[Q33-Q51] 2024 Updated Databricks-Certified-Data-Engineer-Associate Tests Engine pdf - All Free Dumps Guaranteed!

NEW QUESTION 33
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 34
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

NEW QUESTION 35
A data engineer is running code in a Databricks Repo that is cloned from a central Git repository. A colleague of the data engineer informs them that changes have been made and synced to the central Git repository. The data engineer now needs to sync their Databricks Repo to get the changes from the central Git repository.
Which of the following Git operations does the data engineer need to run to accomplish this task?

Merge

Push

Pull

Commit

Clone

NEW QUESTION 36
A data engineering team has two tables. The first table march_transactions is a collection of all retail transactions in the month of March. The second table april_transactions is a collection of all retail transactions in the month of April. There are no duplicate records between the tables.
Which of the following commands should be run to create a new table all_transactions that contains all records from march_transactions and april_transactions without duplicate records?

CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
INNER JOIN SELECT * FROM april_transactions;

CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
UNION SELECT * FROM april_transactions;

CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
OUTER JOIN SELECT * FROM april_transactions;

CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
INTERSECT SELECT * from april_transactions;

CREATE TABLE all_transactions AS
SELECT * FROM march_transactions
MERGE SELECT * FROM april_transactions;

NEW QUESTION 37
In order for Structured Streaming to reliably track the exact progress of the processing so that it can handle any kind of failure by restarting and/or reprocessing, which of the following two approaches is used by Spark to record the offset range of the data being processed in each trigger?

Checkpointing and Write-ahead Logs

Structured Streaming cannot record the offset range of the data being processed in each trigger.

Replayable Sources and Idempotent Sinks

Write-ahead Logs and Idempotent Sinks

Checkpointing and Idempotent Sinks

NEW QUESTION 38
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 39
A data engineer has realized that the data files associated with a Delta table are incredibly small. They want to compact the small files to form larger files to improve performance.
Which of the following keywords can be used to compact the small files?

REDUCE

OPTIMIZE

COMPACTION

REPARTITION

VACUUM

NEW QUESTION 40
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 41
Which of the following SQL keywords can be used to convert a table from a long format to a wide format?

PIVOT

CONVERT

WHERE

TRANSFORM

SUM

NEW QUESTION 42
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 43
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 44
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.
Assuming previously unprocessed data exists and all definitions are valid, what is the expected outcome after clicking Start to update the pipeline?

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 persist without any processing. The compute resources will persist but go unused.

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.

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

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

NEW QUESTION 45
Which of the following data workloads will utilize a Gold table as its source?

A job that enriches data by parsing its timestamps into a human-readable format

A job that aggregates uncleaned data to create standard summary statistics

A job that cleans data by removing malformatted records

A job that queries aggregated data designed to feed into a dashboard

A job that ingests raw data from a streaming source into the Lakehouse

NEW QUESTION 46
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 47
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 supports the use of multiple branches

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

Databricks Repos provides the ability to comment on specific changes

Databricks Repos is wholly housed within the Databricks Lakehouse Platform

NEW QUESTION 48
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 49
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 50
Which of the following describes the type of workloads that are always compatible with Auto Loader?

Dashboard workloads

Streaming workloads

Machine learning workloads

Serverless workloads

Batch workloads

NEW QUESTION 51
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