Postgresql: Pattern match against array elements?

Is there any way to do a pattern match against the elements of an array in postgresql (9.4 if the version makes a difference)? I have an aggregate function that, among other things, returns an array of elements, like:

SELECT 
   lognum
   ,array_agg(flightnum) as flightnums 
FROM logs 
GROUP BY lognum;

Where the flightnum field is a varchar containing either a text string or a three-or-four digit number. Now say I want to select all logs that have a flight number starting with an '8' (so '800' or '8000' series flights). My first thought was to do something like this:

SELECT 
   * 
FROM (
      SELECT 
         lognum
         ,array_agg(flightnum) as flightnums 
      FROM logs 
      GROUP BY 
         lognum
     ) s1 
WHERE 
   '8%' like ANY(flightnums);

But while this doesn't give an error, it also doesn't return any results. I'm guessing that this is because the wild card is on the left of the operator. Of course, turning it around to be:

WHERE ANY(flightnum) like '8%'

gives me a syntax error. So is there any way I can run this query such that I get any rows containing a flight number that starts with an 8 (or whatever)?

Please note that this is a simplified example demonstrating just the section I am having difficulty with.

What I ended up doing was writing a "commutator" operator. In postgres I created a new function and operator using the following two commands:

create function like_rev (text, text) returns boolean as $ select $2 like $1 $ language SQL;
create operator ~~~~ (procedure = like_rev,  leftarg=text, rightarg=text);

Which is effectively identical to a like, but reverses the argument order when comparing. So now I can accomplish my goal of doing a wildcard match against an array by simply replacing like with ~~~~, like so:

SELECT 
   * 
FROM (
      SELECT 
         lognum,
         array_agg(flightnum) as flightnums 
      FROM logs 
      GROUP BY 
         lognum
      ) s1 
WHERE 
   '8%' ~~~~ ANY(flightnums);

Note that this may not be the most performant solution - it's quite possible that the answer from Cassandra would be better if you require maximum performance. However, this works well for me, as it doesn't require any changes to the structure of the query.

StackExchange Database Administrators Q#117767, answer score: 5