "days" ... this means that we can just add this running total to the first date and that will always be the next date in the desired sequence. One finesse: to put the "days" back into the result, we calculated the current running total less the previous running total to arrive at the original amount.
assuming that table name is table1
select
id,
date,
days,
first_value(date) over (order by id) +
(sum(days) over (order by id rows between unbounded preceding and current row))
*interval '1 day' calval
from table1;
We just add cumulative sum of days to first date in table. It's not really what you want to do (we don't need date from previous row, just cumulative days sum)
Solution with recursion
with recursive prev_row as (
select id, date, days, date+ days*interval '1 day' calval
from table1
where id = 1
union all
select t.id, t.date, t.days, p.calval + t.days*interval '1 day' calval
from prev_row p
join table1 t on t.id = p.id+ 1
)
select *
from prev_row
I can't get my head around whether this is even possible, but I feel like I might have done it before and lost that bit of code. I am trying to craft a select statement that contains an inner join on a subquery to show the number of days between two dates from the same table.
A simple example of the data structure would look like:
Name ID Date Day Hours
Bill 1 3/3/20 Thursday 8
Fred 2 4/3/20 Monday 6
Bill 1 8/3/20 Tuesday 2
Based on this data, I want to select each row plus an extra column which is the number of days between the date from each row for each ID. Something like:
Select * from tblData
Inner join (datediff(Select Top(1) Date from tblData where Date < Date), Date) And ID = ID)
or for simplicity:
Select * from tblData
Inner join (datediff(Select Top(1) Date from tblData where Date < 8/3/20), 8/3/20) And ID = 1)
The resulting dataset would look like:
Name ID Date Day Hours DaysBtwn
Bill 1 3/3/20 Thursday 8 4 (Assuming there was an earlier row in the table)
Fred 2 4/3/20 Monday 6 5 (Assuming there was an earlier row in the table)
Bill 1 8/3/20 Tuesday 2 5 (Based on the previous row date being 3/3/20 for Bill)
Does this make sense and am I trying to do this the wrong way? I want to do this for about 600000 rows in table and therefore efficiency is the key, so if there is a better way to do this, i'm open to suggestions.
You can use lag():
select t.*, datediff(day, lag(date) over(partition by id order by date), date) diff
from mytable t
I think you just want lag():
select t.*,
datediff(day,
lag(date) over (partition by name order by date),
date
) as diff
from tblData t;
Note: If you want to filter the data so rows in the result set are used for the lag() but not in the result set, then use a subquery:
select t.*
from (select t.*,
datediff(day,
lag(date) over (partition by name order by date),
date
) as diff
from tblData t
) t
where date < '2020-08-03';
Also note the use of the date constant as a string in YYYY-MM-DD format.
How do we select the count of the record that appears more than once in 48hrs?
for eg
ID DATE
1 9/24/2018
1 9/23/2018
1 9/20/2018
2 9/20/2018
ID 1 APPEARED MORE THAN ONCE IN 48 HOURS
please let me know how to write a sql query to do this
There are lots of ways, but I'd start with using LAG() and a date comparison. Assuming your DATE column is a date data-type?
WITH
entity_summary AS
(
SELECT
ID,
CASE
WHEN LAG("DATE") OVER (PARTITION BY ID ORDER BY "DATE") >= "DATE" - INTERVAL '2' DAY
THEN 1
ELSE 0
END
AS occurence_within_2_day
FROM
Table1
)
SELECT
ID,
SUM(occurence_within_2_day)
FROM
entity_summary
GROUP BY
ID
HAVING
SUM(occurence_within_2_day) >= 1
I'm trying to count the number of months that have passed based on ID, it's possible that for some records the months will not increase by 1 each time (i.e. someone could have a record for 1/1/13 and 3/1/13 but not 2/1/13) however I only want a count of the records in my table. So missing months don't matter.
An example table would be: (notice the missing month and it's irrelevancy).
DATE ID Months Passed
----------- --- --------------
2013-11-01 105 1
2013-12-01 105 2
2014-02-01 105 3
2014-03-01 105 4
Essentially an Excel COUNTIFSin SQL, which I've written:
=COUNTIFS(IDColumn, ID, MonthColumn, "<=" & Month)
Does anyone know of a way to generate the desired column using SQL?
Try ROW_NUMBER(). If you just want the "Months Passed" column to increase by 1 each time, and for each ID, that will do the trick.
SELECT
Date,
Id,
Indicator,
ROW_NUMBER() OVER(PARTITION BY Id ORDER BY Date) AS RowNum
FROM YourTable
WHERE Indicator = 'YES'
UNION
SELECT
Date,
Id,
Indicator,
0 AS RowNum
FROM YourTable
WHERE Indicator = 'NO'
You could more simply count rows grouped by month (more complex if you have count months in different years separately):
SELECT COUNT(derived.monthVal)
FROM (SELECT MONTH(<your date field>) AS monthVal
FROM [your table]
WHERE [Your ID Column] = <the id>
GROUP BY MONTH(<your date field>)) AS derived;
Using SQL I need to return a smooth set of results (i.e. one per day) from a dataset that contains 0-N records per day.
The result per day should be the most recent previous value even if that is not from the same day. For example:
Starting data:
Date: Time: Value
19/3/2014 10:01 5
19/3/2014 11:08 3
19/3/2014 17:19 6
20/3/2014 09:11 4
22/3/2014 14:01 5
Required output:
Date: Value
19/3/2014 6
20/3/2014 4
21/3/2014 4
22/3/2014 5
First you need to complete the date range and fill in the missing dates (21/3/2014 in you example). This can be done by either joining a calendar table if you have one, or by using a recursive common table expression to generate the complete sequence on the fly.
When you have the complete sequence of dates finding the max value for the date, or from the latest previous non-null row becomes easy. In this query I use a correlated subquery to do it.
with cte as (
select min(date) date, max(date) max_date from your_table
union all
select dateadd(day, 1, date) date, max_date
from cte
where date < max_date
)
select
c.date,
(
select top 1 max(value) from your_table
where date <= c.date group by date order by date desc
) value
from cte c
order by c.date;
May be this works but try and let me know
select date, value from test where (time,date) in (select max(time),date from test group by date);