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NEW QUESTION: 1
ソリューションアーキテクトは、AWSクラウドでハイパフォーマンスコンピューティング（HPC）ワークロードをホストする必要があります。ワークロードは数百のAmazon EC2インスタンスで実行され、大規模なデータセットの分散処理を可能にするために共有ファイルシステムへの並列アクセスが必要になります。データセットは、複数のインスタンスから同時にアクセスされます。ワークロードには、1ミリ秒以内のアクセス遅延が必要です。処理が完了した後、エンジニアは手動の後処理のためにデータセットにアクセスする必要があります。
これらの要件を満たすソリューションはどれですか？
A. Amazon S3バケットを共有するようにAWSResource Access Managerを設定して、処理と後処理のためにすべてのインスタンスにマウントできるようにします
B. 共有ファイルシステムとして機能するAmazonS3バケットをマウントするS3バケットから直接後処理を実行する
C. Amazon Elastic File System（Amazon EFS）を共有ファイルシステムとして使用するAmazonEFSからデータセットにアクセスします。
D. 共有ファイルシステムとしてAmazon FSx forLustreを使用します。後処理のためにファイルシステムをAmazonS3バケットにリンクします。
Answer: C
NEW QUESTION: 2
Azure Active Directory（Azure AD）統合を使用して、Azure Data Lake Storage Gen2に自動的に接続するAzure Databricksクラスターを実装する必要があります。
新しいクラスターをどのように構成する必要がありますか？回答するには、回答エリアで適切なオプションを選択します。
注：それぞれの正しい選択には1ポイントの価値があります。
Answer:
Explanation:
Explanation
Box 1: High Concurrency
Enable Azure Data Lake Storage credential passthrough for a high-concurrency cluster.
Incorrect:
Support for Azure Data Lake Storage credential passthrough on standard clusters is in Public Preview.
Standard clusters with credential passthrough are supported on Databricks Runtime 5.5 and above and are limited to a single user.
Box 2: Azure Data Lake Storage Gen1 Credential Passthrough
You can authenticate automatically to Azure Data Lake Storage Gen1 and Azure Data Lake Storage Gen2 from Azure Databricks clusters using the same Azure Active Directory (Azure AD) identity that you use to log into Azure Databricks. When you enable your cluster for Azure Data Lake Storage credential passthrough, commands that you run on that cluster can read and write data in Azure Data Lake Storage without requiring you to configure service principal credentials for access to storage.
References:
https://docs.azuredatabricks.net/spark/latest/data-sources/azure/adls-passthrough.html
NEW QUESTION: 3
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:
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.
NEW QUESTION: 4
You are working for a company that designs mobile applications. They maintain a server where player records are assigned to their different games. The tracking system is new and in development.
The application uses Entity Framework to connect to an Azure Database. The database holds a Player table and Game table.
When adding a player, the code should insert a new player record, and add a relationship between an existing game record and the new player record.
The application will call CreatePlayerWithGame with the correct gameIdand the playerId to start the process.
(Line numbers are included for reference only.)
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
Many-to-many relationships without an entity class to represent the join table are not yet supported. However, you can represent a many-to-many relationship by including an entity class for the join table and mapping two separate one-to-many relationships.
protected override void OnModelCreating(ModelBuilder modelBuilder)
{
modelBuilder.Entity<PostTag>()
HasKey(t => new { t.PostId, t.TagId });
modelBuilder.Entity<PostTag>()
HasOne(pt => pt.Post)
WithMany(p => p.PostTags)
HasForeignKey(pt => pt.PostId);
modelBuilder.Entity<PostTag>()
HasOne(pt => pt.Tag)
WithMany(t => t.PostTags)
HasForeignKey(pt => pt.TagId);
}
}