I have a table containing the fields:
cazi, cdip, date
1 2 13/03/2021
1 2 14/03/2021
1 2 15/03/2021
1 2 18/03/2021
1 2 19/03/2021
1 3 13/03/2021
1 3 14/03/2021
1 3 15/03/2021
1 3 20/03/2021
1 3 21/03/2021
I can't get the result with the columns:
cazi, cdip, date1, date2, num_dd
1 2 13/03/2021 15/03/2021 3
1 2 18/03/2021 19/03/2021 2
1 3 13/03/2021 15/03/2021 3
1 3 20/03/2021 21/03/2021 2
Can you help me ?
With the following code I get the min and max of the records, but I need the consecutive records:
WITH
dateGroup AS
(
SELECT DISTINCT
UniqueDate = [date]
,DateGroup = DATEADD(dd, - ROW_NUMBER() OVER (ORDER BY [date]), [date])
FROM malt
GROUP BY [date]
)
SELECT distinct
StartDate = MIN(UniqueDate)
,EndDate = MAX(UniqueDate)
,Days = DATEDIFF(dd,MIN(UniqueDate),MAX(UniqueDate))+1
,cazi
,cdip
FROM dateGroup JOIN
malt u ON u.date = UniqueDate
GROUP BY
DateGroup
,cazi
,cdip
This is traditional GAPS & ISLAND problem. You can try below query to achieve the desired result -
SELECT cazi, cdip, MIN(T.[date]), MAX(T.[date])
FROM (SELECT M.*, ROW_NUMBER() OVER(PARTITION BY cdip ORDER BY [date]) RN
FROM malt M) T
GROUP BY cazi, cdip, DATEADD(DAY, - RN, [date]);
Demo.
Related
I have a table with messages and I need to find chats where were two or more messages in period of 10 seconds. table
id message_id time
1 1 2021.11.10 13:09:00
1 2 2021.11.10 13:09:01
1 3 2021.11.10 13:09:50
2 1 2021.11.10 15:18:00
2 2 2021.11.10 15:20:00
3 1 2021.11.12 15:00:00
3 2 2021.11.12 15:10:00
3 2 2021.11.12 15:10:10
So the result looks like
id
1
3
I can't come up with the idea how to group by a period or maybe it can be done other way?
select id
from t
group by id, ?
having count(message_id) > 1
You can join the table with itself, matching them on the chat id and your timeframe.
create table messages (chat_id integer,message_id integer,"time" timestamp);
insert into messages values
(1,1,'2021.11.10 13:09:00'),
(1,2,'2021.11.10 13:09:01'),
(1,3,'2021.11.10 13:09:50'),
(2,1,'2021.11.10 15:18:00'),
(2,2,'2021.11.10 15:20:00'),
(3,1,'2021.11.12 15:00:00'),
(3,2,'2021.11.12 15:10:00'),
(3,2,'2021.11.12 15:10:10');
select target_chat,
target_message,
count(*) "number of messages preceding by no more than 10 seconds"
from
(select t1.chat_id target_chat,
t1.message_id target_message,
t1.time,
t2.chat_id,
t2.message_id,
t2.time
from messages t1
inner join messages t2
on t1.chat_id=t2.chat_id
and t1.message_id<>t2.message_id
and (t2.time<=t1.time-'10 seconds'::interval and t2.time<=t1.time)) a
group by 1,2;
-- target_chat | target_message | number of messages preceding by no more than 10 seconds
---------------+----------------+---------------------------------------------------------
-- 1 | 3 | 2
-- 2 | 2 | 1
-- 3 | 2 | 2
--(3 rows)
From that you can select the records with your desired number of preceding messages.
