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NEW QUESTION: 1
The output information of router routing table is as follows. Which is correct? (Muitiple choice)

A. The NextHop of this router reaching 10.0.0.1 is 10.0.21.2.
B. The NextHop of this router reaching 10.0.0.1 is 10.0.12.2
C. The NextHop of this router reaching 10.0.2.2 is 10.0.12.2
D. The NextHop of this router reaching 10.0.2.2 is 10.0.21.2
Answer: B,D

NEW QUESTION: 2
The implementations group has been using the test bed to do a `proof-of-concept' that requires both Client 1 and Client 2 to access the WEB Server at 209.65.200.241. After several changes to the network addressing, routing scheme, DHCP services, NTP services, layer 2 connectivity, FHRP services, and device security, a trouble ticket has been opened indicating that Client 1 cannot ping the 209.65.200.241 address.
Use the supported commands to isolated the cause of this fault and answer the following questions.
What is the solution to the fault condition?


A. DSW1
B. ASW2
C. DSW2
D. ASW1
E. R3
F. R1
G. R2
H. R4
Answer: D

NEW QUESTION: 3
You are designing a service that aggregates clickstream data in batch and delivers reports to subscribers via
email only once per week. Data is extremely spikey, geographically distributed, high-scale, and unpredictable.
How should you design this system?
A. Use a CloudFront distribution with access log delivery to S3. Clicks should be recorded as querystring
GETs to the distribution. Reports are built and sent by periodically running EMRjobs over the access
logs in S3.
C Use API Gateway invoking Lambdas which PutRecords into Kinesis, and EMR running Spark
performing GetRecords on Kinesis to scale with spikes. Spark on EMR outputs the analysis to S3, which
are sent out via email.
D- Use AWS Elasticsearch service and EC2 Auto Scaling groups. The Autoscaling groups scale based
on click throughput and stream into the Elasticsearch domain, which is also scalable. Use Kibana to
generate reports periodically.
B. Use a large RedShift cluster to perform the analysis, and a fleet of Lambdas to perform record inserts
into the RedShift tables. Lambda will scale rapidly enough for the traffic spikes.
Answer: A
Explanation:
Explanation
When you look at building reports or analyzing data from a large data set, you need to consider CMR because
this service is built on the Hadoop framework which is used to processes large data sets.
The ideal approach to getting data onto CMR is to use S3. Since the Data is extremely spikey and
geographically distributed, using edge locations via Cloudfront distributions is the best way to fetch the data.
Option A is invalid because RedShift is more of a petabyte storage cluster.
Option C is invalid because having both Kinesis and CMR for the job analysis is redundant.
Option D is invalid because Elastic Search is not an option for processing records.
For more information on Amazon CMR, please visit the below URL:
* https://aws.amazon.com/emr/