Advanced Options

Additional advanced options are available to customise the custom model deployment, enabling explicit inclusion or exclusion of event_name values and event_param/user_property keys.

There are a number of reasons why you might want to pre-filter the data stream. This could be because of historical setup issues, to exclude values defined during a testing period, automated migration from an external tool or Google, or simply because the event_names, event_params or user_properties you use have evolved over time.

We provide a mechanism to pre-filter the stream to implement a variety of logical scenarios.

Event Options

Advanced filters are implemented via the event_options JSON variable, which is passed as a NULL JSON value in the basic deployment guide. JSON paths are parsed from the event_options variable, the schema for which will comprise a subset of the following JSON keys:

{
    "start_date": "<[DATE]>",
    "end_date": "<[DATE]>",
    "stream_id_in": ["<ARRAY<STRING>"],
    "stream_id_not_in": ["<ARRAY<STRING>"],
    "event_name_like_any": ["<ARRAY<STRING>"],
    "event_name_not_like_any": ["<ARRAY<STRING>"],
    "event_param_like_any": ["<ARRAY<STRING>"],
    "event_param_not_like_any": ["<ARRAY<STRING>"],
    "user_property_like_any": ["<ARRAY<STRING>"],
    "user_property_not_like_any" ["<ARRAY<STRING>"]
}

Note that the placeholders need to be replaced by a valid JSON value or array. Placeholder "<[DATE]>" would be replaced by e.g. "2024-01-01" and placeholder ["<ARRAY<STRING>"] would be replaced by e.g. ["12345678", "87654321"].

Data Profile Filters

Note that in each logical case, events are not filtered out, simply excluded from the profiling and therefore not included in the relevant output STRUCT (event_count, event_param, user_property). This means that the row count for the result of a query against the [dataset_id].GA4_EVENTS date-bounded table function for a specific date range should precisely match the row count in both the source GA4 table shard range [dataset_id].events_* and the output table [dataset_id].EVENTS.

Date Range

Date ranges filter the specific date range used to build the custom decoder functions, only including columns in the decoded model which are observed in the defined date range (in addition to the standard set of columns). Neither or both start_date and end_date need to be passed in order for the deployment to be executed.

advanced event_options: start_date, end_date

JSONGoogleSQL (Static)GoogleSQL (Dynamic)

{
    "start_date": "2023-01-01",
    "end_date": "2023-12-31"
}

DECLARE event_options JSON; 

SET event_options = JSON """
{
    "start_date": "2023-01-01",
    "end_date": "2023-12-31"
}    
"""

DECLARE event_options JSON; 

SET event_options = SELECT TO_JSON(( 
SELECT AS STRUCT
CURRENT_DATE - 365 AS start_date,
CURRENT_DATE AS end_date
))

Stream ID

Filtering on stream_id is typically only required if there have been setup irregularities, which are more commonly observed on Firebase data streams rather than GA4.

stream_id_in

This will only profile rows where the stream_id matches one defined in the stream_id_in ARRAY<STRING>:

advanced event_options: stream_id_in

JSONGoogleSQL

{
    "stream_id_in": ["12345678"]
}

DECLARE event_options JSON; 

SET event_options = JSON """
{
    "stream_id_in": ["12345678"]
}    
"""

stream_id_not_in

This will only profile rows where the stream_id does not match any defined in the stream_id_in ARRAY<STRING>:

advanced event_options: stream_id_not_in

JSONGoogleSQL

{
    "stream_id_not_in": ["87654321", "98765432"]
}

DECLARE event_options JSON; 

SET event_options = JSON """
{
    "stream_id_not_in": ["87654321", "98765432"]
}    
"""

Event Names

event_name_like_any

The event_name profile include filter is implemented using the LIKE ANY Quantified Like Operator. It will only include values in the event_name profile and decoder which match one of the values in the event_name_like_any STRING ARRAY (note that wildcards can be used to match specific patterns).

Note that is is a more common pattern to filter out unwanted values from the profile by using the event_name_not_like_any filter option.

event_name_not_like_any

The event_name profile exclude filter is implemented using the NOT LIKE ANY Quantified Like Operator. It will only include values in the event_name profile and decoder which do not match one of the values in the event_name_not_like_any STRING ARRAY (note that wildcards can be used to match specific patterns).

advanced event_options: event_name_not_like_any

JSONGoogleSQL

{
    "event_name_like_any": ["test%", "http:%"]
}

DECLARE event_options JSON; 

SET event_options = JSON """
{
    "event_name_like_any": ["test%", "http:%"]
}    
"""

Event Params

event_param_like_any

The event_param profile include filter is implemented using the LIKE ANY Quantified Like Operator. It will only include values in the event_param profile and decoder which match one of the values in the event_param_like_any STRING ARRAY (note that wildcards can be used to match specific patterns).

Note that is is a more common pattern to filter out unwanted values from the profile by using the event_param_not_like_any filter option.

event_param_not_like_any

The event_param profile exclude filter is implemented using the NOT LIKE ANY Quantified Like Operator. It will only include values in the event_param profile and decoder which do not match one of the values in the event_param_not_like_any STRING ARRAY (note that wildcards can be used to match specific patterns).

advanced event_options: event_param_not_like_any

JSONGoogleSQL

{
    "event_param_not_like_any": ["test%", "http:%", "%_test"]
}

DECLARE event_options JSON; 

SET event_options = JSON """
{
    "event_param_not_like_any": ["test%", "http:%", "%_test"]
}    
"""

User Properties

user_property_like_any

The user_property profile include filter is implemented using the LIKE ANY Quantified Like Operator. It will only include values in the user_property profile and decoder which match one of the values in the user_property_like_any STRING ARRAY (note that wildcards can be used to match specific patterns).

Note that is is a more common pattern to filter out unwanted values from the profile by using the user_property_not_like_any filter option.

user_property_not_like_any

The user_property profile exclude filter is implemented using the NOT LIKE ANY Quantified Like Operator. It will only include values in the user_property profile and decoder which do not match one of the values in the user_property_not_like_any STRING ARRAY (note that wildcards can be used to match specific patterns).

advanced event_options: event_param_not_like_any

JSONGoogleSQL

{
    "user_property_not_like_any": ["test%", "http:%", "%_test"]
}

DECLARE event_options JSON; 

SET event_options = JSON """
{
    "user_property_not_like_any": ["test%", "http:%", "%_test"]
}    
"""