I have an unusual problem I'm trying to solve with SQL where I need to generate sequential numbers for partitioned rows but override specific numbers with values from the data, while not breaking the sequence (unless the override causes a number to be used greater than the number of rows present).
I feel I might be able to achieve this by selecting the rows where I need to override the generated sequence value and the rows I don't need to override the value, then unioning them together and somehow using coalesce to get the desired dynamically generated sequence value, or maybe there's some way I can utilise recursive.
I've not been able to solve this problem yet, but I've put together a SQL Fiddle which provides a simplified version:
http://sqlfiddle.com/#!17/236b5/5
The desired_dynamic_number is what I'm trying to generate and the generated_dynamic_number is my current work-in-progress attempt.
Any pointers around the best way to achieve the desired_dynamic_number values dynamically?
Update:
I'm almost there using lag:
http://sqlfiddle.com/#!17/236b5/24
step-by-step demo:db<>fiddle
SELECT
*,
COALESCE( -- 3
first_value(override_as_number) OVER w -- 2
, 1
)
+ row_number() OVER w - 1 -- 4, 5
FROM (
SELECT
*,
SUM( -- 1
CASE WHEN override_as_number IS NOT NULL THEN 1 ELSE 0 END
) OVER (PARTITION BY grouped_by ORDER BY secondary_order_by)
as grouped
FROM sample
) s
WINDOW w AS (PARTITION BY grouped_by, grouped ORDER BY secondary_order_by)
Create a new subpartition within your partitions: This cumulative sum creates a unique group id for every group of records which starts with a override_as_number <> NULL followed by NULL records. So, for instance, your (AAA, d) to (AAA, f) belongs to the same subpartition/group.
first_value() gives the first value of such subpartition.
The COALESCE ensures a non-NULL result from the first_value() function if your partition starts with a NULL record.
row_number() - 1 creates a row count within a subpartition, starting with 0.
Adding the first_value() of a subpartition with the row count creates your result: Beginning with the one non-NULL record of a subpartition (adding the 0 row count), the first following NULL records results in the value +1 and so forth.
Below query gives exact result, but you need to verify with all combinations
select c.*,COALESCE(c.override_as_number,c.act) as final FROM
(
select b.*, dense_rank() over(partition by grouped_by order by grouped_by, actual) as act from
(
select a.*,COALESCE(override_as_number,row_num) as actual FROM
(
select grouped_by , secondary_order_by ,
dense_rank() over ( partition by grouped_by order by grouped_by, secondary_order_by ) as row_num
,override_as_number,desired_dynamic_number from fiddle
) a
) b
) c ;
column "final" is the result
grouped_by | secondary_order_by | row_num | override_as_number | desired_dynamic_number | actual | act | final
------------+--------------------+---------+--------------------+------------------------+--------+-----+-------
AAA | a | 1 | 1 | 1 | 1 | 1 | 1
AAA | b | 2 | | 2 | 2 | 2 | 2
AAA | c | 3 | 3 | 3 | 3 | 3 | 3
AAA | d | 4 | 3 | 3 | 3 | 3 | 3
AAA | e | 5 | | 4 | 5 | 4 | 4
AAA | f | 6 | | 5 | 6 | 5 | 5
AAA | g | 7 | 999 | 999 | 999 | 6 | 999
XYZ | a | 1 | | 1 | 1 | 1 | 1
ZZZ | a | 1 | | 1 | 1 | 1 | 1
ZZZ | b | 2 | | 2 | 2 | 2 | 2
(10 rows)
Hope this helps!
The real world problem I was trying to solve did not have a nicely ordered secondary_order_by column, instead it would be something a bit more randomised (a created timestamp).
For the benefit of people who stumble across this question with a similar problem to solve, a colleague solved this problem using a cartesian join, who's solution I'm posting below. The solution is Snowflake SQL which should be possible to adapt to Postgres. It does fall down on higher override_as_number values though unless the from table(generator(rowcount => 1000)) 1000 value is not increased to something suitably high.
The SQL:
with tally_table as (
select row_number() over (order by seq4()) as gen_list
from table(generator(rowcount => 1000))
),
base as (
select *,
IFF(override_as_number IS NULL, row_number() OVER(PARTITION BY grouped_by, override_as_number order by random),override_as_number) as rownum
from "SANDPIT"."TEST"."SAMPLEDATA" order by grouped_by,override_as_number,random
) --select * from base order by grouped_by,random;
,
cart_product as (
select *
from tally_table cross join (Select distinct grouped_by from base ) as distinct_grouped_by
) --select * from cart_product;
,
filter_product as (
select *,
row_number() OVER(partition by cart_product.grouped_by order by cart_product.grouped_by,gen_list) as seq_order
from cart_product
where CONCAT(grouped_by,'~',gen_list) NOT IN (select concat(grouped_by,'~',override_as_number) from base where override_as_number is not null)
) --select * from try2 order by 2,3 ;
select base.grouped_by,
base.random,
base.override_as_number,
base.answer, -- This is hard coded as test data
IFF(override_as_number is null, gen_list, seq_order) as computed_answer
from base inner join filter_product on base.rownum = filter_product.seq_order and base.grouped_by = filter_product.grouped_by
order by base.grouped_by,
random;
In the end I went for a simpler solution using a temporary table and cursor to inject override_as_number values and shuffle other numbers.
Related
To get 2 rows from each group I can use ROW_NUMBER() with condition <= 2 at last but my question is what If I want to get different limits on each group e.g 3 rows for section_id 1, 1 rows for 2 and 1 rows for 3?
Given the following table:
db=# SELECT * FROM xxx;
id | section_id | name
----+------------+------
1 | 1 | A
2 | 1 | B
3 | 1 | C
4 | 1 | D
5 | 2 | E
6 | 2 | F
7 | 3 | G
8 | 2 | H
(8 rows)
I get the first 2 rows (ordered by name) for each section_id, i.e. a result similar to:
id | section_id | name
----+------------+------
1 | 1 | A
2 | 1 | B
5 | 2 | E
6 | 2 | F
7 | 3 | G
(5 rows)
Current Query:
SELECT
*
FROM (
SELECT
ROW_NUMBER() OVER (PARTITION BY section_id ORDER BY name) AS r,
t.*
FROM
xxx t) x
WHERE
x.r <= 2;
Create a table to contain the section limits, then join. The big advantage being that as new sections are required or limits change maintenance is reduced to a single table update and comes at very little cost. See example.
select s.section_id, s.name
from (select section_id, name
, row_number() over (partition by section_id order by name) rn
from sections
) s
left join section_limits sl on (sl.section_id = s.section_id)
where
s.rn <= coalesce(sl.limit_to,2);
Just fix up your where clause:
with numbered as (
select row_number() over (partition by section_id
order by name) as r,
t.*
from xxx t
)
select *
from numbered
where (section_id = 1 and r <= 3)
or (section_id = 2 and r <= 1)
or (section_id = 3 and r <= 1);
I am using PostgreSQL and I am using PostGIS extension.
I am able to compare one point with this query:
SELECT st_distance(geom, 'SRID=4326;POINT(12.601828337172 50.5173393068512)'::geometry) as d
FROM pointst1
ORDER BY d
but I want to compare not to one fixed point but to a column of points. And I want to do this with some sort of indexing so that it is computationally cheap and not 10000x10000 like a cross join within that table.
Create table:
create table pointst1
(
id integer not null
constraint pointst1_id_pk
primary key,
geom geometry(Point, 4325)
);
create unique index pointst1_id_uindex
on pointst1 (id);
create index geomidx
on pointst1 (geom);
Edit:
Refined query (comparing 10000 points with their nearest neighbor but getting the result of the point itself which is 0 and not the next nearest point:
select points.*,
p1.id as p1_id,
ST_Distance(geography(p1.geom), geography(points.geom)) as distance
from
(select distinct on(p2.geom)*
from pointst1 p2
where p2.id is not null) as points
cross join lateral
(select id, geom
from pointst1
order by points.geom <-> geom
limit 1) as p1;
Your query is already calculating the distance from the given geometry to all records in the table pointst1.
Considering these values ..
INSERT INTO pointst1 VALUES (1,'SRID=4326;POINT(16.19 48.21)'),
(2,'SRID=4326;POINT(18.96 47.50)'),
(3,'SRID=4326;POINT(13.47 52.52)'),
(4,'SRID=4326;POINT(-3.70 40.39)');
... if you run your query, it will already calculate the distance from all points in the table:
SELECT ST_Distance(geom, 'SRID=4326;POINT(12.6018 50.5173)'::geometry) as d
FROM pointst1
ORDER BY d
d
------------------
2.1827914536208
4.26600662563949
7.03781262396208
19.1914274750473
(4 Zeilen)
Change your index to GIST, which is the most suitable for geometry data:
create index geomidx on pointst1 using GIST (geom);
Just note that an index won't speed up this query of yours, since you're doing a full scan. But as soon as you start playing more in the where clause, you might see some improvement.
EDIT:
WITH j AS (SELECT id AS id2, geom AS geom2 FROM pointst1)
SELECT id,j.id2,ST_Distance(geom, j.geom2) AS d
FROM pointst1,j
WHERE id <> j.id2
ORDER BY id,id2
id | id2 | d
----+-----+------------------
1 | 2 | 2.85954541841881
1 | 3 | 5.0965184194703
1 | 4 | 21.3720495039666
2 | 1 | 2.85954541841881
2 | 3 | 7.43911957156222
2 | 4 | 23.7492673571207
3 | 1 | 5.0965184194703
3 | 2 | 7.43911957156222
3 | 4 | 21.0225069865609
4 | 1 | 21.3720495039666
4 | 2 | 23.7492673571207
4 | 3 | 21.0225069865609
(12 rows)
Removing duplicate distances:
SELECT DISTINCT ON(d) * FROM (
WITH j AS (SELECT id AS id2, geom AS geom2 FROM pointst1)
SELECT id,j.id2,ST_Distance(geom, j.geom2) AS d
FROM pointst1,j
WHERE id <> j.id2
ORDER BY id,id2) AS j
id | id2 | d
----+-----+------------------
1 | 2 | 2.85954541841881
3 | 1 | 5.0965184194703
3 | 2 | 7.43911957156222
4 | 3 | 21.0225069865609
4 | 1 | 21.3720495039666
2 | 4 | 23.7492673571207
(6 rows)
A tricky query for postgres. Imagine, I have a set of rows with a boolean column called (for example) success. Like this:
id | success
9 | false
8 | false
7 | true
6 | true
5 | true
4 | false
3 | false
2 | true
1 | false
And I need to calculate a length of the latest (not) successful series. E. g. in this case it would be "3" for successful and "2" for not successful. Or using window functions, then something like:
id | success | length
9 | false | 2
8 | false | 2
7 | true | 3
6 | true | 3
5 | true | 3
4 | false | 1
3 | true | 2
2 | true | 2
1 | false | 1
(note that I generally need a length of only the latest series, not all of those)
The closest answer I've found so far was this article:
https://jaxenter.com/10-sql-tricks-that-you-didnt-think-were-possible-125934.html
(See #5)
However, postgres doesn't support "IGNORE NULLS" option so the query doesn't work. Without "IGNORE NULLS" it simply returns me nulls in length column.
Here is the closest I was able to get:
WITH
trx1(id, success, rn) AS (
SELECT id, success, row_number() OVER (ORDER BY id desc)
FROM results
),
trx2(id, success, rn, lo, hi) AS (
SELECT trx1.*,
CASE WHEN coalesce(lag(success) OVER (ORDER BY id DESC), FALSE) != success THEN rn END,
CASE WHEN coalesce(lead(success) OVER (ORDER BY id DESC), FALSE) != success THEN rn END
FROM trx1
)
SELECT trx2.*, 1
- last_value (lo) IGNORE nulls OVER (ORDER BY id DESC ROWS BETWEEN
UNBOUNDED PRECEDING AND CURRENT ROW)
+ first_value(hi) OVER (ORDER BY id DESC ROWS BETWEEN CURRENT ROW
AND UNBOUNDED FOLLOWING)
AS length FROM trx2;
Do you have any ideas of such a query?
You can use the window function row_number() to designate series:
select max(id) as max_id, success, count(*) as length
from (
select *, row_number() over wa - row_number() over wp as grp
from my_table
window
wp as (partition by success order by id desc),
wa as (order by id desc)
) s
group by success, grp
order by 1 desc
max_id | success | length
--------+---------+--------
9 | f | 2
7 | t | 3
4 | f | 2
2 | t | 1
1 | f | 1
(5 rows)
DbFiddle.
Even though answer by Klin is totally correct, I'd like to post another solution my friend suggested:
with last_success as (
select max(id) id from my_table where success
)
select count(mt.id) last_fails_count
from my_table mt, last_success lt
where mt.id > lt.id;
--------------------
| last_fails_count |
--------------------
| 2 |
--------------------
DbFiddle
It is twice faster if I only need to get the last failing or successful series.
I need to calculate value of some column X based on some other columns of the current record and the value of X for the previous record (using some partition and order). Basically I need to implement query in the form
SELECT <some fields>,
<some expression using LAG(X) OVER(PARTITION BY ... ORDER BY ...) AS X
FROM <table>
This is not possible because only existing columns can be used in window function so I'm looking way how to overcome this.
Here is an example. I have a table with events. Each event has type and time_stamp.
create table event (id serial, type integer, time_stamp integer);
I wan't to find "duplicate" events (to skip them). By duplicate I mean the following. Let's order all events for given type by time_stamp ascending. Then
the first event is not a duplicate
all events that follow non duplicate and are within some time frame after it (that is their time_stamp is not greater then time_stamp of the previous non duplicate plus some constant TIMEFRAME) are duplicates
the next event which time_stamp is greater than previous non duplicate by more than TIMEFRAME is not duplicate
and so on
For this data
insert into event (type, time_stamp)
values
(1, 1), (1, 2), (2, 2), (1,3), (1, 10), (2,10),
(1,15), (1, 21), (2,13),
(1, 40);
and TIMEFRAME=10 result should be
time_stamp | type | duplicate
-----------------------------
1 | 1 | false
2 | 1 | true
3 | 1 | true
10 | 1 | true
15 | 1 | false
21 | 1 | true
40 | 1 | false
2 | 2 | false
10 | 2 | true
13 | 2 | false
I could calculate the value of duplicate field based on current time_stamp and time_stamp of the previous non-duplicate event like this:
WITH evt AS (
SELECT
time_stamp,
CASE WHEN
time_stamp - LAG(current_non_dupl_time_stamp) OVER w >= TIMEFRAME
THEN
time_stamp
ELSE
LAG(current_non_dupl_time_stamp) OVER w
END AS current_non_dupl_time_stamp
FROM event
WINDOW w AS (PARTITION BY type ORDER BY time_stamp ASC)
)
SELECT time_stamp, time_stamp != current_non_dupl_time_stamp AS duplicate
But this does not work because the field which is calculated cannot be referenced in LAG:
ERROR: column "current_non_dupl_time_stamp" does not exist.
So the question: can I rewrite this query to achieve the effect I need?
