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Cloudera Certified Administrator for Apache Hadoop CDH4 Upgrade Exam (CCAH) Sample Questions:

1. Which three processes does HDFS High Availability (HA) enable on your cluster?

A) Automatically 'fail over' between NameNodes if one goes down
B) Write data to two clusterssimultaneously
C) Shut one NameNode down for maintenance without halting the cluster
D) Configure unlimited hot standby NameNode.
E) Manually 'fail over' between NameNodes

2. For a MapReduce job, on a cluster running MapReduce v1 (MRv1), what's the relationship between tasks and task templates?

A) The developer sets the number of task attempts on job submission.
B) There are always exactly as many task attempts as there are tasks.
C) There are always at least as many task attempts as there are tasks.
D) There are always at most as many tasks attempts as there are tasks.

3. In the context of configuring a Hadoop cluster for HDFS High Availability (HA), 'fencing' refers to:

A) Isolating both HA NameNodes to prevent a client application from killing the NameNode daemons.
B) Isolating a failed NameNode from write access to the fsimage and edits files so that is cannot resume write operations if it recovers.
C) Isolating the cluster's master daemon to limit write access only to authorized clients.
D) Isolating the standby NameNode from write access to the fsimage and edits files.

4. Your Hadoop cluster has 12 slave nodes, a block size set to 64MB, and a replication factor of three.
Choose which best describes how the Hadoop Framework distributes block writes into HDFS from a Reducer outputting a 150MB file?

A) The slave node on which the Reducer runs gets the first copy of every block written. Other block replicas will be placed on other nodes.
B) Reducers don't write blocks into HDFS
C) The Reducer will generate nine blocks and write them randomly to nodes throughout the cluster.
D) The Reducer will generate twelve blocks and write them to slave nodes nearest the node on which the Reducer runs.

5. 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) Decrease the io.sort.mb value below 100M
C) Increase the IO.sort.mb as high you can, as close to 1GB as possible.
D) For 1GB child heap size an io.sort.mb of 128MB will always maximum memory to disk I/O.

Solutions: