Pelajari alasan keberadaan dbt dan bagaimana dbt digunakan untuk membuat proyek transformasi data.

Dasar-dasar dbt

Menjalankan perintah dbt

Pengenalan dbt

Versi dbt

Mendapatkan bantuan

Pengguna dbt

Membuat proyek dbt

Menginisialisasi proyek dbt

Membuat profil proyek

Selamat datang di dbt

Masuk ke inti dbt dengan bekerja menggunakan model data dan membuat model berbasis SQL di dalam dbt. Pelajari model SQL dasar, tetapkan dependensi, lakukan pembaruan, dan selesaikan berbagai masalah pada model.

Mengerjakan proyek pertama

Alur kerja proyek dbt

Menjalankan sebuah proyek

Apa itu model dbt?

Fitur dari sebuah model data

Membuat model dbt

Memperbarui model dbt

Berkas konfigurasi

Proyek dan model dbt

Pelajari cara menggunakan templat Jinja untuk menyederhanakan model dbt dan mendefinisikan dependensi hierarkis dengan fungsi `ref` untuk memastikan eksekusi model yang benar.

Membuat dan menghasilkan dokumentasi dbt

Opsi Perintah dbt docs

Proses Dokumentasi dbt

Alur dokumentasi dbt

nyc_yellow_taxi:
  outputs:
    dev:
      type: duckdb
      path: dbt.duckdb
  target: dev



# Name your project! Project names should contain only lowercase characters
# and underscores. A good package name should reflect your organization's
# name or the intended use of these models
name: 'taxi_project'
version: '1.0.0'
config-version: 2

# This setting configures which "profile" dbt uses for this project.
profile: 'nyc_yellow_taxi'

# These configurations specify where dbt should look for different types of files.
# The `model-paths` config, for example, states that models in this project can be
# found in the "models/" directory. You probably won't need to change these!
model-paths: ["models"]
analysis-paths: ["analyses"]
test-paths: ["tests"]
seed-paths: ["seeds"]
macro-paths: ["macros"]
snapshot-paths: ["snapshots"]

target-path: "target"  # directory which will store compiled SQL files
clean-targets:         # directories to be removed by `dbt clean`
  - "target"
  - "dbt_packages"


# Configuring models
# Full documentation: https://docs.getdbt.com/docs/configuring-models

# In this example config, we tell dbt to build all models in the example/
# directory as views. These settings can be overridden in the individual model
# files using the `{{ config(...) }}` macro.
models:
  nyc_yellow_taxi:
  # Config indicated by + and applies to all files under models/example/
    taxi_rides:
    +materialized: view


{{ config(materialized='view')}}


with source_data as (
    select * from read_parquet('yellow_tripdata_2023-01-partial.parquet')
)

select * from source_data


version: 2

models:
  - name: taxi_rides_raw
    description: ____
    access: public


Run the following commands in the terminal:

dbt docs generate
dbt docs serve

version: 2

models:
  - name: taxi_rides_raw
    description: Initial import of the NYC Yellow Taxi trip data from Parquet source
    access: public


Membuat dokumentasi dbt

Templat Jinja

Apa yang dapat dilakukan Jinja?


# Name your project! Project names should contain only lowercase characters
# and underscores. A good package name should reflect your organization's
# name or the intended use of these models
name: 'nyc_yellow_taxi'
version: '1.0.0'
config-version: 2

# This setting configures which "profile" dbt uses for this project.
profile: 'nyc_yellow_taxi'

# These configurations specify where dbt should look for different types of files.
# The `model-paths` config, for example, states that models in this project can be
# found in the "models/" directory. You probably won't need to change these!
model-paths: ["models"]
analysis-paths: ["analyses"]
test-paths: ["tests"]
seed-paths: ["seeds"]
macro-paths: ["macros"]
snapshot-paths: ["snapshots"]

target-path: "target"  # directory which will store compiled SQL files
clean-targets:         # directories to be removed by `dbt clean`
  - "target"
  - "dbt_packages"


# Configuring models
# Full documentation: https://docs.getdbt.com/docs/configuring-models

# In this example config, we tell dbt to build all models in the example/
# directory as views. These settings can be overridden in the individual model
# files using the `{{ config(...) }}` macro.
#models:
#  nyc_yellow_taxi:
#  # Config indicated by + and applies to all files under models/example/
#    taxi_rides:
#    +materialized: view
    



select * from 'yellow_tripdata_2023-01-partial.parquet'



select
{% for column_name in ['fare_amount', 'tip_amount', 'tolls_amount', 'total_amount'] %}
  {{column_name}}{% if not loop.last %},{% endif %}
{% endfor %}
from taxi_rides_raw
   

