Pivot for redshift database - sql

Question

I know this question has been asked before but any of the answers were not able to help me to meet my desired requirements. So asking the question in new thread
In redshift how can use pivot the data into a form of one row per each unique dimension set, e.g.:
id Name Category count
8660 Iced Chocolate Coffees 105
8660 Iced Chocolate Milkshakes 10
8662 Old Monk Beer 29
8663 Burger Snacks 18
to
id Name Cofees Milkshakes Beer Snacks
8660 Iced Chocolate 105 10 0 0
8662 Old Monk 0 0 29 0
8663 Burger 0 0 0 18
The category listed above gets keep on changing.
Redshift does not support the pivot operator and a case expression would not be of much help (if not please suggest how to do it)
How can I achieve this result in redshift?
(The above is just an example, we would have 1000+ categories and these categories keep's on changing)

Answer 1

i don't think there is a easy way to do that in Redshift,
also you say you have more then 1000 categories and the number is growing
you need to taking in to account you have limit of 1600 columns per table,
see attached link
[http://docs.aws.amazon.com/redshift/latest/dg/r_CREATE_TABLE_usage.html][1]
you can use case but then you need to create case for each category
select id,
name,
sum(case when Category='Coffees' then count end) as Cofees,
sum(case when Category='Milkshakes' then count end) as Milkshakes,
sum(case when Category='Beer' then count end) as Beer,
sum(case when Category='Snacks' then count end) as Snacks
from my_table
group by 1,2
other option you have is to upload the table for example to R and then you can use cast function for example.
cast(data, name~ category)
and then upload the data back to S3 or Redshift

Answer 2

We do a lot of pivoting at Ro - we built python based tool for autogenerating pivot queries. This tool allows for the same basic options as what you'd find in excel, including specifying aggregation functions as well as whether you want overall aggregates.

Answer 3

Redshift released a Pivot/Unpivot functionality on last re:Invent 2021 (December 2021): https://docs.aws.amazon.com/redshift/latest/dg/r_FROM_clause-pivot-unpivot-examples.html
SELECT *
FROM (SELECT id, Name, Category, count FROM my_table) PIVOT (
SUM(count) FOR Category IN ('Coffees', 'Milkshakes', 'Beer', 'Snacks')
);

Answer 4

If you will typically want to query specific subsets of the categories from the pivot table, a workaround based on the approach linked in the comments might work.
You can populate your "pivot_table" from the original like so:
insert into pivot_table (id, Name, json_cats) (
select id, Name,
'{' || listagg(quote_ident(Category) || ':' || count, ',')
within group (order by Category) || '}' as json_cats
from to_pivot
group by id, Name
)
And access specific categories this way:
select id, Name,
nvl(json_extract_path_text(json_cats, 'Snacks')::int, 0) Snacks,
nvl(json_extract_path_text(json_cats, 'Beer')::int, 0) Beer
from pivot_table
Using varchar(max) for the JSON column type will give 65535 bytes which should be room for a couple thousand categories.

Answer 5

#user3600910 is right with the approach however 'END' is required else '500310' invalid operation would occur.
select id,
name,
sum(case when Category='Coffees' then count END) as Cofees,
sum(case when Category='Milkshakes' then count END) as Milkshakes,
sum(case when Category='Beer' then count END) as Beer,
sum(case when Category='Snacks' then count END) as Snacks
from my_table
group by 1,2

Answer 6

The answer given above worked for me after switching count to 1
select id,
name,
sum(case when Category='Coffees' then 1 end) as Cofees,
sum(case when Category='Milkshakes' then 1 end) as Milkshakes,
sum(case when Category='Beer' then 1 end) as Beer,
sum(case when Category='Snacks' then 1 end) as Snacks
from my_table
group by 1,2