Configuring sources in YAML in dbt - Practice Exercises

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the effect of this source configuration in YAML?

Given this YAML snippet configuring a source in dbt, what will be the resulting source name and table name in dbt's catalog?

dbt

version: 2
sources:
  - name: sales_data
    tables:
      - name: transactions
        description: "Table of all sales transactions"
        identifier: sales_txn

A Source name: sales_data, Table name: transactions

B Source name: sales_data, Table name: sales_txn

C Source name: sales_txn, Table name: transactions

D Source name: transactions, Table name: sales_data

💡 Hint

Look at the 'identifier' field in the table configuration.

In dbt source configuration, the 'name' under 'sources' is the source name. The 'name' under 'tables' is the logical table name used in dbt, but the actual physical table name in the database is set by 'identifier'. Here, 'identifier: sales_txn' means the physical table is 'sales_txn'.

❓ data_output

intermediate

How many sources and tables are defined in this YAML?

Count the total number of sources and tables defined in this YAML configuration.

dbt

version: 2
sources:
  - name: marketing
    tables:
      - name: campaigns
      - name: leads
  - name: finance
    tables:
      - name: invoices
      - name: payments
      - name: refunds

A 3 sources, 4 tables

B 3 sources, 5 tables

C 2 sources, 5 tables

D 2 sources, 4 tables

💡 Hint

Count the top-level source entries and sum their tables.

There are two sources: 'marketing' and 'finance'. Marketing has 2 tables, finance has 3 tables, total 5 tables.

🔧 Debug

advanced

Identify the error in this source YAML configuration

What error will dbt raise when parsing this YAML source configuration?

dbt

version: 2
sources:
  - name: customer_data
    tables:
      - name: customers
        identifier: cust
      - identifier: orders

A TypeError: 'tables' must be a dictionary, not a list

B KeyError: 'identifier' missing for first table

C No error, configuration is valid

D SyntaxError: Missing 'name' for the second table

💡 Hint

Check if every table entry has a 'name' key.

Each table in 'tables' must have a 'name' key. The second table entry lacks 'name', causing a parsing error.

🧠 Conceptual

advanced

What is the purpose of the 'loaded_at_field' in a source configuration?

In dbt source YAML configuration, what does the 'loaded_at_field' property specify?

A It defines the timestamp field indicating when the source data was last loaded.

B It sets the default schema for the source tables.

C It specifies the primary key field of the source table.

D It marks the field used for incremental model partitioning.

💡 Hint

Think about tracking freshness of source data.

'loaded_at_field' tells dbt which column holds the timestamp of the last data load, useful for freshness checks.

🚀 Application

expert

Which YAML snippet correctly configures a source with a schema override and a freshness policy?

Select the YAML snippet that correctly sets a source named 'web_logs' with a schema 'analytics', a table 'events', and a freshness policy of 24 hours.

A

version: 2
sources:
  - name: web_logs
    schema: analytics
    tables:
      - name: events
        freshness:
          warn_after: {count: 24, period: hour}

B

version: 2
sources:
  - name: web_logs
    schema: analytics
    freshness:
      warn_after: {count: 24, period: hour}
    tables:
      - name: events

C

version: 2
sources:
  - name: web_logs
    tables:
      - name: events
        schema: analytics
        freshness:
          warn_after: {count: 24, period: hour}

D

version: 2
sources:
  - name: web_logs
    schema: analytics
    tables:
      - name: events
    freshness:
      warn_after: {count: 24, period: hour}

💡 Hint

Freshness is set per table, schema is set per source.

In dbt, 'schema' is set at the source level. 'freshness' is configured per table inside the tables list. Option A correctly places freshness under the table 'events'.