85 lines
3.7 KiB
Markdown
85 lines
3.7 KiB
Markdown
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# 🚀 Panduan Menambahkan Pipeline Baru (Authoring Tutorial)
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Dokumen ini merupakan panduan praktis langkah-demi-langkah bagi Data Engineer untuk membuat, menguji, dan mempublikasikan data pipeline baru ke platform MERICA.
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---
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## Alur Kerja Penambahan Pipeline
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```
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┌────────────────────────────────────────────────────────────────────────────────────────┐
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│ DATA PIPELINE AUTHORING WORKFLOW │
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├───────────┬──────────────────────────────────┬─────────────────────────────────────────┤
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│ Langkah │ Tindakan Pengembang │ Lokasi Berkas │
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├───────────┼──────────────────────────────────┼─────────────────────────────────────────┤
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│ 1 │ Buat Deklarasi Pipeline YAML │ `configs/ingestion_<nama_pipeline>.yaml`│
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│ 2 │ (Opsional) Buat Model dbt │ `dbt/models/silver/` atau `gold/` │
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│ 3 │ (Opsional) Registrasi Metadata │ `metadata/<nama_pipeline>.json` │
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│ 4 │ Validasi Sintaksis Lokal │ Pemeriksaan struktur YAML │
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│ 5 │ Git Commit & Push │ Server Git On-Premise │
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│ 6 │ Verifikasi Auto-Discovery │ Airflow Web UI (Port 14080) │
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└───────────┴──────────────────────────────────┴─────────────────────────────────────────┘
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```
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---
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## Langkah 1: Menyiapkan File YAML
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Buat file baru di direktori `configs/`, misalnya `configs/ingestion_sensor_kebisingan.yaml`:
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```yaml
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pipeline_id: "ingestion_sensor_kebisingan"
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pipeline_name: "Sensor Kebisingan Kota Realtime"
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description: "Ingestion data kebisingan akustik dari jaringan sensor IoT lingkungan."
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schedule_interval: "*/15 * * * *" # Berjalan setiap 15 menit
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tags:
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- "iot"
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- "sensor"
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- "kebisingan"
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source:
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type: "api"
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connection_id: "conn_spku_api_service"
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endpoint: "/v1/noise/telemetry"
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method: "GET"
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lookback_window_hours: 1
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response_path: "data.records"
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target:
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bucket: "dlh-bronze"
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format: "parquet"
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partition_by: "ingest_date"
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governance:
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owner: "bidang_ppkl@dlh.id"
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tier: "Tier2"
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domain: "Pengendalian Pencemaran Lingkungan"
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```
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---
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## Langkah 2: Menyiapkan Model Transformasi dbt (Bila Perlu)
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Jika pipeline ini memerlukan pembersihan atau agregasi lanjutan:
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1. Buat model Silver: `dbt/models/silver/silver_sensor_kebisingan_clean.sql`
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2. Buat model Gold: `dbt/models/gold/gold_noise_hourly_exceedance.sql`
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---
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## Langkah 3: Commit dan Push ke Git Server
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Commit perubahan ke branch aktif (misal `main`):
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```bash
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git add configs/ingestion_sensor_kebisingan.yaml
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git commit -m "feat(pipeline): register noise sensor telemetry pipeline"
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git push origin main
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```
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---
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## Langkah 4: Verifikasi di Airflow 3 Runtime
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Tunggu paling lama **30 detik**. Buka antarmuka Airflow pada `http://localhost:14080`:
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* DAG `dag_ingestion_sensor_kebisingan` akan muncul secara otomatis.
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* Anda dapat memicu eksekusi manual via tombol **Trigger DAG (Play button)** untuk menguji aliran data dari sumber ke S3 Bronze.
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