Run the following commands in the terminal:
  
  dbt run
  

Memproses template Jinja

Model hierarkis di dbt

Urutan pembuatan model

Pembuatan model hierarkis


-- Update SQL to use Jinja reference
select 
   date_part('day', tpep_pickup_datetime) as day,
   count(*) as total_riders
-- Update the line below to use a Jinja function
from taxi_rides_raw
where payment_type = 1
group by day


#!/usr/bin/env python3
import duckdb
con = duckdb.connect('dbt.duckdb', read_only=True)
print(con.sql('select * from creditcard_riders_by_day'))
if (con.execute('select * from creditcard_riders_by_day').fetchall()[0][1] == 54743):
  with open('/home/repl/workspace/successful_data_check', 'w') as f:
    f.write('54743')
    


Run the following commands in the terminal:
dbt run
dbt run -f



# Name your project! Project names should contain only lowercase characters
# and underscores. A good package name should reflect your organization's
# name or the intended use of these models
name: 'nyc_yellow_taxi'
version: '1.0.0'
config-version: 2

# This setting configures which "profile" dbt uses for this project.
profile: 'nyc_yellow_taxi'

# These configurations specify where dbt should look for different types of files.
# The `model-paths` config, for example, states that models in this project can be
# found in the "models/" directory. You probably won't need to change these!
model-paths: ["models"]
analysis-paths: ["analyses"]
test-paths: ["tests"]
seed-paths: ["seeds"]
macro-paths: ["macros"]
snapshot-paths: ["snapshots"]

target-path: "target"  # directory which will store compiled SQL files
clean-targets:         # directories to be removed by `dbt clean`
  - "target"
  - "dbt_packages"


# Configuring models
# Full documentation: https://docs.getdbt.com/docs/configuring-models

# In this example config, we tell dbt to build all models in the example/
# directory as views. These settings can be overridden in the individual model
# files using the `{{ config(...) }}` macro.
models:
  nyc_yellow_taxi:
  # Config indicated by + and applies to all files under models/example/
    taxi_rides:
    +materialized: view



-- Update SQL to use Jinja reference
select 
   date_part('day', tpep_pickup_datetime) as day,
   count(*) as total_riders
-- Update the line below to use a Jinja function
from {{ ref('taxi_rides_raw') }}
where payment_type = 1
group by day


Memperbarui hierarki model

Lebih lanjut tentang model dbt

Kursus ini memperkenalkan Anda pada dbt (data build tool), sebuah alat populer yang memunculkan analytics engineering untuk pembuatan dan pemeliharaan pipeline extract, transform, and load (ELT). Anda akan mempelajari cara membangun gudang data, melakukan pemodelan dan transformasi data, serta merancang pengujian untuk melakukan validasi data. Anda akan menggunakan SQL dan perintah shell untuk menjalankan berbagai tugas dengan dbt, sekaligus mempelajari cara menghasilkan dokumentasi bagi pengguna gudang data Anda!

dbt, atau alat pembangunan data, telah mengguncang dunia data. Kursus ini memperkenalkan Anda pada konsep, istilah, dan metode penggunaan dbt untuk mengimplementasikan contoh data warehouse. Anda akan memahami apa itu dbt, kapan sebaiknya digunakan, dan praktik terbaik dalam implementasi data warehousing. Anda akan bekerja dengan dataset nyata dan melakukan operasi ekstraksi, pemuatan, dan transformasi yang diterapkan dalam peran analis data, insinyur data, dan insinyur analitik.

Peserta didik akan mengembangkan keterampilan untuk merancang data warehouse dari awal, memodelkan dan mentransformasi data, serta membangun tes! Kursus ini akan memberikan Anda dasar yang kokoh untuk dikembangkan dalam perjalanan DBT Anda, terlepas dari jenis data warehouse yang Anda rencanakan untuk diimplementasikan. Dapatkan kepercayaan diri dalam memahami cara dan waktu yang tepat untuk menggunakan dbt dengan mengerjakan latihan menggunakan SQL dan perintah shell.

Data Warehousing Concepts

Introduction to Shell

Joining Data in SQL

Kursus ini memperkenalkan dbt untuk pemodelan data, transformasi, pengujian, dan pembuatan dokumentasi.

Opsi Perintah dbt docs

Pengantar dbt

Latihan interaktif langsung