I need to find users who have posted three times or more, three months in a row. I wrote this query:
select count(id), owneruserid, extract(month from creationdate) as postmonth from posts
group by owneruserid, postmonth
having count(id) >=3
order by owneruserid, postmonth
And I get this:
count owneruserid postmonth
36 -1 1
23 -1 2
45 -1 3
41 -1 4
18 -1 5
24 -1 6
31 -1 7
78 -1 8
83 -1 9
17 -1 10
88 -1 11
127 -1 12
3 6 11
3 7 12
4 8 1
8 8 12
4 12 4
3 12 5
3 22 2
4 22 4
(truncated)
Which is great. How can I query for users who posted three times or more, three months or more in a row? Thanks.
This is called the Islands and Gaps problem, specifically it's an Island problem with a date range. You should,
Fix this question up.
Flag it to be sent to dba.stackexchange.com
To solve this,
Create a pseudo column with a window that has 1 if the row preceding it does not correspond to the preceding mont
Create groups out of that with COUNT()
Check to make sure the count(*) for the group is greater than or equal to three.
Query,
SELECT l.id, creationdaterange, count(*)
FROM (
SELECT t.id,
t.creationdate,
count(range_reset) OVER (PARTITION BY t.id ORDER BY creationdate) AS creationdaterange
FROM (
SELECT id,
creationdate,
CASE
WHEN date_trunc('month',creationdate::date)::date - interval '1 month' = date_trunc('month',lag(creationdate))::date OVER (PARTITION BY id ORDER BY creationdate)
THEN 1
END AS range_reset
FROM post
ORDER BY id, creationdate
) AS t;
) AS l
GROUP BY t.id, creationdaterange
HAVING count(*) >= 3;
Related
I've a table data as below, now I need to fetch the record with in same code, where (Value2-Value1)*2 of one row >= (Value2-Value1) of consequtive date row. (all dates are uniform with in all codes)
---------------------------------------
code Date Value1 Value2
---------------------------------------
1 1-1-2018 13 14
1 2-1-2018 14 16
1 4-1-2018 15 18
2 1-1-2019 1 3
2 2-1-2018 2 3
2 4-1-2018 3 7
ex: output needs to be
1 1-1-2018 13 14
as I am begginer to SQL coding, tried my best, but cannot get through with compare only on consequtive dates.
Use a self join.
You can specify all the conditions you've listed in the ON clause:
SELECT T0.code, T0.Date, T0.Value1, T0.Value2
FROM Table As T0
JOIN Table As T1
ON T0.code = T1.code
AND T0.Date = DateAdd(Day, 1, T1.Date)
AND (T0.Value2 - T0.Value1) * 2 >= T1.Value2 - T1.Value1
I'm fairly close to this solution, but I just need a little help getting over the end.
I'm trying to get a running count of the occurrences of client_ids regardless of the date, however I need the dates and ids to still appear in my results to verify everything.
I found part of the solution here but have not been able to modify it enough for my needs.
Here is what the answer should be, counting if the occurrences of the client_ids sequentially :
id client_id deliver_on running_total
1 138 2017-10-01 1
2 29 2017-10-01 1
3 138 2017-10-01 2
4 29 2013-10-02 2
5 29 2013-10-02 3
6 29 2013-10-03 4
7 138 2013-10-03 3
However, here is what I'm getting:
id client_id deliver_on running_total
1 138 2017-10-01 1
2 29 2017-10-01 1
3 138 2017-10-01 1
4 29 2013-10-02 3
5 29 2013-10-02 3
6 29 2013-10-03 1
7 138 2013-10-03 2
Rather than counting the times the client_id appears sequentially, the code counts the time the id appears in the previous date range.
Here is my code and any help would be greatly appreciated.
Thank you,
SELECT n.id, n.client_id, n.deliver_on, COUNT(n.client_id) AS "running_total"
FROM orders n
LEFT JOIN orders o
ON (o.client_id = n.client_id
AND n.deliver_on > o.deliver_on)
GROUP BY n.id, n.deliver_on, n.client_id
ORDER BY n.deliver_on ASC
* EDIT WITH ANSWER *
I ending up solving my own question. Here is the solution with comments:
-- Set "1" for counting to be used later
WITH DATA AS (
SELECT
orders.id,
orders.client_id,
orders.deliver_on,
COUNT(1) -- Creates a column of "1" for counting the occurrences
FROM orders
GROUP BY 1
ORDER BY deliver_on, client_id
)
SELECT
id,
client_id,
deliver_on,
SUM(COUNT) OVER (PARTITION BY client_id
ORDER BY client_id, deliver_on
ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) -- Counts the sequential client_ids based on the number of times they appear
FROM DATA
Just the answer posted to close the question:
-- Set "1" for counting to be used later
WITH DATA AS (
SELECT
orders.id,
orders.client_id,
orders.deliver_on,
COUNT(1) -- Creates a column of "1" for counting the occurrences
FROM orders
GROUP BY 1
ORDER BY deliver_on, client_id
)
SELECT
id,
client_id,
deliver_on,
SUM(COUNT) OVER (PARTITION BY client_id
ORDER BY client_id, deliver_on
ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) -- Counts the sequential client_ids based on the number of times they appear
FROM DATA
Suppose I have data formatted in the following way (FYI, total row count is over 30K):
customer_id order_date order_rank
A 2017-02-19 1
A 2017-02-24 2
A 2017-03-31 3
A 2017-07-03 4
A 2017-08-10 5
B 2016-04-24 1
B 2016-04-30 2
C 2016-07-18 1
C 2016-09-01 2
C 2016-09-13 3
I need a 4th column, let's call it days_since_last_order which, in the case where order_rank = 1 then 0 else calculate the number of days since the previous order (with rank n-1).
So, the above would return:
customer_id order_date order_rank days_since_last_order
A 2017-02-19 1 0
A 2017-02-24 2 5
A 2017-03-31 3 35
A 2017-07-03 4 94
A 2017-08-10 5 38
B 2016-04-24 1 0
B 2016-04-30 2 6
C 2016-07-18 1 79
C 2016-09-01 2 45
C 2016-09-13 3 12
Is there an easier way to calculate the above with a window function (or similar) rather than join the entire dataset against itself (eg. on A.order_rank = B.order_rank - 1) and doing the calc?
Thanks!
use the lag window function
SELECT
customer_id
, order_date
, order_rank
, COALESCE(
DATE(order_date)
- DATE(LAG(order_date) OVER (PARTITION BY customer_id ORDER BY order_date))
, 0)
FROM <table_name>
I'm constructing a SQL query for a business report. I need to have both subtotals (grouped by file number) and grand totals on the report.
I'm entering unknown SQL territory, so this is a bit of a first attempt. The query I made is almost working. The only problem is that the entries are being grouped -- I need them separated in the report.
Here is my sample data:
FileNumber Date Cost Charge
3 Dec 22/09 5 10
3 Jan 13/10 6 15
3B Mar 28/10 1 3
3B Mar 28/10 5 10
When I run this query
SELECT
CASE
WHEN (GROUPING(FileNumber) = 1) THEN NULL
ELSE FileNumber
END AS FileNumber,
CASE
WHEN (GROUPING(Date) = 1) THEN NULL
ELSE Date
END AS Date,
SUM(Cost) AS Cost,
SUM(Charge) AS Charge
FROM SubtotalTesting
GROUP BY FileNumber, Date WITH ROLLUP
ORDER BY
(CASE WHEN FileNumber IS NULL THEN 1 ELSE 0 END), -- Put NULLs after data
FileNumber,
(CASE WHEN Date IS NULL THEN 1 ELSE 0 END), -- Put NULLs after data
Date
I get the following:
FileNumber Date Cost Charge
3 Dec 22/09 5 10
3 Jan 13/10 6 15
3 NULL 11 25
3B Mar 28/10 6 13 <--
3B NULL 6 13
NULL NULL 17 38
What I want is:
FileNumber Date Cost Charge
3 Dec 22/09 5 10
3 Jan 13/10 6 15
3 NULL 11 25
3B Mar 28/10 1 3 <--
3B Mar 28/10 5 10 <--
3B NULL 6 13
NULL NULL 17 38
I can clearly see why the entries are being grouped, but I have no idea how to separate them while still returning the subtotals and grand total.
I'm a bit green when it comes to doing advanced SQL queries like this, so if I'm taking the wrong approach to the problem by using WITH ROLLUP, please suggest some preferred alternatives -- you don't have to write the whole query for me, I just need some direction. Thanks!
WITH SubtotalTesting (FileNumber, Date, Cost, Charge) AS
(
SELECT '3', CAST('2009-22-12' AS DATETIME), 5, 10
UNION ALL
SELECT '3', '2010-13-06', 6, 15
UNION ALL
SELECT '3B', '2010-28-03', 1, 3
UNION ALL
SELECT '3B', '2010-28-03', 5, 10
),
q AS (
SELECT *,
ROW_NUMBER() OVER (ORDER BY filenumber) AS rn
FROM SubTotalTesting
)
SELECT rn,
CASE
WHEN (GROUPING(FileNumber) = 1) THEN NULL
ELSE FileNumber
END AS FileNumber,
CASE
WHEN (GROUPING(Date) = 1) THEN NULL
ELSE Date
END AS Date,
SUM(Cost) AS Cost,
SUM(Charge) AS Charge
FROM q
GROUP BY
FileNumber, Date, rn WITH ROLLUP
HAVING GROUPING(rn) <= GROUPING(Date)
ORDER BY
(CASE WHEN FileNumber IS NULL THEN 1 ELSE 0 END),
FileNumber,
(CASE WHEN Date IS NULL THEN 1 ELSE 0 END),
Date
I use Oracle 10g and I have a table that stores a snapshot of data on a person for a given day. Every night an outside process adds new rows to the table for any person whose had any changes to their core data (stored elsewhere). This allows a query to be written using a date to find out what a person 'looked' like on some past day. A new row is added to the table even if only a single aspect of the person has changed--the implication being that many columns have duplicate values from slice to slice since not every detail changed in each snapshot.
