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Cloudera Certified Developer for Apache Hadoop Sample Questions:

1. For each input key-value pair, mappers can emit:

A) As many intermediate key-value pairs as desired. There are no restrictions on the types of those key-value pairs (i.e., they can be heterogeneous).
B) As many intermediate key-value pairs as desired, but they cannot be of the same type as the input key-value pair.
C) One intermediate key value pair, but of the same type.
D) As many intermediate key value pairs as desired, as long as all the keys have the same type and all the values have the same type.
E) One intermediate key value pair, of a different type.

2. What is the behavior of the default partitioner?

A) The default partitioner computes the hash of the value and takes the mod of that value with the number of reducers. The result determines the reducer assigned to process the key value pair.
B) The default partitioner assigns key value pairs to reducers based on an internal random number generator.
C) The default partitioner implements a round robin strategy, shuffling the key value pairs to each reducer in turn. This ensures an even partition of the key space.
D) The default partitioner computes the hash of the key. Hash values between specific ranges are associated with different buckets, and each bucket is assigned to a specific reducer.
E) The default partitioner computes the hash of the key and divides that value modulo the number of reducers. The result determines the reducer assigned to process the key-value pair.

3. You need to create a GUI application to help your company's sales people add and edit customer information. Would HDFS be appropriate for this customer information file?

A) Yes, because HDFS is optimized for fast retrieval of relatively small amounts of data.
B) No, because HDFS can only be accessed by MapReduce applications.
C) No, because HDFS is optimized for write-once, streaming access for relatively large files.
D) Yes, because HDFS is optimized for random access writes.

4. 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 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.
C) 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.
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.

5. 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) Secondary NameNode
B) NameNode
C) TaskTracker
D) DataNode
E) JobTracker

Solutions: