Materializations (view, table, incremental, ephemeral) in dbt - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a view materialization in dbt?

A view materialization creates a virtual table in the database. It does not store data physically but runs the query every time you access it, like a saved question you ask repeatedly.

beginner

How does a table materialization differ from a view in dbt?

A table materialization creates a physical table in the database. It stores the data permanently until refreshed, so queries run faster because data is precomputed.

intermediate

What is the purpose of incremental materialization in dbt?

Incremental materialization updates only new or changed data in a table instead of rebuilding the whole table. This saves time and resources when working with large datasets.

intermediate

Explain ephemeral materialization in dbt.

Ephemeral materialization does not create any table or view. Instead, it inlines the SQL code into downstream models. It's like a temporary helper used only during query execution.

intermediate

When should you use incremental materialization instead of table materialization?

Use incremental when your data updates regularly but only a small part changes each time. It speeds up processing by adding or updating just new data, not rebuilding everything.

Which dbt materialization creates a virtual table that runs the query every time you access it?

A View

B Table

C Incremental

D Ephemeral

A view materialization creates a virtual table that runs the query on demand.

What does table materialization do in dbt?

A Creates a temporary inline SQL snippet

B Creates a physical table storing data

C Updates only new data

D Creates a virtual table without storing data

Table materialization creates a physical table that stores data permanently.

Which materialization is best for large datasets that update incrementally?

A View

B Table

C Incremental

D Ephemeral

Incremental materialization updates only new or changed data, saving time.

What happens with ephemeral materialization in dbt?

A Inlines SQL code into downstream models

B Creates a physical table

C Creates a view

D Updates data incrementally

Ephemeral materialization inlines SQL code and does not create tables or views.

Why choose incremental over table materialization?

A To inline SQL code

B To store data permanently

C To create a virtual table

D To update only new or changed data

Incremental materialization updates only new or changed data, improving efficiency.

Describe the four types of materializations in dbt and when to use each.

Think about how data is stored or updated in each type.

Explain how incremental materialization improves performance compared to full table rebuilds.

Consider what happens when you update a big table fully versus partially.

Practice

1. Which dbt materialization creates a permanent table in the database that stores data physically?

easy

A. table

B. view

C. incremental

D. ephemeral

Solution

1. Step 1: Understand the purpose of 'table' materialization

   The 'table' materialization creates a physical table in the database that stores data permanently.

2. Step 2: Compare with other materializations

   'view' creates a virtual table, 'incremental' updates existing tables efficiently, and 'ephemeral' runs inline SQL without creating tables.

3. Final Answer:

   table -> Option A

4. Quick Check:

   Permanent storage = table [OK]

Hint: Permanent data storage means 'table' materialization [OK]

Common Mistakes:

• Confusing 'view' with 'table' as both represent data
• Thinking 'incremental' creates a full new table every time
• Assuming 'ephemeral' creates physical tables

2. Which of the following is the correct syntax to specify an incremental materialization in a dbt model's config block?

easy

A. config(materialization = 'incremental')

B. config(materialized = 'incremental')

C. materialized('incremental')

D. set materialized = incremental

Solution

1. Step 1: Recall dbt config syntax for materialization

   dbt uses config() with the keyword 'materialized' to set materialization type.

2. Step 2: Identify the correct keyword and format

   The correct syntax is config(materialized = 'incremental'). Other options use wrong keywords or syntax.

3. Final Answer:

   config(materialized = 'incremental') -> Option B

4. Quick Check:

   Correct keyword is 'materialized' inside config() [OK]

Hint: Use config(materialized = 'type') syntax for materializations [OK]

Common Mistakes:

• Using 'materialization' instead of 'materialized'
• Trying to call materialized as a function
• Using SQL-like SET syntax instead of config()

3. Given this dbt model config and SQL snippet:

-- model.sql
{{ config(materialized='incremental', unique_key='id') }}
select id, value from source_table
{% if is_incremental() %}
  where updated_at > (select max(updated_at) from {{ this }})
{% endif %}

What happens when you run this model multiple times?

medium

A. The model rebuilds the entire table every time

B. The model creates a view that always shows fresh data

C. The model appends only new or updated rows based on 'updated_at'

D. The model runs inline SQL without creating a table

Solution

1. Step 1: Understand incremental materialization with unique_key

   The model uses incremental materialization with a unique key 'id' to update data efficiently.

2. Step 2: Analyze the is_incremental() condition

   When running incrementally, it filters rows where 'updated_at' is newer than the max in the existing table, appending only new or updated rows.

3. Final Answer:

   The model appends only new or updated rows based on 'updated_at' -> Option C

4. Quick Check:

   Incremental + filter = append updates [OK]

Hint: Incremental with is_incremental() filters new data only [OK]

Common Mistakes:

• Thinking incremental rebuilds full table every run
• Confusing view materialization with incremental
• Ignoring the is_incremental() condition

4. You wrote this dbt model:

{{ config(materialized='ephemeral') }}
select * from source_table

But when you run dbt, you get an error saying the model is not found. What is the likely cause?

medium

A. Ephemeral models do not create tables or views, so they cannot be run directly

B. The config syntax for ephemeral is incorrect

C. Ephemeral models require a unique_key to run

D. You must specify incremental materialization for ephemeral models

Solution

1. Step 1: Recall what ephemeral materialization does

   Ephemeral models do not create tables or views; their SQL is inlined into dependent models.

2. Step 2: Understand why the error occurs

   Since ephemeral models don't create database objects, running them directly causes a 'model not found' error.

3. Final Answer:

   Ephemeral models do not create tables or views, so they cannot be run directly -> Option A

4. Quick Check:

   Ephemeral = inline SQL, no table/view created [OK]

Hint: Ephemeral models can't be run alone; they inline SQL [OK]

Common Mistakes:

• Trying to run ephemeral models directly
• Assuming ephemeral needs unique_key
• Confusing ephemeral with incremental

5. You want to build a dbt model that:
- Stores data permanently
- Updates only new rows efficiently
- Avoids rebuilding the entire dataset each run

Which materialization should you choose and why?

hard

A. Use 'table' materialization because it stores data permanently and rebuilds fully each run

B. Use 'ephemeral' materialization because it runs inline SQL without storage

C. Use 'view' materialization because it always shows fresh data without storage

D. Use 'incremental' materialization because it stores data permanently and updates only new rows

Solution

1. Step 1: Identify permanent storage requirement

   Both 'table' and 'incremental' materializations store data permanently.

2. Step 2: Consider update efficiency

   'Table' rebuilds fully each run, while 'incremental' updates only new or changed rows efficiently.

3. Step 3: Match requirements

   Since you want to avoid full rebuilds and update only new rows, 'incremental' fits best.

4. Final Answer:

   Use 'incremental' materialization because it stores data permanently and updates only new rows -> Option D

5. Quick Check:

   Permanent + efficient updates = incremental [OK]

Hint: Incremental = permanent storage + efficient updates [OK]

Common Mistakes:

• Choosing 'table' and expecting incremental updates
• Picking 'view' which does not store data permanently
• Confusing ephemeral with storage options