I have a problem with a PostgreSQL query.
I have a table named "pokemons" with different columns :
id | name | pv | attaque | defense | attaque_spe | defense_spe | vitesse | type
-----+------------+-----+---------+---------+-------------+-------------+---------+------------------
1 | Bulbizarre | 45 | 49 | 49 | 65 | 65 | 45 | {Plante,Poison}
2 | Herbizarre | 60 | 62 | 63 | 80 | 80 | 60 | {Plante,Poison}
3 | Florizarre | 80 | 82 | 83 | 100 | 100 | 80 | {Plante,Poison}
4 | Salameche | 39 | 52 | 43 | 60 | 50 | 65 | {Feu}
5 | Reptincel | 58 | 64 | 58 | 80 | 65 | 80 | {Feu}
6 | Dracaufeu | 78 | 84 | 78 | 109 | 85 | 100 | {Feu,Vol}
7 | Carapuce | 44 | 48 | 65 | 50 | 64 | 43 | {Eau}
8 | Carabaffe | 59 | 63 | 80 | 65 | 80 | 58 | {Eau}
9 | Tortank | 79 | 83 | 100 | 85 | 105 | 78 | {Eau}
In this table, I want to select all the rows with a specific type.
Kind of things, I did try :
SELECT * FROM pokemons WHERE 'feu'=ANY(type);
I tried many things with ALL or stuff like that but can't get a single a row.
Can you help me there please.
Thanks.
Adding to the solution mentioned in the comment, you may also make a case insensitive comparison like this.
SELECT * FROM pokemons WHERE 'feu' ilike ANY(type);
Related
Basically, I want to transform this(Initial) into this(Final). In other words, I want to
"squash" the initial table so that it will have only one record per id
"dilate" the initial table so that I won't lose any information: create a different column for every possible combination of source and column from the initial table (create c1_A, c1_B, ...).
I can work with the initial table as a csv in Python (maybe Pandas) and manually hardcode the mapping between the Initial and the Final table. However, I don't find this solution elegant at all and I'm much more interested in a sql / sas solution. Is there any way of doing that?
Edit: I what to change
+----+--------+------+-----+------+
| ID | source | c1 | c2 | c3 |
+----+--------+------+-----+------+
| 1 | A | 432 | 56 | 1 |
| 1 | B | 53 | 3 | 73 |
| 1 | C | 7 | 342 | 83 |
| 1 | D | 543 | 43 | 73 |
| 2 | A | 8 | 882 | 39 |
| 2 | B | 5 | 54 | 46 |
| 2 | C | 8 | 3 | 2226 |
| 2 | D | 87 | 2 | 45 |
| 3 | A | 93 | 143 | 45 |
| 3 | B | 1023 | 72 | 8 |
| 3 | C | 3 | 3 | 704 |
| 4 | A | 2 | 5 | 0 |
| 4 | B | 78 | 888 | 2 |
| 4 | C | 87 | 23 | 34 |
| 4 | D | 112 | 7 | 712 |
+----+--------+------+-----+------+
into
+----+------+------+------+------+------+------+------+------+------+------+------+------+
| ID | c1_A | c1_B | c1_C | c1_D | c2_A | c2_B | c2_C | c2_D | c3_A | c3_B | c3_C | c3_D |
+----+------+------+------+------+------+------+------+------+------+------+------+------+
| 1 | 432 | 53 | 7 | 543 | 56 | 3 | 342 | 43 | 1 | 73 | 83 | 73 |
| 2 | 8 | 5 | 8 | 87 | 882 | 54 | 3 | 2 | 39 | 46 | 2226 | 45 |
| 3 | 93 | 1023 | 3 | | 143 | 72 | 3 | | 45 | 8 | 704 | |
| 4 | 2 | 78 | 87 | 112 | 5 | 888 | 23 | 7 | 0 | 2 | 34 | 712 |
+----+------+------+------+------+------+------+------+------+------+------+------+------+
Abandon hope ... ?
data want;
input
ID source $ c1 c2 c3;datalines;
1 A 432 56 1
1 B 53 3 73
1 C 7 342 83
1 D 543 43 73
2 A 8 882 39
2 B 5 54 46
2 C 8 3 2226
2 D 87 2 45
3 A 93 143 45
3 B 1023 72 8
3 C 3 3 704
4 A 2 5 0
4 B 78 888 2
4 C 87 23 34
4 D 112 7 712
;
* one to grow you oh data;
proc transpose data=want out=stage1;
by id source;
var c1-c3;
run;
* and one to shrink;
proc transpose data=stage1 out=want(drop=_name_) delim=_;
by id;
id _name_ source;
run;
I have a table in the Database which has many features each feature is having its own actual and predicted value in its and we have two more column which is Id_partner and Id_accounts.My main goal is to get the RMSE score for each feature for each accounts in each partners, I have done that with the for loop but it is taking hell lot of time to complete in PySpark is there an efficient way of doing that directly with the help of query while reading the data only so I get the RMSE score for each accounts in each partner.
My Table is something like this
Actual_Feature_1 = Act_F_1
Predicted_Feature_1 = Pred_F_1
Actual_Feature_1 = Act_F_2
Predicted_Feature_1 = Pred_F_2
Table 1:
ID_PARTNER | ID_ACCOUNT | Act_F_1 | Pred_F_1 | Act_F_2 | Pred_F_2 |
4 | 24 | 10 | 12 | 22 | 20 |
4 | 24 | 11 | 13 | 23 | 21 |
4 | 24 | 11 | 12 | 24 | 23 |
4 | 25 | 13 | 15 | 22 | 20 |
4 | 25 | 15 | 12 | 21 | 20 |
4 | 25 | 15 | 14 | 21 | 21 |
4 | 27 | 13 | 12 | 35 | 32 |
4 | 27 | 12 | 16 | 34 | 31 |
4 | 27 | 17 | 14 | 36 | 34 |
5 | 301 | 19 | 17 | 56 | 54 |
5 | 301 | 21 | 20 | 58 | 54 |
5 | 301 | 22 | 19 | 59 | 57 |
5 | 301 | 24 | 22 | 46 | 50 |
5 | 301 | 25 | 22 | 49 | 54 |
5 | 350 | 12 | 10 | 67 | 66 |
5 | 350 | 12 | 11 | 65 | 64 |
5 | 350 | 14 | 13 | 68 | 67 |
5 | 350 | 15 | 12 | 61 | 61 |
5 | 350 | 12 | 10 | 63 | 60 |
7 | 420 | 51 | 49 | 30 | 29 |
7 | 420 | 51 | 48 | 32 | 30 |
7 | 410 | 49 | 45 | 81 | 79 |
7 | 410 | 48 | 44 | 83 | 80 |
7 | 410 | 45 | 43 | 84 | 81 |
I need the RMSE score for each account in each partners in this format
Resulted Table :
ID_PARTNER | ID_ACCOUNT | FEATURE_1 | FEATURE_2 |
4 | 24 | rmse_score | rmse_score |
4 | 25 | rmse_score | rmse_score |
4 | 27 | rmse_score | rmse_score |
5 | 301 | rmse_score | rmse_score |
5 | 350 | rmse_score | rmse_score |
7 | 420 | rmse_score | rmse_score |
7 | 410 | rmse_score | rmse_score |
Note : For this we need to do consideration of both id_account and id_partner by seeing the above table i.e actual table we see that id_accounts can be just used for getting rmse but different id_partner can have the same accounts as other partner is having.
I need an SQL query that provides the resulted table directly while reading the table from the database.
Yes, you can calculate the root-mean-square-error in SQL.
SELECT ID_PARTNER, ID_ACCOUNT
, SQRT(Avg( POWER(Act_F_1 - Pred_F_1 , 2) ) ) as feature_1_rmse
FROM ...
GROUP BY ID_PARTNER, ID_ACCOUNT
I have the current table of data...
| LoanRollupID | NewLoanID | PreviousLoanID |
|--------------|-----------|----------------|
| 11 | 76 | 44 |
| 12 | 80 | 75 |
| 13 | 83 | 82 |
| 14 | 84 | 83 |
| 15 | 86 | 85 |
| 16 | 87 | 54 |
| 17 | 88 | 87 |
| 18 | 90 | 48 |
| 19 | 91 | 34 |
| 20 | 93 | 41 |
| 21 | 94 | 76 |
| 22 | 95 | 90 |
| 23 | 96 | 94 |
| 24 | 100 | 92 |
| 25 | 101 | 99 |
| 26 | 102 | 98 |
| 27 | 103 | 101 |
| 28 | 104 | 81 |
| 29 | 105 | 80 |
| 30 | 107 | 52 |
| 31 | 110 | 108 |
| 1029 | 1105 | 103 |
| 1030 | 1106 | 104 |
| 1031 | 1108 | 1106 |
| 1032 | 1109 | 73 |
I'm trying to jump in at NewLoanID 1108 and see how it has evolved from previous Loans. e.g 1108 came from 1106, which came from 104, which came from 81, etc.
When I run this query:
WITH OldLoans (PreviousLoanID, NewLoanID, start)
AS
(
---- Anchor member definition
SELECT l.NewLoanID, l.PreviousLoanID, 0 as start
FROM dscs_public.LoanRollup l
Where NewLoanID = 1108
UNION ALL
-- Recursive member definition
SELECT l.NewLoanID, l.PreviousLoanID, start + 1
FROM dscs_public.LoanRollup l
INNER JOIN OldLoans AS o
ON o.NewLoanID = l.PreviousLoanID
)
---- Statement that executes the CTE
SELECT PreviousLoanID, NewLoanID, start
FROM OldLoans
It fails with this error:
The statement terminated. The maximum recursion 100 has been exhausted
before statement completion.
Can anyone spot my mistake please?
Thanks.
The aliases in the CTE definition are in the wrong order:
-- Instead of (PreviousLoanID, NewLoanID, start)
WITH OldLoans (NewLoanID, PreviousLoanID, start)
AS
(
---- Anchor member definition
SELECT l.NewLoanID, l.PreviousLoanID, 0 as start
FROM mytable l --LoanRollup l
Where NewLoanID = 1108
UNION ALL
-- Recursive member definition
SELECT l.NewLoanID, l.PreviousLoanID, start + 1
FROM mytable l --dscs_public.LoanRollup l
INNER JOIN OldLoans AS o
-- Instead of o.NewLoanID = l.PreviousLoanID
ON l.NewLoanID = o.PreviousLoanID
)
---- Statement that executes the CTE
SELECT PreviousLoanID, NewLoanID, start
FROM OldLoans
The same thing holds for the ON clause in the recursive member definition.
I am trying to do a group sorting on Datatables. As of now I am having data like:
+-------+-----+--------+
| rowno | mno | result |
+-------+-----+--------+
| 1 | 80 | 20 |
| 1 | 81 | 10 |
| 1 | 82 | 30 |
| 2 | 80 | 40 |
| 2 | 81 | 50 |
| 2 | 82 | 60 |
| 3 | 80 | 70 |
| 3 | 81 | 60 |
| 3 | 82 | 50 |
+-------+-----+--------+
As per the requirement , i will be selecting a particular mno, lets say 81 and then depending on the result for 81 i.e. 10, 50 and 60, I would like to sort entire group in descending order. Which means the result would be something like:
+-------+-----+--------+
| rowno | mno | result |
+-------+-----+--------+
| 3 | 80 | 70 |
| 3 | 81 | 60 |
| 3 | 82 | 50 |
| 2 | 80 | 40 |
| 2 | 81 | 50 |
| 2 | 82 | 60 |
| 1 | 80 | 20 |
| 1 | 81 | 10 |
| 1 | 82 | 30 |
+-------+-----+--------+
I am having the entire set as Datatable and am thinking of applying Linq to solve this one. Or if a SQL Query could be suggested that would also be fine.
Try this
SELECT rowno,mno,result from your_table
order by rowno desc
With LINQ to DataSet (dt is your DataTable):
var sorted = dt.AsEnumerable()
.OrderByDescending(r => r.Field<int>("rowno"))
.CopyToDataTable();
Without LINQ:
var view = dt.DefaultView;
view.Sort = "rowno DESC";
var sorted = view.ToTable();
I have a following result from query:
+---------------+------+------+------+------+------+------+------+-------+
| order_main_id | S36 | S37 | S38 | S39 | S40 | S41 | S42 | total |
+---------------+------+------+------+------+------+------+------+-------+
| 26 | 127 | 247 | 335 | 333 | 223 | 111 | 18 | 1394 |
| 26 | 323 | 606 | 772 | 765 | 573 | 312 | 154 | 3505 |
| 38 | 25 | 35 | 35 | 35 | 20 | NULL | NULL | 150 |
| 38 | 25 | 35 | 35 | 35 | 20 | NULL | NULL | 150 |
| 39 | 65 | 86 | 86 | 42 | 21 | NULL | NULL | 300 |
| 39 | 42 | 58 | 58 | 28 | 14 | NULL | NULL | 200 |
| 35 | 11 | 20 | 21 | 18 | 9 | 2 | NULL | 81 |
| 35 | 10 | 25 | 30 | 23 | 12 | 1 | NULL | 101 |
+---------------+------+------+------+------+------+------+------+-------+
I would like to insert a SUM before enter different order_main_id, it would be like this result:
+---------------+------+------+------+------+------+------+------+-------+
| order_main_id | S36 | S37 | S38 | S39 | S40 | S41 | S42 | total |
+---------------+------+------+------+------+------+------+------+-------+
| 26 | 127 | 247 | 335 | 333 | 223 | 111 | 18 | 1394 |
| 26 | 323 | 606 | 772 | 765 | 573 | 312 | 154 | 3505 |
| | 450 | 853 | 1107 | 1098 | 796 | 423 | 172 | 4899 |
| 38 | 25 | 35 | 35 | 35 | 20 | NULL | NULL | 150 |
| 38 | 25 | 35 | 35 | 35 | 20 | NULL | NULL | 150 |
| | 50 | 70 | 70 | 70 | 40 | NULL | NULL | 300 |
| 39 | 65 | 86 | 86 | 42 | 21 | NULL | NULL | 300 |
| 39 | 42 | 58 | 58 | 28 | 14 | NULL | NULL | 200 |
| | 107 | 144 | 144 | 70 | 35 | NULL | NULL | 500 |
| 35 | 11 | 20 | 21 | 18 | 9 | 2 | NULL | 81 |
| 35 | 10 | 25 | 30 | 23 | 12 | 1 | NULL | 101 |
| | 21 | 45 | 51 | 41 | 21 | 3 | NULL | 182 |
+---------------+------+------+------+------+------+------+------+-------+
How to make this possible ?
You'll need to write a second Query which makes use of GROUP BY order_main_id.
Something like:
SELECT sum(S41+...) FROM yourTable GROUP BY orderMainId
K
You can actually do this in one query, but with a union all (really two queries, but the result sets are combined to make one awesome result set):
select
order_main_id,
S36,
S37,
S38,
S39,
S40,
S41,
S42,
S36 + S37 + S38 + S39 + S40 + S41 + S42 as total,
'Detail' as rowtype
from
tblA
union all
select
order_main_id,
sum(S36),
sum(S37),
sum(S38),
sum(S39),
sum(S40),
sum(S41),
sum(S42),
sum(S36 + S37 + S38 + S39 + S40 + S41 + S42),
'Summary' as rowtype
from
tblA
group by
order_main_id
order by
order_main_id, RowType
Remember that the order by affects the entirety of the union all, not just the last query. So, your resultset would look like this:
+---------------+------+------+------+------+------+------+------+-------+---------+
| order_main_id | S36 | S37 | S38 | S39 | S40 | S41 | S42 | total | rowtype |
+---------------+------+------+------+------+------+------+------+-------+---------+
| 26 | 127 | 247 | 335 | 333 | 223 | 111 | 18 | 1394 | Detail |
| 26 | 323 | 606 | 772 | 765 | 573 | 312 | 154 | 3505 | Detail |
| 26 | 450 | 853 | 1107 | 1098 | 796 | 423 | 172 | 4899 | Summary |
| 35 | 11 | 20 | 21 | 18 | 9 | 2 | NULL | 81 | Detail |
| 35 | 10 | 25 | 30 | 23 | 12 | 1 | NULL | 101 | Detail |
| 35 | 21 | 45 | 51 | 41 | 21 | 3 | NULL | 182 | Summary |
| 38 | 25 | 35 | 35 | 35 | 20 | NULL | NULL | 150 | Detail |
| 38 | 25 | 35 | 35 | 35 | 20 | NULL | NULL | 150 | Detail |
| 38 | 50 | 70 | 70 | 70 | 40 | NULL | NULL | 300 | Summary |
| 39 | 65 | 86 | 86 | 42 | 21 | NULL | NULL | 300 | Detail |
| 39 | 42 | 58 | 58 | 28 | 14 | NULL | NULL | 200 | Detail |
| 39 | 107 | 144 | 144 | 70 | 35 | NULL | NULL | 500 | Summary |
+---------------+------+------+------+------+------+------+------+-------+---------+
This way, you know what is and what isn't a detail or summary row, and the order_main_id that it's for. You could always (and probably should) hide this column in your presentation layer.
For things like these I think you should use a reporting library(such as Crystal Reports), it'll save you a lot of trouble, check JasperReports and similar projects on osalt