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NEW QUESTION: 1
Which statement creates a low overhead, low-contention random number generator that is isolated to
thread to generate a random number between 1 and 100?
A. int i = new random().nextInt(100)+1;
B. int i = ThreadLocalRandom.current().nextInt(1, 101);
C. int i = ThreadSafeRandom.current().nextInt(1, 101);
D. int i = (int) Math.random(1, 101);
E. int i = (int) Math.random()*100+1;
Answer: B
Explanation:
Explanation/Reference:
Explanation:
public class ThreadLocalRandom extends Random
A random number generator isolated to the current thread. Like the global Random generator used by the
Math class, a ThreadLocalRandom is initialized with an internally generated seed that may not otherwise
be modified. When applicable, use of ThreadLocalRandom rather than shared Random objects in
concurrent programs will typically encounter much less overhead and contention. Use of
ThreadLocalRandom is particularly appropriate when multiple tasks (for example, each a ForkJoinTask)
use random numbers in parallel in thread pools. Usages of this class should typically be of the form:
ThreadLocalRandom.current ().nextX(...) (where X is Int, Long, etc). When all usages are of this form, it is
never possible to accidently share
a ThreadLocalRandom across multiple threads.
This class also provides additional commonly used bounded random generation methods.
Reference:Class ThreadLocalRandom

NEW QUESTION: 2
The tasks associated with Landscape transportation are in which workstream?
Please choose the correct answer.
Response:
A. System & Data Migration
B. Application Solution Adoption
C. Technical Architecture and Infrastructure
D. Transition to Operations
Answer: A

NEW QUESTION: 3
You have recently joined a startup company building sensors to measure street noise and air quality in urban areas. The company has been running a pilot deployment of around 100 sensors for 3 months each sensor uploads 1KB of sensor data every minute to a backend hosted on AWS.
During the pilot, you measured a peak or 10 lOPS on the database, and you stored an average of 3GB of sensor data per month in the database.
The current deployment consists of a load-balanced auto scaled Ingestion layer using EC2 instances and a PostgreSQL RDS database with 500GB standard storage.
The pilot is considered a success and your CEO has managed to get the attention or some potential investors. The business plan requires a deployment of at least lOOK sensors which needs to be supported by the backend. You also need to store sensor data for at least two years to be able to compare year over year Improvements.
To secure funding, you have to make sure that the platform meets these requirements and leaves room for further scaling. Which setup win meet the requirements?
A. Replace the RDS instance with a 6 node Redshift cluster with 96TB of storage
B. Ingest data into a DynamoDB table and move old data to a Redshift cluster
C. Add an SQS queue to the ingestion layer to buffer writes to the RDS instance
D. Keep the current architecture but upgrade RDS storage to 3TB and lOK provisioned lOPS
Answer: A