Materializations strategy in dbt - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a materialization in dbt?

A materialization in dbt is a way to tell dbt how to build and store the results of a model, such as creating a table, view, or incremental load in the database.

beginner

Name three common materializations in dbt.

The three common materializations in dbt are:
1. Table - creates a physical table in the database.
2. View - creates a virtual table that runs the query on demand.
3. Incremental - updates only new or changed data in an existing table.

intermediate

Why would you choose an incremental materialization?

You choose incremental materialization to save time and resources by only processing new or changed data instead of rebuilding the entire table every time.

intermediate

What is the difference between a table and a view materialization?

A table materialization stores the data physically in the database, so queries are faster but use storage. A view materialization stores only the query logic, so it uses less storage but runs the query every time you access it.

beginner

How can you specify a materialization strategy in dbt?

You specify a materialization strategy in dbt by adding a config block in your model file or in the dbt_project.yml file using the 'materialized' key, for example:
config(materialized='table').

Which dbt materialization creates a physical table in the database?

A Table

B View

C Incremental

D Ephemeral

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

What is the main benefit of using incremental materialization?

A It creates a virtual table without storing data

B It rebuilds the entire table every time

C It saves time by processing only new or changed data

D It deletes the table after each run

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

Which materialization runs the query every time you access the data without storing it?

A Table

B View

C Snapshot

D Incremental

A view materialization stores the query logic and runs it on demand without storing data.

How do you set a model to use a specific materialization in dbt?

A By editing the database directly

B By renaming the model file

C By changing the SQL query

D By adding a config block with 'materialized' in the model file

You specify materialization by adding a config block like config(materialized='table') in the model file.

Which materialization is best when you want to save storage space and don't need fast query speed?

A View

B Table

C Incremental

D Ephemeral

Views save storage by not storing data physically but run queries on demand, which can be slower.

Explain what a materialization strategy is in dbt and why it matters.

Think about how dbt decides to store or run your data models.

Describe when you would use incremental materialization instead of table or view.

Consider scenarios with frequent data updates.

Practice

1. What does the table materialization do in dbt?

easy

A. Runs the model only when data changes incrementally.

B. Creates a temporary view that disappears after the session ends.

C. Creates a physical table in the database that stores data permanently.

D. Does not create any database object but runs SQL inline.

Solution

1. Step 1: Understand table materialization

   The table materialization creates a real table in the database that stores the data physically.

2. Step 2: Compare with other materializations

   Unlike views or ephemeral models, tables persist data and improve query speed for large datasets.

3. Final Answer:

   Creates a physical table in the database that stores data permanently. -> Option C

4. Quick Check:

   table materialization = physical table [OK]

Hint: Tables store data physically; views do not [OK]

Common Mistakes:

• Confusing tables with views
• Thinking ephemeral models create tables
• Assuming incremental means full table creation

2. Which of the following is the correct syntax to set a model as incremental in dbt?

easy

A. materialized: 'incremental'

B. materialization: 'incremental'

C. materialized = incremental

D. materialize: incremental

Solution

1. Step 1: Recall dbt model config syntax

   In dbt, model materialization is set using materialized: 'type' inside the model config block.

2. Step 2: Identify correct syntax for incremental

   The correct key is materialized with a colon and the value in quotes, like 'incremental'.

3. Final Answer:

   materialized: 'incremental' -> Option A

4. Quick Check:

   Use materialized: 'incremental' for incremental models [OK]

Hint: Use 'materialized' key with colon and quotes [OK]

Common Mistakes:

• Using 'materialization' instead of 'materialized'
• Missing quotes around 'incremental'
• Using equals sign instead of colon

3. Given this dbt model config and SQL, what will be the result when run?

{% if is_incremental() %}
  select * from source_table where updated_at > (select max(updated_at) from {{ this }})
{% else %}
  select * from source_table
{% endif %}

Model config:

materialized: 'incremental'

medium

A. The model will fully refresh the table every run.

B. The model will fail due to syntax error.

C. The model will create a view instead of a table.

D. The model will add only new rows with updated timestamps.

Solution

1. Step 1: Understand the incremental logic in SQL

   The SQL uses is_incremental() to run different queries: full select on first run, then only new rows after.

2. Step 2: Match with incremental materialization behavior

   With materialized: 'incremental', dbt appends new rows where updated_at is greater than the max in the existing table.

3. Final Answer:

   The model will add only new rows with updated timestamps. -> Option D

4. Quick Check:

   Incremental model adds new rows only [OK]

Hint: Incremental models append new data, not full refresh [OK]

Common Mistakes:

• Thinking incremental always refreshes full table
• Confusing view creation with incremental
• Ignoring the is_incremental() condition

4. You wrote this dbt model config:

materialized: incremental

What is the error and how to fix it?

medium

A. Wrong key name; fix: materialization: 'incremental'

B. Missing quotes around 'incremental'; fix: materialized: 'incremental'

C. Should use equals sign; fix: materialized = 'incremental'

D. No error; config is correct

Solution

1. Step 1: Identify syntax error in config

   The value incremental must be a string, so it needs quotes.

2. Step 2: Correct the syntax

   Change to materialized: 'incremental' to fix the error.

3. Final Answer:

   Missing quotes around 'incremental'; fix: materialized: 'incremental' -> Option B

4. Quick Check:

   Materialization values must be strings in quotes [OK]

Hint: Always quote materialization types [OK]

Common Mistakes:

• Forgetting quotes around materialization type
• Using wrong key 'materialization'
• Using equals sign instead of colon

5. You have a large dataset that updates daily with new and changed rows. You want fast query performance and to avoid rebuilding the entire table each time. Which materialization strategy should you choose in dbt?

hard

A. Use incremental materialization to add and update rows efficiently.

B. Use table materialization and rebuild daily.

C. Use view materialization for real-time data.

D. Use ephemeral materialization to avoid creating tables.

Solution

1. Step 1: Analyze dataset size and update pattern

   The dataset is large and updates daily with new and changed rows, so full rebuilds are costly.

2. Step 2: Match materialization to needs

   incremental materialization updates only new or changed rows, improving performance and avoiding full rebuilds.

3. Final Answer:

   Use incremental materialization to add and update rows efficiently. -> Option A

4. Quick Check:

   Incremental = efficient updates for large, changing data [OK]

Hint: Incremental suits large, frequently updated datasets [OK]

Common Mistakes:

• Choosing view which rebuilds every query
• Using table and rebuilding fully each time
• Using ephemeral which does not create tables