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Cloudera CCD-333 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Hadoop Cluster Operations | - Cluster configuration and management basics - Resource management with YARN |
| Data Analysis and Optimization | - Query optimization in Hive - Performance tuning in MapReduce jobs |
| Data Ingestion and Workflow | - Sqoop data import/export - Flume data ingestion concepts |
| Data Processing with Hadoop Ecosystem | - Pig Latin scripting basics - Hive query language and data warehousing |
| Hadoop Fundamentals | - MapReduce programming model - HDFS architecture and data storage concepts |
Cloudera Certified Developer for Apache Hadoop Sample Questions:
You have the following key value pairs as output from your Map task:
(The, 1)
(Fox, 1)
(Runs, 1)
(Faster, 1)
(Than, 1)
(The, 1)
(Dog, 1)
How many keys will be passed to the reducer?
- A. Six
- B. Four
- C. Three
- D. One
- E. Five
- F. Two
Correct Answer: A 🗳️
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In a MapReduce job, you want each of you input files processed by a single map task. How do you configure a MapReduce job so that a single map task processes each input file regardless of how many blocks the input file occupies?
- A. Write a custom FileInputFormat and override the method isSplittable to always return false.
- B. Write a custom MapRunner that iterates over all key-value pairs in the entire file.
- C. Increase the parameter that controls minimum split size in the job configuration.
- D. Set the number of mappers equal to the number of input files you want to process.
Correct Answer: A 🗳️
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Which of the following statements most accurately describes the relationship between MapReduce and Pig?
- A. Pig programs rely on MapReduce but are extensible, allowing developers to do special-purpose processing not provided by MapReduce.
- B. Pig provides additional capabilities that allow certain types of data manipulation not possible with MapReduce.
- C. Pig provides no additional capabilities to MapReduce. Pig programs are executed as MapReduce jobs via the Pig interpreter.
- D. Pig provides the additional capability of allowing you to control the flow of multiple MapReduce jobs.
Correct Answer: D 🗳️
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Which of the following utilities allows you to create and run MapReduce jobs with any executable or script as the mapper and/or the reducer?
- A. Hadoop Streaming
- B. Oozie
- C. Flume
- D. Sqoop
Correct Answer: A 🗳️
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If you run the word count MapReduce program with m mappers and r reducers, how many output files will you get at the end of the job? And how many key-value pairs will there be in each file? Assume k is the number of unique words in the input files.
- A. There will be r files, each with exactly k/r key-value pairs.
- B. There will be m files, each with exactly k/m key value pairs.
- C. There will be m files, each with approximately k/m key-value pairs.
- D. There will be r files, each with approximately k/m key-value pairs.
- E. There will be r files, each with approximately k/r key-value pairs.
Correct Answer: A 🗳️
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