DESCRIPTION >
    Summary with general KPIs per date, including visits, page views, bounce rate and average session duration.
    Accepts `date_from` and `date_to` date filter, all historical data if not passed.
    Daily granularity, except when filtering one single day (hourly)

TOKEN "dashboard" READ

NODE timeseries
DESCRIPTION >
    Generate a timeseries for the specified time range, so we call fill empty data points.
    Filters "future" data points.

SQL >
    %
    {% set _single_day = defined(date_from) and day_diff(date_from, date_to) == 0 %}
    with
        {% if defined(date_from) %}
            toStartOfDay(
                toDate(
                    {{
                        Date(
                            date_from,
                            description="Starting day for filtering a date range",
                            required=False,
                        )
                    }}
                )
            ) as start,
        {% else %} toStartOfDay(timestampAdd(today(), interval -7 day)) as start,
        {% end %}
        {% if defined(date_to) %}
            toStartOfDay(
                toDate(
                    {{
                        Date(
                            date_to,
                            description="Finishing day for filtering a date range",
                            required=False,
                        )
                    }}
                )
            ) as end
        {% else %} toStartOfDay(today()) as end
        {% end %}
    {% if _single_day %}
        select
            arrayJoin(
                arrayMap(
                    x -> toDateTime(x),
                    range(
                        toUInt32(toDateTime(start)), toUInt32(timestampAdd(end, interval 1 day)), 3600
                    )
                )
            ) as date
    {% else %}
        select
            arrayJoin(
                arrayMap(
                    x -> toDate(x),
                    range(toUInt32(start), toUInt32(timestampAdd(end, interval 1 day)), 24 * 3600)
                )
            ) as date
    {% end %}
    where date <= now()

NODE hits
DESCRIPTION >
    Group by sessions and calculate metrics at that level

SQL >
    %
    {% if defined(date_from) and day_diff(date_from, date_to) == 0 %}
        select
            site_uuid,
            toStartOfHour(timestamp) as date,
            session_id,
            uniq(session_id) as visits,
            count() as pageviews,
            case when min(timestamp) = max(timestamp) then 1 else 0 end as is_bounce,
            max(timestamp) as latest_hit_aux,
            min(timestamp) as first_hit_aux
        from analytics_hits
        where toDate(timestamp) = {{ Date(date_from) }}
        group by toStartOfHour(timestamp), session_id, site_uuid
    {% else %}
        select
            site_uuid,
            date,
            session_id,
            uniq(session_id) as visits,
            countMerge(hits) as pageviews,
            case when min(first_hit) = max(latest_hit) then 1 else 0 end as is_bounce,
            max(latest_hit) as latest_hit_aux,
            min(first_hit) as first_hit_aux
        from analytics_sessions_mv
        where
            {% if defined(date_from) %} date >= {{ Date(date_from) }}
            {% else %} date >= timestampAdd(today(), interval -7 day)
            {% end %}
            {% if defined(date_to) %} and date <= {{ Date(date_to) }}
            {% else %} and date <= today()
            {% end %}
        group by date, session_id, site_uuid
    {% end %}

NODE data
DESCRIPTION >
    General KPIs per date, works for both summary metrics and trends charts.

SQL >
    select
        site_uuid,
        date,
        uniq(session_id) as visits,
        sum(pageviews) as pageviews,
        sum(case when latest_hit_aux = first_hit_aux then 1 end) / visits as bounce_rate,
        avg(latest_hit_aux - first_hit_aux) as avg_session_sec
    from hits
    group by date, site_uuid

NODE endpoint
DESCRIPTION >
    Join and generate timeseries with metrics

SQL >
%
    select a.date, b.visits, b.pageviews, b.bounce_rate, b.avg_session_sec
    from timeseries a
    left join data b using date
    where site_uuid = {{String(site_uuid, 'mock_site_uuid', description="Tenant ID", required=True)}}