Cloudera CCD-333 : Cloudera Certified Developer for Apache Hadoop

CCD-333 real exams

Exam Code: CCD-333

Exam Name: Cloudera Certified Developer for Apache Hadoop

Updated: Jun 01, 2026

Q & A: 60 Questions and Answers

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Cloudera Certified Developer for Apache Hadoop Sample Questions:

1. All keys used for intermediate output from mappers must do which of the following:

A) Implement WritableComparable
B) Use a comparator for speedy sorting
C) Be a subclass of Filelnput-Format
D) Override isSplitable
E) Be compressed using a splittable compression algorithm.


2. Your Custer's HOFS block size is 64MB. You have a directory containing 100 plain text files, each of which Is 100MB in size. The InputFormat for your job is TextInputFormat. How many Mappers will run?

A) 640
B) 100
C) 64
D) 200


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


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. In a MapReduce job, the reducer receives all values associated with the same key. Which statement is most accurate about the ordering of these values?

A) The values are arbitrarily ordered, but multiple runs of the same MapReduce job will always have the same ordering.
B) The values are arbitrarily ordered, and the ordering may vary from run to run of the same MapReduce job.
C) The values are in sorted order.
D) Since the values come from mapper outputs, the reducers will receive contiguous sections of sorted values.


Solutions:

Question # 1
Answer: A
Question # 2
Answer: D
Question # 3
Answer: C
Question # 4
Answer: D
Question # 5
Answer: D

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