I have table as following :
Table 1 ( Column1,column2,column3,date)
I want to get count(column 1) & sum(column2) and the same count / sum when date is greater than the minimum date value in date column.
Although the 4 required value can be controlled by one condition on column 3.
Column 1 , Column 2 , Column 3 , Date
A 1 1 5/5/2016
G 5 0 5/10/2016
B 1 2 5/10/2016
A 12 1 5/10/2016
D 1 1 5/5/2016
A 1 1 5/11/2016
C 7 1 5/5/2016
C 1 1 5/12/2016
E 10 2 5/10/2016
I want when filter on column 3 = 1 get the following result :
Count (1) , Sum(2) , Count(1) when date greater than minimum ,Count(2) when date greater than minimum
3 , 23 , 2 , 14
I tried to use case put I don't need to group by values.
how can I generate query fulfill above requirements in oracle
You can use case. As you describe:
select count(column1), sum(column2),
count(case when date > mindate then column1 end),
sum(case when date > mindate then column2 end)
from (select t.*, min(date) over () as mindate
from table1 t
) t;
This uses a window function to get the minimum date, which is used in the case.
Related
I want to add an extra column, where the min and max values of each group (ID) will appear.
Here how the table looks like:
select ID, VALUE from mytable
ID VALUE
1 4
1 1
1 7
2 2
2 5
3 7
3 3
Here is the result I want to get:
ID VALUE min_max_values
1 4 NULL
1 1 min
1 7 max
2 2 min
2 5 max
3 7 max
3 3 min
4 1 both
5 2 min
5 3 max
Thank you for your help in advance!
You can use window functions and a case expression:
select id, value,
case
when value = min_value and min_value = max_value then 'both'
when value = min_value then 'min'
when value = max_value then 'max'
end as min_max_values
from (
select t.*,
min(value) over(partition by id) as min_value,
max(value) over(partition by id) as max_value
from mytable t
) t
The subquery is not strictly necessary, we could use the window min() and max() directly in the outer query. It is just there to avoid repeatedly typing the window function expressions in the outer query.
I have table like this:
value nextValue
1 2
2 3
3 20
20 21
21 22
22 23
23 NULL
Value is ordered ASC, nextValue is next row Value.
requirement is group by with condition nextValue-value>10, and count how many values in different groups.
For example, there should be two groups (1,2,3) and (20,21,22,23), first group count is 3, the second group count is 4.
I'm trying to mark each group with unique number, so I could group by these marked nums
value nextValue mark
1 2 1
2 3 1
3 20 1
20 21 2
21 22 2
22 23 2
23 NULL 2
But I don't know how to write mark column, I need an autocrement variable when nextValue-value>10.
Can I make it happen in Hive? Or there's better solution for the requirement?
If I understand correctly, you can use a cumulative sum. The idea is to set a flag when next_value - value > 10. This identifies the groups. So, this query adds a group number:
select t.*,
sum(case when nextvalue > value + 10 then 1 else 0 end) over (order by value desc) as mark
from t
order by value;
You might not find this solution satisfying, because the numbering is in descending order. So, a bit more arithmetic fixes that:
select t.*,
(sum(case when nextvalue > value + 10 then 1 else 0 end) over () + 1 -
sum(case when nextvalue > value + 10 then 1 else 0 end) over (order by value desc)
) as mark
from t
order by value;
Here is a db<>fiddle.
Calculate previous value, then calculate new_group_flag if value-prev_value >10, then calculate cumulative sum of new_group_flag to get group number (mark). Finally you can calculate group count using analytics function or group-by (in my example analytics count is used to show you the full dataset with all intermediate calculations). See comments in the code.
Demo:
with your_data as (--use your table instead of this
select stack(10, --the number of tuples generated
1 ,
2 ,
3 ,
20 ,
21 ,
22 ,
23 ,
40 ,
41 ,
42
) as value
)
select --4. Calculate group count, etc, etc
value, prev_value, new_group_flag, group_number,
count(*) over(partition by group_number) as group_count
from
(
select --3. Calculate cumulative sum of new group flag to get group number
value, prev_value, new_group_flag,
sum(new_group_flag) over(order by value rows between unbounded preceding and current row)+1 as group_number
from
(
select --2. calculate new_group_flag
value, prev_value, case when value-prev_value >10 then 1 else 0 end as new_group_flag
from
(
select --1 Calculate previous value
value, lag(value) over(order by value) prev_value
from your_data
)s
)s
)s
Result:
value prev_value new_group_flag group_number group_count
1 \N 0 1 3
2 1 0 1 3
3 2 0 1 3
20 3 1 2 4
21 20 0 2 4
22 21 0 2 4
23 22 0 2 4
40 23 1 3 3
41 40 0 3 3
42 41 0 3 3
This works for me
It needs "rows between unbounded preceding and current row" in my case.
