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Databricks Data Engineer Associate exam dumps: questions 401 to 500 of 531

Page 5 of the free Databricks Data Engineer Associate question bank for the Databricks Certified Data Engineer Associate exam. Questions 401 to 500 are listed below, the first 5 in full with answers and explanations. Back to page 1 for the exam overview and FAQ.

Question bank last updated January 2025

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Free Databricks Data Engineer Associate practice questions

Questions 401 to 405 of 531

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Databricks Data Engineer Associate Question 401

Select 2

A data engineer is configuring a Delta table to enforce a NOT NULL constraint on the 'customer_id' column. The engineer wants to understand the impact of using ON VIOLATION DROP ROW versus ON VIOLATION FAIL UPDATE during an insert operation where some rows violate the constraint. What will happen if the constraint is violated?

A
The rows violating the NOT NULL constraint will be excluded from the table with ON VIOLATION DROP ROW.
B
The entire operation will fail if any row violates the constraint when using ON VIOLATION FAIL UPDATE.
C
The violating rows will be inserted into the table with a warning when using ON VIOLATION DROP ROW.
D
The entire table will be dropped if ON VIOLATION FAIL UPDATE is used and a constraint violation occurs.

Show answer and explanation

Correct answers: A, B

Explanation

The ON VIOLATION DROP ROW and ON VIOLATION FAIL UPDATE options define how Delta Lake handles constraint violations during write operations. DROP ROW removes invalid rows from the operation, allowing the rest to succeed, while FAIL UPDATE halts the entire operation if any constraint is violated. Understanding these behaviors is critical for ensuring data integrity and managing errors effectively in Delta tables.

A. Correct.
This is correct because ON VIOLATION DROP ROW excludes rows that violate constraints during the write operation, ensuring only valid rows are inserted.
B. Correct.
This is correct because ON VIOLATION FAIL UPDATE stops the entire transaction if any row violates the defined constraints.
C. Incorrect.
This is incorrect because ON VIOLATION DROP ROW removes violating rows from the operation, not inserts them into the table.
D. Incorrect.
This is incorrect because ON VIOLATION FAIL UPDATE does not drop the entire table, it only fails the specific write or update operation.

Databricks Data Engineer Associate Question 402

Select 2

You are working with a Delta table in Databricks that has a constraint to ensure the 'age' column contains only positive integer values. During a batch data insertion, you encounter a scenario where some rows violate this constraint. Which of the following statements accurately describes the behavior of the 'ON VIOLATION DROP ROW' and 'ON VIOLATION FAIL UPDATE' clauses if they are applied?

A
ON VIOLATION DROP ROW will exclude the violating rows from being inserted into the table.
B
ON VIOLATION DROP ROW will insert the violating rows into the table but mark them as invalid.
C
ON VIOLATION FAIL UPDATE will prevent the entire batch insert operation if any row violates the constraint.
D
ON VIOLATION FAIL UPDATE will skip only the violating rows and proceed with the insertion of valid rows.

Show answer and explanation

Correct answers: A, C

Explanation

The 'ON VIOLATION DROP ROW' clause ensures that rows violating constraints are excluded from the operation, allowing the insertion of only valid rows. Conversely, 'ON VIOLATION FAIL UPDATE' enforces strict validation by failing the entire operation if any row violates the defined constraints. These mechanisms allow for different handling strategies depending on the use case and data quality requirements.

A. Correct.
Correct: When 'ON VIOLATION DROP ROW' is used, any rows that violate the constraint are excluded from being inserted into the table.
B. Incorrect.
Incorrect: Violating rows are not inserted into the table with 'ON VIOLATION DROP ROW'; instead, they are dropped entirely.
C. Correct.
Correct: 'ON VIOLATION FAIL UPDATE' ensures that if any row violates the constraint, the entire batch operation fails, preventing partial or invalid updates.
D. Incorrect.
Incorrect: 'ON VIOLATION FAIL UPDATE' does not skip invalid rows. Instead, it fails the entire operation.

Databricks Data Engineer Associate Question 403

Select 3

A data engineering team is implementing a Change Data Capture (CDC) pipeline using Delta Lake in Databricks. They are using the APPLY CHANGES INTO command to process incremental changes from a source table into a target table. Which of the following statements correctly describe the behavior of APPLY CHANGES INTO?

A
It automatically handles merging of INSERT, UPDATE, and DELETE operations from the source into the target table.
B
It requires a unique key column or combination of columns to identify rows to be updated or deleted in the target table.
C
It performs a full table scan on both the source and target tables during each execution.
D
It supports advanced configurations like handling late-arriving data and custom update logic.
E
It can only be used for batch data processing and does not support streaming sources.

Show answer and explanation

Correct answers: A, B, D

Explanation

APPLY CHANGES INTO is a Delta Lake command that simplifies Change Data Capture (CDC) pipelines by efficiently merging incremental changes from a source table into a target table. It automatically handles INSERT, UPDATE, and DELETE operations, requires a unique key for matching rows, and supports advanced configurations like handling late-arriving data. Contrary to common misconceptions, it does not perform full table scans and supports both batch and streaming sources, making it highly versatile for modern data engineering workflows.

