(2024) PASS Databricks-Certified-Data-Engineer-Associate exam with Databricks Databricks-Certified-Data-Engineer-Associate Real Exam Questions [Q30-Q44]

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(2024) PASS Databricks-Certified-Data-Engineer-Associate exam with Databricks Databricks-Certified-Data-Engineer-Associate Real Exam Questions

Real exam questions are provided for Databricks Certification tests, which can make sure you 100% pass

The GAQM Databricks-Certified-Data-Engineer-Associate (Databricks Certified Data Engineer Associate) Certification Exam is designed to test the skills of data engineers who work with Databricks to build and maintain data pipelines. Databricks-Certified-Data-Engineer-Associate exam covers a wide range of topics, including data modeling, data ingestion, data transformation, and data analysis. Successful completion of the exam demonstrates that a candidate has the skills and knowledge required to work effectively as a data engineer with Databricks.

Databricks Certified Data Engineer Associate certification exam covers topics such as data engineering concepts, data ingestion, data processing, data storage, and data transformation using Apache Spark and Delta Lake. Candidates who pass Databricks-Certified-Data-Engineer-Associate exam will have a deep understanding of the Databricks platform and will be able to design, build, and maintain data pipelines that are scalable, reliable, and efficient. Databricks Certified Data Engineer Associate Exam certification is ideal for data engineers, data analysts, and data scientists who work with big data and want to enhance their skills and advance their careers.

NO.30 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 code block used by the data engineer is below:

If the data engineer only wants the query to process all of the available data in as many batches as required, which of the following lines of code should the data engineer use to fill in the blank?

processingTime(1)

trigger(availableNow=True)

trigger(parallelBatch=True)

trigger(processingTime=”once”)

trigger(continuous=”once”)

NO.31 A single Job runs two notebooks as two separate tasks. A data engineer has noticed that one of the notebooks is running slowly in the Job’s current run. The data engineer asks a tech lead for help in identifying why this might be the case.
Which of the following approaches can the tech lead use to identify why the notebook is running slowly as part of the Job?

They can navigate to the Runs tab in the Jobs UI to immediately review the processing notebook.

They can navigate to the Tasks tab in the Jobs UI and click on the active run to review the processing notebook.

They can navigate to the Runs tab in the Jobs UI and click on the active run to review the processing notebook.

There is no way to determine why a Job task is running slowly.

They can navigate to the Tasks tab in the Jobs UI to immediately review the processing notebook.

NO.32 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 code block used by the data engineer is below:

If the data engineer only wants the query to process all of the available data in as many batches as required, which of the following lines of code should the data engineer use to fill in the blank?

processingTime(1)

trigger(availableNow=True)

trigger(parallelBatch=True)

trigger(processingTime=”once”)

trigger(continuous=”once”)

NO.33 A data engineer has been given a new record of data:
id STRING = ‘a1’
rank INTEGER = 6
rating FLOAT = 9.4
Which of the following SQL commands can be used to append the new record to an existing Delta table my_table?

INSERT INTO my_table VALUES (‘a1’, 6, 9.4)

my_table UNION VALUES (‘a1’, 6, 9.4)

INSERT VALUES ( ‘a1’ , 6, 9.4) INTO my_table

UPDATE my_table VALUES (‘a1’, 6, 9.4)

UPDATE VALUES (‘a1’, 6, 9.4) my_table

NO.34 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?

Replace predict with a stream-friendly prediction function

Replace schema(schema) with option (“maxFilesPerTrigger”, 1)

Replace “transactions” with the path to the location of the Delta table

Replace format(“delta”) with format(“stream”)

Replace spark.read with spark.readStream

NO.35 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?

trigger(“5 seconds”)

trigger()

trigger(once=”5 seconds”)

trigger(processingTime=”5 seconds”)

trigger(continuous=”5 seconds”)

NO.36 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?

Unity Catalog

Data Explorer

Databricks SQL

Delta Lake

Auto Loader

NO.37 A data engineer needs to create a table in Databricks using data from a CSV file at location /path/to/csv.
They run the following command:

Which of the following lines of code fills in the above blank to successfully complete the task?

None of these lines of code are needed to successfully complete the task

USING CSV

FROM CSV

USING DELTA

FROM “path/to/csv”

NO.38 A data engineer needs to determine whether to use the built-in Databricks Notebooks versioning or version their project using Databricks Repos.
Which of the following is an advantage of using Databricks Repos over the Databricks Notebooks versioning?

Databricks Repos automatically saves development progress

Databricks Repos provides the ability to comment on specific changes

Databricks Repos is wholly housed within the Databricks Lakehouse Platform

Databricks Repos supports the use of multiple branches

Databricks Repos allows users to revert to previous versions of a notebook

NO.39 A data engineer has joined an existing project and they see the following query in the project repository:
CREATE STREAMING LIVE TABLE loyal_customers AS
SELECT customer_id –
FROM STREAM(LIVE.customers)
WHERE loyalty_level = ‘high’;
Which of the following describes why the STREAM function is included in the query?

The STREAM function is not needed and will cause an error.

The table being created is a live table.

The customers table is a streaming live table.

The customers table is a reference to a Structured Streaming query on a PySpark DataFrame.

The data in the customers table has been updated since its last run.

NO.40 Which of the following benefits of using the Databricks Lakehouse Platform is provided by Delta Lake?

The ability to manipulate the same data using a variety of languages

The ability to collaborate in real time on a single notebook

The ability to set up alerts for query failures

The ability to support batch and streaming workloads

The ability to distribute complex data operations

NO.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?

Unity Catalog

Data Explorer

Delta Lake

Delta Live Tables

Auto Loader

NO.42 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?

The VACUUM command was run on the table

The TIME TRAVEL command was run on the table

The DELETE HISTORY command was run on the table

The OPTIMIZE command was nun on the table

The HISTORY command was run on the table

NO.43 Which of the following describes a benefit of creating an external table from Parquet rather than CSV when using a CREATE TABLE AS SELECT statement?

Parquet files can be partitioned

CREATE TABLE AS SELECT statements cannot be used on files

Parquet files have a well-defined schema

Parquet files have the ability to be optimized

Parquet files will become Delta tables

NO.44 Which of the following commands will return the number of null values in the member_id column?

SELECT count(member_id) FROM my_table;

SELECT count(member_id) – count_null(member_id) FROM my_table;

SELECT count_if(member_id IS NULL) FROM my_table;

SELECT null(member_id) FROM my_table;

SELECT count_null(member_id) FROM my_table;