#!/usr/bin/env bash # # Повторяемая проверка, что DM-витрины и Superset metadata работают на данных # стартовой истории генератора, а не на архивном сиде 2022 года. set -euo pipefail COMPOSE_BIN="${COMPOSE_BIN:-docker compose}" CLICKHOUSE_SERVICE="${CLICKHOUSE_SERVICE:-clickhouse}" CLICKHOUSE_USER="${CLICKHOUSE_USER:-default}" CLICKHOUSE_PASSWORD="${CLICKHOUSE_PASSWORD:-123456}" GEN_MODEL_T0="${GEN_MODEL_T0:-2026-01-01T00:00:00+00:00}" GEN_MODEL_T_END="${GEN_MODEL_T_END:-2026-01-01T06:00:00+00:00}" REQUIRE_SUPERSET="${REQUIRE_SUPERSET:-1}" fail() { echo "Ошибка: $*" >&2 exit 1 } clickhouse_datetime_literal() { local value="$1" value="${value/T/ }" value="${value%Z}" if [[ "${value}" =~ ^(.*)[+-][0-9]{2}:[0-9]{2}$ ]]; then value="${BASH_REMATCH[1]}" fi echo "${value}" } ch_query() { ${COMPOSE_BIN} exec -T "${CLICKHOUSE_SERVICE}" clickhouse-client \ --user="${CLICKHOUSE_USER}" \ --password="${CLICKHOUSE_PASSWORD}" \ --query "$1" } pg_query() { ${COMPOSE_BIN} exec -T postgres-metadata psql \ -U airflow \ -d superset \ -At \ -c "$1" | tr -d '\r' } CH_MODEL_T0="$(clickhouse_datetime_literal "${GEN_MODEL_T0}")" CH_MODEL_T_END="$(clickhouse_datetime_literal "${GEN_MODEL_T_END}")" echo "=== Проверка ClickHouse: данные генерации в DM ===" stats_query=" WITH toDateTime64('${CH_MODEL_T0}', 6) AS t0, toDateTime64('${CH_MODEL_T_END}', 6) AS t_end SELECT count() AS events, uniqExact(click_id) AS visits, uniqExact(user_domain_id) AS users, toString(min(event_ts)) AS min_event_ts, toString(max(event_ts)) AS max_event_ts, users < visits AND visits < events AS pyramid_ok, min(event_ts) >= t0 AND max(event_ts) < t_end AS half_open_ok, countIf(toYear(event_ts) = 2022) = 0 AS no_2022_rows, hex(sipHash128(groupArray(tuple(event_id, click_id, user_domain_id, event_ts, page_url_path)))) AS digest FROM ( SELECT event_id, click_id, user_domain_id, event_ts, page_url_path FROM dm.v_events_enriched WHERE event_ts >= t0 AND event_ts < t_end ORDER BY event_id ) FORMAT TabSeparated" stats="$(ch_query "${stats_query}")" IFS=$'\t' read -r events visits users min_event_ts max_event_ts pyramid_ok half_open_ok no_2022_rows digest <<< "${stats}" [[ "${events}" =~ ^[0-9]+$ ]] || fail "не удалось прочитать число событий из dm.v_events_enriched" (( events > 0 )) || fail "dm.v_events_enriched пустая в модельном диапазоне" [[ "${pyramid_ok}" == "1" ]] || fail "нарушена пирамида users < visits < events" [[ "${half_open_ok}" == "1" ]] || fail "данные вышли за диапазон [GEN_MODEL_T0, GEN_MODEL_T_END)" [[ "${no_2022_rows}" == "1" ]] || fail "найдены строки 2022 года, похожие на архивный сид" echo "events=${events}" echo "visits=${visits}" echo "users=${users}" echo "min_event_ts=${min_event_ts}" echo "max_event_ts=${max_event_ts}" echo "digest=${digest}" echo "" echo "=== Проверка ClickHouse: возвраты пользователей ===" returns_query=" WITH toDateTime64('${CH_MODEL_T0}', 6) AS t0, toDateTime64('${CH_MODEL_T_END}', 6) AS t_end, users AS ( SELECT user_domain_id, uniqExact(click_id) AS visits FROM dm.v_events_enriched WHERE event_ts >= t0 AND event_ts < t_end AND user_domain_id IS NOT NULL GROUP BY user_domain_id ) SELECT count() AS users, countIf(visits > 1) AS returning_users, returning_users / users AS returning_share, max(visits) AS max_visits_per_user FROM users FORMAT TabSeparated" returns="$(ch_query "${returns_query}")" IFS=$'\t' read -r total_users returning_users returning_share max_visits_per_user <<< "${returns}" [[ "${total_users}" =~ ^[0-9]+$ ]] || fail "не удалось прочитать число пользователей" (( total_users > 0 )) || fail "нет пользователей для проверки возвратов" (( returning_users > 0 )) || fail "нет пользователей с повторными визитами" echo "users=${total_users}" echo "returning_users=${returning_users}" echo "returning_share=${returning_share}" echo "max_visits_per_user=${max_visits_per_user}" echo "" echo "=== Проверка ClickHouse: форма длины визита ===" visit_shape_query=" WITH toDateTime64('${CH_MODEL_T0}', 6) AS t0, toDateTime64('${CH_MODEL_T_END}', 6) AS t_end, 30 AS max_session_events, sessions AS ( SELECT click_id, count() AS events_count, dateDiff('second', min(event_ts), max(event_ts)) AS duration_sec FROM dm.v_events_enriched WHERE event_ts >= t0 AND event_ts < t_end GROUP BY click_id ) SELECT count() AS visits, countIf(events_count <= 2) / visits AS short_visit_share, quantileExact(0.5)(events_count) AS median_events_per_visit, avg(events_count) AS avg_events_per_visit, countIf(events_count = max_session_events) / visits AS capped_visit_share, quantileExact(0.5)(duration_sec) AS median_duration_sec, quantileExact(0.95)(duration_sec) AS p95_duration_sec, max(events_count) AS max_events_per_visit FROM sessions FORMAT TabSeparated" visit_shape="$(ch_query "${visit_shape_query}")" IFS=$'\t' read -r shape_visits short_visit_share median_events_per_visit avg_events_per_visit capped_visit_share median_duration_sec p95_duration_sec max_events_per_visit <<< "${visit_shape}" [[ "${shape_visits}" =~ ^[0-9]+$ ]] || fail "не удалось прочитать число визитов" (( shape_visits > 0 )) || fail "нет визитов для проверки формы" (( max_events_per_visit <= 30 )) || fail "длина визита превысила GEN_MAX_SESSION_EVENTS" echo "visits=${shape_visits}" echo "short_visit_share=${short_visit_share}" echo "median_events_per_visit=${median_events_per_visit}" echo "avg_events_per_visit=${avg_events_per_visit}" echo "capped_visit_share=${capped_visit_share}" echo "median_duration_sec=${median_duration_sec}" echo "p95_duration_sec=${p95_duration_sec}" echo "max_events_per_visit=${max_events_per_visit}" echo "" echo "=== Проверка ClickHouse: ordered funnel ===" ordered_funnel_query=" WITH toDateTime64('${CH_MODEL_T0}', 6) AS t0, toDateTime64('${CH_MODEL_T_END}', 6) AS t_end, sessions AS ( SELECT click_id, minIf(event_ts, page_url_path = '/home') AS home_ts, minIf(event_ts, page_url_path IN ('/product_a', '/product_b')) AS product_ts, minIf(event_ts, page_url_path = '/cart') AS cart_ts, minIf(event_ts, page_url_path = '/payment') AS payment_ts, minIf(event_ts, page_url_path = '/confirmation') AS confirmation_ts FROM dm.v_events_enriched WHERE event_ts >= t0 AND event_ts < t_end GROUP BY click_id ) SELECT countIf(home_ts IS NOT NULL) AS home, countIf(home_ts IS NOT NULL AND product_ts > home_ts) AS products, countIf(home_ts IS NOT NULL AND product_ts > home_ts AND cart_ts > product_ts) AS cart, countIf(home_ts IS NOT NULL AND product_ts > home_ts AND cart_ts > product_ts AND payment_ts > cart_ts) AS payment, countIf(home_ts IS NOT NULL AND product_ts > home_ts AND cart_ts > product_ts AND payment_ts > cart_ts AND confirmation_ts > payment_ts) AS confirmation, products <= home AND cart <= products AND payment <= cart AND confirmation <= payment AS monotonic_ok, confirmation / home AS confirmation_share FROM sessions FORMAT TabSeparated" ordered_funnel="$(ch_query "${ordered_funnel_query}")" IFS=$'\t' read -r ordered_home ordered_products ordered_cart ordered_payment ordered_confirmation ordered_monotonic_ok ordered_confirmation_share <<< "${ordered_funnel}" [[ "${ordered_home}" =~ ^[0-9]+$ ]] || fail "не удалось прочитать ordered funnel" (( ordered_home > 0 )) || fail "ordered funnel: нет /home" [[ "${ordered_monotonic_ok}" == "1" ]] || fail "ordered funnel не монотонен" echo "home=${ordered_home}" echo "products=${ordered_products}" echo "cart=${ordered_cart}" echo "payment=${ordered_payment}" echo "confirmation=${ordered_confirmation}" echo "monotonic_ok=${ordered_monotonic_ok}" echo "confirmation_share=${ordered_confirmation_share}" echo "" echo "=== Проверка ClickHouse: contains funnel ===" contains_funnel_query=" WITH toDateTime64('${CH_MODEL_T0}', 6) AS t0, toDateTime64('${CH_MODEL_T_END}', 6) AS t_end, sessions AS ( SELECT click_id, countIf(page_url_path = '/home') > 0 AS has_home, countIf(page_url_path IN ('/product_a', '/product_b')) > 0 AS has_product, countIf(page_url_path = '/cart') > 0 AS has_cart, countIf(page_url_path = '/payment') > 0 AS has_payment, countIf(page_url_path = '/confirmation') > 0 AS has_confirmation FROM dm.v_events_enriched WHERE event_ts >= t0 AND event_ts < t_end GROUP BY click_id ) SELECT countIf(has_home) AS home, countIf(has_home AND has_product) AS products, countIf(has_home AND has_product AND has_cart) AS cart, countIf(has_home AND has_product AND has_cart AND has_payment) AS payment, countIf(has_home AND has_product AND has_cart AND has_payment AND has_confirmation) AS confirmation, products <= home AND cart <= products AND payment <= cart AND confirmation <= payment AS monotonic_ok, confirmation / home AS confirmation_share FROM sessions FORMAT TabSeparated" contains_funnel="$(ch_query "${contains_funnel_query}")" IFS=$'\t' read -r contains_home contains_products contains_cart contains_payment contains_confirmation contains_monotonic_ok contains_confirmation_share <<< "${contains_funnel}" [[ "${contains_home}" =~ ^[0-9]+$ ]] || fail "не удалось прочитать contains funnel" (( contains_home > 0 )) || fail "contains funnel: нет /home" [[ "${contains_monotonic_ok}" == "1" ]] || fail "contains funnel не монотонен" echo "home=${contains_home}" echo "products=${contains_products}" echo "cart=${contains_cart}" echo "payment=${contains_payment}" echo "confirmation=${contains_confirmation}" echo "monotonic_ok=${contains_monotonic_ok}" echo "confirmation_share=${contains_confirmation_share}" echo "" echo "=== Проверка ClickHouse: основные DM-витрины не пустые ===" views_query=" SELECT source, rows FROM ( SELECT 'dm.v_events_enriched' AS source, count() AS rows FROM dm.v_events_enriched UNION ALL SELECT 'dm.v_daily_traffic', count() FROM dm.v_daily_traffic UNION ALL SELECT 'dm.v_top_pages_daily', count() FROM dm.v_top_pages_daily UNION ALL SELECT 'dm.v_utm_effectiveness', count() FROM dm.v_utm_effectiveness UNION ALL SELECT 'dm.v_session_overview', count() FROM dm.v_session_overview UNION ALL SELECT 'dm.dq_summary', count() FROM dm.dq_summary ) ORDER BY source FORMAT TabSeparated" while IFS=$'\t' read -r source rows; do [[ -n "${source}" ]] || continue [[ "${rows}" =~ ^[0-9]+$ ]] || fail "не удалось прочитать число строк для ${source}" (( rows > 0 )) || fail "${source} пустая" echo "${source}=${rows}" done < <(ch_query "${views_query}") if [[ "${REQUIRE_SUPERSET}" != "1" ]]; then echo "" echo "Проверка Superset пропущена: REQUIRE_SUPERSET=${REQUIRE_SUPERSET}" exit 0 fi echo "" echo "=== Проверка Superset: datasets, charts и dashboard