Di dalam asset bundle

Pengantar Databricks Lakehouse

Gang Wang

Senior Data Scientist

Struktur proyek bundle

my_project/
|-- databricks.yml
|-- src/
|   |-- etl_pipeline.py
|   |-- data_quality.py
|-- resources/
|   |-- jobs/
|   |   |-- nightly_etl.yml
|   |-- pipelines/
|       |-- sales_pipeline.yml
|-- tests/
    |-- test_etl.py

databricks.yml - berkas konfigurasi pusat
src/ - notebook dan kode Anda
resources/ - definisi job dan pipeline
tests/ - berkas uji opsional

Berkas databricks.yml

bundle:
  name: sales_analytics

workspace:
  host: https://myworkspace.databricks.com

targets:
  dev:
    default: true
    workspace:
      root_path: /Users/me/dev
  production:
    workspace:
      root_path: /Shared/production
    permissions:
      - level: CAN_MANAGE
        group_name: data_engineers

Mendefinisikan resources

lapisan: databricks.yml (atas), Resources - Jobs - Pipelines - Dashboards, Code - Notebooks - Python scripts, Targets - dev - staging - production

resources:
  jobs:
    nightly_etl:
      name: "Nightly ETL Pipeline"
      schedule:
        quartz_cron: "0 0 2 * * ?"
      tasks:
        - task_key: ingest
          notebook_task:
            notebook_path: src/etl.py

Perintah CLI bundle

Command	Tujuan
`bundle validate`	Memeriksa kesalahan konfigurasi
`bundle deploy`	Menerapkan ke target
`bundle run`	Memicu job yang diterapkan
`bundle destroy`	Menghapus resources yang diterapkan

# Validasi sebelum menerapkan
databricks bundle validate

# Terapkan ke production
databricks bundle deploy \
  --target production

# Picu satu run
databricks bundle run nightly_etl

Alur kerja penerapan

diagram alur: Alur kerja penerapan

Pengembangan lokal - edit kode dan validasi konfigurasi
Kendali versi - commit perubahan ke Git
Otomasi CI/CD - terapkan ke staging dan jalankan uji
Promosi ke produksi - terapkan dengan yakin

Ringkasan

databricks.yml mendefinisikan proyek, target, dan resources Anda
Resources mencakup jobs, pipelines, dan dashboards
Targets memetakan ke lingkungan (dev, staging, production)
Perintah CLI: validate, deploy, run, destroy

Ayo berlatih!

Pengantar Databricks Lakehouse