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Vendor: Cloudera
Exam Code: CCA-500
Exam Name: Cloudera Certified Administrator for Apache Hadoop (CCAH)
Certification Provider: Cloudera
Total Questions: 60 Q&A
Updated on: Mar 30, 2025
Note: Product instant download. Please sign in and click My account to download your product.You have a cluster running with the fair Scheduler enabled. There are currently no jobs running on the cluster, and you submit a job A, so that only job A is running on the cluster. A while later, you submit Job B. now Job A and Job B are running on the cluster at the same time. How will the Fair Scheduler handle these two jobs? (Choose two)
A. When Job B gets submitted, it will get assigned tasks, while job A continues to run with fewer tasks.
B. When Job B gets submitted, Job A has to finish first, before job B can gets scheduled.
C. When Job A gets submitted, it doesn't consumes all the task slots.
D. When Job A gets submitted, it consumes all the task slots.
You are migrating a cluster from MApReduce version 1 (MRv1) to MapReduce version 2 (MRv2) on YARN. You want to maintain your MRv1 TaskTracker slot capacities when you migrate. What should you do/
A. Configure yarn.applicationmaster.resource.memory-mb and yarn.applicationmaster.resource.cpu-vcores so that ApplicationMaster container allocations match the capacity you require.
B. You don't need to configure or balance these properties in YARN as YARN dynamically balances resource management capabilities on your cluster
C. Configure mapred.tasktracker.map.tasks.maximum and mapred.tasktracker.reduce.tasks.maximum ub yarn-site.xml to match your cluster's capacity set by the yarn-scheduler.minimum-allocation
D. Configure yarn.nodemanager.resource.memory-mb and yarn.nodemanager.resource.cpu- vcores to match the capacity you require under YARN for each NodeManager
A user comes to you, complaining that when she attempts to submit a Hadoop job, it fails. There is a Directory in HDFS named /data/input. The Jar is named j.jar, and the driver class is named DriverClass.
She runs the command:
Hadoop jar j.jar DriverClass /data/input/data/output
The error message returned includes the line: PriviligedActionException as:training (auth:SIMPLE) cause:org.apache.hadoop.mapreduce.lib.input.invalidInputException: Input path does not exist: file:/data/input
What is the cause of the error?
A. The user is not authorized to run the job on the cluster
B. The output directory already exists
C. The name of the driver has been spelled incorrectly on the command line
D. The directory name is misspelled in HDFS
E. The Hadoop configuration files on the client do not point to the cluster
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