I have a database table structured like this (irrelevant fields omitted for brevity):
rankings
------------------
(PK) indicator_id
(PK) alternative_id
(PK) analysis_id
rank
All fields are integers; the first three (labeled "(PK)") are a composite primary key. A given "analysis" has multiple "alternatives", each of which will have a "rank" for each of many "indicators".
I'm looking for an efficient way to compare an arbitrary number of analyses whose ranks for any alternative/indicator combination differ. So, for example, if we have this data:
analysis_id | alternative_id | indicator_id | rank
----------------------------------------------------
1 | 1 | 1 | 4
1 | 1 | 2 | 6
1 | 2 | 1 | 3
1 | 2 | 2 | 9
2 | 1 | 1 | 4
2 | 1 | 2 | 7
2 | 2 | 1 | 4
2 | 2 | 2 | 9
...then the ideal method would identify the following differences:
analysis_id | alternative_id | indicator_id | rank
----------------------------------------------------
1 | 1 | 2 | 6
2 | 1 | 2 | 7
1 | 2 | 1 | 3
2 | 2 | 1 | 4
I came up with a query that does what I want for 2 analysis IDs, but I'm having trouble generalizing it to find differences between an arbitrary number of analysis IDs (i.e. the user might want to compare 2, or 5, or 9, or whatever, and find any rows where at least one analysis differs from any of the others). My query is:
declare #analysisId1 int, #analysisId2 int;
select #analysisId1 = 1, #analysisId2 = 2;
select
r1.indicator_id,
r1.alternative_id,
r1.[rank] as Analysis1Rank,
r2.[rank] as Analysis2Rank
from rankings r1
inner join rankings r2
on r1.indicator_id = r2.indicator_id
and r1.alternative_id = r2.alternative_id
and r2.analysis_id = #analysisId2
where
r1.analysis_id = #analysisId1
and r1.[rank] != r2.[rank]
(It puts the analysis values into additional fields instead of rows. I think either way would work.)
How can I generalize this query to handle many analysis ids? (Or, alternatively, come up with a different, better query to do the job?) I'm using SQL Server 2005, in case it matters.
If necessary, I can always pull all the data out of the table and look for differences in code, but a SQL solution would be preferable since often I'll only care about a few rows out of thousands and there's no point in transferring them all if I can avoid it. (However, if you have a compelling reason not to do this in SQL, say so--I'd consider that a good answer too!)
This will return your desired data set - Now you just need a way to pass the required analysis ids to the query. Or potentially just filter this data inside your application.
select r.* from rankings r
inner join
(
select alternative_id, indicator_id
from rankings
group by alternative_id, indicator_id
having count(distinct rank) > 1
) differ on r.alternative_id = differ.alternative_id
and r.indicator_id = differ.indicator_id
order by r.alternative_id, r.indicator_id, r.analysis_id, r.rank
I don't know wich database you are using, in SQL Server I would go like this:
-- STEP 1, create temporary table with all the alternative_id , indicator_id combinations with more than one rank:
select alternative_id , indicator_id
into #results
from rankings
group by alternative_id , indicator_id
having count (distinct rank)>1
-- STEP 2, retreive the data
select a.* from rankings a, #results b
where a.alternative_id = b.alternative_id
and a.indicator_id = b. indicator_id
order by alternative_id , indicator_id, analysis_id
BTW, THe other answers given here need the count(distinct rank) !!!!!
I think this is what you're trying to do:
select
r.analysis_id,
r.alternative_id,
rm.indicator_id_max,
rm.rank_max
from rankings rm
join (
select
analysis_id,
alternative_id,
max(indicator_id) as indicator_id_max,
max(rank) as rank_max
from rankings
group by analysis_id,
alternative_id
having count(*) > 1
) as rm
on r.analysis_id = rm.analysis_id
and r.alternative_id = rm.alternative_id
You example differences seems wrong. You say you want analyses whose ranks for any alternative/indicator combination differ but the example rows 3 and 4 don't satisfy this criteria. A correct result according to your requirement is:
analysis_id | alternative_id | indicator_id | rank
----------------------------------------------------
1 | 1 | 2 | 6
2 | 1 | 2 | 7
1 | 2 | 1 | 3
2 | 2 | 1 | 4
On query you could try is this:
with distinct_ranks as (
select alternative_id
, indicator_id
, rank
, count (*) as count
from rankings
group by alternative_id
, indicator_id
, rank
having count(*) = 1)
select r.analysis_id
, r.alternative_id
, r.indicator_id
, r.rank
from rankings r
join distinct_ranks d on r.alternative_id = d.alternative_id
and r.indicator_id = d.indicator_id
and r.rank = d.rank
You have to realize that on multiple analysis the criteria you have is ambiguous. What if analysis 1,2 and 3 have rank 1 and 4,5 and 6 have rank 2 for alternative/indicator 1/1? The set (1,2,3) is 'different' from the set (4,5,6) but inside each set there is no difference. what is the behavior you desire in that case, should they show up or not? My query finds all records that have a different rank for the same alternative/indicator *from all other analysis' but is not clear if this is correct in your requirement.
Related
I've got a table that looks like this:
player_id | violation
---------------------
1 | A
1 | A
1 | B
2 | C
3 | D
3 | A
And I want to turn it into this, with a bunch of new columns that refer to the types of violations, and then the sum of the number of each individual type of violation that each player got (not that concerned with what the columns are called; a/b/c/d would work great as well):
player_id | violation_a | violation_b | violation_c | violation_d
-----------------------------------------------------------------
1 | 2 | 1 | 0 | 0
2 | 0 | 0 | 1 | 0
3 | 1 | 0 | 0 | 1
I know how I could do this, but it would take a ton of lines of code, since there are in reality 100+ types of violations. Is there any way (perhaps with a tablefunc()?) that I could do this more concisely than spelling out each of the new 100+ columns that I want and the logic for them each individually?
In pure SQL I don't see how you could avoid declaring the columns yourself. You either have to create subselects or filters in every column ..
SELECT DISTINCT ON (t.player_id)
t.player_id,
count(*) FILTER (WHERE violation = 'A') AS violation_a,
count(*) FILTER (WHERE violation = 'B') AS violation_b,
count(*) FILTER (WHERE violation = 'C') AS violation_c,
count(*) FILTER (WHERE violation = 'D') AS violation_d
FROM t
GROUP BY t.player_id;
.. or create a pivot table:
SELECT *
FROM crosstab(
'SELECT player_id, t2.violation, count(*) FILTER (WHERE t.violation = t2.violation)::INT
FROM t,(SELECT DISTINCT violation FROM t) t2
GROUP BY player_id, t2.violation'
) AS ct(player_id INT,violation_a int,violation_b int,violation_c int,violation_d int);
Demo: db<>fiddle
Introduction:
I have come across an unexpected challenge. I'm hoping someone can help and I am interested in the best method to go about manipulating the data in accordance to this problem.
Scenario:
I need to combine column data associated to two different ID columns. Each row that I have associates an item_id and the quantity for this item_id. Please see below for an example.
+-------+-------+-------+---+
|cust_id|pack_id|item_id|qty|
+-------+-------+-------+---+
| 1 | A | 1 | 1 |
| 1 | A | 2 | 1 |
| 1 | A | 3 | 4 |
| 1 | A | 4 | 0 |
| 1 | A | 5 | 0 |
+-------+-------+-------+---+
I need to manipulate the data shown above so that 24 rows (for 24 item_ids) is combined into a single row. In the example above I have chosen 5 items to make things easier. The selection format I wish to get, assuming 5 item_ids, can be seen below.
+---------+---------+---+---+---+---+---+
| cust_id | pack_id | 1 | 2 | 3 | 4 | 5 |
+---------+---------+---+---+---+---+---+
| 1 | A | 1 | 1 | 4 | 0 | 0 |
+---------+---------+---+---+---+---+---+
However, here's the condition that is making this troublesome. The maximum total quantity for each row must not exceed 5. If the total quantity exceeds 5 a new row associated to the cust_id and pack_id must be created for the rest of the item_id quantities. Please see below for the desired output.
+---------+---------+---+---+---+---+---+
| cust_id | pack_id | 1 | 2 | 3 | 4 | 5 |
+---------+---------+---+---+---+---+---+
| 1 | A | 1 | 1 | 3 | 0 | 0 |
| 1 | A | 0 | 0 | 1 | 0 | 0 |
+---------+---------+---+---+---+---+---+
Notice how the quantities of item_ids 1, 2 and 3 summed together equal 6. This exceeds the maximum total quantity of 5 for each row. For the second row the difference is created. In this case only item_id 3 has a single quantity remaining.
Note, if a 2nd row needs to be created that total quantity displayed in that row also cannot exceed 5. There is a known item_id limit of 24. But, there is no known limit of the quantity associated for each item_id.
Here's an approach which goes from left-field a bit.
One approach would have been to do a recursive CTE, building the rows one-by-one.
Instead, I've taken an approach where I
Create a new (virtual) table with 1 row per item (so if there are 6 items, there will be 6 rows)
Group those items into groups of 5 (I've called these rn_batches)
Pivot those (based on counts per item per rn_batch)
For these, processing is relatively simple
Creating one row per item is done using INNER JOIN to a numbers table with n <= the relevant quantity.
The grouping then just assigns rn_batch = 1 for the first 5 items, rn_batch = 2 for the next 5 items, etc - until there are no more items left for that order (based on cust_id/pack_id).
Here is the code
/* Data setup */
CREATE TABLE #Order (cust_id int, pack_id varchar(1), item_id int, qty int, PRIMARY KEY (cust_id, pack_id, item_id))
INSERT INTO #Order (cust_id, pack_id, item_id, qty) VALUES
(1, 'A', 1, 1),
(1, 'A', 2, 1),
(1, 'A', 3, 4),
(1, 'A', 4, 0),
(1, 'A', 5, 0);
/* Pivot results */
WITH Nums(n) AS
(SELECT (c * 100) + (b * 10) + (a) + 1 AS n
FROM (VALUES (0),(1),(2),(3),(4),(5),(6),(7),(8),(9)) A(a)
CROSS JOIN (VALUES (0),(1),(2),(3),(4),(5),(6),(7),(8),(9)) B(b)
CROSS JOIN (VALUES (0),(1),(2),(3),(4),(5),(6),(7),(8),(9)) C(c)
),
ItemBatches AS
(SELECT cust_id, pack_id, item_id,
FLOOR((ROW_NUMBER() OVER (PARTITION BY cust_id, pack_id ORDER BY item_id, N.n)-1) / 5) + 1 AS rn_batch
FROM #Order O
INNER JOIN Nums N ON N.n <= O.qty
)
SELECT *
FROM (SELECT cust_id, pack_id, rn_batch, 'Item_' + LTRIM(STR(item_id)) AS item_desc
FROM ItemBatches
) src
PIVOT
(COUNT(item_desc) FOR item_desc IN ([Item_1], [Item_2], [Item_3], [Item_4], [Item_5])) pvt
ORDER BY cust_id, pack_id, rn_batch;
And here are results
cust_id pack_id rn_batch Item_1 Item_2 Item_3 Item_4 Item_5
1 A 1 1 1 3 0 0
1 A 2 0 0 1 0 0
Here's a db<>fiddle with
additional data in the #Orders table
the answer above, and also the processing with each step separated.
Notes
This approach (with the virtual numbers table) assumes a maximum of 1,000 for a given item in an order. If you need more, you can easily extend that numbers table by adding additional CROSS JOINs.
While I am in awe of the coders who made SQL Server and how it determines execution plans in millisends, for larger datasets I give SQL Server 0 chance to accurately predict how many rows will be in each step. As such, for performance, it may work better to split the code up into parts (including temp tables) similar to the db<>fiddle example.
I want to be able to filter out groups where the values aren't the same. When doing the query:
SELECT
category.id as category_id,
object.id as object_id,
object.value as value
FROM
category,
object
WHERE
category.id = object.category
We get the following results:
category_id | object_id | value
-------------+-----------+-------
1 | 1 | 1
1 | 2 | 2
1 | 3 | 2
2 | 4 | 3
2 | 5 | 2
3 | 6 | 1
3 | 7 | 1
The goal: Update the query so that it yields:
category_id
-------------
1
2
In other words, find the categories where the values are different from the others in that same category.
I have tried many different methods of joining, grouping and so on, to no avail.
I know it can be done with multiple queries and then filter with a little bit of logic, but this is not the goal.
You can use aggregation:
SELECT o.category as category_id
FROM object o
GROUP BY o.category
HAVING MIN(o.value) <> MAX(o.value);
You have left the FROM clause out of your query. But as written, you don't need a JOIN at all. The object table is sufficient -- because you are only fetching the category id.
I have performing some queries using PostgreSQL SELECT DISTINCT ON syntax. I would like to have the query return the total number of rows alongside with every result row.
Assume I have a table my_table like the following:
CREATE TABLE my_table(
id int,
my_field text,
id_reference bigint
);
I then have a couple of values:
id | my_field | id_reference
----+----------+--------------
1 | a | 1
1 | b | 2
2 | a | 3
2 | c | 4
3 | x | 5
Basically my_table contains some versioned data. The id_reference is a reference to a global version of the database. Every change to the database will increase the global version number and changes will always add new rows to the tables (instead of updating/deleting values) and they will insert the new version number.
My goal is to perform a query that will only retrieve the latest values in the table, alongside with the total number of rows.
For example, in the above case I would like to retrieve the following output:
| total | id | my_field | id_reference |
+-------+----+----------+--------------+
| 3 | 1 | b | 2 |
+-------+----+----------+--------------+
| 3 | 2 | c | 4 |
+-------+----+----------+--------------+
| 3 | 3 | x | 5 |
+-------+----+----------+--------------+
My attemp is the following:
select distinct on (id)
count(*) over () as total,
*
from my_table
order by id, id_reference desc
This returns almost the correct output, except that total is the number of rows in my_table instead of being the number of rows of the resulting query:
total | id | my_field | id_reference
-------+----+----------+--------------
5 | 1 | b | 2
5 | 2 | c | 4
5 | 3 | x | 5
(3 rows)
As you can see it has 5 instead of the expected 3.
I can fix this by using a subquery and count as an aggregate function:
with my_values as (
select distinct on (id)
*
from my_table
order by id, id_reference desc
)
select count(*) over (), * from my_values
Which produces my expected output.
My question: is there a way to avoid using this subquery and have something similar to count(*) over () return the result I want?
You are looking at my_table 3 ways:
to find the latest id_reference for each id
to find my_field for the latest id_reference for each id
to count the distinct number of ids in the table
I therefore prefer this solution:
select
c.id_count as total,
a.id,
a.my_field,
b.max_id_reference
from
my_table a
join
(
select
id,
max(id_reference) as max_id_reference
from
my_table
group by
id
) b
on
a.id = b.id and
a.id_reference = b.max_id_reference
join
(
select
count(distinct id) as id_count
from
my_table
) c
on true;
This is a bit longer (especially the long thin way I write SQL) but it makes it clear what is happening. If you come back to it in a few months time (somebody usually does) then it will take less time to understand what is going on.
The "on true" at the end is a deliberate cartesian product because there can only ever be exactly one result from the subquery "c" and you do want a cartesian product with that.
There is nothing necessarily wrong with subqueries.
I have the following table in my database.
# select * FROM matches;
name | prop | rank
------+------+-------
carl | 1 | 4
carl | 2 | 3
carl | 3 | 9
alex | 1 | 8
alex | 2 | 5
alex | 3 | 6
alex | 3 | 8
alex | 2 | 11
anna | 3 | 8
anna | 3 | 13
anna | 2 | 14
(11 rows)
Each person is ranked at work by different properties/criterias called 'prop' and the performance is called 'rank'. The table contains multiple values of (name, prop) as the example shows. I want to get the best candidate following from some requirements. E.g. I need a candidate that have (prop=1 AND rank > 5) and (prop=3 AND rank >= 8). Then we must be able to sort the candidates by their rankings to get the best candidate.
EDIT: Each person must fulfill ALL requirements
How can I do this in SQL?
select x.name, max(x.rank)
from matches x
join (
select name from matches where prop = 1 AND rank > 5
intersect
select name from matches where prop = 3 AND rank >= 8
) y
on x.name = y.name
group by x.name
order by max(rank);
Filtering the data to match your criteria here is quite simple (as shown by both Amir and sternze):
SELECT *
FROM matches
WHERE prop=1 AND rank>5) OR (prop=3 AND rank>=8
The problem is how to aggregate this data so as to have just one row per candidate.
I suggest you do something like this:
SELECT m.name,
MAX(DeltaRank1) AS MaxDeltaRank1,
MAX(DeltaRank3) AS MaxDeltaRank3
FROM (
SELECT name,
(CASE WHEN prop=1 THEN rank-6 ELSE 0 END) AS DeltaRank1,
(CASE WHEN prop=3 THEN rank-8 ELSE 0 END) AS DeltaRank3,
FROM matches
) m
GROUP BY m.name
HAVING MaxDeltaRank1>0 AND MaxDeltaRank3>0
SORT BY MaxDeltaRank1+MaxDeltaRank3 DESC;
This will order the candidates by the sum of how much they exceeded the target rank in prop1 and prop3. You could use different logic to indicate which is best though.
In the case above, this should be the result:
name | MaxDeltaRank1 | MaxDeltaRank3
------+---------------+--------------
alex | 3 | 0
... because neither anna nor carl reach both the required ranks.
A typical case of relational division. We assembled a whole arsenal of techniques under this related question:
How to filter SQL results in a has-many-through relation
Assuming you want the minimum rank of a person, I might solve your particular case with LEAST():
SELECT m1.name, LEAST(m1.rank, m2.rank, ...) AS best_rank
FROM matches m1
JOIN matches m2 USING (name)
...
WHERE m1.prop = 1 AND m1.rank > 5
AND m2.prop = 3 AND m2.rank >= 8
...
ORDER BY best_rank;
Also assuming name to be unique per individual person. You'd probably use some kind of foreign key to a pk column of a person table in reality.
And if you have such a person table like you should, the best rank would be stored in a column there ...
If I understand you question, then you just need to execute the following operation:
SELECT * FROM matches where (prop = 1 AND rank > 5) OR (prop = 3 AND rank >= 8) ORDER BY rank
It gives you the canidates that either have prop=1 and rank > 5 or prop=3 and rank >= 8 sorted by their rankings.