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NEW QUESTION: 1

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

NEW QUESTION: 2
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: 3
Click the Exhibit button. Your router is configured to peer with your ISP's router using BGP. You can only
control your BGP configuration. Which address families are negotiated between the two BGP peers
shown in the exhibit?

A. inet-unicast inet-vpn-unicast 12vpn
B. inet-vpn-unicast
C. inet-unicast
D. inet-unicast inet-vpn-unicast 12vpn-signaling
Answer: C
Explanation:
From the exhibit we see: NLRI for restart configured on peer: inet-unicast inet-vpn-unicast
1 2vpn But we also see: NLRI that restat is negotiaded for: inet-unicast NLRI of received end-of-rib
markers: inet-unicast NLRI of all end-of-rib markers sent:inet-unicast

NEW QUESTION: 4
Where are two places the amount of time a Business Process (BP) remains online in the
system can be updated? (Choose two.)
A. Performance Tuning Wizard
B. RetentionService configuration
C. archive.properties
D. Business Process Editor
E. Archive Manager
Answer: D,E