созданы ===" if ! ${COMPOSE_BIN} ps --services --filter "status=running" | grep -qx "superset"; then fail "сервис superset не запущен" fi ${COMPOSE_BIN} exec -T superset curl -fsS http://localhost:8088/health >/dev/null \ || fail "Superset health endpoint не отвечает" dataset_count="$(pg_query " SELECT count(*) FROM tables WHERE schema = 'dm' AND table_name IN ( 'v_events_enriched', 'v_daily_traffic', 'v_utm_effectiveness', 'v_top_pages_daily', 'v_session_overview', 'dq_summary' );")" dashboard_count="$(pg_query " SELECT count(*) FROM dashboards WHERE slug = 'ecommerce-analytics';")" chart_count="$(pg_query " SELECT count(*) FROM dashboard_slices ds JOIN dashboards d ON d.id = ds.dashboard_id WHERE d.slug = 'ecommerce-analytics';")" [[ "${dataset_count}" == "6" ]] || fail "ожидалось 6 Superset datasets, найдено ${dataset_count}" [[ "${dashboard_count}" == "1" ]] || fail "dashboard ecommerce-analytics не найден" (( chart_count > 0 )) || fail "dashboard ecommerce-analytics не связан с chart" echo "superset_datasets=${dataset_count}" echo "superset_dashboards=${dashboard_count}" echo "superset_dashboard_charts=${chart_count}" echo "dashboard_url=http://localhost:8088/superset/dashboard/ecommerce-analytics/" echo "" echo "=== Проверка Superset: dashboard открывается и читает ClickHouse ===" superset_probe="$( ${COMPOSE_BIN} exec -T superset bash -s <<'PY' set -euo pipefail python - <<'PYTHON' import json import urllib.request from sqlalchemy import text from superset.app import create_app app = create_app() with app.app_context(): from superset.extensions import db from superset.models.core import Database from superset.models.dashboard import Dashboard dashboard = ( db.session.query(Dashboard) .filter_by(slug="ecommerce-analytics") .one() ) database = ( db.session.query(Database) .filter_by(database_name="clickhouse_dwh") .one() ) with database.get_sqla_engine() as engine: with engine.connect() as connection: events = connection.execute( text("SELECT count() FROM dm.v_events_enriched") ).scalar() login_payload = json.dumps( { "username": "admin", "password": "admin", "provider": "db", "refresh": True, } ).encode("utf-8") login_request = urllib.request.Request( "http://localhost:8088/api/v1/security/login", data=login_payload, headers={"Content-Type": "application/json"}, method="POST", ) with urllib.request.urlopen(login_request, timeout=10) as response: login_status = response.status token = json.loads(response.read().decode("utf-8"))["access_token"] dashboard_request = urllib.request.Request( f"http://localhost:8088/api/v1/dashboard/{dashboard.id}", headers={"Authorization": f"Bearer {token}"}, method="GET", ) with urllib.request.urlopen(dashboard_request, timeout=10) as response: dashboard_status = response.status dashboard_payload = json.loads(response.read().decode("utf-8")) dashboard_title = dashboard_payload["result"]["dashboard_title"] print(f"login_api_status={login_status}") print(f"dashboard_api_status={dashboard_status}") print(f"dashboard_title={dashboard_title}") print(f"superset_clickhouse_events={events}") if login_status >= 400: raise SystemExit("Superset login API failed") if dashboard_status >= 400: raise SystemExit("Superset dashboard API did not open") if "E-commerce Analytics" not in dashboard_title: raise SystemExit("Unexpected dashboard title") if not isinstance(events, int) or events <= 0: raise SystemExit("Superset ClickHouse query returned no data") PYTHON PY )" echo "${superset_probe}"