Exam Questions Answers Braindumps Databricks-Certified-Data-Engineer-Associate Exam Dumps PDF Questions [Q28-Q52]

Posted On September 30, 2024

Exam Questions Answers Braindumps Databricks-Certified-Data-Engineer-Associate Exam Dumps PDF Questions

Download Free Databricks Databricks-Certified-Data-Engineer-Associate Real Exam Questions

NEW QUESTION 28
Which of the following statements regarding the relationship between Silver tables and Bronze tables is always true?

Silver tables contain a less refined, less clean view of data than Bronze data.

Silver tables contain aggregates while Bronze data is unaggregated.

Silver tables contain more data than Bronze tables.

Silver tables contain a more refined and cleaner view of data than Bronze tables.

Silver tables contain less data than Bronze tables.

NEW QUESTION 29
A data engineer has developed a data pipeline to ingest data from a JSON source using Auto Loader, but the engineer has not provided any type inference or schema hints in their pipeline. Upon reviewing the data, the data engineer has noticed that all of the columns in the target table are of the string type despite some of the fields only including float or boolean values.
Which of the following describes why Auto Loader inferred all of the columns to be of the string type?

There was a type mismatch between the specific schema and the inferred schema

JSON data is a text-based format

Auto Loader only works with string data

All of the fields had at least one null value

Auto Loader cannot infer the schema of ingested data

NEW QUESTION 30
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

NEW QUESTION 31
A data engineer needs to apply custom logic to identify employees with more than 5 years of experience in array column employees in table stores. The custom logic should create a new column exp_employees that is an array of all of the employees with more than 5 years of experience for each row. In order to apply this custom logic at scale, the data engineer wants to use the FILTER higher-order function.
Which of the following code blocks successfully completes this task?

Option A

Option B

Option C

Option D

Option E

NEW QUESTION 32
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 HISTORY command was run on the table

The DELETE HISTORY command was run on the table

The OPTIMIZE command was nun on the table

The VACUUM command was run on the table

The TIME TRAVEL command was run on the table

NEW QUESTION 33
Which of the following can be used to simplify and unify siloed data architectures that are specialized for specific use cases?

None of these

Data lake

Data warehouse

All of these

Data lakehouse

NEW QUESTION 34
Which of the following describes the relationship between Bronze tables and raw data?

Bronze tables contain less data than raw data files.

Bronze tables contain more truthful data than raw data.

Bronze tables contain aggregates while raw data is unaggregated.

Bronze tables contain a less refined view of data than raw data.

Bronze tables contain raw data with a schema applied.

NEW QUESTION 35
A data engineer wants to create a relational object by pulling data from two tables. The relational object does not need to be used by other data engineers in other sessions. In order to save on storage costs, the data engineer wants to avoid copying and storing physical data.
Which of the following relational objects should the data engineer create?

Spark SQL Table

View

Database

Temporary view

Delta Table

NEW QUESTION 36
Which of the following describes when to use the CREATE STREAMING LIVE TABLE (formerly CREATE INCREMENTAL LIVE TABLE) syntax over the CREATE LIVE TABLE syntax when creating Delta Live Tables (DLT) tables using SQL?

CREATE STREAMING LIVE TABLE should be used when the subsequent step in the DLT pipeline is static.

CREATE STREAMING LIVE TABLE should be used when data needs to be processed incrementally.

CREATE STREAMING LIVE TABLE is redundant for DLT and it does not need to be used.

CREATE STREAMING LIVE TABLE should be used when data needs to be processed through complicated aggregations.

CREATE STREAMING LIVE TABLE should be used when the previous step in the DLT pipeline is static.

NEW QUESTION 37
A data engineer runs a statement every day to copy the previous day’s sales into the table transactions. Each day’s sales are in their own file in the location “/transactions/raw”.
Today, the data engineer runs the following command to complete this task:

After running the command today, the data engineer notices that the number of records in table transactions has not changed.
Which of the following describes why the statement might not have copied any new records into the table?

The format of the files to be copied were not included with the FORMAT_OPTIONS keyword.

The names of the files to be copied were not included with the FILES keyword.

The previous day’s file has already been copied into the table.

The PARQUET file format does not support COPY INTO.

The COPY INTO statement requires the table to be refreshed to view the copied rows.

NEW QUESTION 38
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?

All datasets will be updated once and the pipeline will shut down. The compute resources will be terminated.

All datasets will be updated at set intervals until the pipeline is shut down. The compute resources will persist to allow for additional testing.

All datasets will be updated once and the pipeline will shut down. The compute resources will persist to allow for additional testing.

All datasets will be updated at set intervals until the pipeline is shut down. The compute resources will be deployed for the update and terminated when the pipeline is stopped.

NEW QUESTION 39
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.

NEW QUESTION 40
A dataset has been defined using Delta Live Tables and includes an expectations clause:
CONSTRAINT valid_timestamp EXPECT (timestamp > ‘2020-01-01’) ON VIOLATION DROP ROW What is the expected behavior when a batch of data containing data that violates these constraints is processed?

Records that violate the expectation are dropped from the target dataset and loaded into a quarantine table.

Records that violate the expectation are added to the target dataset and flagged as invalid in a field added to the target dataset.

Records that violate the expectation are dropped from the target dataset and recorded as invalid in the event log.

Records that violate the expectation are added to the target dataset and recorded as invalid in the event log.

Records that violate the expectation cause the job to fail.

NEW QUESTION 41
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?

org.apache.spark.sql.jdbc

autoloader

DELTA

sqlite

org.apache.spark.sql.sqlite

NEW QUESTION 42
A data engineer needs access to a table new_table, but they do not have the correct permissions. They can ask the table owner for permission, but they do not know who the table owner is.
Which of the following approaches can be used to identify the owner of new_table?

Review the Permissions tab in the table’s page in Data Explorer

All of these options can be used to identify the owner of the table

Review the Owner field in the table’s page in Data Explorer

Review the Owner field in the table’s page in the cloud storage solution

There is no way to identify the owner of the table

NEW QUESTION 43
What is stored in a Databricks customer’s cloud account?

Data

Cluster management metadata

Databricks web application

Notebooks

NEW QUESTION 44
Which of the following describes the relationship between Gold tables and Silver tables?

Gold tables are more likely to contain aggregations than Silver tables.

Gold tables are more likely to contain valuable data than Silver tables.

Gold tables are more likely to contain a less refined view of data than Silver tables.

Gold tables are more likely to contain more data than Silver tables.

Gold tables are more likely to contain truthful data than Silver tables.

NEW QUESTION 45
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?

org.apache.spark.sql.jdbc

autoloader

DELTA

sqlite

org.apache.spark.sql.sqlite

NEW QUESTION 46
A data engineer only wants to execute the final block of a Python program if the Python variable day_of_week is equal to 1 and the Python variable review_period is True.
Which of the following control flow statements should the data engineer use to begin this conditionally executed code block?

if day_of_week = 1 and review_period:

if day_of_week = 1 and review_period = “True”:

if day_of_week == 1 and review_period == “True”:

if day_of_week == 1 and review_period:

if day_of_week = 1 & review_period: = “True”:

NEW QUESTION 47
A data engineer is attempting to drop a Spark SQL table my_table. The data engineer wants to delete all table metadata and data.
They run the following command:
DROP TABLE IF EXISTS my_table
While the object no longer appears when they run SHOW TABLES, the data files still exist.
Which of the following describes why the data files still exist and the metadata files were deleted?

The table’s data was larger than 10 GB

The table’s data was smaller than 10 GB

The table was external

The table did not have a location

The table was managed

NEW QUESTION 48
Which of the following is hosted completely in the control plane of the classic Databricks architecture?

Worker node

JDBC data source

Databricks web application

Databricks Filesystem

Driver node

NEW QUESTION 49
A data engineer has a Python variable table_name that they would like to use in a SQL query. They want to construct a Python code block that will run the query using table_name.
They have the following incomplete code block:
____(f”SELECT customer_id, spend FROM {table_name}”)
Which of the following can be used to fill in the blank to successfully complete the task?

spark.delta.sql

spark.delta.table

spark.table

dbutils.sql

spark.sql

NEW QUESTION 50
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

NEW QUESTION 51
A data engineer only wants to execute the final block of a Python program if the Python variable day_of_week is equal to 1 and the Python variable review_period is True.
Which of the following control flow statements should the data engineer use to begin this conditionally executed code block?

if day_of_week = 1 and review_period:

if day_of_week = 1 and review_period = “True”:

if day_of_week == 1 and review_period == “True”:

if day_of_week == 1 and review_period:

if day_of_week = 1 & review_period: = “True”:

NEW QUESTION 52
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?

SELECT * FROM sales

There is no way to share data between PySpark and SQL.

spark.sql(“sales”)

spark.delta.table(“sales”)

spark.table(“sales”)