Below is a data sample:
SliceID PersonID StartDt Detail1 Detail2 Detail3 Detail4 ...
1 101 08/20/09 Red Vanilla N 23
2 101 08/31/09 Orange Chocolate N 23
3 101 09/15/09 Yellow Chocolate Y 24
4 101 09/16/09 Green Chocolate N 24
5 102 01/10/09 Blue Lemon N 36
6 102 01/11/09 Indigo Lemon N 36
7 102 02/02/09 Violet Lemon Y 36
8 103 07/07/09 Red Orange N 12
9 104 01/31/09 Orange Orange N 12
10 104 10/20/09 Yellow Orange N 13
I need to write a query that pulls out time slices records where some pertinent bits, not the whole record, have changed. So, referring to the above, if I only want to know the slices in which Detail3 has changed from its previous value, then I would expect to only get rows having SliceID 1, 3 and 4 for PersonID 101 and SliceID 5 and 7 for PersonID 102 and SliceID 8 for PersonID 103 and SliceID 9 for PersonID 104.
I'm thinking I should be able to use some sort of Oracle Hierarchical Query (using CONNECT BY [PRIOR]) to get what I want, but I have not figured out how to write it yet. Perhaps YOU can help.
Thanks you for your time and consideration.
Here is my take on the LAG() solution, which is basically the same as that of egorius, but I show my workings ;)
SQL> select * from
2 (
3 select sliceid
4 , personid
5 , startdt
6 , detail3 as new_detail3
7 , lag(detail3) over (partition by personid
8 order by startdt) prev_detail3
9 from some_table
10 )
11 where prev_detail3 is null
12 or ( prev_detail3 != new_detail3 )
13 /
SLICEID PERSONID STARTDT N P
---------- ---------- --------- - -
1 101 20-AUG-09 N
3 101 15-SEP-09 Y N
4 101 16-SEP-09 N Y
5 102 10-JAN-09 N
7 102 02-FEB-09 Y N
8 103 07-JUL-09 N
9 104 31-JAN-09 N
7 rows selected.
SQL>
The point about this solution is that it hauls in results for 103 and 104, who don't have slice records where detail3 has changed. If that is a problem we can apply an additional filtration, to return only rows with changes:
SQL> with subq as (
2 select t.*
3 , row_number () over (partition by personid
4 order by sliceid ) rn
5 from
6 (
7 select sliceid
8 , personid
9 , startdt
10 , detail3 as new_detail3
11 , lag(detail3) over (partition by personid
12 order by startdt) prev_detail3
13 from some_table
14 ) t
15 where t.prev_detail3 is null
16 or ( t.prev_detail3 != t.new_detail3 )
17 )
18 select sliceid
19 , personid
20 , startdt
21 , new_detail3
22 , prev_detail3
23 from subq sq
24 where exists ( select null from subq x
25 where x.personid = sq.personid
26 and x.rn > 1 )
27 order by sliceid
28 /
SLICEID PERSONID STARTDT N P
---------- ---------- --------- - -
1 101 20-AUG-09 N
3 101 15-SEP-09 Y N
4 101 16-SEP-09 N Y
5 102 10-JAN-09 N
7 102 02-FEB-09 Y N
SQL>
edit
As egorius points out in the comments, the OP does want hits for all users, even if they haven't changed, so the first version of the query is the correct solution.
In addition to OMG Ponies' answer: if you need to query slices for all persons, you'll need partition by:
SELECT s.sliceid
, s.personid
FROM (SELECT t.sliceid,
t.personid,
t.detail3,
LAG(t.detail3) OVER (
PARTITION BY t.personid ORDER BY t.startdt
) prev_val
FROM t) s
WHERE (s.prev_val IS NULL OR s.prev_val != s.detail3)
I think you'll have better luck with the LAG function:
SELECT s.sliceid
FROM (SELECT t.sliceid,
t.personid,
t.detail3,
LAG(t.detail3) OVER (PARTITION BY t.personid ORDER BY t.startdt) 'prev_val'
FROM TABLE t) s
WHERE s.personid = 101
AND (s.prev_val IS NULL OR s.prev_val != s.detail3)
Subquery Factoring alternative:
WITH slices AS (
SELECT t.sliceid,
t.personid,
t.detail3,
LAG(t.detail3) OVER (PARTITION BY t.personid ORDER BY t.startdt) 'prev_val'
FROM TABLE t)
SELECT s.sliceid
FROM slices s
WHERE s.personid = 101
AND (s.prev_val IS NULL OR s.prev_val != s.detail3)