I have an index where some data's has duplicate, all fields are similar except for latitude,longitude and id (field id is not realy ID, just generated row_number() OVER () AS id).
it's example:
mysql> select id,vacancy_id,prof_area_ids,latitude,longitude from jobVacancy;
+------+------------+---------------+----------+-----------+
| id | vacancy_id | prof_area_ids | latitude | longitude |
+------+------------+---------------+----------+-----------+
| 1 | 917 | 11,199,202 | 0.973178 | 0.743566 |
| 2 | 916 | 17,283,288 | 0.973178 | 0.743566 |
| 3 | 915 | 17,288 | 0.973178 | 0.743566 |
| 4 | 914 | 30,482 | 0.973178 | 0.743566 |
| 5 | 919 | 15,243 | 0.825153 | 0.692837 |
| 6 | 919 | 15,243 | 0.825162 | 0.692828 |
| 7 | 918 | 8,154 | 0.825153 | 0.692837 |
| 8 | 918 | 8,154 | 0.825162 | 0.692828 |
| 9 | 920 | 17,283,288 | 0.958914 | 1.282161 |
| 10 | 920 | 17,283,288 | 0.958915 | 1.282215 |
| 11 | 924 | 12,208 | 0.97333 | 0.658246 |
| 12 | 924 | 12,208 | 0.973336 | 0.658237 |
| 13 | 923 | 21,365 | 0.97333 | 0.658246 |
| 14 | 923 | 21,365 | 0.973336 | 0.658237 |
| 15 | 922 | 20,359 | 0.97333 | 0.658246 |
| 16 | 922 | 20,359 | 0.973336 | 0.658237 |
| 17 | 921 | 19,346 | 0.97333 | 0.658246 |
| 18 | 921 | 19,346 | 0.973336 | 0.658237 |
| 19 | 926 | 12,17,208,292 | 0.88396 | 2.389868 |
| 20 | 925 | 12,208 | 0.88396 | 2.389868 |
+------+------------+---------------+----------+-----------+
20 rows in set (0.00 sec)
Now I want to group data by vacancy_id
mysql> select id,vacancy_id,prof_area_ids,latitude,longitude from jobVacancy group by vacancy_id;
+------+------------+---------------+----------+-----------+
| id | vacancy_id | prof_area_ids | latitude | longitude |
+------+------------+---------------+----------+-----------+
| 1 | 917 | 11,199,202 | 0.973178 | 0.743566 |
| 2 | 916 | 17,283,288 | 0.973178 | 0.743566 |
| 3 | 915 | 17,288 | 0.973178 | 0.743566 |
| 4 | 914 | 30,482 | 0.973178 | 0.743566 |
| 5 | 919 | 15,243 | 0.825153 | 0.692837 |
| 7 | 918 | 8,154 | 0.825153 | 0.692837 |
| 9 | 920 | 17,283,288 | 0.958914 | 1.282161 |
| 11 | 924 | 12,208 | 0.97333 | 0.658246 |
| 13 | 923 | 21,365 | 0.97333 | 0.658246 |
| 15 | 922 | 20,359 | 0.97333 | 0.658246 |
| 17 | 921 | 19,346 | 0.97333 | 0.658246 |
| 19 | 926 | 12,17,208,292 | 0.88396 | 2.389868 |
| 20 | 925 | 12,208 | 0.88396 | 2.389868 |
| 21 | 961 | 4,105 | 0.959217 | 1.280721 |
| 23 | 960 | 8,155 | 0.959217 | 1.280721 |
| 25 | 959 | 12,208 | 0.959217 | 1.280721 |
| 27 | 928 | 1,60 | 0.963734 | 1.070297 |
| 29 | 927 | 32,513 | 0.963734 | 1.070297 |
| 31 | 929 | 6,140 | 0.786553 | 0.678649 |
| 33 | 932 | 1,40,46 | 0.824627 | 0.694182 |
+------+------------+---------------+----------+-----------+
20 rows in set (0.00 sec)
Result is awesome! But problem begins when I want to get all grouped data with faceted
mysql> select id,vacancy_id,prof_area_ids,latitude,longitude from jobVacancy where prof_area_ids=199 group by vacancy_id facet prof_area_ids;
+------+------------+-----------------+----------+-----------+
| id | vacancy_id | prof_area_ids | latitude | longitude |
+------+------------+-----------------+----------+-----------+
| 1 | 917 | 11,199,202 | 0.973178 | 0.743566 |
| 191 | 1004 | 11,196,199 | 0.925335 | 2.768874 |
| 313 | 1072 | 1,11,60,197,199 | 0.963968 | 1.070624 |
| 318 | 1136 | 11,196,199 | 0.96071 | 1.448998 |
| 374 | 1097 | 11,199 | 0.785255 | 0.678504 |
+------+------------+-----------------+----------+-----------+
5 rows in set (0.00 sec)
+---------------+----------+
| prof_area_ids | count(*) |
+---------------+----------+
| 202 | 1 |
| 199 | 12 |
| 11 | 12 |
| 196 | 5 |
| 197 | 3 |
| 60 | 3 |
| 1 | 3 |
+---------------+----------+
7 rows in set (0.02 sec)
Faceted result is incorrect. Because in fact data's count where prof_area_ids=199 must be 5 and not 12. So how I can group field for faceted?
Additionaly
I fount here http://sphinxsearch.com/blog/2013/06/21/faceted-search-with-sphinx/ but just written "If you have a MVA facet, you need to use the GROUPBY() function which returns the actual value on which the grouping was made." and without examle.
mysql> select id,vacancy_id,prof_area_ids,latitude,longitude,GROUPBY() as selected,COUNT(*) from jobVacancy where prof_area_ids=199 group by vacancy_id facet prof_area_ids;
+------+------------+-----------------+----------+-----------+----------+----------+
| id | vacancy_id | prof_area_ids | latitude | longitude | selected | count(*) |
+------+------------+-----------------+----------+-----------+----------+----------+
| 1 | 917 | 11,199,202 | 0.973178 | 0.743566 | 917 | 1 |
| 191 | 1004 | 11,196,199 | 0.925335 | 2.768874 | 1004 | 2 |
| 313 | 1072 | 1,11,60,197,199 | 0.963968 | 1.070624 | 1072 | 3 |
| 318 | 1136 | 11,196,199 | 0.96071 | 1.448998 | 1136 | 3 |
| 374 | 1097 | 11,199 | 0.785255 | 0.678504 | 1097 | 3 |
+------+------------+-----------------+----------+-----------+----------+----------+
5 rows in set (0.00 sec)
+---------------+----------+
| prof_area_ids | count(*) |
+---------------+----------+
| 202 | 1 |
| 199 | 12 |
| 11 | 12 |
| 196 | 5 |
| 197 | 3 |
| 60 | 3 |
| 1 | 3 |
+---------------+----------+
7 rows in set (0.02 sec)
Also faceted result is wrong.
Seems, wanting effectively COUNT(DISTINCT vacancy_id) on the FACET rather than the default COUNT(*), but alas it turns out
... FACET prof_area_ids,COUNT(DISTINCT vacancy_id) AS vacancies BY prof_area_ids
doesnt work. The bit before BY only supports attributes, not custom functions.
... will just have to write it out the long way, with full queries...
select id,vacancy_id,prof_area_ids,latitude,longitude from jobVacancy
where prof_area_ids=199 group by vacancy_id;
SELECT GROUPBY() AS prof_area_id, COUNT(DISTINCT vacancy_id) FROM jobVacancy
WHERE prof_area_ids=199 GROUP BY prof_area_id;
Same results, just slightly more verbose. ie rather than using FACET shorthand, write it
out in full, as multiple seperate queries.
Faceted result is incorrect. Because in fact data's count where prof_area_ids=199 must be 5 and not 12. So how I can group field for faceted?
It looks like you misunderstand how FACET works. It seems to me, that you think it takes as a base the main query's result, but it actually just does another grouping. E.g. here:
mysql> select g, t from idx_mva where t = 11 group by g facet t;
+------+----------+
| g | t |
+------+----------+
| 1 | 11,12 |
| 2 | 11,13,15 |
| 3 | 9,11 |
| 5 | 11,12,15 |
+------+----------+
4 rows in set (0.00 sec)
+------+----------+
| t | count(*) |
+------+----------+
| 12 | 2 |
| 11 | 6 |
| 15 | 4 |
| 13 | 1 |
| 9 | 1 |
| 3 | 1 |
+------+----------+
6 rows in set (0.00 sec)
for t=11 you can see that as in your case it's found 3 times in the 1st query's result, but the count for that is 6 in the FACET's query result. This is because it actually occurs 6 times in the index:
mysql> select * from idx_mva where t = 11;
+------+------+----------+
| id | g | t |
+------+------+----------+
| 2 | 1 | 11,12 |
| 3 | 1 | 11,15 |
| 3 | 2 | 11,13,15 |
| 6 | 3 | 9,11 |
| 8 | 5 | 11,12,15 |
| 11 | 2 | 3,11,15 |
+------+------+----------+
6 rows in set, 1 warning (0.00 sec)
and it happens 3 times in the 1st case only because the t's value is returned only once for each of the groups. You can use group_concat() to see more values from the same group:
mysql> select g, group_concat(to_string(t)) from idx_mva where t = 11 group by g facet t;
+------+----------------------------+
| g | group_concat(to_string(t)) |
+------+----------------------------+
| 1 | 11,12,11,15 |
| 2 | 11,13,15,3,11,15 |
| 3 | 9,11 |
| 5 | 11,12,15 |
+------+----------------------------+
4 rows in set (0.00 sec)
+------+----------+
| t | count(*) |
+------+----------+
| 12 | 2 |
| 11 | 6 |
| 15 | 4 |
| 13 | 1 |
| 9 | 1 |
| 3 | 1 |
+------+----------+
6 rows in set (0.00 sec)
If you want to learn more about faceting here's an interactive course about that - https://play.manticoresearch.com/faceting/
Related
I have a DB with a field of timestamp,
I want to partition it for every 2 seconds (I know how to do it for 1 minute and one second)
this is an example of the DB:
create table data_t(id integer, time_t timestamp without time zone, data_t integer );
insert into data_t(id,time_t,data_t) values(1,'1999-01-08 04:05:06',248),
(2,'1999-01-08 04:05:06.03',45),
(3,'1999-01-08 04:05:06.035',98),
(4,'1999-01-08 04:05:06.9',57),
(5,'1999-01-08 04:05:07',86),
(6,'1999-01-08 04:05:08',84),
(7,'1999-01-08 04:05:08.5',832),
(8,'1999-01-08 04:05:08.7',86),
(9,'1999-01-08 04:05:08.9',863),
(10,'1999-01-08 04:05:9',866),
(11,'1999-01-08 04:05:10',862),
(12,'1999-01-08 04:05:10.5',863),
(13,'1999-01-08 04:05:10.55',826),
(14,'1999-01-08 04:05:11',816),
(15,'1999-01-08 04:05:11.7',186),
(16,'1999-01-08 04:05:12',862),
(17,'1999-01-08 04:05:12.5',826)
;
with t as (
select id,
time_t,
date_trunc('second', data_t.time_t) as time_t_1,
