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NEW QUESTION: 1
You have a virtual network named VNet1 that has the configuration shown in the following exhibit.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Box 1: add a subnet
Your IaaS virtual machines (VMs) and PaaS role instances in a virtual network automatically receive a private IP address from a range that you specify, based on the subnet they are connected to. We need to add the
192.168.1.0/24 subnet.
Box 2: add a network interface
The 10.2.1.0/24 network exists. We need to add a network interface.
References:
https://docs.microsoft.com/en-us/azure/virtual-network/virtual-networks-static-private-ip-arm-pportal

NEW QUESTION: 2
A customer has purchased EMC Data Protection Advisor (DPA) and wants to collect system performance information from 100 HP-UX servers.
In addition to the DPA server, how many agents are required in an environment with four data centers?
A. 0
B. 1
C. 2
D. 3
Answer: A

NEW QUESTION: 3
In a MapReduce job, the reducer receives all values associated with the same key. Which statement is most accurate about the ordering of these values?
A. The values are in sorted order.
B. Since the values come from mapper outputs, the reducers will receive contiguous sections of sorted values.
C. The values are arbitrarily ordered, and the ordering may vary from run to run of the same MapReduce job.
D. The values are arbitrarily ordered, but multiple runs of the same MapReduce job will always have the same ordering.
Answer: B
Explanation:
Note:
*The Mapper outputs are sorted and then partitioned per Reducer.
*The intermediate, sorted outputs are always stored in a simple (key-len, key, value-len, value)
format.
*Input to the Reducer is the sorted output of the mappers. In this phase the framework fetches the
relevant partition of the output of all the mappers, via HTTP.
*A MapReduce job usually splits the input data-set into independent chunks which are processed
by the map tasks in a completely parallel manner. The framework sorts the outputs of the maps,
which are then input to the reduce tasks.
*The MapReduce framework operates exclusively on <key, value> pairs, that is, the framework
views the input to the job as a set of <key, value> pairs and produces a set of <key, value> pairs
as the output of the job, conceivably of different types.
The key and value classes have to be serializable by the framework and hence need to implement
the Writable interface. Additionally, the key classes have to implement the WritableComparable
interface to facilitate sorting by the framework.
Reference:MapReduce Tutorial

NEW QUESTION: 4
A gas company needs to monitor gas pressure in their pipelines. Pressure data is streamed from sensors placed throughout the pipelines to monitor the data in real time. When an anomaly is detected, the system must send a notification to open valve. An Amazon Kinesis stream collects the data from the sensors and an anomaly Kinesis stream triggers an AWS Lambda function to open the appropriate valve.
Which solution is the MOST cost-effective for responding to anomalies in real time?
A. Launch a fleet of Amazon EC2 instances with a Kinesis Client Library application that consumes the stream and aggregates sensor data over time to identify anomalies. When an anomaly is detected, the application sends a message to the anomaly stream to open the valve.
B. Attach a Kinesis Firehose to the stream and persist the sensor data in an Amazon S3 bucket.
Schedule an AWS Lambda function to run a query in Amazon Athena against the data in Amazon S3 to identify anomalies. When a change is detected, the Lambda function sends a message to the anomaly stream to open the valve.
C. Create a Kinesis Analytics application by using the RANDOM_CUT_FOREST function to detect an anomaly. When the anomaly score that is returned from the function is outside of an acceptable range, a message is sent to the anomaly stream to open the valve.
D. Launch an Amazon EMR cluster that uses Spark Streaming to connect to the Kinesis stream and Spark machine learning to detect anomalies. When a change is detected, the Spark application sends a message to the anomaly stream to open the valve.
Answer: B