Databricks-DA-Assoc Executing Queries with Databricks SQL Practice Question
Exhibit
Error: [DELTA_MISSING_CHANGE_DATA_FEED] The Change Data Feed feature is not enabled on table 'sales_bronze'.
Refer to the exhibit. An analyst attempts to query table changes using the table changes function (table_changes()) to track incremental updates for a reporting pipeline, but encounters the error shown in the exhibit. How should the analyst resolve this issue?
⚠ Common exam trap
Candidates often assume Change Data Feed is enabled by default on all Delta tables or attempt to use it without altering table properties first, resulting in query failures.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Run an ALTER TABLE command to set delta.enableChangeDataFeed = true, then re-run the query.
The Change Data Feed (CDF) must be explicitly enabled on a Delta table via table properties either at creation time or through an ALTER TABLE command. Without this configuration, Delta Lake does not record the low-level row insertions, updates, and deletions required for changestream queries.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Run an ALTER TABLE command to set delta.enableChangeDataFeed = true, then re-run the query.
Why this is correct
The table_changes() function requires Change Data Feed enabled on the source table. Running ALTER TABLE to set delta.enableChangeDataFeed = true activates change tracking, after which the incremental query returns the row-level changes the reporting pipeline needs.
- ✗
Restart the SQL warehouse to clear internal metadata caches preventing change data feed access.
Why it's wrong here
Restarting the SQL warehouse cannot enable change data feed, which is a table-level property persisted in the Delta transaction log. The error arises because the table was created without delta.enableChangeDataFeed=true. Restarting warehouses clears cached metadata and sessions, which helps with stale schema or connectivity glitches, not a disabled table feature.
- ✗
Convert the table format from Delta Lake to standard Apache Parquet using a CTAS statement.
Why it's wrong here
Converting to Parquet removes the Delta transaction log entirely, and table_changes() reads that log's change data feed; Parquet has no equivalent mechanism, so the function cannot run at all. Parquet suits external tools reading static files directly, but change tracking requires Delta Lake's log and CDF property.
- ✗
Execute a VACUUM command with a retention period of zero hours to force immediate log compaction.
Why it's wrong here
VACUUM deletes unreferenced data files and does not enable change data feed; with zero hours retention it also risks breaking concurrent readers and removes history needed for change queries. VACUUM is used to reclaim storage from obsolete files, not to activate table features or repair CDF metadata.
Visual reference
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Databricks exam blueprint
This Databricks-DA-Assoc practice question is part of Courseiva's free Databricks certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Databricks-DA-Assoc exam.