Cloudera CCA-470

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

1. Identity four pieces of cluster information that are stored on disk on the NameNode?

A) Names of the files in HDFS.
B) A catalog of DataNodes and the blocks that are stored on them.
C) An edit log of changes that have been made since the last snapshot compaction by the Secondary NameNode.
D) The status of the heartbeats of each DataNode.
E) The directory structure of the files in HDFS.
F) File permissions of the files in HDFS.
G) An edit log of changes that have been made since the last snapshot of the NameNode.

2. How does the NameNode know DataNodes are available on a cluster running MapReduce v1 (MRv1)

A) The NameNode send a broadcast across the network when it first starts, and DataNodes respond.
B) DataNodes heartbeat in the master on a regular basis.
C) DataNodes listed in the dfs.hosts file. The NameNode uses as the definitive list of available DataNodes.
D) The NameNode broadcasts a heartbeat on the network on a regular basis, and DataNodes respond.

3. You are planning a Hadoop duster, and you expect to be receiving just under 1TB of data per week which will be stored on the cluster, using Hadoop's default replication. You decide that your slave nodes will be configured with 4 x 1TB disks.
Calculate how many slave nodes you need to deploy at a minimum to store one year's worth of data.

A) 10 slave nodes
B) 50 slave nodes
C) 100 slave nodes
D) 100 slave nodes

4. You configure you cluster with HDFS High Availability (HA) using Quorum-Based storage. You do not implement HDFS Federation.
What is the maximum number of NameNodes daemon you should run on you cluster in order to avoid a "split-brain" scenario with your NameNodes?

A) One active NameNode and one Standby NameNode
B) Two active NameNodes and two Standby NameNodes
C) Two active NameNodes and one Standby NameNode
D) Unlimited. HDFS High Availability (HA) is designed to overcome limitations on the number of NameNodes you can deploy.

5. Where does a MapReduce job store the intermediate data output from Mappers?

A) In HDFS, in temporary directory defined mapred.tmp.dir.
B) In HDFS, in the job's output directory.
C) On the underlying filesystem of the local disk machine on which the JobTracker ran.
D) Stores on the underlying filesystem of the local disk of the machine on which the Reducer.
E) On the underlying filesystem of the local disk of the machine on which the Mapper ran.

Solutions: