I have a table mytable with the following structure and data (Oracle 11g)
Job_name job_execution_time(JET in seconds) Run_Date records_processed
A1 0 7/1/2013 0
A1 0 7/5/2013 0
A1 3 7/12/2013 5
A1 9 7/22/2013 14
A1 0 8/1/2013 0
A1 15 8/16/2013 20
A2 0 8/15/2013 0
A2 0 8/17/2013 0
A2 10 9/15/2013 25
A2 45 9/17/2013 70
I am trying to get the average(ignoring '0' values) of the (JET) column for each job for that specific month. Also I need to get a count of the non-zero values which I am using for my average calculation.
For example:
For job A1 for the month of July, the average of the JET column will be (9+3)/2 = 6 and the count of the nonzero values used for the calculation of this average would be 2.
I got the average value using the following code but have problem getting the count.
select job_name , to_char(Run_Date, 'Month') Mon ,
nvl(avg(nullif(job_execution_time,0)), 0) Average_secs
from mytable
group by job_name, to_char(Run_Date, 'Month')
How can I get the count of the nonzero values which are used for the calculation of every average? I tried the following for count but does not work.
count(nullif(job_execution_time, 0)) count_nonzeros
sum(CASE nvl(job_execution_time, 0) !=0 THEN 1 ELSE 0 END) AS "Count_NonZeros"
Thanks.
You can use SUM and CASE statement
select job_name , to_char(Run_Date, 'Month') Mon ,
nvl(avg(nullif(job_execution_time,0)), 0) Average_secs,
sum(case when job_execution_time !=0 then 1 else 0 end) counts
from table1 group by job_name, to_char(Run_Date, 'Month');
Related
I'm trying to create a query which allows to categorize the average percentage for specific data per month.
Here's how my dataset presents itself:
Date
Name
Group
Percent
2022-01-21
name1
gr1
5.2
2022-01-22
name1
gr1
6.1
2022-01-26
name1
gr1
4.9
2022-02-01
name1
gr1
3.2
2022-02-03
name1
gr1
8.1
2022-01-22
name2
gr1
36.1
2022-01-25
name2
gr1
32.1
2022-02-10
name2
gr1
35.8
...
...
...
...
And here's what I want to obtain with my query (based on what I showed of the table):
Month
<=25%
25<_<=50%
50<_<=75%
75<_<=100%
01
1
1
0
0
02
1
1
0
0
...
...
...
...
...
The result needs to:
Be ordered by month
Have the average use for each name counted and categorized
So far I know how to get the average of the Percent value per Name:
SELECT Name,
AVG(Percent)
from `table`
where Group = 'gr1'
group by Name
and how to count iterations of Percent in the categories created for the query:
SELECT EXTRACT(MONTH FROM Date) as Month,
COUNT(CASE WHEN Percent <= 25 AND Group = 'gr1' THEN Name END) `_25`,
COUNT(CASE WHEN Percent > 25 AND Percent <= 50 AND Group = 'gr1' THEN Name END) `_50`,
COUNT(CASE WHEN Percent > 50 AND Percent <= 75 AND Group = 'gr1' THEN Name END) `_75`,
COUNT(CASE WHEN Percent > 75 AND Percent <= 100 AND Group = 'gr1' THEN Name END) `_100`,
FROM `table`
GROUP BY Month
ORDER BY Month
but this counts all iterations of every name where I want the average of those values.
I've been struggling to figure out how to combine the two queries or to create a new one that answers my need.
I'm working with the BigQuery service from Google Cloud
This query produces the needed result, based on your example. So basically this combines your 2 queries using subquery, where the subquery is responsible to calculate AVG grouped by Name, Month and Group, and the outer query is for COUNT and "categorization"
SELECT
Month,
COUNT(CASE
WHEN avg <= 25 THEN Name
END) AS _25,
COUNT(CASE
WHEN avg > 25
AND avg <= 50 THEN Name
END) AS _50,
COUNT(CASE
WHEN avg > 50
AND avg <= 75 THEN Name
END) AS _75,
COUNT(CASE
WHEN avg > 75
AND avg <= 100 THEN Name
END) AS _100
FROM
(
SELECT
EXTRACT(MONTH from Date) AS Month,
Name,
AVG(Percent) AS avg
FROM
table1
GROUP BY Month, Name, Group
HAVING Group = 'gr1'
) AS namegr
GROUP BY Month
This is the result:
Month
_25
_50
_75
_100
1
1
1
0
0
2
1
1
0
0
See also Fiddle (BUT on MySql) - http://sqlfiddle.com/#!9/16c5882/9
You can use this query to Group By Month and each Name
SELECT CONCAT(EXTRACT(MONTH FROM Date), ', ', Name) AS DateAndName,
CASE
WHEN AVG(Percent) <= 25 THEN '1'
ELSE '0'
END AS '<=25%',
CASE
WHEN AVG(Percent) > 25 AND AVG(Percent) <= 50 THEN '1'
ELSE '0'
END AS '25<_<=50%',
CASE
WHEN AVG(Percent) > 50 AND AVG(Percent) <= 75 THEN '1'
ELSE '0'
END AS '50<_<=75%',
CASE
WHEN AVG(Percent) > 75 AND AVG(Percent) <= 100 THEN '1'
ELSE '0'
END AS '75<_<=100%'
from DataTable /*change to your table name*/
group by EXTRACT(MONTH FROM Date), Name
order by DateAndName
It gives the following result:
DateAndName
<=25%
25<_<=50%
50<_<=75%
75<_<=100%
1, name1
1
0
0
0
1, name2
0
1
0
0
2, name1
1
0
0
0
2, name2
0
1
0
0
I'm completely new to PostgreSQL. I have the following table called my_table:
a b c date
1 0 good 2019-05-02
0 1 good 2019-05-02
1 1 bad 2019-05-02
1 1 good 2019-05-02
1 0 bad 2019-05-01
0 1 good 2019-05-01
1 1 bad 2019-05-01
0 0 bad 2019-05-01
I want to calculate the percentage of 'good' from column c for each date. I know how to get the number of 'good':
SELECT COUNT(c), date FROM my_table WHERE c != 'bad' GROUP BY date;
That returns:
count date
3 2019-05-02
1 2019-05-01
My goal is to get this:
date perc_good
2019-05-02 25
2019-05-01 75
So I tried the following:
SELECT date,
(SELECT COUNT(c)
FROM my_table
WHERE c != 'bad'
GROUP BY date) / COUNT(c) * 100 as perc_good
FROM my_table
GROUP BY date;
And I get an error saying
more than one row returned by a subquery used as an expression.
I found this answer but not sure how to or if it applies to my case:
Calculating percentage in PostgreSql
How do I go about calculating the percentage for multiple rows?
avg() is convenient for this purpose:
select date,
avg( (c = 'good')::int ) * 100 as percent_good
from t
group by date
order by date;
How does this work? c = 'good' is a boolean expression. The ::int converts it to a number, with 1 for true and 0 for false. The average is then the average of a bunch of 1s and 0s -- and is the ratio of the true values.
For this case you need to use conditional AVG():
SELECT
date,
100 * avg(case when c = 'good' then 1 else 0 end) perc_good
FROM my_table
GROUP BY date;
See the demo.
You could use a conditional sum for get the good value and count for total
below an exaustive code sample
select date
, count(c) total
, sum(case when c='good' then 1 else 0 end) total_good
, sum(case when c='bad' then 1 else 0 end) total_bad
, (sum(case when c='good' then 1 else 0 end) / count(c))* 100 perc_good
, (sum(case when c='bad' then 1 else 0 end) / count(c))* 100 perc_bad
from my_table
group by date
and for your result
select date
, (sum(case when c='good' then 1 else 0 end) / count(c))* 100 perc_good
from my_table
group by date
or as suggested by a_horse_with_no_name using count(*) filter()
select date
, ((count(*) filter(where c='good'))/count(*))* 100 perc_good
from my_table
group by date
I am trying to calculate running total based on the value plus/minus in another column by Account and Date.
Example
Data
ID Account Date Operation Qty Running_Total
1 A 01/01/2018 plus 10 10
2 A 01/02/2018 plus 20 30
3 A 01/03/2018 minus 5 20
4 A 01/03/2018 minus 5 20
5 A 01/04/2018 plus 30 50
6 B 01/01/2018 plus 15 15
the total
Code:
select ID, Date, Operation, Total,
case when Operation = 'Use Table B' then TableB.RunningTotalQty
else
SUM( case when Operation = 'plus' then Qty
else case when Operation = 'minus' then -Qty end)
OVER (PARTITION BY Account ORDER BY Date) end
From TableA A left Join TableB B
on A.ID = B.ID ...
THIS ANSWERS THE ORIGINAL VERSION OF THE QUESTION.
The case goes inside the sum():
select ID, Date, Operation, Total,
sum(case when Operation = 'plus' then qty else - qty end) over
(partition by Account order by Date) as Running_Total
From TableA ;
This assumes only two operations. If you have more:
select ID, Date, Operation, Total,
sum(case when Operation = 'plus' then qty
then Operation = 'minus' then - qty
else 0
end) over
(partition by Account order by Date) as Running_Total
From TableA ;
Background Info
I have a large table 400M+ rows that changes daily (one days data drops out an a new days data drops in) The table is partitioned on a 'day' field so there are 31 paritions.
Each row in the table has data similar to this:
ID, Postcode, DeliveryPoint, Quantity, Day, Month
1 SN1 1BG A1 6 29 1
2 SN1 1BG A1 1 28 1
3 SN1 1BG A2 2 27 1
4 SN1 1BG A1 3 28 1
5 SN2 1AQ B1 1 29 12
6 SN1 1BG A1 2 26 12
I need to pull out 7 days of data in the format:
Postcode, Deliverypoint, 7dayAverage, Day1,day2,Day3,Day4,Day5,Day6,Day7
SN1 1BG A1 2 0 1 2 1 3 4 0
I can easily extract the data for the 7 day period but need to create a columnar version as shown above.
I have something like this:
select postcode,deliverypoint,
sum (case day when 23 then quantity else 0 end) as day1,
sum (case day when 24 then quantity else 0 end) as day2,
sum(case day when 25 then quantity else 0 end) as day3,
sum(case day when 26 then quantity else 0 end) as day4,
sum(case day when 27 then quantity else 0 end) as day5,
sum(case day when 28 then quantity else 0 end) as day6,
sum(case day when 29 then quantity else 0 end) as day7,
sum(quantity)*1.0/#daysinweek as wkavg
into #allweekdp
from maintable dp with (nolock)
where day in (select day from #days)
group by postcode,deliverypoint
where #days has the day numbers in the 7 day period.
But as you can see, I've hard-coded the day numbers into the query, I want to get them out of my temporary table #days but can't see a way of doing it (an array would be perfect here)
Or a I going about this in completely the wrong way ?
Kind Regards
Steve
If I understand correctly, what I would do is:
Convert the day and month columns into datetime values,
Get the first day of the week and day of the weekday (1-7) for each date, and
Pivot the data and group by the first day of the week
see here: sqlfiddle
As utexaspunk suggested, Pivot might be the way to go. I've never been comfortable with pivot and have preferred to pivot it manually so I control how everything looks, so I'm using a similar solution to how you did your script to solve the issue. No idea how the performance between my way and utexaspunk's will compare.
Declare #Min_Day Integer = Select MIN(day) as Min_Day From #days;
With Day_Coding_CTE as (
Select Distinct day
, day - #Min_Day + 1 as Day_Label
From #days
)
, Non_Columnar_CTE as (
Select dp.postcode
, dp.deliverypoint
, d.day
, c.Day_Label
, SUM(quantity) as Quantity
From maintable dp with (nolock)
Left Outer Join #days d
on dp.day = d.day --It also seems like you'll need more criteria here, but you'll have to figure out what those should be
Left Outer Join Day_Coding_CTE c
on d.day = c.day
)
Select postcode
, deliverypoint
, SUM(Case
When Day_Label = 1
Then Quantity
Else 0
End) as Day1
, SUM(Case
When Day_Label = 2
Then Quantity
Else 0
End) as Day2
, SUM(Case
When Day_Label = 3
Then Quantity
Else 0
End) as Day3
, SUM(Case
When Day_Label = 4
Then Quantity
Else 0
End) as Day4
, SUM(Case
When Day_Label = 5
Then Quantity
Else 0
End) as Day5
, SUM(Case
When Day_Label = 6
Then Quantity
Else 0
End) as Day6
, SUM(Case
When Day_Label = 7
Then Quantity
Else 0
End) as Day7
, SUM(Quantity)/#daysinweek as wkavg
From Non_Columnar_CTE
Group by postcode
deliverypoint
I'm sorry if the title wasn't too clear, but the following explanation will be more accurate.
I have the following view:
DATE USER CONDITION
20140101 1 A
20140101 2 B
20140101 3 C
20140108 1 C
20140108 3 B
20140108 2 C
What I need to do is present how many users where in all conditions this week and 7 days before today.
Output should be like this:
Condition Today Last_Week (Today-7)
A 0 1
B 1 1
C 2 1
How can I do this in Oracle? I will need to do this for 4 weeks so itll be Today-7,14-21.
I've tried this with group by but I get the "week2" as rows. Then I've tried something like Select conditions, (select count(users) from MyView where DATE='Today') FROM MyView(looking at something thats actually working) but it doesnt work for me.
Achieved this with a little modification of the accepted answer:
select condition,
count(case when to_date(xdate) = to_date(sysdate) then 1 end) to_day,
count(case when to_date(xdate) = to_date(sysdate-7) then 1 end) last_7_days
from my_table
group by condition
select condition, count(case when to_date(xdate) = to_date(sysdate) then 1 end) to_day,
count(case when to_date(xdate) < to_date(sysdate) then 1 end) last_7_days
from my_table
where to_date(xdate) >= to_date(sysdate) - 7
group by condition
select condition
, sum
( case
when date between trunc(sysdate) - 7 and trunc(sysdate) - 1
then 1
else 0
end
)
last_week
, sum
( case
when date between trunc(sysdate) and trunc(sysdate + 1)
then 1
else 0
end
)
this_week
from table
group
by condition
By using the conditional count (as a sum) and grouping on condition you can filter out all desired dates. Note that using trunc will cause to use the begin of the day.