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Pass Guaranteed Quiz 2025 Databricks-Certified-Data-Engineer-Associate - Pass Databricks Certified Data Engineer Associate Exam Rate

Pass Guaranteed Quiz 2025 Databricks-Certified-Data-Engineer-Associate - Pass Databricks Certified Data Engineer Associate Exam Rate

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q16-Q21):

NEW QUESTION # 16
A data engineer has been using a Databricks SQL dashboard to monitor the cleanliness of the input data to a data analytics dashboard for a retail use case. The job has a Databricks SQL query that returns the number of store-level records where sales is equal to zero. The data engineer wants their entire team to be notified via a messaging webhook whenever this value is greater than 0.
Which of the following approaches can the data engineer use to notify their entire team via a messaging webhook whenever the number of stores with $0 in sales is greater than zero?

  • A. They can set up an Alert with a custom template.
  • B. They can set up an Alert with one-time notifications.
  • C. They can set up an Alert without notifications.
  • D. They can set up an Alert with a new webhook alert destination.
  • E. They can set up an Alert with a new email alert destination.

Answer: D

Explanation:
A webhook alert destination is a notification destination that allows Databricks to send HTTP POST requests to a third-party endpoint when an alert is triggered. This enables the data engineer to integrate Databricks alerts with their preferred messaging or collaboration platform, such as Slack, Microsoft Teams, or PagerDuty.
To set up a webhook alert destination, the data engineer needs to create and configure a webhook connector in their messaging platform, and then add the webhook URL to the Databricks notification destination. After that, the data engineer can create an alert for their Databricks SQL query, and select the webhook alert destination as the notification destination. The alert can be configured with a custom condition, such as when the number of stores with $0 in sales is greater than zero, and a custom message template, such as "Alert:{number_of_stores} stores have $0 in sales". The alert can also be configured with a recurrence interval, such as every hour, to check the query result periodically. When the alert condition is met, the data engineer and their team will receive a notification via the messaging webhook, with the custom message and a link to the Databricks SQL query. The other options are either not suitable for sending notifications via a messaging webhook (A, B, E), or not suitable for sending recurring notifications.
References: Databricks Documentation - Manage notification destinations, Databricks Documentation - Create alerts for Databricks SQL queries, Databricks Documentation - Configure alert conditions and messages.


NEW QUESTION # 17
A data engineer has a Python variable table_name that they would like to use in a SQL query. They want to construct a Python code block that will run the query using table_name.
They have the following incomplete code block:
____(f"SELECT customer_id, spend FROM {table_name}")
Which of the following can be used to fill in the blank to successfully complete the task?

  • A. spark.table
  • B. dbutils.sql
  • C. spark.delta.table
  • D. spark.delta.sql
  • E. spark.sql

Answer: E

Explanation:
The spark.sql method can be used to execute SQL queries programmatically and return the result as a DataFrame. The spark.sql method accepts a string argument that contains a valid SQL statement. The data engineer can use a formatted string literal (f-string) to insert the Python variable table_name into the SQL query. The other methods are either invalid or not suitable for running SQL queries. Reference: Running SQL Queries Programmatically, Formatted string literals, spark.sql


NEW QUESTION # 18
A data engineer wants to schedule their Databricks SQL dashboard to refresh once per day, but they only want the associated SQL endpoint to be running when it is necessary.
Which of the following approaches can the data engineer use to minimize the total running time of the SQL endpoint used in the refresh schedule of their dashboard?

  • A. They can ensure the dashboard's SQL endpoint matches each of the queries' SQL endpoints.
  • B. They can ensure the dashboard's SQL endpoint is not one of the included query's SQL endpoint.
  • C. They can set up the dashboard's SQL endpoint to be serverless.
  • D. They can turn on the Auto Stop feature for the SQL endpoint.
  • E. They can reduce the cluster size of the SQL endpoint.

Answer: C

Explanation:
A serverless SQL endpoint is a compute resource that is automatically managed by Databricks and scales up or down based on the workload. A serverless SQL endpoint can be used to run queries and dashboards without requiring manual configuration or management. A serverless SQL endpoint is only active when it is needed and shuts down automatically when idle, minimizing the total running time and cost. A serverless SQL endpoint can be created and assigned to a dashboard using the Databricks SQL UI or the SQL Analytics API. References:
* Create a serverless SQL endpoint
* Assign a SQL endpoint to a dashboard
* SQL Analytics API


NEW QUESTION # 19
Which of the following Structured Streaming queries is performing a hop from a Silver table to a Gold table?

  • A.
  • B.
  • C.
  • D.
  • E.

Answer: D


NEW QUESTION # 20
Which of the following describes when to use the CREATE STREAMING LIVE TABLE (formerly CREATE INCREMENTAL LIVE TABLE) syntax over the CREATE LIVE TABLE syntax when creating Delta Live Tables (DLT) tables using SQL?

  • A. CREATE STREAMING LIVE TABLE should be used when data needs to be processed incrementally.
  • B. CREATE STREAMING LIVE TABLE should be used when the previous step in the DLT pipeline is static.
  • C. CREATE STREAMING LIVE TABLE should be used when data needs to be processed through complicated aggregations.
  • D. CREATE STREAMING LIVE TABLE is redundant for DLT and it does not need to be used.
  • E. CREATE STREAMING LIVE TABLE should be used when the subsequent step in the DLT pipeline is static.

Answer: A

Explanation:
Explanation
The CREATE STREAMING LIVE TABLE syntax is used when you want to create Delta Live Tables (DLT) tables that are designed for processing data incrementally. This is typically used when your data pipeline involves streaming or incremental data updates, and you want the table to stay up to date as new data arrives.
It allows you to define tables that can handle data changes incrementally without the need for full table refreshes.


NEW QUESTION # 21
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