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Cloudera Certified Administrator for Apache Hadoop CDH4 Sample Questions:

1. You have a cluster running with the fair scheduler enabled and configured. You submit multiple jobs to the cluster. Each job is assigned to a pool. What are the two key points to remember about how jobs are scheduled with the fair scheduler?

A) Pools are assigned priorites.pools with higher priorities an executed b4 pools with lower priorities
B) Each pool gets 1/N of the total available tasks slots, where N is the no of jobs running on the cluster
C) Each pools share of the tasks slots remains static within the execution of any individual job
D) Each pool gets 1/M of the total available tasks slots, where M is the no. of nodes in the cluster
E) Pools get a dynamically-allocated share of the available task slots (subject to additional constraints)
F) Each pools share of task slots may change throughout the course of job execution

2. A client application opens a file write stream on your cluster. Which two metadata changes occur during a file write?

A) the change is written to the secondary namenode
B) The change is written to the namenode disk
C) the metadata in Ram on the namenode is flushed to disk
D) The change is written to the edits file
E) The metadata in a Ram on the name node is updated
F) the change is written to the fsimage file
G) the namenode triggers a block report to update block locations in the edits file

3. You observe that the number of spilled records from map tasks for exceeds the number of map output records. You child heap size is 1 GB and your io.sort.mb value is set to 100MB. How would you tune your io.sort.mb value to achieve maximum memory to disk I/O ratio?

A) Tune io.sort.mb value until you observe that the number of spilled records equals (or is as close to equals) the number of map output records.
B) Increase the IO.sort.mb as high you can, as close to 1GB as possible.
C) Decrease the io.sort.mb value below 100M
D) For 1GB child heap size an io.sort.mb of 128MB will always maximum memory to disk I/O.

4. Compare the hardware requirements of the NameNode with that of the DataNodes in a Hadoop cluster running MapReduce v1 (MRv1):

A) The NameNode requires more memory and requires greater disk capacity than the DataNodes.
B) The NameNode requires more memory but less disk capacity.
C) The NameNode requires less memory and less disk capacity than the DataNodes.
D) The NameNode requires more memory and no disk drives.
E) The NameNode and DataNodes should the same hardware configuration.

5. Choose three reasons why should you run the HDFS balancer periodically?

A) To improve data locality for MapReduce tasks.
B) To ensure that there is capacity in HDFS tor additional data.
C) To help HDFS deliver consistent performance under heavy loads.
D) To ensure that all blocks in the cluster are 128MB in size.
E) To ensure that there is consistent disk utilization across the DataNodes.

Solutions: