How to order rows with linked parts in PostgreSQL - postgresql

I have a table A with columns: id, title, condition
And i have another table B with information about position for some rows from table A. Table B have columns id, next_id, prev_id
How to sort rows from A based on information from table B?
For example,
Table A
id| title
---+-----
1 | title1
2 | title2
3 | title3
4 | title4
5 | title5
Table B
id| next_id | prev_id
---+-----
2 | 1 | null
5 | 4 | 3
I want to get this result:
id| title
---+-----
2 | title2
1 | title1
3 | title3
5 | title5
4 | title4
And after apply this sort, i want to sort by condition column yet.
I've already spent a lot of time looking for a solution, and hope for your help.


You have to add weights to your data, so you can order accordingly. This example uses next_id, not sure if you need to use prev_id, you don't explain the use of it.
Anyway, here's a code example:
-- Temporal Data for the test:
CREATE TEMP TABLE table_a(id integer,tittle text);
CREATE TEMP TABLE table_b(id integer,next_id integer, prev_id integer);
INSERT INTO table_a VALUES
(1,'title1'),
(2,'title2'),
(3,'title3'),
(4,'title4'),
(5,'title5');
INSERT INTO table_b VALUES
(2,1,null),
(5,4,3);
-- QUERY:
SELECT
id,tittle,
CASE -- Adding weight
WHEN next_id IS NULL THEN (id + 0.1)
ELSE next_id
END AS orden
FROM -- Joining tables
(SELECT ta.*,tb.next_id
FROM table_a ta
LEFT JOIN table_b tb
ON ta.id=tb.id)join_a_b
ORDER BY orden
And here's the result:
id | tittle | orden
--------------------------
2 | title2 | 1
1 | title1 | 1.1
3 | title3 | 3.1
5 | title5 | 4
4 | title4 | 4.1

Related

T-SQL. HOW to create a table with a sequence of values

I have a table with a list of names and indices. For example like this:
ID | Name | Index
1 | Value 1 | 3
2 | Value 2 | 4
...
N | Value N | NN
I need to create a new table, where every value from field "Name" will be repeat repeated as many times as the "Index" field is specified. For example like this:
ID | Name_2 | ID_2
1 | Value 1 | 1
2 | Value 1 | 2
3 | Value 1 | 3
4 | Value 2 | 1
5 | Value 2 | 2
6 | Value 2 | 3
7 | Value 2 | 4
...
N | Value N | 1
N+1| Value N | 2
...
I have no idea how to write a cycle to get such result. Please, give me an advice.

Here is solution to repeat the rows based on a column value
declare #order table ( Id int, name varchar(20), indx int)
Insert into #order
(Id, name, indx)
VALUES
(1,'Value1',3),
(2,'Value2',4),
(3,'Value3',2)
;WITH cte AS
(
SELECT * FROM #order
UNION ALL
SELECT cte.[ID], cte.name, (cte.indx - 1) indx
FROM cte INNER JOIN #order t
ON cte.[ID] = t.[ID]
WHERE cte.indx > 1
)
SELECT ROW_NUMBER() OVER(ORDER BY name ASC) AS Id, name as [name_2], 1 as [Id_2]
FROM cte
ORDER BY 1

DB2 SQL to aggregate value for months with no gaps

I have 2 tables which I need to join against, along with a table that is generated inline using WITH. The WITH is a daterange, and I need to display all rows from 1 table for all months, even where no data exists in the 2nd table.
This is the data within the tables :
Table REFERRAL_GROUPINGS
referral_group
--------------
VER
FRD
FCC
Table DATA_VALUES
referral_group | task_date | task_id | over_threshold
---------------+------------+---------+---------------
VER | 2015-10-01 | 10 | 0
FRD | 2015-11-04 | 20 | 1
The date range will need to select 3 months :
Oct-2015
Nov-2015
Dec-2015
The data I expect to end up with will be :
MonthYear | referral_group | count_of_group | total_over_threshold
----------+----------------+----------------+---------------------
Oct-2015 | VER | 1 | 0
Oct-2015 | FRD | 0 | 0
Oct-2015 | FCC | 0 | 0
Nov-2015 | VER | 0 | 0
Nov-2015 | FRD | 1 | 1
Nov-2015 | FCC | 0 | 0
Dec-2015 | VER | 0 | 0
Dec-2015 | FRD | 0 | 0
Dec-2015 | FCC | 0 | 0
DDL to create the 2 tables and populate with data is as below..
CREATE TABLE test_data (
referral_group char(3),
task_date date,
task_id integer,
over_threshold integer);
insert into test_data values
('VER','2015-10-01',10,1),
('FRD','2015-11-04',20,0);
CREATE TABLE referral_grouper (
referral_group char(3));
insert into referral_grouper values
('FRD'),
('VER'),
('FCC');
This is a very cut-down example which uses the minimal tables/columns for this example, which is why I have no primary keys/indexes.
I can get this running under LUW no problem, by using NOT EXISTS in the joins as per this SQL.
WITH DATERANGE(FROM_DTE,yyyymm, TO_DTE) AS
(
SELECT DATE('2015-10-01'), YEAR('2015-10-01')*100+MONTH('2015-10-01'), '2015-12-31'
FROM SYSIBM.SYSDUMMY1
UNION ALL
SELECT FROM_DTE + 1 DAY, YEAR(FROM_DTE+1 DAY)*100+MONTH(FROM_DTE+1 DAY), TO_DTE
FROM DATERANGE
WHERE FROM_DTE < TO_DTE
)
select
referral_grouper.referral_group,
daterange.yyyymm,
count(test_data.task_id) AS total_count,
COALESCE(SUM(over_threshold),0) AS total_over_threshold
FROM
test_data
RIGHT OUTER JOIN daterange ON (daterange.from_dte=test_data.task_date OR NOT EXISTS (SELECT 1 FROM daterange d2 WHERE d2.from_dte=test_data.task_date))
RIGHT OUTER JOIN referral_grouper ON (referral_grouper.referral_group=test_data.referral_group OR NOT EXISTS (SELECT 1 FROM referral_grouper g2 WHERE g2.referral_group=test_data.referral_group))
GROUP BY
referral_grouper.referral_group,
daterange.yyyymm
However... This needs to work on ZOS, and under ZOS you cannot use subqueries with EXISTS in a join. Removing the NOT EXISTS means the non existing rows no longer show up.
There must be a way to write the SQL to return all rows from the 2 linking tables without using NOT EXISTS, but I just cannot seem to find it. Any help with this would be very appreciated as it has me stumped

How to eliminate repeated field with GROUP BY clause?

I have 3 tables called:
1.app_tenant pk:id, fk:pasar_id
---+--------+-----------+
id | nama | pasar_id |
----+--------+-----------+
1 | joe | 1 |
2 | adi | 2 |
3 | adam | 3 |
2.app_pasar pk:id
----+------------- +
id | nama |
----+------------- +
1 | kosambi |
2 | gede bage |
3 | pasar minggu |
3.app_kios pk:id, fk:tenant_id
----+---------------+----------
id | nama |tenant_id
----+-------------- +----------
1 | kios1 |1
2 | kios2 |2
3 | kios3 |3
4 | kios4 |1
5 | kios5 |1
6 | kios6 |2
7 | kios7 |2
8 | kios8 |3
9 | kios9 |3
Then with a LEFT JOIN query and grouping by id in every table I want to displaying data like this:
----+---------------+------------+-----------
id | nama_tenant |nama_pasar |nama_kios
----+-------------- +------------------------
1 | joe |kosambi |kios 1
2 | adi |gede bage |kios 2
2 | adam |pasar minggu|kios 3
but after I execute this query, data are not shown as expected. The problem is
redundancy in the nama_tenant field. How can I eliminate repeated nama_tenantrecords?
This is my query:
select a.id,a.nama as nama_tenant,
b.nama as nama_pasar,
c.nama as nama_kios
from app_tenant a
left join app_pasar b on a.id=b.id
left join app_kios c on a.id= c.tenant_id
group by
a.id,
b.id,
c.id
Table definitions:
CREATE TABLE app_tenant (
id serial PRIMARY KEY,
nama character varying,
pasar_id integer);
CREATE TABLE app_kios (
id serial PRIMARY KEY,
nama character varying,
tenant_id integer REFERENCES app_tenant);

The problem is that tenants can have multiple kiosks. From your sample data it looks like you want to display the first kiosk of every tenant (although "first" is a vague concept on strings, here I use alphabetical sort order). Your query would be like this:
SELECT t.id, t.nama AS nama_tenant, p.nama AS nama_pasar, k.nama AS nama_kios
FROM app_tenant t
LEFT JOIN app_pasar p ON p.id = t.pasar_id
LEFT JOIN (
SELECT tenant_id, nama, rank() OVER (PARTITION BY tenant_id ORDER BY nama) AS rnk
FROM app_kios
WHERE rnk = 1) k ON k.tenant_id = t.id
ORDER BY t.id
The sub-query on app_kios uses a window function to get the first kiosk name after sorting the names of the kiosk for each tenant.
I would also suggest to use meaningful aliases for table names instead of simply a, b, c.

SQL Server recursive query·

I have a table in SQL Server 2008 R2 which contains product orders. For the most part, it is one entry per product
ID | Prod | Qty
------------
1 | A | 1
4 | B | 1
7 | A | 1
8 | A | 1
9 | A | 1
12 | C | 1
15 | A | 1
16 | A | 1
21 | B | 1
I want to create a view based on the table which looks like this
ID | Prod | Qty
------------------
1 | A | 1
4 | B | 1
9 | A | 3
12 | C | 1
16 | A | 2
21 | B | 1
I've written a query using a table expression, but I am stumped on how to make it work. The sql below does not actually work, but is a sample of what I am trying to do. I've written this query multiple different ways, but cannot figure out how to get the right results. I am using row_number to generate a sequential id. From that, I can order and compare consecutive rows to see if the next row has the same product as the previous row since ReleaseId is sequential, but not necessarily contiguous.
;with myData AS
(
SELECT
row_number() over (order by a.ReleaseId) as 'Item',
a.ReleaseId,
a.ProductId,
a.Qty
FROM OrdersReleased a
UNION ALL
SELECT
row_number() over (order by b.ReleaseId) as 'Item',
b.ReleaseId,
b.ProductId,
b.Qty
FROM OrdersReleased b
INNER JOIN myData c ON b.Item = c.Item + 1 and b.ProductId = c.ProductId
)
SELECT * from myData

Usually you drop the ID out of something like this, since it is a summary.
SELECT a.ProductId,
SUM(a.Qty) AS Qty
FROM OrdersReleased a
GROUP BY a.ProductId
ORDER BY a.ProductId
-- if you want to do sub query you can do it as a column (if you don't have a very large dataset).
SELECT a.ProductId,
SUM(a.Qty) AS Qty,
(SELECT COUNT(1)
FROM OrdersReleased b
WHERE b.ReleasedID - 1 = a.ReleasedID
AND b.ProductId = b.ProductId) as NumberBackToBack
FROM OrdersReleased a
GROUP BY a.ProductId
ORDER BY a.ProductId

Equivalent to unpivot() in PostgreSQL

Is there a unpivot equivalent function in PostgreSQL?

Create an example table:
CREATE TEMP TABLE foo (id int, a text, b text, c text);
INSERT INTO foo VALUES (1, 'ant', 'cat', 'chimp'), (2, 'grape', 'mint', 'basil');
You can 'unpivot' or 'uncrosstab' using UNION ALL:
SELECT id,
'a' AS colname,
a AS thing
FROM foo
UNION ALL
SELECT id,
'b' AS colname,
b AS thing
FROM foo
UNION ALL
SELECT id,
'c' AS colname,
c AS thing
FROM foo
ORDER BY id;
This runs 3 different subqueries on foo, one for each column we want to unpivot, and returns, in one table, every record from each of the subqueries.
But that will scan the table N times, where N is the number of columns you want to unpivot. This is inefficient, and a big problem when, for example, you're working with a very large table that takes a long time to scan.
Instead, use:
SELECT id,
unnest(array['a', 'b', 'c']) AS colname,
unnest(array[a, b, c]) AS thing
FROM foo
ORDER BY id;
This is easier to write, and it will only scan the table once.
array[a, b, c] returns an array object, with the values of a, b, and c as it's elements.
unnest(array[a, b, c]) breaks the results into one row for each of the array's elements.

You could use VALUES() and JOIN LATERAL to unpivot the columns.
Sample data:
CREATE TABLE test(id int, a INT, b INT, c INT);
INSERT INTO test(id,a,b,c) VALUES (1,11,12,13),(2,21,22,23),(3,31,32,33);
Query:
SELECT t.id, s.col_name, s.col_value
FROM test t
JOIN LATERAL(VALUES('a',t.a),('b',t.b),('c',t.c)) s(col_name, col_value) ON TRUE;
DBFiddle Demo
Using this approach it is possible to unpivot multiple groups of columns at once.
EDIT
Using Zack's suggestion:
SELECT t.id, col_name, col_value
FROM test t
CROSS JOIN LATERAL (VALUES('a', t.a),('b', t.b),('c',t.c)) s(col_name, col_value);
<=>
SELECT t.id, col_name, col_value
FROM test t
,LATERAL (VALUES('a', t.a),('b', t.b),('c',t.c)) s(col_name, col_value);
db<>fiddle demo

Great article by Thomas Kellerer found here
Unpivot with Postgres
Sometimes it’s necessary to normalize de-normalized tables - the opposite of a “crosstab” or “pivot” operation. Postgres does not support an UNPIVOT operator like Oracle or SQL Server, but simulating it, is very simple.
Take the following table that stores aggregated values per quarter:
create table customer_turnover
(
customer_id integer,
q1 integer,
q2 integer,
q3 integer,
q4 integer
);
And the following sample data:
customer_id | q1 | q2 | q3 | q4
------------+-----+-----+-----+----
1 | 100 | 210 | 203 | 304
2 | 150 | 118 | 422 | 257
3 | 220 | 311 | 271 | 269
But we want the quarters to be rows (as they should be in a normalized data model).
In Oracle or SQL Server this could be achieved with the UNPIVOT operator, but that is not available in Postgres. However Postgres’ ability to use the VALUES clause like a table makes this actually quite easy:
select c.customer_id, t.*
from customer_turnover c
cross join lateral (
values
(c.q1, 'Q1'),
(c.q2, 'Q2'),
(c.q3, 'Q3'),
(c.q4, 'Q4')
) as t(turnover, quarter)
order by customer_id, quarter;
will return the following result:
customer_id | turnover | quarter
------------+----------+--------
1 | 100 | Q1
1 | 210 | Q2
1 | 203 | Q3
1 | 304 | Q4
2 | 150 | Q1
2 | 118 | Q2
2 | 422 | Q3
2 | 257 | Q4
3 | 220 | Q1
3 | 311 | Q2
3 | 271 | Q3
3 | 269 | Q4
The equivalent query with the standard UNPIVOT operator would be:
select customer_id, turnover, quarter
from customer_turnover c
UNPIVOT (turnover for quarter in (q1 as 'Q1',
q2 as 'Q2',
q3 as 'Q3',
q4 as 'Q4'))
order by customer_id, quarter;

