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Which of the following is the correct syntax to start a Hadoop job on AWS EMR using the AWS CLI?

easy📝 Conceptual Q12 of 15

Hadoop - Modern Data Architecture with Hadoop

Which of the following is the correct syntax to start a Hadoop job on AWS EMR using the AWS CLI?

Aaws emr run-job --id j-2AXXXXXXGAPLF --type Spark --file myapp.jar

Baws emr start-job --cluster j-2AXXXXXXGAPLF --job Spark --args s3://mybucket/myapp.jar

Caws emr add-steps --cluster-id j-2AXXXXXXGAPLF --steps Type=Spark,Name="Spark Program",ActionOnFailure=CONTINUE,Args=[--class,org.apache.spark.examples.SparkPi,s3://mybucket/myapp.jar,10]

Daws emr submit-step --cluster j-2AXXXXXXGAPLF --step Spark --jar myapp.jar

Step-by-Step Solution

Solution:

Step 1: Review AWS EMR CLI syntax for adding steps
The correct command uses aws emr add-steps with detailed step parameters.
Step 2: Match syntax with options
aws emr add-steps --cluster-id j-2AXXXXXXGAPLF --steps Type=Spark,Name="Spark Program",ActionOnFailure=CONTINUE,Args=[--class,org.apache.spark.examples.SparkPi,s3://mybucket/myapp.jar,10] matches the official syntax with cluster ID, step type, name, failure action, and arguments.
Final Answer:
aws emr add-steps --cluster-id j-2AXXXXXXGAPLF --steps Type=Spark,Name="Spark Program",ActionOnFailure=CONTINUE,Args=[--class,org.apache.spark.examples.SparkPi,s3://mybucket/myapp.jar,10] -> Option C
Quick Check:
Use add-steps with detailed args [OK]

Quick Trick: Remember AWS EMR uses add-steps command [OK]

Common Mistakes:

Using non-existent commands like start-job
Omitting required step parameters
Incorrect option names or flags

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