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Cloudera Certified Developer for Apache Hadoop Sample Questions:

1. You need to create a job that does frequency analysis on input data. You will do this by writing a Mapper that uses TextInputForma and splits each value (a line of text from an input file) into individual characters. For each one of these characters, you will emit the character as a key and as IntWritable as the value. Since this will produce proportionally more intermediate data than input data, which resources could you expect to be likely bottlenecks?

A) Processor and RAM
B) Processor and network I/O
C) Processor and disk I/O
D) Disk I/O and network I/O

2. Which of the following best describes the workings of TextInputFormat?

A) Input file splits may cross line breaks. A line that crosses file splits is read by the RecordReaders of both splits containing the broken line.
B) Input file splits may cross line breaks. A line that crosses file splits is read by the RecordReader of the split that contains the beginning of the broken line.
C) Input file splits may cross line breaks. A line that crosses file splits is read by the RecordReader of the split that contains the end of the broken line.
D) Input file splits may cross line breaks. A line that crosses tile splits is ignored.
E) The input file is split exactly at the line breaks, so each Record Reader will read a series of complete lines.

3. Workflows expressed in Oozie can contain:

A) Sequences of MapReduce and Pig jobs. These are limited to linear sequences of actions with exception handlers but no forks.
B) Sequences of MapReduce and Pig. These sequences can be combined with other actions including forks, decision points, and path joins.
C) Sequences of MapReduce jobs only; no Pig or Hive tasks or jobs. These MapReduce sequences can be combined with forks and path joins.
D) Iterative repetition of MapReduce jobs until a desired answer or state is reached.

4. Which of the Following best describes the lifecycle of a Mapper?

A) The JobTracker spawns a new Mapper to process all records in a single file.
B) The TaskTracker spawns a new Mapper to process all records in a single input split.
C) The TaskTracker spawns a new Mapper to process each key-value pair.
D) The JobTracker calls the FastTracker's configure () method, then its map () method and finally its closer ()

5. You've written a MapReduce job that will process 500 million input records and generate 500 million key-value pairs. The data is not uniformly distributed. Your MapReduce job will create a significant amount of intermediate data that it needs to transfer between mappers and reducers which is a potential bottleneck. A custom implementation of which of the following interfaces is most likely to reduce the amount of intermediate data transferred across the network?

A) Partitioner
B) Writable
C) InputFormat
D) WritableComparable
E) Combiner
F) OutputFormat

Solutions: