I have a table of surveys which contains (amongst others) the following columns
survey_id - unique id
user_id - the id of the person the survey relates to
created - datetime
ip_address - of the submission
ip_count - the number of duplicates
Due to a large record set, its impractical to run this query on the fly, so trying to create an update statement which will periodically store a "cached" result in ip_count.
The purpose of the ip_count is to show the number of duplicate ip_address survey submissions have been recieved for the same user_id with a 12 month period (+/- 6months of created date).
Using the following dataset, this is the expected result.
survey_id user_id created ip_address ip_count #counted duplicates survey_id
1 1 01-Jan-12 123.132.123 1 # 2
2 1 01-Apr-12 123.132.123 2 # 1, 3
3 2 01-Jul-12 123.132.123 0 #
4 1 01-Aug-12 123.132.123 3 # 2, 6
6 1 01-Dec-12 123.132.123 1 # 4
This is the closest solution I have come up with so far but this query is failing to take into account the date restriction and struggling to come up with an alternative method.
UPDATE surveys
JOIN(
SELECT ip_address, created, user_id, COUNT(*) AS total
FROM surveys
WHERE surveys.state IN (1, 3) # survey is marked as completed and confirmed
GROUP BY ip_address, user_id
) AS ipCount
ON (
ipCount.ip_address = surveys.ip_address
AND ipCount.user_id = surveys.user_id
AND ipCount.created BETWEEN (surveys.created - INTERVAL 6 MONTH) AND (surveys.created + INTERVAL 6 MONTH)
)
SET surveys.ip_count = ipCount.total - 1 # minus 1 as this query will match on its own id.
WHERE surveys.ip_address IS NOT NULL # ignore surveys where we have no ip_address
Thank you for you help in advance :)