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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

A. destination-MAC
B. dest-source-MAC
C. source-MAC
D. source-IP
E. destination-IP
Answer: B,C

NEW QUESTION: 3
You are updating a Magento Commerce Cloud project from version 2.2.5 to 2.3.0 with the command Composer require magento/product-enterprise-edition:2,3,0 However, composer is unable to complete the task because the installed version of magento/magento-cloud-metapackage is not compatible.
How do you upgrade magento to the desired version?
A. Revert the composer.join to the last commit before the update and run the command again with the
-with-dependencies argument
B. Create a new project based on magento/ project-enterprise-edition: 2, 3, 0, the add eco-tools, custommodules and themes again with composer and migrate the data
C. Remove magento.produce-enterprise-edition from the root composer, Json requirements and run composer update
D. Run composer require magento/magento-cloud-metapakage:'' =2, 3.0 < 2, 3,1'' - update-with dependencies
Answer: D

NEW QUESTION: 4
A project manager receives a request for proposal (RFP) from a client. The client is very clear about the requirements. A requirements analysis must be done in the first month of the project, and the client wants to see a demo of the work completed every two weeks.
What project approach should the project manager use?
A. Predictive for the requirements analysis and agile for delivery of the project
B. Agile for all of the phases of the project, including the requirements analysis and delivery
C. Iterative for the requirements analysis and delivery phases of the project
D. Predictive for the requirements analysis and delivery phases of the project
Answer: A