data_t
from data_t
), t1 as(
select *,
extract(hour from time_t_1) as h,
extract(minute from time_t_1) as m,
extract(second from time_t_1) as s
from t ) select *,
row_number() over(partition by h,m,s order by time_t_1) as t_sequence
from t1;
the output of this is:
| id | time_t | time_t_1 | data_t | h | m | s | t_sequence |
|----|--------------------------|----------------------|--------|---|---|----|------------|
| 1 | 1999-01-08T04:05:06Z | 1999-01-08T04:05:06Z | 248 | 4 | 5 | 6 | 1 |
| 2 | 1999-01-08T04:05:06.03Z | 1999-01-08T04:05:06Z | 45 | 4 | 5 | 6 | 2 |
| 3 | 1999-01-08T04:05:06.035Z | 1999-01-08T04:05:06Z | 98 | 4 | 5 | 6 | 3 |
| 4 | 1999-01-08T04:05:06.9Z | 1999-01-08T04:05:06Z | 57 | 4 | 5 | 6 | 4 |
| 5 | 1999-01-08T04:05:07Z | 1999-01-08T04:05:07Z | 86 | 4 | 5 | 7 | 1 |
| 6 | 1999-01-08T04:05:08Z | 1999-01-08T04:05:08Z | 84 | 4 | 5 | 8 | 1 |
| 7 | 1999-01-08T04:05:08.5Z | 1999-01-08T04:05:08Z | 832 | 4 | 5 | 8 | 2 |
| 8 | 1999-01-08T04:05:08.7Z | 1999-01-08T04:05:08Z | 86 | 4 | 5 | 8 | 3 |
| 9 | 1999-01-08T04:05:08.9Z | 1999-01-08T04:05:08Z | 863 | 4 | 5 | 8 | 4 |
| 10 | 1999-01-08T04:05:09Z | 1999-01-08T04:05:09Z | 866 | 4 | 5 | 9 | 1 |
| 11 | 1999-01-08T04:05:10Z | 1999-01-08T04:05:10Z | 862 | 4 | 5 | 10 | 1 |
| 12 | 1999-01-08T04:05:10.5Z | 1999-01-08T04:05:10Z | 863 | 4 | 5 | 10 | 2 |
| 13 | 1999-01-08T04:05:10.55Z | 1999-01-08T04:05:10Z | 826 | 4 | 5 | 10 | 3 |
| 14 | 1999-01-08T04:05:11Z | 1999-01-08T04:05:11Z | 816 | 4 | 5 | 11 | 1 |
| 15 | 1999-01-08T04:05:11.7Z | 1999-01-08T04:05:11Z | 186 | 4 | 5 | 11 | 2 |
| 16 | 1999-01-08T04:05:12Z | 1999-01-08T04:05:12Z | 862 | 4 | 5 | 12 | 1 |
| 17 | 1999-01-08T04:05:12.5Z | 1999-01-08T04:05:12Z | 826 | 4 | 5 | 12 | 2 |
as you can see the t_sequence start over every second but I want it to start over every 2 seconds,
is there a way to do it?
link for SQL fiddle with all the data
I have a table where field with multiple value by comma:
+------+---------------+
| id | education_ids |
+------+---------------+
| 3 | 7,5 |
| 4 | 7,3 |
| 5 | 1,5 |
| 8 | 3 |
| 9 | 5,7 |
| 11 | 9 |
...
+------+---------------+
when I trying use faceted search:
select id,education_ids from jobResume facet education_ids;
I'm getting this response:
+---------------+----------+
| education_ids | count(*) |
+---------------+----------+
| 7,5 | 3558 |
| 7,3 | 3655 |
| 1,5 | 3686 |
| 3 | 31909 |
| 5,7 | 3490 |
| 9 | 31743 |
| 9,6 | 3535 |
| 8,2 | 3547 |
| 6,2,7 | 291 |
| 7,8,1 | 291 |
| 1,2 | 3637 |
| 7 | 31986 |
| 5,9,7 | 408 |
| 1,1,5 | 365 |
| 5 | 31768 |
| 3,8,3,7 | 32 |
| 3,7,6 | 431 |
| 2 | 31617 |
| 5,5 | 3614 |
| 9,9,2,2 | 6 |
+---------------+----------+
but that's not what I wanted to see. I would like to where each value had its own count, for example like here:
+---------------+----------+
| education_ids | count(*) |
+---------------+----------+
| 10 | 961 |
| 11 | 1653 |
| 12 | 1998 |
| 13 | 2090 |
| 14 | 1058 |
| 15 | 347 |
...
+---------------+----------+
can I get such a result with sphinx?
Make sure you use an MVA, not a string attribute:
index rt
{
type = rt
rt_field = f
rt_attr_multi = education_ids
path = rt
}
snikolaev#dev:$ mysql -P9306 -h0
Welcome to the MySQL monitor. Commands end with ; or \g.
Your MySQL connection id is 1
Server version: 3.2.2 62ea5ff#191220 release
Copyright (c) 2000, 2019, Oracle and/or its affiliates. All rights reserved.
Oracle is a registered trademark of Oracle Corporation and/or its
affiliates. Other names may be trademarks of their respective
owners.
Type 'help;' or '\h' for help. Type '\c' to clear the current input statement.
mysql> insert into rt(education_ids) values((7,5)), ((7,3)), ((7,1)), ((5,1)), ((5,3));
Query OK, 5 rows affected (0.00 sec)
mysql> select * from rt facet education_ids;
+---------------------+---------------+
| id | education_ids |
+---------------------+---------------+
| 2810610458032078849 | 5,7 |
| 2810610458032078850 | 3,7 |
| 2810610458032078851 | 1,7 |
| 2810610458032078852 | 1,5 |
| 2810610458032078853 | 3,5 |
+---------------------+---------------+
5 rows in set (0.00 sec)
+---------------+----------+
| education_ids | count(*) |
+---------------+----------+
| 7 | 3 |
| 5 | 3 |
| 3 | 2 |
| 1 | 2 |
+---------------+----------+
4 rows in set (0.00 sec)
BTW here's an interactive course about faceting in Sphinx / Manticore in case you want to learn more about that - https://play.manticoresearch.com/faceting/
I'm trying to generate a serial number based on a few conditions.
My dataset:
+--------+------------+------------+---------+--------+
| Client | Start_Date | End_date | Product | Ser_No |
+--------+------------+------------+---------+--------+
| 44 | 22-01-2018 | 31-12-2018 | A | |
+--------+------------+------------+---------+--------+
| 44 | 24-02-2018 | 01-01-2019 | B | |
+--------+------------+------------+---------+--------+
| 44 | 12-03-2018 | 01-01-2019 | C | |
+--------+------------+------------+---------+--------+
| 100 | 24-01-2018 | 30-11-2018 | A | |
+--------+------------+------------+---------+--------+
| 100 | 26-01-2018 | 15-12-2018 | D | |
+--------+------------+------------+---------+--------+
| 100 | 26-01-2018 | 01-02-2019 | E | |
+--------+------------+------------+---------+--------+
| 100 | 01-03-2018 | 31-01-2019 | F | |
+--------+------------+------------+---------+--------+
What I did to configure my serial number:
RANK() OVER(PARTITION BY Client ORDER BY Client, Start_date ASC)
So now it generates a serial number for my which looks like this:
+--------+------------+------------+---------+--------+
| Client | Start_Date | End_date | Product | Ser_No |
+--------+------------+------------+---------+--------+
| 44 | 22-01-2018 | 31-12-2018 | A | 1 |
+--------+------------+------------+---------+--------+
| 44 | 24-02-2018 | 01-01-2019 | B | 2 |
+--------+------------+------------+---------+--------+
| 44 | 12-03-2018 | 01-01-2019 | C | 3 |
+--------+------------+------------+---------+--------+
| 100 | 24-01-2018 | 30-11-2018 | A | 1 |
+--------+------------+------------+---------+--------+
| 100 | 26-01-2018 | 15-12-2018 | D | 2 |
+--------+------------+------------+---------+--------+
| 100 | 26-01-2018 | 01-02-2019 | E | 2 |
+--------+------------+------------+---------+--------+
| 100 | 01-03-2018 | 31-01-2019 | F | 4 |
+--------+------------+------------+---------+--------+
What goes wrong for my analysis is the last line, it generates the serial number. What it has to be is 3.
Can anayone help me to generate it in this order?
Thanks in advance!
Extra
In addition to my question from yesterday, there is something extra that I need to do. Because the Ser_No has to be the same when my Start_Date is the same, but the Ser_No has also be the same when my folowing records is the same product (also when it has a different Start_Date)
So what I I expect and what I get right now:
+--------+------------+------------+---------+--------+------------+
| Client | Start_Date | End_date | Product | Ser_No | Ser_No New |
+--------+------------+------------+---------+--------+------------+
| 44 | 22-01-2018 | 31-12-2018 | A | 1 | 1 |
+--------+------------+------------+---------+--------+------------+
| 44 | 24-02-2018 | 01-01-2019 | B | 2 | 2 |
+--------+------------+------------+---------+--------+------------+
| 44 | 12-03-2018 | 01-01-2019 | C | 2 | 2 |
+--------+------------+------------+---------+--------+------------+
| 100 | 24-01-2018 | 30-11-2018 | A | 1 | 1 |
+--------+------------+------------+---------+--------+------------+
| 100 | 26-01-2018 | 15-12-2018 | D | 2 | 2 |
+--------+------------+------------+---------+--------+------------+
| 100 | 26-01-2018 | 01-02-2019 | E | 2 | 2 |
+--------+------------+------------+---------+--------+------------+
| 100 | 01-03-2018 | 31-01-2019 | F | 3 | 3 |
+--------+------------+------------+---------+--------+------------+
| 100 | 11-04-2018 | 31-03-2019 | F | 4 | 3 |
+--------+------------+------------+---------+--------+------------+
| 100 | 20-04-2018 | 31-01-2019 | G | 5 | 4 |
+--------+------------+------------+---------+--------+------------+
| 100 | 21-04-2018 | 31-01-2019 | A | 6 | 5 |
+--------+------------+------------+---------+--------+------------+
| 100 | 21-04-2018 | 31-01-2019 | B | 6 | 5 |
+--------+------------+------------+---------+--------+------------+
| 100 | 01-05-2018 | 31-01-2019 | B | 7 | 5 |
+--------+------------+------------+---------+--------+------------+
Any idea on how to achieve this, because I won't get it
You need to use DENSE_RANK instead:
This function returns the rank of each row within a result set partition, with no gaps in the ranking values.
DENSE_RANK() OVER(PARTITION BY Client ORDER BY Start_date) AS Ser_no
Additionaly the Client in ORDER BY has no effect because it has the same value per partition.
Suppose such a spreadsheet in org table
|------------+-------+------------+--------+--------+------------|
| Date | Items | Unit Price | Amount | Amount | Categories |
|------------+-------+------------+--------+--------+------------|
| 2019/09/17 | A | 2.64 | 1 | 2.64 | materials |
| | B | 52.67 | 2 | 105.34 | diagnosis |
| | C | 3.08 | 1 | 3.08 | materials |
| | D | 3.85 | 2 | 7.7 | materials |
| | E | 33.66 | 2 | 67.32 | materials |
| | F | 40 | 1 | 40 | treatments |
| | G | 16.5 | 1 | 16.5 | materials |
| | H | 4 | 3 | 12 | treatments |
| | I | 40 | 1 | 40 | bed |
| x | M | 6 | 13 | 78 | treatments |
|------------+-------+------------+--------+--------+------------|
#+TBLFM: $5=$3*$4
I want to sum up the material fees.
Is it possible to calculate it by grouping like vsum(where Categories == materials)?
One way to do this with an elisp expression will be:
|------------+-------+------------+--------+--------+------------|
| Date | Items | Unit Price | Amount | Amount | Categories |
|------------+-------+------------+--------+--------+------------|
| 2019/09/17 | A | 2.64 | 1 | 2.64 | materials |
| | B | 52.67 | 2 | 105.34 | diagnosis |
| | C | 3.08 | 1 | 3.08 | materials |
| | D | 3.85 | 2 | 7.7 | materials |
| | E | 33.66 | 2 | 67.32 | materials |
| | F | 40 | 1 | 40 | treatments |
| | G | 16.5 | 1 | 16.5 | materials |
| | H | 4 | 3 | 12 | treatments |
| | I | 40 | 1 | 40 | bed |
| x | M | 6 | 13 | 78 | treatments |
|------------+-------+------------+--------+--------+------------|
| TOTAL: | | | | 97.24 | |
|------------+-------+------------+--------+--------+------------|
#+TBLFM: $5=$3*$4
#+TBLFM: #12$5='(apply #'+ (cl-mapcar (lambda (num category) (if (eq category 'materials) num 0)) '(#II$5..#III$5) '(#II$6..#III$6)));L
cl-mapcar applies + to cell #12$5 by comparing the list which is column 6 to symbol'materials.
This solution and a `calc solution in emacsSE
I looked through similar questions like this one, but they seem to have a definite number of columns. I would like to input a table that I do not know the number of columns.
Question:
How to calculate aggregate functions (e.g. avg() or sum() ) for each row across several columns if number of columns is not known in advance?
I have put the input table panel_stats_rnd csv and a DLL to create it here.
I would like to calculate for each row the rnd_avg_parcelcount as average of all columns c_1_avg_parcelcount, c_2_avg_parcelcount, ... where I can have input tables with any number (say 100) columns of _avg_parcelcount. And for columns rnd_sum_parcelcount I would like to calculate sum() of all columns that start with c_ and end with _sum_parcelcount.
The table looks like this:
SELECT * FROM panel_stats_rnd;
gid | d | dist_from | dist_to | distlabel | rnd_avg_parcelcount | rnd_sum_parcelcount | rnd_avg_callcount | rnd_sum_callcount | rnd_avg_perccalled | called_avg_parcelcount | called_sum_parcelcount | called_avg_callcount | called_sum_callcount | called_avg_perccalled | c_1_avg_parcelcount | c_1_sum_parcelcount | c_1_avg_callcount | c_1_sum_callcount | c_1_avg_perccalled | c_2_avg_parcelcount | c_2_sum_parcelcount | c_2_avg_callcount | c_2_sum_callcount | c_2_avg_perccalled
-----+----+-----------+---------+-----------+---------------------+---------------------+-------------------+-------------------+--------------------+------------------------+------------------------+----------------------+----------------------+-----------------------+---------------------+---------------------+-------------------+-------------------+----------------------+---------------------+---------------------+-------------------+-------------------+----------------------
1 | 0 | 0 | 100 | 0-100 | | | | | | 119045 | 119045 | 119045 | 23 | 0.000193204250493511 | 119045 | 119045 | 119045 | 16 | 0.000134402956865051 | 119045 | 119045 | 119045 | 16 | 0.000134402956865051
2 | 1 | 100 | 200 | 100-200 | | | | | | 163140 | 163140 | 163140 | 22 | 0.000134853500061297 | 163140 | 163140 | 163140 | 17 | 0.000104204977320093 | 163140 | 163140 | 163140 | 18 | 0.000110334681868334
3 | 2 | 200 | 300 | 200-300 | | | | | | 135934 | 135934 | 135934 | 10 | 7.3565112481057e-05 | 135934 | 135934 | 135934 | 18 | 0.000132417202465903 | 135934 | 135934 | 135934 | 15 | 0.000110347668721585
4 | 3 | 300 | 400 | 300-400 | | | | | | 116874 | 116874 | 116874 | 13 | 0.000111230898232284 | 116874 | 116874 | 116874 | 11 | 9.41184523503944e-05 | 116874 | 116874 | 116874 | 18 | 0.000154012012937009
5 | 4 | 400 | 500 | 400-500 | | | | | | 93216 | 93216 | 93216 | 12 | 0.000128733264675592 | 93216 | 93216 | 93216 | 10 | 0.000107277720562993 | 93216 | 93216 | 93216 | 12 | 0.000128733264675592
6 | 5 | 500 | 600 | 500-600 | | | | | | 69992 | 69992 | 69992 | 7 | 0.0001000114298777 | 69992 | 69992 | 69992 | 10 | 0.000142873471253858 | 69992 | 69992 | 69992 | 7 | 0.0001000114298777
7 | 6 | 600 | 700 | 600-700 | | | | | | 50816 | 50816 | 50816 | 10 | 0.000196788413098237 | 50816 | 50816 | 50816 | 6 | 0.000118073047858942 | 50816 | 50816 | 50816 | 0 | 0
8 | 7 | 700 | 800 | 700-800 | | | | | | 34814 | 34814 | 34814 | 0 | 0 | 34814 | 34814 | 34814 | 6 | 0.000172344459125639 | 34814 | 34814 | 34814 | 4 | 0.000114896306083759
9 | 8 | 800 | 900 | 800-900 | | | | | | 23023 | 23023 | 23023 | 1 | 4.34348260435217e-05 | 23023 | 23023 | 23023 | 4 | 0.000173739304174087 | 23023 | 23023 | 23023 | 1 | 4.34348260435217e-05
10 | 9 | 900 | 1000 | 900-1000 | | | | | | 14215 | 14215 | 14215 | 1 | 7.03482237073514e-05 | 14215 | 14215 | 14215 | 1 | 7.03482237073514e-05 | 14215 | 14215 | 14215 | 5 | 0.000351741118536757
11 | 10 | 1000 | 5000 | 1000-5000 | | | | | | 23527 | 23527 | 23527 | 0 | 0 | 23527 | 23527 | 23527 | 0 | 0 | 23527 | 23527 | 23527 | 3 | 0.000127513070089684
(11 rows)
I tried the following for 2 columns (works but I'd rather not write it 5 times for 100 columns, besides the number of columns has to be a parameter):
SELECT d,c_1_avg_parcelcount,c_2_avg_parcelcount,
(SELECT avg(c) FROM (VALUES (c_1_avg_parcelcount) , (c_2_avg_parcelcount) ) T (c)) AS Avg_,
(SELECT sum(c) FROM (VALUES (c_1_avg_parcelcount) , (c_2_avg_parcelcount) ) T (c)) AS sum_
FROM panel_stats_rnd;
I also tried the following but doesn't work.
WITH cols AS (
select value(column_name) from information_schema.columns
where table_name = 'panel_stats_rnd'
AND column_name SIMILAR TO 'c_%avg_parcelcount'
AND column_name != 'called_avg_parcelcount'
)
SELECT *, (SELECT avg(Col) FROM cols V(Col) ) AS col_average
FROM panel_stats_rnd;
I am almost there but something is missing...
select
*,
(select avg(v::numeric)
from json_each_text(row_to_json(panel_stats_rnd.*)) as j(k,v)
where k like 'c\_%\_avg\_parcelcount') as rnd_avg_parcelcount,
(select sum(v::numeric)
from json_each_text(row_to_json(panel_stats_rnd.*)) as j(k,v)
where k like 'c\_%\_sum\_parcelcount') as rnd_sum_parcelcount
from
panel_stats_rnd;
Look at the documentation about functions involved.
There are escapes for underlying characters (\_) because for like operator it is meaning any single character, for example select 'a' like '_'; is true.