this is a simple query that finds every previous value that is included in our interval
select id from test_table t where
t.time + interval '10 second' >=
(select time from test_table where id=t.id and time>t.time limit 1)
group by id;
results
id
----
1
3
To find rows within an period of time, you can tipically use a window function which avoids a self join on the table :
SELECT id, count(*) OVER (ORDER BY time RANGE BETWEEN CURRENT ROW AND '10 minutes' FOLLOWING)
FROM t
GROUP BY id
Then you can use this query as a sub-query if you only want the id with count(*) > 1 :
SELECT DISTINCT ON (l.id) l.id
FROM
( SELECT id, count(*) OVER (ORDER BY time RANGE BETWEEN CURRENT ROW AND '10 minutes' FOLLOWING) AS ct
FROM t
GROUP BY id
) AS l
WHERE l.ct > 1 ;
I have the following table
id num sub_id
1 3 1
1 5 2
1 1 1
1 4 2
2 1 5
2 2 5
I want to get this result
id num sub_id number
1 3 1 1
1 5 2 2
1 1 1 1
1 4 2 2
2 1 5 1
2 2 5 1
I tried to do this row_number() over (partition by id order by num,sub_id DESC) but th result is obviosly differs
I don't understand your business because you don't explain your logic and information about that, but maybe this query helps you?
Result and info: dbfiddle
with recursive
cte_r as (
select id,
num,
sub_id,
row_number() over () as rn
from test),
cte as (
select id,
num,
sub_id,
rn,
rn as grp
from cte_r
where rn = 1
union all
select cr.id,
cr.num,
cr.sub_id,
cr.rn,
case
when cr.id != c.id then 1
when cr.id = c.id and cr.sub_id = c.sub_id then c.grp
when cr.id = c.id and cr.sub_id > c.sub_id then c.grp + 1
when cr.id = c.id and cr.sub_id < c.sub_id then 1
end
from cte c,
cte_r cr
where c.rn = cr.rn - 1)
select id,
num,
sub_id,
grp
from cte
order by id
It looks like you actually want to ignore the num column and then use DENSE_RANK on sub_id:
SELECT *, dense_rank() AS number OVER (PARTITION BY id ORDER BY sub_id) FROM …;
I have a postgres table test_table that looks like this:
date | test_hour
------------+-----------
2000-01-01 | 1
2000-01-01 | 2
2000-01-01 | 3
2000-01-02 | 1
2000-01-02 | 2
2000-01-02 | 3
2000-01-02 | 4
2000-01-03 | 1
2000-01-03 | 2
I need to select all the dates which don't have test_hour = 1, 2, and 3, so it should return
date
------------
2000-01-03
Here is what I have tried:
SELECT date FROM test_table WHERE test_hour NOT IN (SELECT generate_series(1,3));
But that only returns dates that have extra hours beyond 1, 2, 3
You can use aggregation and conditional HAVING clauses, like so:
SELECT mydate
FROM mytable
GROUP BY mydate
HAVING
MAX(CASE WHEN test_hour = 1 THEN 1 END) != 1
OR MAX(CASE WHEN test_hour = 2 THEN 1 END) != 1
OR MAX(CASE WHEN test_hour = 3 THEN 1 END) != 1
Another possibility would be to join it against the series (or another subquery containing the hours) and do a [distinct] count on the hours aggregatet per date:
select date from tst
inner join (select generate_series(1,3) "hour") hours on hours.hour = tst.hour
group by tst.date
having count(distinct tst.hour) < 3;
or
select date from tst
where hour in (select generate_series(1,3))
group by date
having count(distinct tst.hour) < 3;
[You don't need the distinct if date/hour combinations in Your table are unique]
A solution using set difference, giving you exactly the rows that are missing:
(SELECT DISTINCT
date, all_hour
FROM test_table
CROSS JOIN generate_series(1,3) all_hour)
EXCEPT
(TABLE test_table)
And a solution using an array aggregate and the array contains operator:
SELECT date
FROM test_table
GROUP BY date
HAVING NOT array_agg(test_hour) #> ARRAY(SELECT generate_series(1,3))
(online demos)
I have a table that lists all transactions as follows:
ID Account Date Amount
---------------------------
1 2 02/01/2015 30
2 5 05/01/2015 25
3 2 05/01/2015 12
4 2 07/01/2015 42
5 5 10/012015 19
6 2 11/01/2015 58
7 3 15/01/2015 36
Would like to write a select statement that will list only the last 3 transactions of each account, as follows please.
