ddadminandClaude Opus 4.6
5ca4e6b2ca
- fact_flight_sales_dq: student SK (passenger/route/airplane) → NOTICE, airport_sk → порог 1% (эталон через ods.routes) - routes_dq: закомментирован RI airplane_code → ods.airplanes - ODS DAG: убрана зависимость dq_ods_airplanes → load_ods_routes - 18 студенческих файлов заменены заглушками (ODS/DDS/DM load+dq) - test_ods_sql_contract: SNAPSHOT_ENTITIES без airplanes/seats - test_dags_smoke: убран assert dq_ods_airplanes → dq_ods_routes Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
276 lines
9.7 KiB
Python
276 lines
9.7 KiB
Python
from __future__ import annotations
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"""
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Учебный DAG: загрузка из STG в ODS (Greenplum) по домену bookings.
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Ключевая идея:
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- весь запуск ODS работает с одним stg_batch_id;
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- для каждой сущности выполняем пару задач load -> dq;
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- загрузка реализована как SCD1 UPSERT (UPDATE изменившихся + INSERT новых).
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"""
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from datetime import timedelta
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from logging import getLogger
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import pendulum
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from airflow.operators.python import PythonOperator
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from airflow.providers.postgres.hooks.postgres import PostgresHook
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from airflow.providers.postgres.operators.postgres import PostgresOperator
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from airflow import DAG
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GREENPLUM_CONN_ID = "greenplum_conn"
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log = getLogger(__name__)
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default_args = {
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"owner": "airflow",
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"retries": 1,
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"retry_delay": timedelta(seconds=30),
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}
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def _resolve_stg_batch_id(**context) -> str:
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"""
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Возвращает stg_batch_id из dag_run.conf или вычисляет последний согласованный батч.
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ВНИМАНИЕ: Это значение используется ТОЛЬКО для загрузки snapshot-справочников
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(airports, airplanes, routes, seats).
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Для инкрементальных транзакционных таблиц (bookings, tickets, flights, segments,
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boarding_passes) этот батч НЕ используется. Вместо этого они грузят все новые
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записи по HWM: WHERE _load_ts > (SELECT MAX(_load_ts) FROM ods.table).
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Это сделано для того, чтобы не потерять инкременты, если STG-DAG запускался
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несколько раз до запуска ODS-DAG'а.
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Зачем нужна согласованность (INTERSECT по всем справочникам)?
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Чтобы ODS загружал только те данные, для которых уже приехали ВСЕ связанные
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справочники. Это защищает от рассинхрона данных, когда часть измерений в текущем
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батче обновилась, а часть — упала или не доехала, что могло бы привести к
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потере ссылочной целостности при сборке витрин.
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"""
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conf = context["dag_run"].conf or {}
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stg_batch_id = conf.get("stg_batch_id")
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if not stg_batch_id:
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hook = PostgresHook(postgres_conn_id=GREENPLUM_CONN_ID)
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result = hook.get_first(
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"""
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WITH candidate_batches AS (
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SELECT _load_id
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FROM stg.airports
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WHERE _load_id IS NOT NULL AND _load_id <> ''
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GROUP BY _load_id
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INTERSECT
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SELECT _load_id
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FROM stg.airplanes
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WHERE _load_id IS NOT NULL AND _load_id <> ''
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GROUP BY _load_id
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INTERSECT
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SELECT _load_id
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FROM stg.routes
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WHERE _load_id IS NOT NULL AND _load_id <> ''
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GROUP BY _load_id
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INTERSECT
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SELECT _load_id
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FROM stg.seats
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WHERE _load_id IS NOT NULL AND _load_id <> ''
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GROUP BY _load_id
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),
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batch_ready AS (
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SELECT
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c._load_id,
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GREATEST(
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COALESCE(
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(SELECT MAX(_load_ts) FROM stg.airports a WHERE a._load_id = c._load_id),
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TIMESTAMP '1900-01-01 00:00:00'
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),
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COALESCE(
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(SELECT MAX(_load_ts) FROM stg.airplanes a WHERE a._load_id = c._load_id),
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TIMESTAMP '1900-01-01 00:00:00'
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),
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COALESCE(
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(SELECT MAX(_load_ts) FROM stg.routes r WHERE r._load_id = c._load_id),
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TIMESTAMP '1900-01-01 00:00:00'
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),
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COALESCE(
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(SELECT MAX(_load_ts) FROM stg.seats s WHERE s._load_id = c._load_id),
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TIMESTAMP '1900-01-01 00:00:00'
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)
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) AS ready_dttm
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FROM candidate_batches c
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)
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SELECT _load_id
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FROM batch_ready
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ORDER BY ready_dttm DESC
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LIMIT 1
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"""
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)
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stg_batch_id = result[0] if result and result[0] else None
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if not stg_batch_id:
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raise ValueError(
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"stg_batch_id не найден: передайте stg_batch_id в conf или "
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"сначала выполните bookings_to_gp_stage для snapshot-справочников"
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)
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log.info("Используем stg_batch_id=%s", stg_batch_id)
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return stg_batch_id
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def _finish_summary() -> None:
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"""Логирует краткий итог выполнения ODS-ветки."""
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log.info("DAG bookings_to_gp_ods завершён. Подробности смотрите в логах задач.")
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with DAG(
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dag_id="bookings_to_gp_ods",
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start_date=pendulum.datetime(2017, 1, 1, tz="UTC"),
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schedule=None,
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catchup=False,
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max_active_runs=1,
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template_searchpath="/sql",
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default_args=default_args,
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tags=["demo", "bookings", "greenplum", "ods"],
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description="Учебный DAG: загрузка STG -> ODS (SCD1 UPSERT) + DQ проверки",
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) as dag:
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resolve_stg_batch_id = PythonOperator(
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task_id="resolve_stg_batch_id",
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python_callable=_resolve_stg_batch_id,
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)
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load_ods_bookings = PostgresOperator(
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task_id="load_ods_bookings",
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postgres_conn_id=GREENPLUM_CONN_ID,
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sql="ods/bookings_load.sql",
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)
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dq_ods_bookings = PostgresOperator(
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task_id="dq_ods_bookings",
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postgres_conn_id=GREENPLUM_CONN_ID,
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sql="ods/bookings_dq.sql",
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)
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load_ods_tickets = PostgresOperator(
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task_id="load_ods_tickets",
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postgres_conn_id=GREENPLUM_CONN_ID,
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sql="ods/tickets_load.sql",
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)
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dq_ods_tickets = PostgresOperator(
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task_id="dq_ods_tickets",
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postgres_conn_id=GREENPLUM_CONN_ID,
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sql="ods/tickets_dq.sql",
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)
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load_ods_airports = PostgresOperator(
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task_id="load_ods_airports",
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postgres_conn_id=GREENPLUM_CONN_ID,
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sql="ods/airports_load.sql",
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)
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dq_ods_airports = PostgresOperator(
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task_id="dq_ods_airports",
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postgres_conn_id=GREENPLUM_CONN_ID,
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sql="ods/airports_dq.sql",
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)
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load_ods_airplanes = PostgresOperator(
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task_id="load_ods_airplanes",
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postgres_conn_id=GREENPLUM_CONN_ID,
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sql="ods/airplanes_load.sql",
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)
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dq_ods_airplanes = PostgresOperator(
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task_id="dq_ods_airplanes",
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postgres_conn_id=GREENPLUM_CONN_ID,
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sql="ods/airplanes_dq.sql",
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)
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load_ods_routes = PostgresOperator(
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task_id="load_ods_routes",
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postgres_conn_id=GREENPLUM_CONN_ID,
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sql="ods/routes_load.sql",
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)
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dq_ods_routes = PostgresOperator(
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task_id="dq_ods_routes",
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postgres_conn_id=GREENPLUM_CONN_ID,
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sql="ods/routes_dq.sql",
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)
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load_ods_seats = PostgresOperator(
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task_id="load_ods_seats",
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postgres_conn_id=GREENPLUM_CONN_ID,
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sql="ods/seats_load.sql",
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)
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dq_ods_seats = PostgresOperator(
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task_id="dq_ods_seats",
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postgres_conn_id=GREENPLUM_CONN_ID,
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sql="ods/seats_dq.sql",
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)
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load_ods_flights = PostgresOperator(
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task_id="load_ods_flights",
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postgres_conn_id=GREENPLUM_CONN_ID,
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sql="ods/flights_load.sql",
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)
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dq_ods_flights = PostgresOperator(
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task_id="dq_ods_flights",
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postgres_conn_id=GREENPLUM_CONN_ID,
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sql="ods/flights_dq.sql",
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)
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load_ods_segments = PostgresOperator(
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task_id="load_ods_segments",
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postgres_conn_id=GREENPLUM_CONN_ID,
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sql="ods/segments_load.sql",
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)
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dq_ods_segments = PostgresOperator(
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task_id="dq_ods_segments",
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postgres_conn_id=GREENPLUM_CONN_ID,
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sql="ods/segments_dq.sql",
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)
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load_ods_boarding_passes = PostgresOperator(
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task_id="load_ods_boarding_passes",
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postgres_conn_id=GREENPLUM_CONN_ID,
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sql="ods/boarding_passes_load.sql",
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)
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dq_ods_boarding_passes = PostgresOperator(
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task_id="dq_ods_boarding_passes",
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postgres_conn_id=GREENPLUM_CONN_ID,
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sql="ods/boarding_passes_dq.sql",
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)
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finish_ods_summary = PythonOperator(
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task_id="finish_ods_summary",
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python_callable=_finish_summary,
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)
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# stg_batch_id нужен всем загрузочным веткам.
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(
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resolve_stg_batch_id
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>> load_ods_bookings
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>> dq_ods_bookings
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>> load_ods_tickets
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>> dq_ods_tickets
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)
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resolve_stg_batch_id >> load_ods_airports >> dq_ods_airports
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resolve_stg_batch_id >> load_ods_airplanes >> dq_ods_airplanes
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# На main routes не зависит от airplanes (ods.airplanes — студенческая заглушка).
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# На ветке solution: [dq_ods_airports, dq_ods_airplanes] >> load_ods_routes
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dq_ods_airports >> load_ods_routes >> dq_ods_routes
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dq_ods_airplanes >> load_ods_seats >> dq_ods_seats
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dq_ods_routes >> load_ods_flights >> dq_ods_flights
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[dq_ods_flights, dq_ods_tickets] >> load_ods_segments >> dq_ods_segments
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dq_ods_segments >> load_ods_boarding_passes >> dq_ods_boarding_passes
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[dq_ods_boarding_passes, dq_ods_seats] >> finish_ods_summary
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