Naive recursive chain knitter:
-- temp view to avoid nested CTE
CREATE TEMP VIEW drag AS
SELECT e.type,e.time_stamp
, ROW_NUMBER() OVER www as rn -- number the records
, FIRST_VALUE(e.time_stamp) OVER www as fst -- the "group leader"
, EXISTS (SELECT * FROM event x
WHERE x.type = e.type
AND x.time_stamp < e.time_stamp) AS is_dup
FROM event e
WINDOW www AS (PARTITION BY type ORDER BY time_stamp)
;
WITH RECURSIVE ttt AS (
SELECT d0.*
FROM drag d0 WHERE d0.is_dup = False -- only the "group leaders"
UNION ALL
SELECT d1.type, d1.time_stamp, d1.rn
, CASE WHEN d1.time_stamp - ttt.fst > 20 THEN d1.time_stamp
ELSE ttt.fst END AS fst -- new "group leader"
, CASE WHEN d1.time_stamp - ttt.fst > 20 THEN False
ELSE True END AS is_dup
FROM drag d1
JOIN ttt ON d1.type = ttt.type AND d1.rn = ttt.rn+1
)
SELECT * FROM ttt
ORDER BY type, time_stamp
;
Results:
CREATE TABLE
INSERT 0 10
CREATE VIEW
type | time_stamp | rn | fst | is_dup
------+------------+----+-----+--------
1 | 1 | 1 | 1 | f
1 | 2 | 2 | 1 | t
1 | 3 | 3 | 1 | t
1 | 10 | 4 | 1 | t
1 | 15 | 5 | 1 | t
1 | 21 | 6 | 1 | t
1 | 40 | 7 | 40 | f
2 | 2 | 1 | 2 | f
2 | 10 | 2 | 2 | t
2 | 13 | 3 | 2 | t
(10 rows)
An alternative to a recursive approach is a custom aggregate. Once you master the technique of writing your own aggregates, creating transition and final functions is easy and logical.
State transition function:
create or replace function is_duplicate(st int[], time_stamp int, timeframe int)
returns int[] language plpgsql as $$
begin
if st is null or st[1] + timeframe <= time_stamp
then
st[1] := time_stamp;
end if;
st[2] := time_stamp;
return st;
end $$;
Final function:
create or replace function is_duplicate_final(st int[])
returns boolean language sql as $$
select st[1] <> st[2];
$$;
Aggregate:
create aggregate is_duplicate_agg(time_stamp int, timeframe int)
(
sfunc = is_duplicate,
stype = int[],
finalfunc = is_duplicate_final
);
Query:
select *, is_duplicate_agg(time_stamp, 10) over w
from event
window w as (partition by type order by time_stamp asc)
order by type, time_stamp;
id | type | time_stamp | is_duplicate_agg
----+------+------------+------------------
1 | 1 | 1 | f
2 | 1 | 2 | t
4 | 1 | 3 | t
5 | 1 | 10 | t
7 | 1 | 15 | f
8 | 1 | 21 | t
10 | 1 | 40 | f
3 | 2 | 2 | f
6 | 2 | 10 | t
9 | 2 | 13 | f
(10 rows)
Read in the documentation: 37.10. User-defined Aggregates and CREATE AGGREGATE.
This feels more like a recursive problem than windowing function. The following query obtained the desired results:
WITH RECURSIVE base(type, time_stamp) AS (
-- 3. base of recursive query
SELECT x.type, x.time_stamp, y.next_time_stamp
FROM
-- 1. start with the initial records of each type
( SELECT type, min(time_stamp) AS time_stamp
FROM event
GROUP BY type
) x
LEFT JOIN LATERAL
-- 2. for each of the initial records, find the next TIMEFRAME (10) in the future
( SELECT MIN(time_stamp) next_time_stamp
FROM event
WHERE type = x.type
AND time_stamp > (x.time_stamp + 10)
) y ON true
UNION ALL
-- 4. recursive join, same logic as base
SELECT e.type, e.time_stamp, z.next_time_stamp
FROM event e
JOIN base b ON (e.type = b.type AND e.time_stamp = b.next_time_stamp)
LEFT JOIN LATERAL
( SELECT MIN(time_stamp) next_time_stamp
FROM event
WHERE type = e.type
AND time_stamp > (e.time_stamp + 10)
) z ON true
)
-- The actual query:
-- 5a. All records from base are not duplicates
SELECT time_stamp, type, false
FROM base
UNION
-- 5b. All records from event that are not in base are duplicates
SELECT time_stamp, type, true
FROM event
WHERE (type, time_stamp) NOT IN (SELECT type, time_stamp FROM base)
ORDER BY type, time_stamp
There are a lot of caveats with this. It assumes no duplicate time_stamp for a given type. Really the joins should be based on a unique id rather than type and time_stamp. I didn't test this much, but it may at least suggest an approach.
This is my first time to try a LATERAL join. So there may be a way to simplify that moe. Really what I wanted to do was a recursive CTE with the recursive part using MIN(time_stamp) based on time_stamp > (x.time_stamp + 10), but aggregate functions are not allowed in CTEs in that manner. But it seems the lateral join can be used in the CTE.
Related to - PostgreSQL DISTINCT ON with different ORDER BY
I have table purchases (product_id, purchased_at, address_id)
Sample data:
| id | product_id | purchased_at | address_id |
| 1 | 2 | 20 Mar 2012 21:01 | 1 |
| 2 | 2 | 20 Mar 2012 21:33 | 1 |
| 3 | 2 | 20 Mar 2012 21:39 | 2 |
| 4 | 2 | 20 Mar 2012 21:48 | 2 |
The result I expect is the most recent purchased product (full row) for each address_id and that result must be sorted in descendant order by the purchased_at field:
| id | product_id | purchased_at | address_id |
| 4 | 2 | 20 Mar 2012 21:48 | 2 |
| 2 | 2 | 20 Mar 2012 21:33 | 1 |
Using query:
SELECT DISTINCT ON (address_id) purchases.address_id, purchases.*
FROM "purchases"
WHERE "purchases"."product_id" = 2
ORDER BY purchases.address_id ASC, purchases.purchased_at DESC
I'm getting:
| id | product_id | purchased_at | address_id |
| 2 | 2 | 20 Mar 2012 21:33 | 1 |
| 4 | 2 | 20 Mar 2012 21:48 | 2 |
So the rows is same, but order is wrong. Any way to fix it?
Quite a clear question :)
SELECT t1.* FROM purchases t1
LEFT JOIN purchases t2
ON t1.address_id = t2.address_id AND t1.purchased_at < t2.purchased_at
WHERE t2.purchased_at IS NULL
ORDER BY t1.purchased_at DESC
And most likely a faster approach:
SELECT t1.* FROM purchases t1
JOIN (
SELECT address_id, max(purchased_at) max_purchased_at
FROM purchases
GROUP BY address_id
) t2
ON t1.address_id = t2.address_id AND t1.purchased_at = t2.max_purchased_at
ORDER BY t1.purchased_at DESC
Your ORDER BY is used by DISTINCT ON for picking which row for each distinct address_id to produce. If you then want to order the resulting records, make the DISTINCT ON a subselect and order its results:
SELECT * FROM
(
SELECT DISTINCT ON (address_id) purchases.address_id, purchases.*
FROM "purchases"
WHERE "purchases"."product_id" = 2
ORDER BY purchases.address_id ASC, purchases.purchased_at DESC
) distinct_addrs
order by distinct_addrs.purchased_at DESC
This query is trickier to rephrase properly than it looks.
The currently accepted, join-based answer doesn’t correctly handle the case where two candidate rows have the same given purchased_at value: it will return both rows.
You can get the right behaviour this way:
SELECT * FROM purchases AS given
WHERE product_id = 2
AND NOT EXISTS (
SELECT NULL FROM purchases AS other
WHERE given.address_id = other.address_id
AND (given.purchased_at < other.purchased_at OR given.id < other.id)
)
ORDER BY purchased_at DESC
Note how it has a fallback of comparing id values to disambiguate the case in which the purchased_at values match. This ensures that the condition can only ever be true for a single row among those that have the same address_id value.
The original query using DISTINCT ON handles this case automatically!
Also note the way that you are forced to encode the fact that you want “the latest for each address_id” twice, both in the given.purchased_at < other.purchased_at condition and the ORDER BY purchased_at DESC clause, and you have to make sure they match. I had to spend a few extra minutes to convince myself that this query is really positively correct.
It’s much easier to write this query correctly and understandbly by using DISTINCT ON together with an outer subquery, as suggested by dbenhur.
Try this !
SELECT DISTINCT ON (address_id) *
FROM purchases
WHERE product_id = 2
ORDER BY address_id, purchased_at DESC