FYI for those of us looking for how to unpivot in RedShift.
The long form solution given by Stew appears to be the only way to accomplish this.
For those who cannot see it there, here is the text pasted below:
We do not have built-in functions that will do pivot or unpivot. However,
you can always write SQL to do that.
create table sales (regionid integer, q1 integer, q2 integer, q3 integer, q4 integer);
insert into sales values (1,10,12,14,16), (2,20,22,24,26);
select * from sales order by regionid;
regionid | q1 | q2 | q3 | q4
----------+----+----+----+----
1 | 10 | 12 | 14 | 16
2 | 20 | 22 | 24 | 26
(2 rows)
pivot query
create table sales_pivoted (regionid, quarter, sales)
as
select regionid, 'Q1', q1 from sales
UNION ALL
select regionid, 'Q2', q2 from sales
UNION ALL
select regionid, 'Q3', q3 from sales
UNION ALL
select regionid, 'Q4', q4 from sales
;
select * from sales_pivoted order by regionid, quarter;
regionid | quarter | sales
----------+---------+-------
1 | Q1 | 10
1 | Q2 | 12
1 | Q3 | 14
1 | Q4 | 16
2 | Q1 | 20
2 | Q2 | 22
2 | Q3 | 24
2 | Q4 | 26
(8 rows)
unpivot query
select regionid, sum(Q1) as Q1, sum(Q2) as Q2, sum(Q3) as Q3, sum(Q4) as Q4
from
(select regionid,
case quarter when 'Q1' then sales else 0 end as Q1,
case quarter when 'Q2' then sales else 0 end as Q2,
case quarter when 'Q3' then sales else 0 end as Q3,
case quarter when 'Q4' then sales else 0 end as Q4
from sales_pivoted)
group by regionid
order by regionid;
regionid | q1 | q2 | q3 | q4
----------+----+----+----+----
1 | 10 | 12 | 14 | 16
2 | 20 | 22 | 24 | 26
(2 rows)
Hope this helps, Neil

Pulling slightly modified content from the link in the comment from #a_horse_with_no_name into an answer because it works:
Installing Hstore
If you don't have hstore installed and are running PostgreSQL 9.1+, you can use the handy
CREATE EXTENSION hstore;
For lower versions, look for the hstore.sql file in share/contrib and run in your database.
Assuming that your source (e.g., wide data) table has one 'id' column, named id_field, and any number of 'value' columns, all of the same type, the following will create an unpivoted view of that table.
CREATE VIEW vw_unpivot AS
SELECT id_field, (h).key AS column_name, (h).value AS column_value
FROM (
SELECT id_field, each(hstore(foo) - 'id_field'::text) AS h
FROM zcta5 as foo
) AS unpiv ;
This works with any number of 'value' columns. All of the resulting values will be text, unless you cast, e.g., (h).value::numeric.

Just use JSON:
with data (id, name) as (
values (1, 'a'), (2, 'b')
)
select t.*
from data, lateral jsonb_each_text(to_jsonb(data)) with ordinality as t
order by data.id, t.ordinality;
This yields
|key |value|ordinality|
|----|-----|----------|
|id |1 |1 |
|name|a |2 |
|id |2 |1 |
|name|b |2 |
dbfiddle

I wrote a horrible unpivot function for PostgreSQL. It's rather slow but it at least returns results like you'd expect an unpivot operation to.
https://cgsrv1.arrc.csiro.au/blog/2010/05/14/unpivotuncrosstab-in-postgresql/
Hopefully you can find it useful..

Depending on what you want to do... something like this can be helpful.
with wide_table as (
select 1 a, 2 b, 3 c
union all
select 4 a, 5 b, 6 c
)
select unnest(array[a,b,c]) from wide_table

