Free PDF 2025 Perfect Databricks Databricks-Certified-Data-Engineer-Associate: High Databricks Certified Data Engineer Associate Exam Passing Score

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q40-Q45):

NEW QUESTION # 40
A data engineer is using the following code block as part of a batch ingestion pipeline to read from a composable table:

Which of the following changes needs to be made so this code block will work when the transactions table is a stream source?

A. Replace "transactions" with the path to the location of the Delta table
B. Replace predict with a stream-friendly prediction function
C. Replace spark.read with spark.readStream
D. Replace schema(schema) with option ("maxFilesPerTrigger", 1)
E. Replace format("delta") with format("stream")

Answer: C

Explanation:
To read from a stream source, the data engineer needs to use the spark.readStream method instead of the spark.read method. The spark.readStream method returns a DataStreamReader object that can be used to specify the details of the input source, such as the format, the schema, the path, and the options. The spark.read method is only suitable for batch processing, not streaming processing. The other changes are not necessary or correct for reading from a stream source. Reference: Structured Streaming Programming Guide, Read a stream, Databricks Data Sources

NEW QUESTION # 41
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. Data Explorer
B. Unity Catalog
C. Auto Loader
D. Delta Live Tables
E. Delta Lake

Answer: D

Explanation:
Delta Live Tables is a tool that enables data engineers to build and manage reliable data pipelines with minimal code. One of the features of Delta Live Tables is data quality monitoring, which allows data engineers to define quality expectations for their data and automatically check them at every step of the pipeline. Data quality monitoring can help detect and resolve data quality issues, such as missing values, duplicates, outliers, or schema changes. Data quality monitoring can also generate alerts and reports on the quality level of the data, and enable data engineers to troubleshoot and fix problems quickly. Reference: Delta Live Tables Overview, Data Quality Monitoring

NEW QUESTION # 42
A data engineer has configured a Structured Streaming job to read from a table, manipulate the data, and then perform a streaming write into a new table.
The cade block used by the data engineer is below:

If the data engineer only wants the query to execute a micro-batch to process data every 5 seconds, which of the following lines of code should the data engineer use to fill in the blank?

A. trigger(continuous="5 seconds")
B. trigger()
C. trigger(processingTime="5 seconds")
D. trigger(once="5 seconds")
E. trigger("5 seconds")

Answer: C

Explanation:
The processingTime option specifies a time-based trigger interval for fixed interval micro-batches. This means that the query will execute a micro-batch to process data every 5 seconds, regardless of how much data is available. This option is suitable for near-real time processing workloads that require low latency and consistent processing frequency. The other options are either invalid syntax (A, C), default behavior (B), or experimental feature (E). References: Databricks Documentation - Configure Structured Streaming trigger intervals, Databricks Documentation - Trigger.

NEW QUESTION # 43
An engineering manager uses a Databricks SQL query to monitor ingestion latency for each data source. The manager checks the results of the query every day, but they are manually rerunning the query each day and waiting for the results.
Which of the following approaches can the manager use to ensure the results of the query are updated each day?

A. They can schedule the query to refresh every 12 hours from the SQL endpoint's page in Databricks SQL.
B. They can schedule the query to refresh every 1 day from the query's page in Databricks SQL.
C. They can schedule the query to refresh every 1 day from the SQL endpoint's page in Databricks SQL.
D. They can schedule the query to run every 12 hours from the Jobs UI.
E. They can schedule the query to run every 1 day from the Jobs UI.

Answer: B

Explanation:
Databricks SQL allows users to schedule queries to run automatically at a specified frequency and time zone. This can help users to keep their dashboards or alerts updated with the latest data. To schedule a query, users need to do the following steps:
In the Query Editor, click Schedule > Add schedule to open a menu with schedule settings.
Choose when to run the query. Use the dropdown pickers to specify the frequency, period, starting time, and time zone. Optionally, select the Show cron syntax checkbox to edit the schedule in Quartz Cron Syntax.
Choose More options to show optional settings. Users can also choose a name for the schedule, and a SQL warehouse to power the query.
Click Create. The query will run automatically according to the schedule.
The other options are incorrect because they do not refer to the correct location or frequency to schedule the query. The query's page in Databricks SQL is the place where users can edit, run, or schedule the query. The SQL endpoint's page in Databricks SQL is the place where users can manage the SQL warehouses and SQL endpoints. The Jobs UI is the place where users can create, run, or schedule jobs that execute notebooks, JARs, or Python scripts. Reference: Schedule a query, What are Databricks SQL alerts?, Jobs.

NEW QUESTION # 44
A data engineer is working with two tables. Each of these tables is displayed below in its entirety.

The data engineer runs the following query to join these tables together:

Which of the following will be returned by the above query?

A. Option A
B. Option C
C. Option E
D. Option B
E. Option D

Answer: B

NEW QUESTION # 45
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Free PDF 2025 Perfect Databricks Databricks-Certified-Data-Engineer-Associate: High Databricks Certified Data Engineer Associate Exam Passing Score

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q40-Q45):

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