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NEW QUESTION: 1
You are developing a solution using a Lambda architecture on Microsoft Azure.
The data at test layer must meet the following requirements:
Data storage:
* Serve as a repository (or high volumes of large files in various formats.
* Implement optimized storage for big data analytics workloads.
* Ensure that data can be organized using a hierarchical structure.
Batch processing:
* Use a managed solution for in-memory computation processing.
* Natively support Scala, Python, and R programming languages.
* Provide the ability to resize and terminate the cluster automatically.
Analytical data store:
* Support parallel processing.
* Use columnar storage.
* Support SQL-based languages.
You need to identify the correct technologies to build the Lambda architecture.
Which technologies should you use? To answer, select the appropriate options in the answer area NOTE: Each correct selection is worth one point.

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

NEW QUESTION: 2
Your domain has contains a Windows 8 computer name Computer1 using BitLocker. The E:\ drive is encrypted and currently locked.
You need to unlock the E:\ drive with the recovery key stored on C:\
What should you run?
A. Disable-BitLocker
B. Unlock-BitLocker
C. Suspend-BitLocker
D. Enable-BitLockerAutoUnloc
Answer: B
Explanation:
Unlock-BitLocker - Restores access to data on a BitLocker volume.
The Unlock-BitLocker cmdlet restores access to encrypted data on a volume that uses BitLocker Drive
Encryption.
http://technet.microsoft.com/en-us/library/jj649833(v=wps.620).aspx

NEW QUESTION: 3
Which two methods change the IP MTU value for an interface? (Choose two.)
A. Configure the IP system MTU.
B. Configure the interface IP MTU.
C. Configure the interface MTU.
D. Configure the default MTU.
Answer: B,C
Explanation:
An IOS device configured for IP+MPLS routing uses three different Maximum Transmission Unit (MTU) values: The hardware MTU configured with the mtu interface configuration command
- The IP MTU configured with the ip mtu interface configuration command
- The MPLS MTU configured with the mpls mtu interface configuration command
The hardware MTU specifies the maximum packet length the interface can support ... or at least that's the theory behind it. In reality, longer packets can be sent (assuming the hardware interface chipset doesn't complain); therefore you can configure MPLS MTU to be larger than the interface MTU and still have a working network. Oversized packets might not be received correctly if the interface uses fixed-length buffers; platforms with scatter/gather architecture (also called particle buffers) usually survive incoming oversized packets. IP MTU is used to determine whether am IP packet forwarded through an interface has to be fragmented. It has to be lower or equal to hardware MTU (and this limitation is enforced). If it equals the HW MTU, its value does not appear in the running configuration and it tracks the changes in HW MTU. For example, if you configure ip mtu 1300 on a Serial interface, it will appear in the running configuration as long as the hardware MTU is not equal to 1300 (and will not change as the HW MTU changes). However, as soon as the mtu 1300 is configured, the ip mtu 1300 command disappears from the configuration and the IP MTU yet again tracks the HW MTU.
Reference: http://blog.ipspace.net/2007/10/tale-of-three-mtus.html