select t.*,
sum(case when nextvalue > value + 10 then 1 else 0 end) over (order by value desc rows between unbounded preceding and current row) as mark
from t
order by value;
I have my data as follows:
Pagetype member_id created_at rownum
A 2 date 1
B 2 date 2
C 2 date 3
D 4 date 1
B 4 date 2
R 4 date 3
B 13 date 1
S 13 date 2
B 13 date 3
And I would like to add another column to it as follows:
Pagetype member_id created_at rownum DesiredRownum
A 2 date 1 -1
B 2 date 2 0
C 2 date 3 1
D 4 date 1 -1
B 4 date 2 0
R 4 date 3 1
B 13 date 1 0
S 13 date 2 1
B 13 date 3 2
I would like to assign the value 0 to this DesiredColumn whenever PageType is B for a given member_id. Any values of PageType before B for any member_id should be assigned negative values, and any values of PageType after B for any member_id should be asigned increasing positive values.
The query I used to get my data is as follows:
select pagetype,
member_id,
created_at,
row_number() over(partition by member_id order by created_at)
from table
order by member_id,
created_at
How do I add this new column to my data?
EDIT: Slight change. The PageType can repeat for any given user. For example, the PageType B repeats for member_id 13. In this case, we would want to calculate values wrt the first occurence of B.
After calculating the row numbers, you can get the value for "B" and use that for the calculation:
select t.*,
(seqnum -
max(case when pagetype = 'B' then seqnum end) over (partition by member_id)
) as b_diff
from (select pagetype, member_id, created_at,
row_number() over (partition by member_id order by created_at) as seqnum
from table
) t
order by member_id, created_at
How to get optimized query for this
date_one | date_two
------------------------
01.02.1999 | 31.05.2003
01.01.2004 | 01.01.2010
02.01.2010 | 10.10.2011
11.10.2011 | (null)
I need to get this
date_one | date_two | group
------------------------------------
01.02.1999 | 31.05.2003 | 1
01.01.2004 | 01.01.2010 | 2
02.01.2010 | 10.10.2011 | 2
11.10.2011 | (null) | 2
The group number is assigned as follows. Order the rows by date_one ascending. First row gets group = 1. Then for each row if date_one is the date immediately following date_two of the previous row, the group number stays the same as in the previous row, otherwise it increases by one.
You can do this using left join and a cumulative sum:
select t.*, sum(case when tprev.date_one is null then 1 else 0 end) over (order by t.date_one) as grp
from t left join
t tprev
on t.date_one = tprev.date_two + 1;
The idea is to find where the gaps begin (using the left join) and then do a cumulative sum of such beginnings to define the group.
If you want to be more inscrutable, you could write this as:
select t.*,
count(*) over (order by t.date_one) - count(tprev.date_one) over (order by t.date_one) as grp
from t left join
t tprev
on t.date_one = tprev.date_two + 1;
One way is using window function:
select
date_one,
date_two,
sum(x) over (order by date_one) grp
from (
select
t.*,
case when
lag(date_two) over (order by date_one) + 1 =
date_one then 0 else 1 end x
from t
);
It finds the date_two from the last row using analytic function lag and check if it in continuation with date_one from this row (in increasing order of date_one).
How it works:
lag(date_two) over (order by date_one)
(In the below explanation, when I say first, next, previous or last row, it's based on increasing order of date_one with null values at the end)
The above produces produces NULL for the first row as there is no row before it to get date_two from and previous row's date_two for the subsequent rows.
case when
lag(date_two)
over (order by date_one) + 1 = date_one then 0
else 1 end
Since, the lag produces NULL for the very first row (since NULL = anything expression always finally evaluates to false), output of case will be 1.
For further rows, similar check will be done to produce a new column x in the query output which has value 1 when the previous row's date_two is not in continuation with this row's date_one.
Then finally, we can do an incremental sum on x to find the required group values. See the value of x below for understanding:
SQL> with t (date_one,date_two) as (
2 select to_date('01.02.1999','dd.mm.yyyy'),to_date('31.05.2003','dd.mm.yyyy') from dual union
all
3 select to_date('01.01.2004','dd.mm.yyyy'),to_date('01.01.2010','dd.mm.yyyy') from dual union
all
4 select to_date('02.01.2010','dd.mm.yyyy'),to_date('10.10.2011','dd.mm.yyyy') from dual union
all
5 select to_date('11.10.2011','dd.mm.yyyy'),null from dual
6 )
7 select
8 date_one,
9 date_two,
10 x,
11 sum(x) over (order by date_one) grp
12 from (
13 select
14 t.*,
15 case when
16 lag(date_two) over (order by date_one) + 1 =
17 date_one then 0 else 1 end x
18 from t
19 );
DATE_ONE DATE_TWO X GRP
--------- --------- ---------- ----------
01-FEB-99 31-MAY-03 1 1
01-JAN-04 01-JAN-10 1 2
02-JAN-10 10-OCT-11 0 2
11-OCT-11 0 2
SQL>
I have a table which have Identity, RecordId, Type, Reading And IsDeleted columns. Identity is primary key that is auto increment, RecordId is integer that can have duplicate values, Type is a type of reading that can be either 'one' or 'average', Reading is integer that contains any integer value, and IsDeleted is bit that can be 0 or 1 i.e. false or true.