Account Date1 Amount Date2 Amount Date3 Amount
---------------------------------------------------------------
2 11/01/2015 58 07/01/2015 42 05/01/2015 12
3 15/01/2015 36
5 10/01/2015 19 05/01/2015 25
Thank you for any advice
You can use the row_number() function in a derived table to partition the data by account, and give each date within the partition a number, and then do a conditional aggregation over the rows with the top 3 numbers, grouped by account:
select
account,
date1 = max(case when rn = 1 then date end),
amount = max(case when rn = 1 then amount end),
date2 = max(case when rn = 2 then date end),
amount = max(case when rn = 2 then amount end),
date3 = max(case when rn = 3 then date end),
amount = max(case when rn = 3 then amount end)
from (
select *, rn = row_number() over (partition by account order by date desc)
from your_table
) a
where rn <= 3
group by account
Sample SQL Fiddle
I have two tables and for each ID and Level combination in table1, I need to get a count of times matching ID appears in table2 in between sequential times for levels in table1.
So for example, for ID = 1 and Level=1 in table1, two Time entries from table2 for ID=1 fall between Time of Level=1 and Level=2 in table1, so result will be 2 in the result table.
table1:
ID Level Time
1 1 6/7/13 7:03
1 2 6/9/13 7:05
1 3 6/12/13 12:02
1 4 6/17/13 5:01
2 1 6/18/13 8:38
2 3 6/20/13 9:38
2 4 6/23/13 10:38
2 5 6/28/13 1:38
table2:
ID Time
1 6/7/13 11:51
1 6/7/13 14:15
1 6/9/13 16:39
1 6/9/13 19:03
2 6/20/13 11:02
2 6/20/13 15:50
Result would be
ID Level Count
1 1 2
1 2 2
1 3 0
1 4 0
2 1 0
2 3 2
2 4 0
2 5 0
select transformed_tab1.id, transformed_tab1.level, count(tab2.id)
from
(select tab1.id, tab1.level, tm, lead(tm) over (partition by id order by tm) as next_tm
from
(
select 1 as id, 1 as level, '2013-06-07 07:03'::timestamp as tm union
select 1 as id, 2 as level, '2013-06-09 07:05 '::timestamp as tm union
select 1 as id, 3 as level, '2013-06-12 12:02'::timestamp as tm union
select 1 as id, 4 as level, '2013-06-17 05:01'::timestamp as tm union
select 2 as id, 1 as level, '2013-06-18 08:38'::timestamp as tm union
select 2 as id, 3 as level, '2013-06-20 09:38'::timestamp as tm union
select 2 as id, 4 as level, '2013-06-23 10:38'::timestamp as tm union
select 2 as id, 5 as level, '2013-06-28 01:38'::timestamp as tm) tab1
) transformed_tab1
left join
(select 1 as id, '2013-06-07 11:51'::timestamp as tm union
select 1 as id, '2013-06-07 14:15'::timestamp as tm union
select 1 as id, '2013-06-09 16:39'::timestamp as tm union
select 1 as id, '2013-06-09 19:03'::timestamp as tm union
select 2 as id, '2013-06-20 11:02'::timestamp as tm union
select 2 as id, '2013-06-20 15:50'::timestamp as tm) tab2
on transformed_tab1.id=tab2.id and tab2.tm between transformed_tab1.tm and transformed_tab1.next_tm
group by transformed_tab1.id, transformed_tab1.level
order by transformed_tab1.id, transformed_tab1.level
;
SQL Fiddle
select t1.id, level, count(t2.id)
from
(
select id, level,
tsrange(
"time",
lead("time", 1, 'infinity') over(
partition by id order by level
),
'[)'
) as time_range
from t1
) t1
left join
t2 on t1.id = t2.id and t1.time_range #> t2."time"
group by t1.id, level
order by t1.id, level
The solution starts creating a range of timestamps using the lead window function. Notice the [) parameter to the tsrange constructor. It means to include the lower and exclude the upper bound.
Then it joins the two tables with the #> range operator. It means the range includes the element.
It is necessary to left join t1 to have the zero counts.