In DPQL you can use the LIKE operator in the WHERE clause to check for certain patterns.
You would use it alongside wildcards:
% represents any number of characters
_ represents one character
An example of this you could use would be if you wanted to look at all tickets from users under a specific email domain.
The query below wouldn't work as the email address is incomplete:
SELECT Tickets.id, tickets.person.emails.email FROM tickets WHERE tickets.person.emails.email = 'deskpro.com'
However if rather than = we use Like and the % wildcard we can pull all emails that end in deskpro.com
SELECT Tickets.id, tickets.person.emails.email FROM tickets WHERE tickets.person.emails.email LIKE '%deskpro.com'
Similarly if we wanted to pull all tickets submitted from Deskpro.com and Deskpro.co.uk we could use the following as the second % would bypass the characters specified after deskpro:
SELECT Tickets.id, tickets.person.emails.email FROM tickets WHERE tickets.person.emails.email LIKE '%deskpro%'
You can play around with the way you use wildcards to return values in different scenarios.
Below are some wildcard variations that return firstname.lastname@example.org :
|WHERE person.emails.email||LIKE 'Support%'||Any values that begin with support|
|WHERE person.emails.email||LIKE '%Deskpro.com'||Any values that end with deskpro.com|
|WHERE person.emails.email||LIKE '%Deskpro%'||Any values that contain Deskpro|
|WHERE person.emails.email||LIKE 's%m'||Any value that starts with S and ends with M|
|WHERE person.emails.email||LIKE '_u%'||Any value that has a U at the second position|