backfill/2024-04-26-active_users_aggregates/firefox_ios_query.sql (94 lines of code) (raw):
WITH baseline AS (
SELECT
activity_segment AS segment,
attribution_medium,
attribution_source,
attribution_medium IS NOT NULL
OR attribution_source IS NOT NULL AS attributed,
city,
country,
um.distribution_id AS distribution_id,
um.first_seen_date AS first_seen_date,
is_default_browser,
normalized_channel AS channel,
normalized_os AS os,
normalized_os_version AS os_version,
os_version_major,
os_version_minor,
um.submission_date,
um.locale,
att.adjust_network,
CAST(NULL AS STRING) AS install_source,
normalized_app_name as app_name,
days_since_seen,
uri_count,
active_hours_sum,
um.app_version as app_version,
um.client_id,
durations
FROM
`moz-fx-data-shared-prod.telemetry_derived.unified_metrics_v1` AS um
LEFT JOIN
firefox_ios.firefox_ios_clients AS att
ON
um.client_id = att.client_id
WHERE
um.submission_date BETWEEN DATE_SUB(@submission_date, INTERVAL 28 DAY) AND @submission_date
AND normalized_app_name IN ('Firefox iOS', 'Firefox iOS BrowserStack')
),
um_dau AS (
SELECT
submission_date,
client_id,
(
LOGICAL_AND(days_since_seen = 0) AND LOGICAL_AND(durations > 0)
) AS is_dau
FROM baseline
GROUP BY ALL
),
um_is_active AS (
SELECT
submission_date,
client_id,
is_dau,
LOGICAL_OR(is_dau) OVER (PARTITION BY client_id ORDER BY submission_date ASC ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) AS is_wau,
LOGICAL_OR(is_dau) OVER (PARTITION BY client_id ORDER BY submission_date ASC ROWS BETWEEN 27 PRECEDING AND CURRENT ROW) AS is_mau,
FROM um_dau
)
SELECT
segment,
app_version,
attribution_medium,
attribution_source,
attributed,
city,
country,
distribution_id,
EXTRACT(YEAR FROM first_seen_date) AS first_seen_year,
is_default_browser,
COALESCE(REGEXP_EXTRACT(locale, r'^(.+?)-'), locale, NULL) AS locale,
app_name,
channel,
os,
os_version,
os_version_major,
os_version_minor,
submission_date,
adjust_network,
install_source,
COUNTIF(is_dau) AS dau,
COUNTIF(is_wau) AS wau,
COUNTIF(is_mau) AS mau,
COUNT(DISTINCT IF(days_since_seen = 0, client_id, NULL)) AS daily_users,
COUNT(DISTINCT IF(days_since_seen < 7, client_id, NULL)) AS weekly_users,
COUNT(DISTINCT IF(days_since_seen < 28, client_id, NULL)) AS monthly_users,
SUM(uri_count) AS uri_count,
SUM(active_hours_sum) AS active_hours
FROM
baseline
LEFT JOIN
um_is_active USING(submission_date, client_id)
WHERE
submission_date = @submission_date
GROUP BY
ALL