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NEW QUESTION: 1
Which statement is true about the NameNode in Hadoop?
A. When loading data, the NameNode tells the client or program where to write the data.
B. All data passes through the NameNode; so if it is not sized properly, it could be a potential bottleneck.
C. A query in Hadoop requires a MapReduce job to be run so the NameNode gets the location of the data from the JobTracker.
D. If the NameNode goes down and a secondary NameNode has not been defined, the cluster is still accessible.
Answer: D
Explanation:
Note that, in an HA cluster, the Standby NameNode also performs checkpoints of the namespace state, and thus it is not necessary to run a Secondary NameNode,
CheckpointNode, or BackupNode in an HA cluster. In fact, to do so would be an error.
In a typical HA cluster, two separate machines are configured as NameNodes. At any point in time, exactly one of the NameNodes is in an Active state, and the other is in a Standby state.
Note that, in an HA cluster, the Standby NameNode also performs checkpoints of the namespace state, and thus it is not necessary to run a Secondary NameNode,
CheckpointNode, or BackupNode in an HA cluster.
References: https://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop- hdfs/HDFSHighAvailabilityWithNFS.html

NEW QUESTION: 2
Click the Exhibit button.

You configured the route filter shown in the exhibit.
In this scenario, which IP addresses would term-One accept?
A. IP addresses that are part of the 172.35.0.0/16 network and IP addresses that are in the 172.35.0.0/16 and 172.36.0.0/16 subnets.
B. IP addresses that are part of the 172.35.0.0/16 network and IP addresses that are in the subnets of 172.35.0.0/16 network.
C. IP addresses that are part of the 172.35.0.0/16 network, but not IP addresses that are part of the
172.35.0.0/16 network itself.
D. IP addresses that are part of the 172.35.0.0/16 network only.
Answer: B

NEW QUESTION: 3
DRAG DROP
Drag each statement about QoS features on the left to the matching QoS feature on the right.
Select and Place:

Answer:
Explanation:

NEW QUESTION: 4
A company is currently using AWS CodeCommit for its source control and AWS CodePipeline for continuous integration. The pipeline has a build stage for building the artifacts which is then staged in an Amazon S3 bucket.
The company has identified various improvement opportunities in the existing process, and a Solutions Architect has been given the following requirement:

Create a new pipeline to support feature development

Support feature development without impacting production applications

Incorporate continuous testing with unit tests

Isolate development and production artifacts

Support the capability to merge tested code into production code.
How should the Solutions Architect achieve these requirements?
A. Trigger a separate pipeline from CodeCommit feature branches. Use AWS CodeBuild for running unit tests. Use CodeBuild to stage the artifacts within an S3 bucket in a separate testing account.
B. Trigger a separate pipeline from CodeCommit feature branches. Use AWS Lambda for running unit tests. Use AWS CodeDeploy to stage the artifacts within an S3 bucket in a separate testing account.
C. Trigger a separate pipeline from CodeCommit tags Use Jenkins for running unit tests. Create a stage in the pipeline with S3 as the target for staging the artifacts with an S3 bucket in a separate testing account.
D. Create a separate CodeCommit repository for feature development and use it to trigger the pipeline. Use AWS Lambda for running unit tests. Use AWS CodeBuild to stage the artifacts within different S3 buckets in the same production account.
Answer: D
Explanation:
Explanation
https://docs.aws.amazon.com/codebuild/latest/userguide/how-to-create-pipeline.html