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NEW QUESTION: 1
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
You are planning a big data infrastructure by using an Apache Spark cluster in Azure HDInsight. The cluster has 24 processor cores and 512 GB of memory.
The architecture of the infrastructure is shown in the exhibit. (Click the Exhibit button.)

The architecture will be used by the following users:
Support analysts who run applications that will use REST to submit Spark jobs.

Business analysts who use JDBC and ODBC client applications from a real-time view. The business

analysts run monitoring queries to access aggregate results for 15 minutes. The results will be referenced by subsequent queries.
Data analysts who publish notebooks drawn from batch layer, serving layer, and speed layer queries.

All of the notebooks must support native interpreters for data sources that are batch processed. The serving layer queries are written in Apache Hive and must support multiple sessions. Unique GUIDs are used across the data sources, which allow the data analysts to use Spark SQL.
The data sources in the batch layer share a common storage container. The following data sources are used:
Hive for sales data

Apache HBase for operations data

HBase for logistics data by using a single region server

You need to ensure that the support analysts can develop embedded analytics applications by using the least amount of development effort.
Which technology should you implement?
A. Jupyter
B. Livy
C. Zeppelin
D. Apache Ambari
Answer: B
Explanation:
Explanation/Reference:
Explanation:
References: https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-apache-spark-livy-rest-interface

NEW QUESTION: 2
You are managing the development of an application that uses DynamoDB to store JSON data. You have already set the Read and Write capacity of the DynamoDB table. You are unsure of the amount of the traffic that will be received by the application during the deployment time. How can you ensure that the DynamoDB is not highly throttled and does not become a bottleneck for the application? Choose 2 answers from the options below.
A. Createa Cloudwatch alarm which would then send a trigger to AWS Lambda to create anew DynamoDB table.
B. Monitorthe SystemErrors metric using Cloudwatch
C. Monitorthe ConsumedReadCapacityUnits and ConsumedWriteCapacityUnits metric usingCloudwatch.
D. Createa Cloudwatch alarm which would then send a trigger to AWS Lambda to increasethe Read and Write capacity of the DynamoDB table.
Answer: C,D
Explanation:
Explanation
Refer to the following AWS Documentation that specifies what should be monitored for a DynamoDB table.

For more information on monitoring DynamoDB please seethe below link:
* http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/monitoring-cloudwatch.html

NEW QUESTION: 3
Scenario: Jack is the administrator of project prj1. The project involves a large volume of sensitive data such as bank account, medical record, etc. Jack wants to properly protect the data. Which of the follow statements is necessary?
A. use prj1;
B. set ProjectACL=true;
C. set ProjectProtection=true;
D. add accountprovider ram;
Answer: C