Latest Databricks-Certified-Data-Engineer-Associate Actual Free Exam Questions Updated 89 Questions
Free Databricks-Certified-Data-Engineer-Associate Exam Braindumps certification guide Q&A
NEW QUESTION # 14
In which of the following file formats is data from Delta Lake tables primarily stored?
- A. A proprietary, optimized format specific to Databricks
- B. CSV
- C. Parquet
- D. Delta
- E. JSON
Answer: C
Explanation:
Explanation
https://docs.delta.io/latest/delta-faq.html
NEW QUESTION # 15
A data engineer has realized that they made a mistake when making a daily update to a table. They need to use Delta time travel to restore the table to a version that is 3 days old. However, when the data engineer attempts to time travel to the older version, they are unable to restore the data because the data files have been deleted.
Which of the following explains why the data files are no longer present?
- A. The TIME TRAVEL command was run on the table
- B. The HISTORY command was run on the table
- C. The OPTIMIZE command was nun on the table
- D. The VACUUM command was run on the table
- E. The DELETE HISTORY command was run on the table
Answer: E
NEW QUESTION # 16
A data architect has determined that a table of the following format is necessary:
Which of the following code blocks uses SQL DDL commands to create an empty Delta table in the above format regardless of whether a table already exists with this name?
- A. Option E
- B. Option D
- C. Option A
- D. Option C
- E. Option B
Answer: A
NEW QUESTION # 17
Which of the following commands can be used to write data into a Delta table while avoiding the writing of duplicate records?
- A. INSERT
- B. DROP
- C. APPEND
- D. IGNORE
- E. MERGE
Answer: E
Explanation:
Explanation
To write data into a Delta table while avoiding the writing of duplicate records, you can use the MERGE command. The MERGE command in Delta Lake allows you to combine the ability to insert new records and update existing records in a single atomic operation. The MERGE command compares the data being written with the existing data in the Delta table based on specified matching criteria, typically using a primary key or unique identifier. It then performs conditional actions, such as inserting new records or updating existing records, depending on the comparison results. By using the MERGE command, you can handle the prevention of duplicate records in a more controlled and efficient manner. It allows you to synchronize and reconcile data from different sources while avoiding duplication and ensuring data integrity.
NEW QUESTION # 18
A data engineer needs to create a table in Databricks using data from their organization's existing SQLite database.
They run the following command:
Which of the following lines of code fills in the above blank to successfully complete the task?
- A. autoloader
- B. sqlite
- C. org.apache.spark.sql.jdbc
- D. org.apache.spark.sql.sqlite
- E. DELTA
Answer: D
NEW QUESTION # 19
Which of the following Git operations must be performed outside of Databricks Repos?
- A. Clone
- B. Push
- C. Pull
- D. Merge
- E. Commit
Answer: A
NEW QUESTION # 20
A data engineer is attempting to drop a Spark SQL table my_table and runs the following command:
DROP TABLE IF EXISTS my_table;
After running this command, the engineer notices that the data files and metadata files have been deleted from the file system.
Which of the following describes why all of these files were deleted?
- A. The table's data was larger than 10 GB
- B. The table was external
- C. The table did not have a location
- D. The table's data was smaller than 10 GB
- E. The table was managed
Answer: E
Explanation:
Explanation
managed tables files and metadata are managed by metastore and will be deleted when the table is dropped .
while external tables the metadata is stored in a external location. hence when a external table is dropped you clear off only the metadata and the files (data) remain.
NEW QUESTION # 21
Which of the following benefits is provided by the array functions from Spark SQL?
- A. An ability to work with complex, nested data ingested from JSON files
- B. An ability to work with data in a variety of types at once
- C. An ability to work with an array of tables for procedural automation
- D. An ability to work with time-related data in specified intervals
- E. An ability to work with data within certain partitions and windows
Answer: A
Explanation:
Explanation
Array functions in Spark SQL are primarily used for working with arrays and complex, nested data structures, such as those often encountered when ingesting JSON files. These functions allow you to manipulate and query nested arrays and structures within your data, making it easier to extract and work with specific elements or values within complex data formats. While some of the other options (such as option A for working with different data types) are features of Spark SQL or SQL in general, array functions specifically excel at handling complex, nested data structures like those found in JSON files.
