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NEW QUESTION: 1

A. Option A
B. Option D
C. Option C
D. Option B
Answer: B

NEW QUESTION: 2
Your network contains an Active Directory domain. The domain contains a server named Server1.Server1 runs Windows Server 2008 R2.
You need to mount an Active Directory Lightweight Directory Services (AD LDS) snapshot from Server1.
What should you do?
A. Run ldp.exe and use the Bind option.
B. Run imagex.exe and specify the /mount parameter.
C. Run diskpart.exe and use the Attach option.
D. Run dsdbutil.exe and use the snapshot option.
Answer: D
Explanation:
http://technet.microsoft.com/en-us/library/cc753151%28v=ws.10%29.aspx Dsdbutil Performs database maintenance of the Active Directory Domain Services (AD DS) store, facilitates configuration of Active Directory Lightweight Directory Services (AD LDS) communication ports, and views AD LDS instances that are installed on a computer. Commands snapshot Manages snapshots. http://technet.microsoft.com/en-us/library/cc731620%28v=ws.10%29.aspx snapshot Manages snapshots of the volumes that contain the Active Directory database and log files, which you can view on a domain controller without starting in Directory Services Restore Mode (DSRM). You can also run the snapshot subcommand on an Active Directory Lightweight Directory Services (AD LDS) server. This is a subcommand of Ntdsutil and Dsdbutil. Ntdsutil and Dsdbutil are command-line tools that are built into Windows Server 2008 and Windows Server 2008 R2. Syntax activate instance %s [create] [delete %s] [unmount %s] [list all] [list mounted ] [mount %s] [quit] Parameters Mount %s Mounts a snapshot with GUID %s. You can refer to an index number of any mounted snapshot instead of its GUID.

NEW QUESTION: 3
Microsoft AzureでLambdaアーキテクチャを使用してソリューションを開発しています。
テストレイヤーのデータは、次の要件を満たしている必要があります。
データストレージ：
*リポジトリ（またはさまざまな形式の大量の大容量ファイル）として機能します。
*ビッグデータ分析ワークロード用に最適化されたストレージを実装します。
*階層構造を使用してデータを整理できるようにします。
バッチ処理：
*メモリ内の計算処理にはマネージドソリューションを使用します。
* Scala、Python、およびRプログラミング言語をネイティブにサポートします。
*クラスターを自動的にサイズ変更および終了する機能を提供します。
Analytical data store:
* Support parallel processing.
* Use columnar storage.
* Support SQL-based languages.
Lambdaアーキテクチャを構築するには、正しいテクノロジーを特定する必要があります。
どのテクノロジーを使用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

Data storage: Azure Data Lake Store
A key mechanism that allows Azure Data Lake Storage Gen2 to provide file system performance at object storage scale and prices is the addition of a hierarchical namespace. This allows the collection of objects/files within an account to be organized into a hierarchy of directories and nested subdirectories in the same way that the file system on your computer is organized. With the hierarchical namespace enabled, a storage account becomes capable of providing the scalability and cost-effectiveness of object storage, with file system semantics that are familiar to analytics engines and frameworks.
Batch processing: HD Insight Spark
Aparch Spark is an open-source, parallel-processing framework that supports in-memory processing to boost the performance of big-data analysis applications.
HDInsight is a managed Hadoop service. Use it deploy and manage Hadoop clusters in Azure. For batch processing, you can use Spark, Hive, Hive LLAP, MapReduce.
Languages: R, Python, Java, Scala, SQL
Analytic data store: SQL Data Warehouse
SQL Data Warehouse is a cloud-based Enterprise Data Warehouse (EDW) that uses Massively Parallel Processing (MPP).
SQL Data Warehouse stores data into relational tables with columnar storage.
References:
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-namespace
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-overview-what-is