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基于 SOC 职业分类
| name | dbt-coder |
| description | dbt (data build tool) patterns for model organization, incremental strategies, and testing. |
| allowed-tools | Read Write Edit Grep Glob Bash |
Patterns for dbt (data build tool) transform layer development.
my_dbt_project/
├── dbt_project.yml
├── profiles.yml
├── models/
│ ├── staging/ # 1:1 with sources, light transforms
│ │ ├── stg_orders.sql
│ │ └── _staging.yml
│ ├── intermediate/ # Joins, business logic
│ │ └── int_orders_enriched.sql
│ └── marts/ # Final consumption layer
│ ├── finance/
│ │ └── fct_revenue.sql
│ └── marketing/
│ └── dim_customers.sql
├── seeds/ # Static lookup data
├── snapshots/ # SCD Type 2
├── macros/ # Reusable SQL
└── tests/ # Custom tests
name: 'my_project'
version: '1.0.0'
config-version: 2
profile: 'my_project'
model-paths: ["models"]
seed-paths: ["seeds"]
test-paths: ["tests"]
macro-paths: ["macros"]
snapshot-paths: ["snapshots"]
models:
my_project:
staging:
+materialized: view
+schema: staging
intermediate:
+materialized: ephemeral
marts:
+materialized: table
+schema: marts
-- models/staging/stg_orders.sql
-- Naming: stg_<source>_<entity>
with source as (
select * from {{ source('raw', 'orders') }}
),
renamed as (
select
-- Rename to consistent naming
id as order_id,
customer_id,
order_date,
total_amount as order_total,
-- Type casting
cast(status as varchar(50)) as order_status,
-- Timestamps
created_at,
updated_at
from source
)
select * from renamed
# models/staging/_sources.yml
version: 2
sources:
- name: raw
database: raw_db
schema: public
freshness:
warn_after: {count: 12, period: hour}
error_after: {count: 24, period: hour}
tables:
- name: orders
identifier: orders_table
columns:
- name: id
tests:
- unique
- not_null
- name: customers
-- models/intermediate/int_orders_enriched.sql
-- Join staging models, apply business logic
with orders as (
select * from {{ ref('stg_orders') }}
),
customers as (
select * from {{ ref('stg_customers') }}
),
products as (
select * from {{ ref('stg_products') }}
)
select
o.order_id,
o.order_date,
o.order_total,
c.customer_id,
c.customer_name,
c.customer_segment,
-- Business logic
case
when o.order_total >= 1000 then 'high_value'
when o.order_total >= 100 then 'medium_value'
else 'low_value'
end as order_tier
from orders o
left join customers c on o.customer_id = c.customer_id
-- models/marts/finance/fct_revenue.sql
-- Final aggregated fact table
{{ config(
materialized='table',
partition_by={
"field": "order_date",
"data_type": "date",
"granularity": "month"
}
) }}
with orders as (
select * from {{ ref('int_orders_enriched') }}
)
select
date_trunc('day', order_date) as revenue_date,
customer_segment,
order_tier,
count(*) as order_count,
sum(order_total) as total_revenue,
avg(order_total) as avg_order_value
from orders
group by 1, 2, 3
-- models/marts/fct_events.sql
{{ config(
materialized='incremental',
unique_key='event_id',
incremental_strategy='merge' -- or 'delete+insert', 'append'
) }}
select
event_id,
user_id,
event_type,
event_timestamp,
properties
from {{ source('raw', 'events') }}
{% if is_incremental() %}
-- Only new/updated rows since last run
where event_timestamp > (select max(event_timestamp) from {{ this }})
{% endif %}
-- snapshots/snap_customers.sql
{% snapshot snap_customers %}
{{
config(
target_schema='snapshots',
unique_key='customer_id',
strategy='timestamp',
updated_at='updated_at',
)
}}
select * from {{ source('raw', 'customers') }}
{% endsnapshot %}
# models/marts/_schema.yml
version: 2
models:
- name: fct_revenue
description: Daily revenue aggregations
columns:
- name: revenue_date
tests:
- not_null
- name: total_revenue
tests:
- not_null
- dbt_utils.accepted_range:
min_value: 0
tests:
# Model-level tests
- dbt_utils.unique_combination_of_columns:
combination_of_columns:
- revenue_date
- customer_segment
- order_tier
-- tests/assert_positive_revenue.sql
-- Returns rows that fail the test
select
revenue_date,
total_revenue
from {{ ref('fct_revenue') }}
where total_revenue < 0
-- macros/cents_to_dollars.sql
{% macro cents_to_dollars(column_name) %}
round({{ column_name }} / 100.0, 2)
{% endmacro %}
-- Usage in model:
-- select {{ cents_to_dollars('amount_cents') }} as amount_dollars
-- macros/generate_schema_name.sql
{% macro generate_schema_name(custom_schema_name, node) %}
{% if custom_schema_name %}
{{ custom_schema_name }}
{% else %}
{{ target.schema }}
{% endif %}
{% endmacro %}
# Run all models
dbt run
# Run specific model and dependencies
dbt run --select fct_revenue+
# Run models with tag
dbt run --select tag:finance
# Test all
dbt test
# Generate docs
dbt docs generate
dbt docs serve
# Freshness check
dbt source freshness
# Full refresh of incremental
dbt run --full-refresh --select fct_events
# Build (run + test)
dbt build
# 1. Use ref() for model references
# BAD: select * from schema.stg_orders
# GOOD: select * from {{ ref('stg_orders') }}
# 2. Use source() for raw tables
# BAD: select * from raw_db.orders
# GOOD: select * from {{ source('raw', 'orders') }}
# 3. Document models
models:
- name: fct_revenue
description: |
Daily revenue by segment. Grain: one row per day/segment/tier.
Updated daily by the finance_dag.
meta:
owner: data-team
pii: false
# packages.yml
packages:
- package: dbt-labs/dbt_utils
version: 1.1.1
- package: dbt-labs/codegen
version: 0.12.1
- package: calogica/dbt_expectations
version: 0.10.1
# Install packages
dbt deps
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