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DP-201 PDF DEMO:

QUESTION NO: 1
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You plan to store delimited text files in an Azure Data Lake Storage account that will be organized into department folders.
You need to configure data access so that users see only the files in their respective department folder.
Solution: From the storage account, you disable a hierarchical namespace, and you use access control lists (ACLs).
Does this meet the goal?
A. Yes
B. No
Answer: A
Explanation
Azure Data Lake Storage implements an access control model that derives from HDFS, which in turn derives from the POSIX access control model.
Blob container ACLs does not support the hierarchical namespace, so it must be disabled.
References:
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-known-issues
https://docs.microsoft.com/en-us/azure/data-lake-store/data-lake-store-access-control

QUESTION NO: 2
You are designing a data processing solution that will run as a Spark job on an HDInsight cluster. The solution will be used to provide near real-time information about online ordering for a retailer.
The solution must include a page on the company intranet that displays summary information.
The summary information page must meet the following requirements:
* Display a summary of sales to date grouped by product categories, price range, and review scope.
* Display sales summary information including total sales, sales as compared to one day ago and sales as compared to one year ago.
* Reflect information for new orders as quickly as possible.
You need to recommend a design for the solution.
What should you recommend? To answer, select the appropriate configuration in the answer area.
Answer:
Explanation
Box 1: DataFrame
DataFrames
Best choice in most situations.
Provides query optimization through Catalyst.
Whole-stage code generation.
Direct memory access.
Low garbage collection (GC) overhead.
Not as developer-friendly as DataSets, as there are no compile-time checks or domain object programming.
Box 2: parquet
The best format for performance is parquet with snappy compression, which is the default in Spark
2.x.
Parquet stores data in columnar format, and is highly optimized in Spark.

QUESTION NO: 3
You need to recommend a security solution for containers in Azure Blob storage. The solution must ensure that only read permissions are granted to a specific user for a specific container.
What should you include in the recommendation?
A. public read access for blobs only
B. access keys
C. shared access signatures (SAS)
D. an RBAC role in Azure Active Directory (Azure AD)
Answer: C
Explanation
You can delegate access to read, write, and delete operations on blob containers, tables, queues, and file shares that are not permitted with a service SAS.
Note: A shared access signature (SAS) provides secure delegated access to resources in your storage account without compromising the security of your data. With a SAS, you have granular control over how a client can access your data. You can control what resources the client may access, what permissions they have on those resources, and how long the SAS is valid, among other parameters.

QUESTION NO: 4
You need to design the disaster recovery solution for customer sales data analytics.
Which three actions should you recommend? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. Use Geo-redundant storage.
B. Use zone redundant storage.
C. Provision multiple Azure Databricks workspaces in separate Azure regions.
D. Migrate users, notebooks, and cluster configurations from one workspace to another in the same region.
E. Provision a second Azure Databricks workspace in the same region.
F. Migrate users, notebooks, and cluster configurations from one region to another.
Answer: A,C,F
Explanation
Scenario: The analytics solution for customer sales data must be available during a regional outage.
To create your own regional disaster recovery topology for databricks, follow these requirements:
1. Provision multiple Azure Databricks workspaces in separate Azure regions
2. Use Geo-redundant storage.
3. Once the secondary region is created, you must migrate the users, user folders, notebooks, cluster configuration, jobs configuration, libraries, storage, init scripts, and reconfigure access control.
Note: Geo-redundant storage (GRS) is designed to provide at least 99.99999999999999% (16 9's) durability of objects over a given year by replicating your data to a secondary region that is hundreds of miles away from the primary region. If your storage account has GRS enabled, then your data is durable even in the case of a complete regional outage or a disaster in which the primary region isn't recoverable.
References:
https://docs.microsoft.com/en-us/azure/storage/common/storage-redundancy-grs

QUESTION NO: 5
A company stores large datasets in Azure, including sales transactions and customer account information.
You must design a solution to analyze the data. You plan to create the following HDInsight clusters:
You need to ensure that the clusters support the query requirements.
Which cluster types should you recommend? To answer, select the appropriate configuration in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation
Box 1: Interactive Query
Choose Interactive Query cluster type to optimize for ad hoc, interactive queries.
Box 2: Hadoop
Choose Apache Hadoop cluster type to optimize for Hive queries used as a batch process.
Note: In Azure HDInsight, there are several cluster types and technologies that can run Apache Hive queries.
When you create your HDInsight cluster, choose the appropriate cluster type to help optimize performance for your workload needs.
For example, choose Interactive Query cluster type to optimize for ad hoc, interactive queries.
Choose Apache Hadoop cluster type to optimize for Hive queries used as a batch process. Spark and
HBase cluster types can also run Hive queries.
References:
https://docs.microsoft.com/bs-latn-ba/azure/hdinsight/hdinsight-hadoop-optimize-hive- query?toc=%2Fko-kr%2F

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Updated: May 28, 2022