Now, I want the query that contains all the records of table in such a manner that if COUNT(Id) for each RecordId is greater than 2 then display all the records of that RecordId.
If COUNT(Id) == 2 for that specific RecordId and Reading value of both i.e. 'one' or 'average' type of the records are same then display only average record.
If COUNT(Id) ==1 then display only that record.
For example :
Id RecordId Type Reading IsDeleted
1 1 one 4 0
2 1 one 5 0
3 1 one 6 0
4 1 average 5 0
5 2 one 1 0
6 2 one 3 0
7 2 average 2 0
8 3 one 2 0
9 3 average 2 0
10 4 one 5 0
11 4 average 6 0
12 5 one 7 0
Ans result can be
Id RecordId Type Reading IsDeleted
1 1 one 4 0
2 1 one 5 0
3 1 one 6 0
4 1 average 5 0
5 2 one 1 0
6 2 one 3 0
7 2 average 2 0
9 3 average 2 0
10 4 one 5 0
11 4 average 6 0
12 5 one 7 0
In short I want to skip the 'one' type reading which have an average reading with same value and its count for 'one' type reading not more than one.
Check out this program
DECLARE #t TABLE(ID INT IDENTITY,RecordId INT,[Type] VARCHAR(10),Reading INT,IsDeleted BIT)
INSERT INTO #t VALUES
(1,'one',4,0),(1,'one',5,0),(1,'one',6,0),(1,'average',5,0),(2,'one',1,0),(2,'one',3,0),
(2,'average',2,0),(3,'one',2,0),(3,'average',2,0),(4,'one',5,0),(4,'average',6,0),(5,'one',7,0),
(6,'average',6,0),(6,'average',6,0),(7,'one',6,0),(7,'one',6,0)
--SELECT * FROM #t
;WITH GetAllRecordsCount AS
(
SELECT *,Cnt = COUNT(RecordId) OVER(PARTITION BY RecordId ORDER BY RecordId)
FROM #t
)
-- Condition 1 : When COUNT(RecordId) for each RecordId is greater than 2
-- then display all the records of that RecordId.
, GetRecordsWithCountMoreThan2 AS
(
SELECT * FROM GetAllRecordsCount WHERE Cnt > 2
)
-- Get all records where count = 2
, GetRecordsWithCountEquals2 AS
(
SELECT * FROM GetAllRecordsCount WHERE Cnt = 2
)
-- Condition 3 : When COUNT(RecordId) == 1 then display only that record.
, GetRecordsWithCountEquals1 AS
(
SELECT * FROM GetAllRecordsCount WHERE Cnt = 1
)
-- Condition 1: When COUNT(RecordId) > 2
SELECT * FROM GetRecordsWithCountMoreThan2 UNION ALL
-- Condition 2 : When COUNT(RecordId) == 2 for that specific RecordId and Reading value of
-- both i.e. 'one' or 'average' type of the records are same then display only
-- average record.
SELECT t1.* FROM GetRecordsWithCountEquals2 t1
JOIN (Select RecordId From GetRecordsWithCountEquals2 Where [Type] = ('one') )X
ON t1.RecordId = X.RecordId
AND t1.Type = 'average' UNION ALL
-- Condition 2: When COUNT(RecordId) = 1
SELECT * FROM GetRecordsWithCountEquals1
Result
ID RecordId Type Reading IsDeleted Cnt
1 1 one 4 0 4
2 1 one 5 0 4
3 1 one 6 0 4
4 1 average5 0 4
5 2 one 1 0 3
6 2 one 3 0 3
7 2 average2 0 3
9 3 average2 0 2
11 4 average6 0 2
12 5 one 7 0 1
;with a as
(
select Id,RecordId,Type,Reading,IsDeleted, count(*) over (partition by RecordId, Reading) cnt,
row_number() over (partition by RecordId, Reading order by Type, RecordId) rn
from table
)
select Id,RecordId,Type,Reading,IsDeleted
from a where cnt <> 2 or rn = 1
Assuming your table is named the_table, let's do this:
select main.*
from the_table as main
inner join (
select recordId, count(Id) as num, count(distinct Reading) as reading_num
from the_table
group by recordId
) as counter on counter.recordId=main.recordId
where num=1 or num>2 or reading_num=2 or main.type='average';
Untested, but it should be some variant of that.
EDIT TEST HERE ON FIDDLE
The short summary is that we want to join the table with an aggregated version of o=itself, then filter it based in the count criteria you mentioned (num=1, then show it; num=2, show just average record if reading numbers are the same otherwise show both; num>2, show all records).