Redshift subquery not accepted - sql

Question

I'm trying to execute the following query against my dataset stored in Redshift:
SELECT v_users.user_id AS user_id,
v_users.first_name AS first_name,
v_users.email AS email,
COALESCE(v_users.country, accounts.region) AS country_code,
profiles.language AS language,
v_users.mobilenum AS mobile_num,
NULL as mobile_verification_date,
COALESCE(v_users.registration_date, accounts.date_created) AS activation_date,
EXISTS (SELECT 1
FROM cds.user_session_201612 AS users_session,
cds.access_logs_summary_201612 AS access_logs_summary,
views_legacy AS views_legacy
WHERE users_session.userid = v_users.user_id
OR access_logs_summary.userid = v_users.user_id
OR views_legacy.user_id = v_users.user_id) AS has_viewed,
NULL as preferred_genre_1,
NULL as preferred_genre_2,
NULL as preferred_genre_3
FROM users AS v_users,
users_metadata AS v_users_metadata,
account.account AS accounts,
account.profile AS profiles
WHERE accounts.id = v_users.user_id
AND profiles.id = v_users.user_id
AND v_users_metadata.user_id = v_users.user_id
The problem which I get is the following:
ERROR: This type of correlated subquery pattern is not supported due to internal error
which is caused by the subquery but how can I solve it? can you provide me some suggestions?

Answer 1

Redshift doesn't allow correlated subqueries in the SELECT clause, which I don't think is a limitation as all the examples I've encountered can be otherwise expressed.
I've refactored the subquery as a CTE, and used a left join with an is not null to mark users who have or not viewed some thing.
This particular query below may not work, but any solution will likely take the following form:
WITH has_viewed AS (
SELECT
u.user_id
FROM users u
LEFT JOIN cds.user_session_201612 AS users_session
ON users_session.userid = u.user_id
LEFT JOIN cds.access_logs_summary_201612 AS access_logs_summary
ON access_logs_summary.userid = users.user_id
LEFT JOIN views_legacy
ON views_legacy.user_id = v_users.user_id
WHERE users_session.userid IS NOT NULL
OR access_logs_summary.userid IS NOT NULL
OR views_legacy.user_id
GROUP BY 1
)
SELECT
v_users.user_id AS user_id
, v_users.first_name AS first_name
, v_users.email AS email
, COALESCE(v_users.country, accounts.region) AS country_code
, profiles.language AS language
, v_users.mobilenum AS mobile_num
, NULL as mobile_verification_date
, COALESCE(v_users.registration_date, accounts.date_created) AS activation_date
, has_viewed.user_id IS NOT NULL AS has_viewed
, NULL as preferred_genre_1
, NULL as preferred_genre_2
, NULL as preferred_genre_3
FROM users AS v_users
JOIN users_metadata AS v_users_metadata
ON v_users_metadata.user_id = v_users.user_id
JOIN account.account AS accounts
ON accounts.id = v_users.user_id
JOIN account.profile AS profiles ON profiles.id = v_users.user_id
LEFT JOIN has_viewed
ON has_viewed.user_id = v_users.user_id

Answer 2

I have tried all possible combinations,
SELECT subquery doesn't work
CTE (Common Table Expression) as shown by Haleemur Ali doesn't work either.
Now what I have tried - I needed an alternative to GROUP BY, as redshift doesn't accept GROUP BY.
So I got this solution -
the OVER keyword.
SO as a replacement for GROUP BY I used OVER and PARTITION BY which goes like -
SELECT *
FROM (
SELECT *,ROW_NUMBER()
OVER (PARTITION BY **VARIOUS COLUMNS** ORDER BY datetime DESC) rn
FROM schema.tableName
) derivedTable
WHERE derivedTable.rn = 1;
Maybe OVER might help you out. I am not sure though.