A. Correct.
APPLY CHANGES INTO is designed to handle incremental changes, including INSERT, UPDATE, and DELETE operations automatically. This is a core feature of the command.
B. Correct.
A unique key column or combination of columns is mandatory for APPLY CHANGES INTO to determine how changes should be applied to the target table.
C. Incorrect.
APPLY CHANGES INTO does not perform a full table scan; instead, it processes changes incrementally for efficiency.
D. Correct.
APPLY CHANGES INTO supports advanced configurations such as custom update logic and handling late-arriving data, making it flexible for various use cases.
E. Incorrect.
APPLY CHANGES INTO supports both batch and streaming sources, making it suitable for real-time data pipelines as well as batch workloads.

Databricks Data Engineer Associate Question 404

Single answer

A company is using Databricks to manage their data warehouse and has set up a Delta table to track customer order updates. They want to ensure that their analytics dashboard always shows the most recent customer order state by processing incremental changes from a source table. Which statement best describes the behavior of the APPLY CHANGES INTO operation in this scenario?

A
APPLY CHANGES INTO processes incremental changes and ensures that the target table reflects the latest state of the records in the source table.
B
APPLY CHANGES INTO deletes historical records in the target table to keep only the most recent changes.
C
APPLY CHANGES INTO appends all incremental changes from the source table into the target table without reconciling the state of the records.
D
APPLY CHANGES INTO is used to create a new Delta table from scratch and does not support updates to an existing table.

Show answer and explanation

Correct answer: A

Explanation

The APPLY CHANGES INTO operation is used in Delta Live Tables to implement Change Data Capture (CDC). It processes incremental changes from a source table and applies them to a target Delta table, ensuring the target reflects the latest state of the source data. This makes it ideal for scenarios where the most up-to-date information is needed, such as analytics dashboards.

A. Correct.
Correct: APPLY CHANGES INTO is specifically designed to process incremental changes and update the target Delta table to reflect the latest state of records in the source table. It reconciles changes such as inserts, updates, and deletes.
B. Incorrect.
Incorrect: APPLY CHANGES INTO does not delete historical records unless explicitly configured to do so. By default, it maintains a full record of changes.
C. Incorrect.
Incorrect: APPLY CHANGES INTO does not simply append changes; it aligns the target table with the source table by applying updates, inserts, and deletes based on the source data.
D. Incorrect.
Incorrect: APPLY CHANGES INTO is not used to create a new table but rather to update and manage an existing Delta table's state.

Databricks Data Engineer Associate Question 405

Select 3

You are implementing a Change Data Capture (CDC) pipeline using Databricks, and you are utilizing the APPLY CHANGES INTO command to process incremental updates into a target Delta table. The source table contains change records with the following columns: id, value, timestamp, and operation (with possible values 'insert', 'update', or 'delete'). Which of the following statements accurately describe the behavior of APPLY CHANGES INTO in this scenario?

A
APPLY CHANGES INTO requires a unique key column, such as id, to track changes and apply them correctly to the target table.
B
APPLY CHANGES INTO automatically manages merging, including handling insert, update, and delete operations, based on the operation column in the source data.
C
When using APPLY CHANGES INTO, the target Delta table schema must exactly match the schema of the source table.
D
APPLY CHANGES INTO processes only the latest change for each key within a single batch, ensuring idempotent updates to the target Delta table.
E
The APPLY CHANGES INTO command does not support delete operations and will ignore any rows where the operation column is set to 'delete'.

Show answer and explanation

Correct answers: A, B, D

Explanation

APPLY CHANGES INTO is a Databricks-specific command for implementing Change Data Capture (CDC) patterns. It requires a unique key column to track changes, supports insert, update, and delete operations, and ensures idempotency by processing only the latest change for each unique key within a batch. This makes it highly efficient and reliable for managing incremental updates to Delta tables in a CDC pipeline.

A. Correct.
Correct: APPLY CHANGES INTO requires a unique key column to identify rows in the target table and apply changes such as inserts, updates, or deletes correctly.
B. Correct.
Correct: APPLY CHANGES INTO handles all types of operations (insert, update, delete) automatically as long as the source data provides the necessary information (e.g., the operation column).
C. Incorrect.
Incorrect: The schema of the target Delta table does not have to exactly match the schema of the source table. However, the target must include the necessary columns for processing changes.
D. Correct.
Correct: APPLY CHANGES INTO ensures idempotency by processing only the latest change for each unique key within a batch, avoiding duplicate or conflicting updates.
E. Incorrect.
Incorrect: APPLY CHANGES INTO supports delete operations and will apply them to the target table when specified in the source data.

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Databricks Data Engineer Associate practice questions 401 to 500 of 531

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