You may try using a pivot query here. For example, if you wanted the difference in minutes for each person/campaign from the time of receiving an email to opening that email, you could try this:

SELECT
    campaign_id,
    person_id,
    TIMESTAMP_DIFF(
        MAX(CASE WHEN event_type = 'Opened Email' THEN timestamp END),
        MAX(CASE WHEN event_type = 'Received Email' THEN timestamp END),
        MINUTE) AS diff_in_minutes
FROM yourTable
GROUP BY
    campaign_id,
    person_id;

In order to query multiple REPEATED Records as we intended to do originally, we’ll need to make use of the FLATTEN function. This acts similarly to Entity SQL’s FLATTEN function by purposefully flattening the specified field into the rest of the dataset.

For example, if we want to perform our original query to return all the data from our persons table, we’ll need to FLATTEN one of the REPEATED records:

SELECT
  *
FROM
  FLATTEN([primary.persons], children)

Here we’re FLATTENING the children REPEATED Record into the rest of the table, so our results are duplicated as often as necessary to accomodate for every repetition of nested fields (children and citiesLives):

Row kind    fullName    age gender  phoneNumber_areaCode    phoneNumber_number  children_name   children_gender children_age    citiesLived_place   citiesLived_yearsLived
1   person  John Doe    22  Male    206 1234567 Jane    Female  6   Seattle 1995
2   person  John Doe    22  Male    206 1234567 Jane    Female  6   Stockholm   2005
3   person  John Doe    22  Male    206 1234567 John    Male    15  Seattle 1995
4   person  John Doe    22  Male    206 1234567 John    Male    15  Stockholm   2005
5   person  Mike Jones  35  Male    622 1567845 Earl    Male    10  Los Angeles 1989
6   person  Mike Jones  35  Male    622 1567845 Earl    Male    10  Los Angeles 1993
7   person  Mike Jones  35  Male    622 1567845 Earl    Male    10  Los Angeles 1998
8   person  Mike Jones  35  Male    622 1567845 Earl    Male    10  Los Angeles 2002
9   person  Mike Jones  35  Male    622 1567845 Earl    Male    10  Washington DC   1990
10  person  Mike Jones  35  Male    622 1567845 Earl    Male    10  Washington DC   1993
...