Databricks Databricks Certifications DATABRICKS-CERTIFIED-DATA-ENGINEER-ASSOCIATE Questions & Answers

• Question 71:

  Which of the following code blocks will remove the rows where the value in column age is greater than 25 from the existing Delta table my_table and save the updated table?

  A. SELECT * FROM my_table WHERE age > 25;

  B. UPDATE my_table WHERE age > 25;

  C. DELETE FROM my_table WHERE age > 25;

  D. UPDATE my_table WHERE age <= 25;

  E. DELETE FROM my_table WHERE age <= 25;

  Correct Answer: C

• Question 72:

  A data engineer is maintaining a data pipeline. Upon data ingestion, the data engineer notices that the source data is starting to have a lower level of quality. The data engineer would like to automate the process of monitoring the quality level.

  Which of the following tools can the data engineer use to solve this problem?

  A. Unity Catalog

  B. Data Explorer

  C. Delta Lake

  D. Delta Live Tables

  E. Auto Loader

  Correct Answer: D

  Explanation: https://docs.databricks.com/delta-live-tables/expectations.html Delta Live Tables is a tool provided by Databricks that can help data engineers automate the monitoring of data quality. It is designed for managing data pipelines, monitoring data quality, and automating workflows. With Delta Live Tables, you can set up data quality checks and alerts to detect issues and anomalies in your data as it is ingested and processed in real-time. It provides a way to ensure that the data quality meets your desired standards and can trigger actions or notifications when issues are detected. While the other tools mentioned may have their own purposes in a data engineeringenvironment, Delta Live Tables is specifically designed for data quality monitoring and automation within the Databricks ecosystem.

• Question 73:

  A data engineer wants to create a data entity from a couple of tables. The data entity must be used by other data engineers in other sessions. It also must be saved to a physical location.

  Which of the following data entities should the data engineer create?

  A. Database

  B. Function

  C. View

  D. Temporary view

  E. Table

  Correct Answer: E

  Explanation: In the context described, creating a "Table" is the most suitable choice. Tables in SQL are data entities that exist independently of any session and are saved in a physical location. They can be accessed and manipulated by other data engineers in different sessions, which aligns with the requirements stated. A "Database" is a collection of tables, views, and other database objects. A "Function" is a stored procedure that performs an operation. A "View" is a virtual table based on the result-set of an SQL statement, but it is not stored physically. A "Temporary view" is a feature that allows you to store the result of a query as a view that disappears once your session with the database is closed.

• Question 74:

  A data engineer has developed a data pipeline to ingest data from a JSON source using Auto Loader, but the engineer has not provided any type inference or schema hints in their pipeline. Upon reviewing the data, the data engineer has noticed that all of the columns in the target table are of the string type despite some of the fields only including float or boolean values.

  Which of the following describes why Auto Loader inferred all of the columns to be of the string type?

  A. There was a type mismatch between the specific schema and the inferred schema

  B. JSON data is a text-based format

  C. Auto Loader only works with string data

  D. All of the fields had at least one null value

  E. Auto Loader cannot infer the schema of ingested data

  Correct Answer: B

  Explanation: JSON data is a text-based format that uses strings to represent all values. When Auto Loader infers the schema of JSON data, it assumes that all values are strings. This is because Auto Loader cannot determine the type of a value based on its string representation. https://docs.databricks.com/en/ingestion/auto-loader/schema.html Forexample, the following JSON string represents a value that is logically a boolean: JSON "true" Use code with caution. Learn more However, Auto Loader would infer that the type of this value is string. This is because Auto Loader cannot determine that the value is a boolean based on its string representation. In order to get Auto Loader to infer the correct types for columns, the data engineer can provide type inference or schema hints. Type inference hints can be used to specify the types of specific columns. Schema hints can be used to provide the entire schema of the data. Therefore, the correct answer is B. JSON data is a text-based format.

• Question 75:

  Which of the following Structured Streaming queries is performing a hop from a Silver table to a Gold table?

  

  A. Option A

  B. Option B

  C. Option C

  D. Option D

  E. Option E

  Correct Answer: E

• Question 76:

  A data engineer has a single-task Job that runs each morning before they begin working. After identifying an upstream data issue, they need to set up another task to run a new notebook prior to the original task.

  Which of the following approaches can the data engineer use to set up the new task?

  A. They can clone the existing task in the existing Job and update it to run the new notebook.

  B. They can create a new task in the existing Job and then add it as a dependency of the original task.

  C. They can create a new task in the existing Job and then add the original task as a dependency of the new task.

  D. They can create a new job from scratch and add both tasks to run concurrently.

  E. They can clone the existing task to a new Job and then edit it to run the new notebook.

  Correct Answer: B

  Explanation: To set up the new task to run a new notebook prior to the original task in a single-task Job, the data engineer can use the following approach: In the existing Job, create a new task that corresponds to the new notebook that needs to be run. Set up the new task with the appropriate configuration, specifying the notebook to be executed and any necessary parameters or dependencies. Once the new task is created, designate it as a dependency of the original task in the Job configuration. This ensures that the new task is executed before the original task.

• Question 77:

  Which of the following is stored in the Databricks customer's cloud account?

  A. Databricks web application

  B. Cluster management metadata

  C. Repos

  D. Data

  E. Notebooks

  Correct Answer: D

• Question 78:

  A data engineer wants to create a relational object by pulling data from two tables. The relational object does not need to be used by other data engineers in other sessions. In order to save on storage costs, the data engineer wants to avoid copying and storing physical data.

  Which of the following relational objects should the data engineer create?

  A. Spark SQL Table

  B. View

  C. Database

  D. Temporary view

  E. Delta Table

  Correct Answer: D

  Explanation: Temp view : session based Create temp view view_name as query All these are termed as session ended: Opening a new notebook Detaching and reattaching a cluster Installing a python package Restarting a cluster

• Question 79:

  A data engineer has a Job with multiple tasks that runs nightly. Each of the tasks runs slowly because the clusters take a long time to start. Which of the following actions can the data engineer perform to improve the start up time for the clusters used for the Job?

  A. They can use endpoints available in Databricks SQL

  B. They can use jobs clusters instead of all-purpose clusters

  C. They can configure the clusters to be single-node

  D. They can use clusters that are from a cluster pool

  E. They can configure the clusters to autoscale for larger data sizes

  Correct Answer: D

  Explanation: Cluster pools are a way to pre-provision clusters that are ready to use. This can reduce the start up time for clusters, as they do not have to be created from scratch. All-purpose clusters are not pre-provisioned, so they will take longer to start up. Jobs clusters are a type of cluster pool, but they are not the best option for this use case. Jobs clusters are designed for long-running jobs, and they can be more expensive than other types of cluster pools. Single-node clusters are the smallest type of cluster, and they will start up the fastest. However, they may not be powerful enough to run the Job's tasks. Autoscaling clusters can scale up or down based on demand. This can help to improve the start up time for clusters, as they will only be created when they are needed. However, autoscaling clusters can also be more expensive than other types of cluster pool. https://docs.databricks.com/en/clusters/pool-best-practices.html

• Question 80:

  A data engineer needs access to a table new_table, but they do not have the correct permissions. They can ask the table owner for permission, but they do not know who the table owner is. Which of the following approaches can be used to identify the owner of new_table?

  A. Review the Permissions tab in the table's page in Data Explorer

  B. All of these options can be used to identify the owner of the table

  C. Review the Owner field in the table's page in Data Explorer

  D. Review the Owner field in the table's page in the cloud storage solution

  E. There is no way to identify the owner of the table

  Correct Answer: C