You can use FROM UNNEST() array handling to UnPivot a dataset, tandem with a correlated subquery (works w/ PG 9.4).
FROM UNNEST() is more powerful & flexible than the typical method of using FROM (VALUES .... ) to unpivot datasets. This is b/c FROM UNNEST() is variadic (with n-ary arity). By using a correlated subquery the need for the lateral ORDINAL clause is eliminated, & Postgres keeps the resulting parallel columnar sets in the proper ordinal sequence.
This is, BTW, FAST -- in practical use spawning 8 million rows in < 15 seconds on a 24-core system.
WITH _students AS ( /** CTE **/
SELECT * FROM
( SELECT 'jane'::TEXT ,'doe'::TEXT , 1::INT
UNION
SELECT 'john'::TEXT ,'doe'::TEXT , 2::INT
UNION
SELECT 'jerry'::TEXT ,'roe'::TEXT , 3::INT
UNION
SELECT 'jodi'::TEXT ,'roe'::TEXT , 4::INT
) s ( fn, ln, id )
) /** end WITH **/
SELECT s.id
, ax.fanm -- field labels, now expanded to two rows
, ax.anm -- field data, now expanded to two rows
, ax.someval -- manually incl. data
, ax.rankednum -- manually assigned ranks
,ax.genser -- auto-generate ranks
FROM _students s
,UNNEST /** MULTI-UNNEST() BLOCK **/
(
( SELECT ARRAY[ fn, ln ]::text[] AS anm -- expanded into two rows by outer UNNEST()
/** CORRELATED SUBQUERY **/
FROM _students s2 WHERE s2.id = s.id -- outer relation
)
,( /** ordinal relationship preserved in variadic UNNEST() **/
SELECT ARRAY[ 'first name', 'last name' ]::text[] -- exp. into 2 rows
AS fanm
)
,( SELECT ARRAY[ 'z','x','y'] -- only 3 rows gen'd, but ordinal rela. kept
AS someval
)
,( SELECT ARRAY[ 1,2,3,4,5 ] -- 5 rows gen'd, ordinal rela. kept.
AS rankednum
)
,( SELECT ARRAY( /** you may go wild ... **/
SELECT generate_series(1, 15, 3 )
AS genser
)
)
) ax ( anm, fanm, someval, rankednum , genser )
;
RESULT SET:
+--------+----------------+-----------+----------+---------+-------
| id | fanm | anm | someval |rankednum| [ etc. ]
+--------+----------------+-----------+----------+---------+-------
| 2 | first name | john | z | 1 | .
| 2 | last name | doe | y | 2 | .
| 2 | [null] | [null] | x | 3 | .
| 2 | [null] | [null] | [null] | 4 | .
| 2 | [null] | [null] | [null] | 5 | .
| 1 | first name | jane | z | 1 | .
| 1 | last name | doe | y | 2 | .
| 1 | | | x | 3 | .
| 1 | | | | 4 | .
| 1 | | | | 5 | .
| 4 | first name | jodi | z | 1 | .
| 4 | last name | roe | y | 2 | .
| 4 | | | x | 3 | .
| 4 | | | | 4 | .
| 4 | | | | 5 | .
| 3 | first name | jerry | z | 1 | .
| 3 | last name | roe | y | 2 | .
| 3 | | | x | 3 | .
| 3 | | | | 4 | .
| 3 | | | | 5 | .
+--------+----------------+-----------+----------+---------+ ----

Here's a way that combines the hstore and CROSS JOIN approaches from other answers.
It's a modified version of my answer to a similar question, which is itself based on the method at https://blog.sql-workbench.eu/post/dynamic-unpivot/ and another answer to that question.
-- Example wide data with a column for each year...
WITH example_wide_data("id", "2001", "2002", "2003", "2004") AS (
VALUES
(1, 4, 5, 6, 7),
(2, 8, 9, 10, 11)
)
-- that is tided to have "year" and "value" columns
SELECT
id,
r.key AS year,
r.value AS value
FROM
example_wide_data w
CROSS JOIN
each(hstore(w.*)) AS r(key, value)
WHERE
-- This chooses columns that look like years
-- In other cases you might need a different condition
r.key ~ '^[0-9]{4}$';
It has a few benefits over other solutions:
By using hstore and not jsonb, it hopefully minimises issues with type conversions (although hstore does convert everything to text)
The columns don't need to be hard coded or known in advance. Here, columns are chosen by a regex on the name, but you could use any SQL logic based on the name, or even the value.
It doesn't require PL/pgSQL - it's all SQL