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Databricks Certified Data Engineer Associate Exam Sample Questions (Q109-Q114):

NEW QUESTION # 109
Which single Databricks CLI command deploys local bundle assets to the target workspace specified in the configuration file?

Answer: D

Explanation:
databricks bundle deploy deploys the local bundle files and resources to the target workspace defined in the bundle configuration.


NEW QUESTION # 110
Which single Databricks CLI command deploys local bundle assets to the target workspace specified in the bundle configuration file?

Answer: D


NEW QUESTION # 111
Which of the following is stored in the Databricks customer's cloud account?

Answer: A


NEW QUESTION # 112
A data engineer streams customer orders into a Kafka topic (orders_topic) and is currently writing the ingestion script of a DLT pipeline. The data engineer needs to ingest the data from Kafka brokers to DLT using Databricks. What is the correct code for ingesting the data?

Answer: D

Explanation:
The correct way to ingest Kafka data into a Delta Live Tables pipeline is with SQL using CREATE LIVE TABLE ... AS SELECT ... FROM STREAM kafka.... This properly connects to the Kafka broker, subscribes to the topic, and casts the Kafka message value field for downstream processing in DLT.


NEW QUESTION # 113
A Delta Live Table pipeline includes two datasets defined using streaming live table. Three datasets are defined against Delta Lake table sources using live table.
The table is configured to run in Production mode using the Continuous Pipeline Mode.
What is the expected outcome after clicking Start to update the pipeline assuming previously unprocessed data exists and all definitions are valid?

Answer: D

Explanation:
In Delta Live Tables (DLT), when configured to run in Continuous Pipeline Mode, particularly in a production environment, the system is designed to continuously process and update data as it becomes available. This mode keeps the compute resources active to handle ongoing data processing and automatically updates all datasets defined in the pipeline at predefined intervals. Once the pipeline is manually stopped, the compute resources are terminated to conserve resources and reduce costs. This mode is suitable for production environments where datasets need to be kept up-to-date with the latest data.
Reference:
Databricks documentation on Delta Live Tables: Delta Live Tables Guide


NEW QUESTION # 114
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