QUESTION 27
You have an Azure Databricks workspace that is enabled for Unity Catalog and contains two Delta tables named Table1 and Table2 of the same data type.
Table1 contains a column named Column1. Table2 contains a column named Column2.
You run the following query.
SELECT Colum1
FROM Table1
GROUP BY Column1
HAVING COUNT(*) > 1
INTERSECT
SELECT Column2
FROM Table2
GROUP BY Column2
HAVING COUNT(*) > 1;
What occurs when you run the query?

QUESTION 28
You have an Azure Databricks workspace that contains a job in Lakeflow Jobs named Job1. Job1 contains multiple tasks.
Failures of non-critical tasks must be logged but must NOT trigger notifications. Notifications must be triggered only when critical tasks have failed, and Job1 has completed You need to configure the job alerting behavior.
What should trigger a notification?

QUESTION 29
You need to curate Unity Catalog objects that reference the ERP data. The solution must meet the governance requirements.
What should you do?

QUESTION 30
Hotspot Question
You have an Azure Databricks workspace that contains a job in Lakeflow Jobs named Job1.
Job1 contains three tasks named Task1, Task2, and Task3.
If Task1 fails, Task2 and Task3 must be prevented from running. Successfully completed tasks must NOT rerun during recovery.
You need to configure Job1 to support controlled failure handling and recovery.
What should you configure? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

QUESTION 31
You have an Azure Databricks workspace named Workspace1 that contains a Git folder linked to a remote Git repository. The Git folder contains a Databricks notebook named Notebook1.
From the main branch, you create a feature branch named Branch1 and commit changes to Notebook1.
Another user commits changes to Notebook1 in main.
When you attempt to merge Branch1 into main, a merge conflict occurs.
You need to ensure that Notebook1 in main includes the changes from both branches.
What should you do?

QUESTION 32
You have an Azure Databricks workspace that is enabled for Unity Catalog and contains a Delta table named Orders You load the Orders table into an Apache Spark DataFrame named df.
You need to create a DataFrame that excludes rows where the order amount is null.
Solution: You run the following expression.
df-fillna(0, subset=[‘order_amount’])
Does this meet the goal?

QUESTION 33
You have an Azure Databricks workspace.
Users report that a Databricks notebook that runs each day takes longer than expected to run.
When reading the Directed Acyclic Graph (DAG), you discover the following issues concerning the Apache Spark stage:
* Most tasks in the stage finish quickly.
* A few tasks in the stage run more slowly.
* The CPU is underutilized at the end of the stage.
* The slow tasks process many more input records.
* The stage is blocked while it waits for the few slow tasks.
What is the root cause of the issues?

QUESTION 34
You need to configure compute for the ingestion of telemetry data. The solution must meet the data ingestion and processing requirements.
What should you do?

QUESTION 35
You have an Azure Databricks workspace named Workspace1 that contains a lakehouse and is enabled for Unity Catalog.
You have a connection to a Microsoft SQL Server database named DB1.
You need to expose the schemas and tables of DB1 to meet the following requirements:
* The schemas and tables can be queried in Databricks.
* The schemas and tables appear alongside other Unity Catalog objects.
* The data is NOT copied into Databricks-managed storage.
Solution: You create a foreign catalog in Catalog Explorer.
Does this meet the goal?

QUESTION 36
You have an Azure Databricks workspace that is enabled for Unity Catalog.
You have a complex job named Job1 that contains eight tasks. Job1 takes multiple hours to complete.
During the last job run, the final task fails due to a transient issue.
You need to retry the last task without rerunning tasks that have already completed.
What should you do?

QUESTION 37
You have an Azure Databricks workspace that is enabled for Unity Catalog and contains a Delta table named Orders.
You load the Orders table into an Apache Spark DataFrame named df.
You need to create a DataFrame that excludes rows where the order amount is null.
Solution: You run the following expression.
df.dropna(subset=[“order_amount”])
Does this meet the goal?

QUESTION 38
You have an Azure Databricks workspace that contains an all-purpose cluster named Cluster1.
You need to configure Cluster1 to meet the following requirements:
– The cluster must scale up automatically when workloads increase.
– The cluster must scale down automatically when workloads decrease.
The solution must minimize costs.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

QUESTION 39
Which operation guarantees ACID compliance in Delta Lake?

QUESTION 40
You have an Azure Databricks workspace that uses Unity Catalog.
You have a Lakeflow Spark Declarative Pipelines (SDP) pipeline that ingests data into a managed Delta table named Table1. Table! is used for analytics.
New columns are added to the source data, causing pipeline failures during writes to Table!
You need to prevent the pipeline failures. The solution must ensure that schema changes are detected and handled.
What should you do?

QUESTION 41
You have an Azure Databricks workspace that is enabled for Unity Catalog and contains a Delta table named Sales_orders. Sales.orders stores historical sales data.
You receive a daily CSV file daily that contains new sales records only. The file does NOT contain updates to existing rows You need to load the daily data into Sales.orders. The solution must meet the following requirements:
* Preserve the existing data.
* Add only the new records.
* Minimize processing effort.
Which command should include in the loading strategy?

QUESTION 42
You have an Azure Databricks workspace that contains an all-purpose cluster named Cluster1.
You discover that out of- memory (OOM) errors intermittently cause jobs running on Cluster1 to fail.
You need to identify the root cause of the failures by analyzing the runtime execution behavior. What should you do? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

QUESTION 43
A Delta table receives new fields in incoming JSON data. You want to automatically adapt without breaking pipelines. What should you enable?

QUESTION 44
Hotspot Question
You have an Azure Databricks workspace that is enabled for Unity Catalog and contains a managed Delta table named Table1.
Table1 is written by batch jobs every hour and is queried frequently by filtering two columns named Customerid and EventDate.
You expect Table1 to grow significantly over time.
The rows in Table1 are frequently updated and deleted to support compliance requests.
You need to keep query performance consistent as Table1 grows. The solution must minimize update and deletion effort.
What should you include in the solution? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

QUESTION 45
You have an Azure Databricks workspace that is enabled for Unity Catalog and contains a catalog named Catalog 1. Catalog 1 contains a table named Transactions. Transactions contains the following columns:
* transaction_id
* customet_name
* email address
* credit_card_number
* transaction_amount
You need to ensure that business analysts can query all the tows in the Transactions table. The solution must meet the following requirements:
* Prevent the analysts from seeing the full values in the email_address and credit_catd_number columns.
* Ensure that the analysts can see only the values after the @ character in each email address.
* Ensure that the analysts can see only the last four digits of each credit card number.
* Enable the analysts to query the table without errors.
* Follow the principle of least privilege.
What should you do?

QUESTION 46
You have an Azure Databricks workspace that is enabled for Unity Catalog You plan to ingest data from CSV files stored in Azure Data Lake Storage Gen2. New rows are appended frequently.
You need to implement a data ingestion solution that meets the following requirements:
* New data must be available in near-real time (NRT).
* The data must be stored in managed Delta tables.
* The solution must minimize custom code and maintenance effort.
What should you include in the solution?

QUESTION 47
You have an Azure Databricks workspace.
You are creating a Lakeflow Spark Declarative Pipelines (SDP) pipeline that scales automatically.
You need to configure compute for the pipeline. The solution must minimize operational costs and effort.
What should you use?

QUESTION 48
Note: This section contains one or more sets of questions with the same scenario and problem. Each question presents a unique solution to the problem. You must determine whether the solution meets the stated goals. More than one solution in the set might solve the problem. It is also possible that none of the solutions in the set solve the problem.
After you answer a question in this section, you will NOT be able to return. As a result, these questions do not appear on the Review Screen.
You have an Azure Databricks workspace that is enabled for Unity Catalog and contains a Delta table named Orders.
You load the Orders table into an Apache Spark DataFrame named df.
You need to create a DataFrame that excludes rows where the order amount is null.
Solution: You run the following expression.
df.dropna(subset=[“order_amount”])
Does this meet the goal?

QUESTION 49
Hotspot Question
You have an Azure Databricks workspace that is enabled for Unity Catalog.
You plan to run the following PySpark code.

QUESTION 50
You have an Azure Databricks workspace named Workspace1. You create a compute cluster named Cluser1 that will be used to ingest data.
You need to install the required libraries on Cluster 1. The solution must use Unity Catalog for access control.
What should you do?