Optimising dax with filter

[Anonymous]

Hello to all,
I have a performance problem with the following formula.

Clients with call after =
  COUNTROWS (
    DISTINCT (
      SELECTCOLUMNS (
        FILTER (
          ADDCOLUMNS (
             GENERATE (
                SUMMARIZE ( 'GA web', 'GA web'[id_client], 'GA web'[timestamp] ),
                SUMMARIZE (
                  FILTER ('Call data',
                    'Call data'[id_client] = 'GA web'[id_client]
                    && 'GA web'[id_client] > 0 ),
                  'Call data'[TIMESTAMP] )
                 ),
             "Dif.", DATEDIFF ( 'GA web'[timestamp], 'Call data'[TIMESTAMP], MINUTE )
           ),
           AND ( [Dif.] >= 0, [Dif.] <= 60 )
        ),
     "id_client", 'GA web'[id_client]
)))

I have two tables:

GA-web: log customer activity on the web, with a unique customer identifier.
Calls: I register the phone activity of the call centre and the calls they have for each unique customer identifier.

id_client is a number between 4 and 11 numbers.
timestamp is the date, hour, minute and second value of when the event occurs.

What I am looking for is to search for each Google Analytics event, if the id_person has a subsequent call in less than an hour.
The module works fine, but when I ask it to calculate longer periods it tells me that I don't have enough memory.
I have tried replacing FILTERs with TREATAS, KEEPFILTERs, USERELANTIONSHIP or CROSSFILTER, however, the calculation time increases to half an hour or more.
Can you think of a way to optimise it?
Thank you very much.

[parry2k]

@Anonymous there is a lot more going on in your DAX, just DAX doesn't give the full picture, I would recommend sharing a relationship diagram for the tables involved, provide sample data and expected output, it will help tremendously to understand the problem and provide an effective solution.

[Anonymous]

Hello @parry2k !
I just edited the initial post to include more information.
Thank you very much!