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Free PDF Databricks - Databricks-Certified-Data-Engineer-Associate - The Best Test Databricks Certified Data Engineer Associate Exam Engine

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The Databricks Databricks-Certified-Data-Engineer-Associate exam has 50 multiple-choice questions, and the candidate has 90 minutes to complete it. It is an online exam that can be taken at any time and from anywhere in the world. The questions in the exam are designed to test the candidate's ability to handle real-world data engineering challenges. Databricks-Certified-Data-Engineer-Associate Exam also tests the candidate's understanding of the Databricks platform and how it can be used to solve data engineering problems.

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Becoming a Databricks Certified Data Engineer Associate provides several benefits to candidates. Firstly, it validates their skills and knowledge in data engineering, making them more competitive in the job market. Secondly, it demonstrates their commitment to staying current with the latest technologies and their dedication to professional development. Finally, it provides them with access to a community of Databricks-certified professionals, which can help them network and collaborate with other data engineers.

Databricks Certified Data Engineer Associate Exam Sample Questions (Q107-Q112):

NEW QUESTION # 107
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 1 day from the query's page in Databricks SQL.
B. They can schedule the query to refresh every 1 day from the SQL endpoint's page in Databricks SQL.
C. They can schedule the query to refresh every 12 hours from the SQL endpoint's page in Databricks SQL.
D. They can schedule the query to run every 1 day from the Jobs UI.
E. They can schedule the query to run every 12 hours from the Jobs UI.

Answer: A

Explanation:
Explanation
https://docs.databricks.com/en/sql/user/queries/schedule-query.html

NEW QUESTION # 108
A new data engineering team team. has been assigned to an ELT project. The new data engineering team will need full privileges on the database customers to fully manage the project.
Which of the following commands can be used to grant full permissions on the database to the new data engineering team?

A. GRANT SELECT PRIVILEGES ON DATABASE customers TO teams;
B. GRANT USAGE ON DATABASE customers TO team;
C. GRANT ALL PRIVILEGES ON DATABASE team TO customers;
D. GRANT SELECT CREATE MODIFY USAGE PRIVILEGES ON DATABASE customers TO team;
E. GRANT ALL PRIVILEGES ON DATABASE customers TO team;

Answer: E

Explanation:
To grant full permissions on a database to a user, group, or service principal, the GRANT ALL PRIVILEGES ON DATABASE command can be used. This command grants all the applicable privileges on the database, such as CREATE, SELECT, MODIFY, and USAGE. The other options are either incorrect or incomplete, as they do not grant all the privileges or specify the wrong database or principal. Reference:
GRANT
Privileges

NEW QUESTION # 109
A data engineer is designing a data pipeline. The source system generates files in a shared directory that is also used by other processes. As a result, the files should be kept as is and will accumulate in the directory. The data engineer needs to identify which files are new since the previous run in the pipeline, and set up the pipeline to only ingest those new files with each run.
Which of the following tools can the data engineer use to solve this problem?

A. Auto Loader
B. Delta Lake
C. Unity Catalog
D. Data Explorer
E. Databricks SQL

Answer: A

Explanation:
Auto Loader is a tool that can incrementally and efficiently process new data files as they arrive in cloud storage without any additional setup. Auto Loader provides a Structured Streaming source called cloudFiles, which automatically detects and processes new files in a given input directory path on the cloud file storage.
Auto Loader also tracks the ingestion progress and ensures exactly-once semantics when writing data into Delta Lake. Auto Loader can ingest various file formats, such as JSON, CSV, XML, PARQUET, AVRO, ORC, TEXT, and BINARYFILE. Auto Loader has support for both Python and SQL in Delta Live Tables, which are a declarative way to build production-quality data pipelines with Databricks. References: What is Auto Loader?, Get started with Databricks Auto Loader, Auto Loader in Delta Live Tables

NEW QUESTION # 110
A data analyst has created a Delta table sales that is used by the entire data analysis team. They want help from the data engineering team to implement a series of tests to ensure the data is clean. However, the data engineering team uses Python for its tests rather than SQL.
Which of the following commands could the data engineering team use to access sales in PySpark?

A. spark.sql("sales")
B. spark.delta.table("sales")
C. There is no way to share data between PySpark and SQL.
D. SELECT * FROM sales
E. spark.table("sales")

Answer: E

NEW QUESTION # 111
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(processingTime="5 seconds")
C. trigger(once="5 seconds")
D. trigger("5 seconds")
E. trigger()

Answer: B

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 # 112
......

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