Cloudera Certified Developer for Apache Hadoop Sample Questions:

1. What is a Writable?

A) Writable is an abstract class that all keys, but not values, in MapReduce must extend. Classes extending this abstract base class must implement methods for serializing and deserializing themselves.
B) Writable is an interface that all keys and values in MapReduce must implement. Classes implementing this interface must implement methods for serializing and deserializing themselves.
C) Writable is an interface that all keys, but not values, in MapReduce must implement. Classes implementing this interface must implement methods for serializing and deserializing themselves.
D) Writable is an abstract class that all keys and values in MapReduce must extend. Classes extending this abstract base class must implement methods for serializing and deserializing themselves

2. What is the difference between a failed task attempt and a killed task attempt?

A) A failed task attempt is a task attempt that threw an unhandled exception. A killed task attempt is one that was terminated by the JobTracker.
B) A failed task attempt is a task attempt that completed, but with an unexpected status value. A killed task attempt is a duplicate copy of a task attempt that was started as part of speculative execution.
C) A failed task attempt is a task attempt that threw a RuntimeException (i.e., the task fails). A killed task attempt is a task attempt that threw any other type of exception (e.g., IOException); the execution framework catches these exceptions and reports them as killed.
D) A failed task attempt is a task attempt that did not generate any key value pairs. A killed task attempt is a task attempt that threw an exception, and thus killed by the execution framework.

3. Your client application submits a MapReduce job to your Hadoop cluster. The Hadoop framework looks for an available slot to schedule the MapReduce operations on which of the following Hadoop computing daemons?

A) NameNode
B) TaskTracker
C) DataNode
D) JobTracker
E) Secondary NameNode

4. You are running a job that will process a single InputSplit on a cluster which has no other jobs currently running. Each node has an equal number of open Map slots. On which node will Hadoop first attempt to run the Map task?

A) The node with the most free local disk space
B) The node with the most memory
C) The node with the lowest system load
D) The node on which this InputSplit is stored

5. Which of the following describes how a client reads a file from HDFS?

A) The client queries the NameNode for the block location(s). The NameNode returns the block location(s) to the client. The client reads the data directly off the DataNode(s).
B) The client contacts the NameNode for the block location(s). The NameNode contacts theDataNode that holds the requested data block. Data is transferred from the DataNode to the NameNode, and then from the NameNode to the client.
C) The client contacts the NameNode for the block location(s). The NameNode then queries the DataNodes for block locations. The DataNodes respond to the NameNode, and the NameNode redirects the client to the DataNode that holds the requested data block(s). The client then reads the data directly off the DataNode.
D) The client queries all DataNodes in parallel. The DataNode that contains the requested data responds directly to the client. The client reads the data directly off the DataNode.

Solutions: