I have a scenario where I'd like to eliminate the number of query-of-queries I'm performing on a page. Let's say I have this, a result set called filtered_table:
SELECT
col_a
,col_b
,col_c
FROM
table
where
col_a = 1
Then I have a set of all possible results, were the query not filtered, distinct_col_a, distinct_col_b, distinct_col_c.
SELECT
distinct col_a
FROM
table
SELECT
distinct col_b
FROM
table
SELECT
distinct col_c
FROM
table
Finally, for each value that distinct_col_a, distinct_col_b, distinct_col_c could contain, I perform a query of queries to get a count in filtered_table.
(for each value in distinct_col_a)
SELECT
count(col_a)
FROM
filtered_table
It's clunky and it's resource-heavy. I feel like there should be some way to do a rollup or something instead of the for each and get these numbers all in one go, but I can't wrap my head around it.
As an example:
table
col_a | col_b | col_c
1 | a | x
2 | b | y
3 | c | z
3 | c | x
1 | d | x
filtered_table, using where col_a = 1
col_a | col_b | col_c
1 | a | x
1 | d | x
The results I'm looking for:
col_name| col_value| number results
col_a | 1 | 2
col_a | 2 | 0
col_a | 3 | 0
col_b | a | 1
col_b | b | 0
col_b | c | 0
col_b | d | 1
col_c | x | 2
col_c | y | 0
col_c | z | 0
We can use a funky combination of unpivot and a separate aggregate to create these results in a fairly compact query:
declare #t table (col_a char(1), col_b char(1), col_c char(1))
insert into #t(col_a,col_b,col_c) values
('1','a','x'),
('2','b','y'),
('3','c','z'),
('3','c','x'),
('1','d','x')
select
col_name, col_value, SUM(Cnt) as results_count
from
(select *,CASE WHEN col_a = 1 THEN 1 ELSE 0 END as Cnt from #t) t
unpivot
(col_value for col_name in (col_a, col_b, col_c)) p
group by col_name,col_value
Result:
col_name col_value results_count
--------- --------- -------------
col_a 1 2
col_a 2 0
col_a 3 0
col_b a 1
col_b b 0
col_b c 0
col_b d 1
col_c x 2
col_c y 0
col_c z 0
(Note - these results came out in the same order as your desired output. But there's currently no ORDER BY clause so that wasn't guaranteed)
Not that you apply your "WHERE clause" instead as a check within the CASE expression. If you can't see how this is working immediately, I'd suggest running
select
*
from
(select *,CASE WHEN col_a = 1 THEN 1 ELSE 0 END as Cnt from #t) t
unpivot
(col_value for col_name in (col_a, col_b, col_c)) p
first to see the effects that the unpivot produces.
Related
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.
I have the following query code
query = """
with double_entry_book as (
SELECT to_address as address, value as value
FROM `bigquery-public-data.crypto_ethereum.traces`
WHERE to_address is not null
AND block_timestamp < '2022-01-01 00:00:00'
AND status = 1
AND (call_type not in ('delegatecall', 'callcode', 'staticcall') or call_type is null)
union all
-- credits
SELECT from_address as address, -value as value
FROM `bigquery-public-data.crypto_ethereum.traces`
WHERE from_address is not null
AND block_timestamp < '2022-01-01 00:00:00'
AND status = 1
AND (call_type not in ('delegatecall', 'callcode', 'staticcall') or call_type is null)
union all
)
SELECT address,
sum(value) / 1000000000000000000 as balance
from double_entry_book
group by address
order by balance desc
LIMIT 15000000
"""
In the last part, I want to drop rows where "balance" is less than, let's say, 0.02 and then group, order, etc. I imagine this should be a simple code. Any help will be appreciated!
We can delete on a CTE and use returning to get the id's of the rows being deleted, but they still exist until the transaction is comitted.
CREATE TABLE t (
id serial,
variale int);
insert into t (variale) values
(1),(2),(3),(4),(5);
✓
5 rows affected
with del as
(delete from t
where variale < 3
returning id)
select
t.id,
t.variale,
del.id ids_being_deleted
from t
left join del
on t.id = del.id;
id | variale | ids_being_deleted
-: | ------: | ----------------:
1 | 1 | 1
2 | 2 | 2
3 | 3 | null
4 | 4 | null
5 | 5 | null
select * from t;
id | variale
-: | ------:
3 | 3
4 | 4
5 | 5
db<>fiddle here
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 have some sql which has some hard coded values which I am trying to replace with values from a database column
with pre as (
with a(k, v) as (select id, my_column from mytable),
col(s, n) as (select * from unnest(array['Title', 'First', 'Middle', 'Last']) with ordinality c (s, n))
I'm trying to replace the unnest sql with something like this:
select unnest(string_to_array(my_column, ':')) as elements from mytable
mycolumn contents vary in length but an example could be title=aaa:first=bbb:middle=ccc:last=ddd
Thanks
I base my answer on your previous post. Here is an example of how you can join unnest(string_to_array(my_column, ':')) with named columns on ordinality:
t=# with a as (select id,k,v from my_table, unnest(string_to_array(my_column, ':')) with ordinality as t(k,v))
, col(s, n) as (select * from unnest(array['Title', 'First', 'Middle', 'Last']) with ordinality c (s, n))
select * from a join col on n=v;
id | k | v | s | n
----+------------+---+--------+---
1 | title=aaa | 1 | Title | 1
1 | first=bbb | 2 | First | 2
1 | middle=ccc | 3 | Middle | 3
1 | last=ddd | 4 | Last | 4
(4 rows)
Of course you will have to join differently (based on your previous post). But if the unclear part was how you select from table instead of select from values, the example above should help.
update
put values to table:
t=# create table keys(t text);
CREATE TABLE
Time: 91.908 ms
t=# insert into keys select unnest(array['Title', 'First', 'Middle', 'Last']);
INSERT 0 4
Time: 11.552 ms
t=# select * from keys ;
t
--------
Title
First
Middle
Last
(4 rows)
and now join against keys table:
t=# with a as (select id,k,v from my_table, unnest(string_to_array(my_column, ':')) with ordinality as t(k,v))
select * from a join keys on split_part(k,'=',1) = lower(t);
id | k | v | t
----+------------+---+--------
1 | first=bbb | 2 | First
1 | last=ddd | 4 | Last
1 | middle=ccc | 3 | Middle
1 | title=aaa | 1 | Title
(4 rows)
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.