Is there anyway to join two tables on multiple potential conditions?
I'm currently migrating some code from Postgres to Bigquery where I joined on multiple potential values like:
SELECT
*
FROM
(
SELECT
offer_table.offer_id
,customer_table.customer_name
,customer_table.visit_count
,ROW_NUMBER() OVER (PARTITION BY offer_table.offer_id ORDER BY customer_table.visit_count DESC) AS customer_visit_rank
FROM
offer_table
LEFT JOIN customer_table ON
(
offer_table.customer_id = customer_table.customer_id
OR offer_table.email = customer_table.email
OR offer_table.phone = customer_table.phone
)
) dummy
WHERE
customer_visit_rank = 1
I needed to this because my offer and customer data had inconsistent usage of our id, email, and phone fields but all were valid potential matches. If multiple fields worked (ex: id and email matched), there would be duplicate rows and I'd filter them out based on the row_number column after ranking using the ORDER BY section.
However when I try to join on multiple conditions in BigQuery, I get this error message:
LEFT OUTER JOIN cannot be used without a condition that is an equality of fields from both sides of the join.
Has anyone figured out a solution to join on multiple values instead of doing the above?
You can write separate queries, then use COALESCE
:
SELECT
*
FROM
(
SELECT
offer_table.offer_id
,COALESCE(c1.customer_name,c2.customer_name,c3.customer_name)
,COALESCE(c1.visit_count,c2.visit_count,c3.visit_count)
,ROW_NUMBER() OVER (PARTITION BY offer_table.offer_id ORDER BY customer_table.visit_count DESC) AS customer_visit_rank
FROM
offer_table
LEFT JOIN customer_table c1
ON offer_table.customer_id = customer_table.customer_id
LEFT JOIN customer_table c2
ON offer_table.email = customer_table.email
LEFT JOIN customer_table c3
ON offer_table.phone = customer_table.phone
)
) AS dummy
WHERE
customer_visit_rank = 1
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