NEW QUESTION # 22
Which of the following can be used to simplify and unify siloed data architectures that are specialized for specific use cases?
- A. All of these
- B. Data lake
- C. Data lakehouse
- D. Data warehouse
- E. None of these
Answer: C
NEW QUESTION # 23
Which of the following describes a scenario in which a data engineer will want to use a single-node cluster?
- A. When they are working interactively with a small amount of data
- B. When they are manually running reports with a large amount of data
- C. When they are working with SQL within Databricks SQL
- D. When they are running automated reports to be refreshed as quickly as possible
- E. When they are concerned about the ability to automatically scale with larger data
Answer: A
Explanation:
Explanation
A Single Node cluster is a cluster consisting of an Apache Spark driver and no Spark workers. A Single Node cluster supports Spark jobs and all Spark data sources, including Delta Lake. A Standard cluster requires a minimum of one Spark worker to run Spark jobs.
NEW QUESTION # 24
Which of the following describes the type of workloads that are always compatible with Auto Loader?
- A. Streaming workloads
- B. Machine learning workloads
- C. Dashboard workloads
- D. Serverless workloads
- E. Batch workloads
Answer: A
Explanation:
Explanation
Auto Loader is a feature of Databricks that simplifies and automates the process of loading streaming data into Delta Lake tables. Auto Loader can detect new and updated files in cloud storage and efficiently load them as micro-batches or as a continuous stream. Auto Loader is always compatible with streaming workloads, as it is designed to handle streaming sources such as Amazon S3, Azure Data Lake Storage Gen2, and Azure Blob Storage. The other types of workloads may or may not be compatible with Auto Loader, depending on the data source and the use case. References: The information can be referenced from Databricks documentation on Auto Loader: Auto Loader.
https://community.databricks.com/t5/data-engineering/practice-exams-for-databricks-certified-data-engineer/td-p
NEW QUESTION # 25
Which of the following is hosted completely in the control plane of the classic Databricks architecture?
- A. JDBC data source
- B. Worker node
- C. Databricks Filesystem
- D. Databricks web application
- E. Driver node
Answer: E
NEW QUESTION # 26
A data engineer that is new to using Python needs to create a Python function to add two integers together and return the sum?
Which of the following code blocks can the data engineer use to complete this task?
- A.
- B.
- C.
- D.
- E.
Answer: A
Explanation:
Explanation
https://www.w3schools.com/python/python_functions.asp
NEW QUESTION # 27
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 reduce the cluster size of the SQL endpoint.
- B. They can turn on the Auto Stop feature for the SQL endpoint.
- C. They can ensure the dashboard's SQL endpoint is not one of the included query's SQL endpoint.
- D. They can set up the dashboard's SQL endpoint to be serverless.
- E. They can ensure the dashboard's SQL endpoint matches each of the queries' SQL endpoints.
Answer: B
NEW QUESTION # 28
A data engineer needs to create a table in Databricks using data from their organization's existing SQLite database.
They run the following command:
Which of the following lines of code fills in the above blank to successfully complete the task?
- A. autoloader
- B. sqlite
- C. org.apache.spark.sql.jdbc
- D. org.apache.spark.sql.sqlite
- E. DELTA
Answer: C
Explanation:
CREATE TABLE new_employees_table
USING JDBC
OPTIONS (
url "<jdbc_url>",
dbtable "<table_name>",
user '<username>',
password '<password>'
) AS
SELECT * FROM employees_table_vw
https://docs.databricks.com/external-data/jdbc.html#language-sql
NEW QUESTION # 29
Which of the following must be specified when creating a new Delta Live Tables pipeline?
- A. A location of a target database for the written data
- B. A key-value pair configuration
- C. At least one notebook library to be executed
- D. A path to cloud storage location for the written data
- E. The preferred DBU/hour cost
Answer: C
Explanation:
Explanation
https://docs.databricks.com/en/delta-live-tables/tutorial-pipelines.html
NEW QUESTION # 30
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