Commit Graph
4 Commits
Author SHA1 Message Date
ddadmin 10f5bc3510 feat(airflow): реализован DAG kafka_load для загрузки в Kafka (фаза 2)
- Добавлен kafka-python==2.0.6 в airflow/requirements.txt
- Создан dags/utils/kafka_helpers.py с функциями:
  - check_kafka_ready() — проверка доступности брокера
  - prepare_topics() — создание/сброс топиков через KafkaAdminClient
  - load_jsonl() — загрузка данных через KafkaProducer (limit=0 = все)
  - validate_load_params(), check_input_files() — валидация
- Создан dags/kafka_load_dag.py с TaskGroup:
  - precheck: check_kafka, check_input_files, validate_load_params
  - ingest: prepare_topics, параллельная загрузка 4 потоков, verify_publish_counts
- Параметры DAG: limit (0 = все), reset_topics, load_* (выбор потоков)
- Обновлена документация: AGENTS.md, README.md, plans/runbook.md,
  plans/airflow_dags_plan.md, docs/ARCHITECTURE.md

Тестирование:
- Подключение к Kafka:  (kafka:29092 доступен, брокер 2.6.0)
- Загрузка данных:  (1000 сообщений — полный файл browser_events)
- Python синтаксис:  (py_compile проходит)
- Структура DAG:  (все 9 задач корректно определены)
2026-02-08 18:13:22 +03:00
ddadmin 284dc3dc1f Move STG->ODS to Airflow batch and align monitoring 2026-02-08 16:36:01 +03:00
ddadmin 14d16c5cae feat(airflow): implement dag orchestration for ddl and etl
Add comprehensive DAG implementation for ClickHouse schema initialization
and ETL pipeline orchestration. The ddl_init_dag manages database schema
creation across stg/ods/dds/dm layers with verification capabilities. The
etl_pipeline_dag implements full ODS to DDS to DM transformation flow with
data quality checks, branching logic for full/incremental loads, and
timeout handling for data availability.

Additional changes:
- Upgrade Airflow from 2.9.3 to 2.10.5
- Fix ClickHouse connection to use native protocol port 9000
- Mount SQL directory in docker-compose for DAG execution
- Update project requirements and documentation comments
- Remove unused pandas dependency
2026-02-07 21:52:31 +03:00
ddadmin fe9c15c0fe feat(airflow): configure ClickHouse connection and update infrastructure
Update Airflow configuration to integrate with ClickHouse DWH instead of
PostgreSQL training database. Changes include:

- Switch Airflow dependencies from PostgreSQL to ClickHouse connector
- Update docker-compose to use ClickHouse connection and correct Dockerfile
- Refactor airflow/requirements.txt to include only essential packages
- Add DAGs directory for ETL pipeline orchestration
- Update documentation to reflect Airflow integration and access credentials
- Adjust service dependencies to wait for ClickHouse startup
2026-02-06 23:34:45 +03:00