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Cloudera Certified Developer for Apache Hadoop Sample Questions:

1. 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) Yes, because HDFS is optimized for random access writes.
C) No, because HDFS can only be accessed by MapReduce applications.
D) No, because HDFS is optimized for write-once, streaming access for relatively large files.

2. Given a directory of files with the following structure: line number, tab character, string:
Example:
1.abialkjfjkaoasdfjksdlkjhqweroij
2.kadf jhuwqounahagtnbvaswslmnbfgy
3.kjfteiomndscxeqalkzhtopedkfslkj
You want to send each line as one record to your Mapper. Which InputFormat would you use to complete the line: setInputFormat (________.class);

A) KeyValueTextInputFormat
B) BDBInputFormat
C) SequenceFileInputFormat
D) SequenceFileAsTextInputFormat

3. You use the hadoop fs -put command to write a 300 MB file using an HDFS block size of 64 MB. Just after this command has finished writing 200 MB of this file, what would another user see when trying to access this file?

A) They would see no content until the whole file is written and closed.
B) They would see the current state of the file, up to the last bit written by the command.
C) They would see Hadoop throw an concurrentFileAccessException when they try to access this file.
D) They would see the content of the file through the last completed block.

4. What is the standard configuration of slave nodes in a Hadoop cluster?

A) Each slave node runs a JobTracker and a DataNode daemon.
B) Each slave node runs a DataNode daemon, but only a fraction of the slave nodes run TaskTrackers.
C) Each slave node runs a TaskTracker and a DataNode daemon.
D) Each slave node either runs a TaskTracker or a DataNode daemon, but not both.
E) Each slave node runs a TaskTracker, but only a fraction of the slave nodes run DataNode daemons.

5. Combiners Increase the efficiency of a MapReduce program because:

A) They aggregate intermediate map output horn a small number of nearby (i.e., rack-local) machines and therefore reduce the amount of data that needs to be shuffled across the network to the reducers.
B) They provide an optimization and reduce the total number of computations that are needed to execute an algorithm by a factor of n, where is the number of reducer.
C) They aggregate intermediate map output locally on each individual machine and therefore reduce the amount of data that needs to be shuffled across the network to the reducers.
D) They provide a mechanism for different mappers to communicate with each Other, thereby reducing synchronization overhead.

Solutions: