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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Secure and govern Unity Catalog objects | 15-20% | - Implement governance and security
|
| Topic 2: Prepare and process data | 30-35% | - Ingest and transform data
|
| Topic 3: Set up and configure an Azure Databricks environment | 15-20% | - Create and configure Azure Databricks workspaces
|
| Topic 4: Deploy and maintain data pipelines and workloads | 30-35% | - Manage production workloads
|
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NEW QUESTION # 23
You have an Azure Databricks workspace that is enabled for Unity Catalog.
You have a CSV file stored in an Azure Data Lake Storage Gen2 container.
You plan to ingest the data into an existing table by running the following SQL statement:
COPY INTO Customer
FROM ' abfss://container1@storageaccount.dfs.core.windows.net/data/customer ' FILEFORMAT = CSV; You need to ensure that the statement can access the data in the container.
What should you configure?
Answer: A
Explanation:
A Unity Catalog external location associates a cloud-storage path with a storage credential. The storage credential contains the managed identity or service principal that Azure Databricks uses to authenticate to the ADLS Gen2 account. Configuring an external location for the specified abfss path therefore enables Unity Catalog to govern access to the source files while allowing COPY INTO to read them. The user or execution identity must also have the required READ FILES permission on the external location. Microsoft Learn An external table is unnecessary because Customer already exists as the destination table, and the CSV files are being used only as the ingestion source. A Unity Catalog volume could be used if the statement referenced a /Volumes/... path, but the displayed command directly references the ADLS container through an abfss URL. A Lakeflow ingestion gateway is not used to authorize access to ADLS files for COPY INTO.
Therefore, an external location backed by a storage credential is the correct configuration.
NEW QUESTION # 24
You have an Azure Databricks workspace that contains a cluster named Cluster1. Cluster1 has the following characteristics:
* Configured as a single node cluster
* Uses a general purpose virtual machine node type
The cluster runtime environment has the following configurations:
* Uses Databricks Runtime for Machine Learning (Databricks Runtime Ml)
* Includes common machine learning libraries
* Supports Python workloads
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
The first statement is No . Although Databricks Runtime ML includes machine learning and deep-learning libraries, GPU acceleration also requires a GPU-enabled virtual machine node type and a compatible GPU runtime. Cluster1 uses a general-purpose node type, which provides CPU-based compute rather than GPU acceleration. Microsoft Learn The second statement is No . A single-node cluster has no separate worker nodes. The driver operates as both the master and worker, and Spark runs locally. Consequently, Cluster1 cannot distribute machine learning processing across multiple nodes. A multi-node cluster would be required for distributed workloads.
Microsoft Learn
The third statement is Yes . Databricks Runtime ML provides a ready-to-use machine learning environment containing commonly used libraries such as scikit-learn, TensorFlow, PyTorch, XGBoost, and MLflow.
Because Cluster1 supports Python, Python workloads can import and use these preinstalled libraries without requiring each package to be installed separately.
NEW QUESTION # 25
You have an Azure Databricks workspace that contains a Delta table named Table 1. Table 1 has accumulated obsolete files.
You need to reduce storage costs. The solution must preserve 30 days of time travel history. Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: B,D
Explanation:
The correct answers are B and E.
The goal is to reduce storage costs while preserving 30 days of time travel. Two actions are needed:
Set delta.deletedFileRetentionDuration to a value aligned with the 30-day requirement (Option B). Note: the answer option states '10 days' which would be insufficient for 30-day time travel - in practice this property should be set to at least 30 days. This property defines the retention floor: VACUUM will not delete any file newer than this threshold.
Run VACUUM on Table1 (Option E). VACUUM physically removes unreferenced data files older than the retention duration from storage. Without running VACUUM, obsolete files accumulate indefinitely regardless of the retention property setting - the property tells VACUUM what to keep; VACUUM is what does the actual cleanup.
Option C (OPTIMIZE) compacts small files for better query performance but never deletes anything. Option D (logRetentionDuration) keeps the transaction log for time travel but doesn't free up the data file storage.
Reference: https://learn.microsoft.com/en-us/azure/databricks/sql/language-manual/delta-vacuum
NEW QUESTION # 26
You have an Azure Databricks workspace that is enabled for Unity Catalog and contains:
* A catalog named Corpdb
* A schema named Finance in the Corpdb catalog
* A table named Sales in the Finance schema
You have a group named Analysts.
You assign the following permissions to Analysts:
* USE CATALOG on the Corpdb catalog
* USE SCHEMA on the Finance schema
* SELECT on the Sales table
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
The Analysts group can query the Sales table because it has all three privileges required by the Unity Catalog hierarchy: USE CATALOG on Corpdb, USE SCHEMA on Finance, and SELECT on Sales. These permissions allow the group to navigate through the catalog and schema and read the table. However, USE SCHEMA does not grant permission to create tables. Creating a table in Finance would additionally require CREATE TABLE on that schema. Similarly, USE CATALOG only permits access to the catalog; it does not permit schema creation. Creating a schema in Corpdb would require the CREATE SCHEMA privilege on the catalog. Therefore, only the first statement is true.
NEW QUESTION # 27
You have an Azure Databricks workspace and a remote Git repository named Repo1. Repo1 contains two branches named main and Branch1.
You are on a development team that works in Repo1.
You commit changes to Branch1 and must merge the changes into main.
Before completing the merge, you need to meet the following requirements:
* Ensure that Branch1 includes the changes committed to main since Branch1 was created.
* Ensure that merge conflicts are detected and resolved.
What should you do first?
Answer: B
Explanation:
The latest remote changes from main must first be retrieved so that the development environment has the current main-branch state. After pulling those updates, main can be merged into Branch1, and any conflicts can be detected and resolved before Branch1 is proposed for integration into main. Immediately merging a stale local copy of main into Branch1 could omit commits added remotely after Branch1 was created. Pulling Branch1 only synchronizes the feature branch and does not retrieve the required main-branch changes.
Creating a pull request before updating and testing Branch1 would defer conflict discovery until later in the integration process. Pulling the latest main changes is therefore the correct first operation in the sequence.
Microsoft Learn
NEW QUESTION # 28
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