Store test failures for analysis in dbt - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to select all columns from the test failures table.

dbt

SELECT [1] FROM test_failures;

Drag options to blanks, or click blank then click option'

A*

Bid

Cfailure_reason

Dtest_name

Attempts:

3 left

💡 Hint

Common Mistakes

Selecting only one column when all columns are needed.

Using incorrect column names.

Using * selects all columns from the table.

2fill in blank

medium

Complete the code to filter test failures where the failure count is greater than 5.

dbt

SELECT * FROM test_failures WHERE failure_count [1] 5;

Drag options to blanks, or click blank then click option'

A<

B<=

C=

D>

Attempts:

3 left

💡 Hint

Common Mistakes

Using < instead of >.

Using = which only matches exactly 5.

The operator > filters rows where failure_count is greater than 5.

3fill in blank

hard

Fix the error in the code to count failures grouped by test name.

dbt

SELECT test_name, COUNT([1]) FROM test_failures GROUP BY test_name;

Drag options to blanks, or click blank then click option'

Afailure_count

B*

Ctest_name

Dfailure_reason

Attempts:

3 left

💡 Hint

Common Mistakes

Counting a column that may have NULLs.

Using COUNT(test_name) which is redundant here.

Using COUNT(*) counts all rows per group.

4fill in blank

hard

Fill both blanks to create a dictionary of test names and their failure counts where count is greater than 10.

dbt

SELECT [1], [2] FROM test_failures WHERE failure_count > 10;

Drag options to blanks, or click blank then click option'

Atest_name

Bfailure_count

Cfailure_reason

Dtest_date

Attempts:

3 left

💡 Hint

Common Mistakes

Selecting columns unrelated to failure counts.

Forgetting to filter by failure count > 10.

Selecting test_name and failure_count gives the test and its failure count.

5fill in blank

hard

Fill all three blanks to create a summary of failures grouped by test name and ordered by failure count descending.

dbt

SELECT [1], SUM([2]) AS total_failures FROM test_failures GROUP BY [3] ORDER BY total_failures DESC;

Drag options to blanks, or click blank then click option'

Atest_name

Bfailure_count

Dfailure_reason

Attempts:

3 left

💡 Hint

Common Mistakes

Grouping by wrong column.

Summing wrong column.

Not ordering results correctly.

Grouping by test_name and summing failure_count gives total failures per test.

Practice

1. What does setting store_failures = true in a dbt test configuration do?

easy

A. It sends an email notification when a test fails.

B. It skips the test execution entirely.

C. It deletes the rows that fail the test from the source table.

D. It saves the rows that fail the test for later analysis.

Solution

1. Step 1: Understand the purpose of store_failures

   This setting controls whether dbt saves the rows that fail a test.

2. Step 2: Identify the effect of setting it to true

   When set to true, dbt stores failing rows in a table for analysis.

3. Final Answer:

   It saves the rows that fail the test for later analysis. -> Option D

4. Quick Check:

   store_failures = true means save failing rows [OK]

Hint: Remember: store_failures saves failing rows for review [OK]

Common Mistakes:

• Thinking it skips tests instead of saving failures
• Assuming it deletes data on failure
• Confusing it with notification settings

2. Which of the following is the correct way to enable storing failures in a dbt test config?

easy

A. config(store_failures == true)

B. config(store_failures: true)

C. config(store_failures = true)

D. config(store_failures = "true")

Solution

1. Step 1: Recall dbt config syntax

   dbt uses Python-like syntax with keyword arguments inside config().

2. Step 2: Identify the correct assignment

   The correct syntax uses equals sign and boolean true without quotes.

3. Final Answer:

   config(store_failures = true) -> Option C

4. Quick Check:

   Use equals and boolean true without quotes [OK]

Hint: Use equals sign and true without quotes in config() [OK]

Common Mistakes:

• Using colon instead of equals sign
• Using double equals (==) instead of single equals
• Putting true in quotes making it a string

3. After running a dbt test with store_failures = true, which SQL query will show the failing rows for a model named orders and test unique?

medium

A. SELECT * FROM dbt_test__orders__unique

B. SELECT * FROM orders WHERE test = 'unique' AND status = 'fail'

C. SELECT * FROM dbt_failures.orders_unique

D. SELECT * FROM test_failures.orders_unique

Solution

1. Step 1: Recall naming convention for failure tables

   dbt stores failures in tables named dbt_test__model__test.

2. Step 2: Apply model and test names

   For model 'orders' and test 'unique', the table is dbt_test__orders__unique.

3. Final Answer:

   SELECT * FROM dbt_test__orders__unique -> Option A

4. Quick Check:

   Failure table = dbt_test__model__test [OK]

Hint: Use dbt_test__model__test naming to find failure tables [OK]

Common Mistakes:

• Assuming failure data is in original model table
• Using incorrect table prefixes
• Trying to filter failures in source tables

4. You set store_failures = true in your test config, but after running tests, no failure tables appear. What is the most likely cause?

medium

A. The test did not find any failing rows, so no failure table was created.

B. You must manually create failure tables before running tests.

C. The store_failures setting only works for schema tests, not data tests.

D. Failure tables are stored in a different schema and need to be queried there.

Solution

1. Step 1: Understand when failure tables are created

   Failure tables are only created if the test finds failing rows.

2. Step 2: Check if test found failures

   If no failures, no failure table is generated.

3. Final Answer:

   The test did not find any failing rows, so no failure table was created. -> Option A

4. Quick Check:

   No failures means no failure table [OK]

Hint: No failure rows means no failure table created [OK]

Common Mistakes:

• Thinking failure tables must be pre-created
• Assuming store_failures only works for some test types
• Looking in wrong schema without verifying failures

5. You want to analyze failing rows from multiple tests on the customers model. Which approach best helps you combine all failure data for analysis?

hard

A. Manually export failure tables and merge them outside the database.

B. Create a union query combining all dbt_test__customers__* failure tables.

C. Run each test again with store_failures = false to avoid duplicates.

D. Use the original customers table and filter rows with errors.

Solution

1. Step 1: Identify failure tables for each test

   Each test creates a failure table named dbt_test__customers__testname.

2. Step 2: Combine failure tables using SQL UNION

   Use a UNION query to combine all failure rows from these tables into one result set.

3. Final Answer:

   Create a union query combining all dbt_test__customers__* failure tables. -> Option B

4. Quick Check:

   Union failure tables to analyze all failures together [OK]

Hint: Use UNION on all failure tables for combined analysis [OK]

Common Mistakes:

• Disabling store_failures loses failure data
• Merging outside database is inefficient
• Filtering original table misses failure details