Cloudera CCD-333 : Cloudera Certified Developer for Apache Hadoop

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Cloudera Certified Developer for Apache Hadoop Sample Questions:

1. 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.

2. MapReduce is well-suited for all of the following applications EXCEPT? (Choose one):

A) Online transaction processing (OLTP) for an e-commerce Website.
B) Text mining on a large collections of unstructured documents.
C) Analysis of large amounts of Web logs (queries, clicks, etc.).
D) Graph mining on a large social network (e.g., Facebook friends network).

3. In the standard word count MapReduce algorithm, why might using a combiner reduce the overall Job running time?

A) Because combiners perform local aggregation of word counts, thereby reducing the number of mappers that need to run.
B) Because combiners perform local aggregation of word counts, thereby allowing the mappers to process input data faster.
C) Because combiners perform local aggregation of word counts, thereby reducing the number of key-value pairs that need to be snuff let across the network to the reducers.
D) Because combiners perform local aggregation of word counts, and then transfer that data to reducers without writing the intermediate data to disk.

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

5. Workflows expressed in Oozie can contain:

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

Solutions: