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Cloudera CCD-333 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: MapReduce Design and Development | 35% | - Mappers, reducers, combiners, partitioners - MapReduce workflow and execution - Job configuration and optimization - Input/output formats and data serialization |
| Topic 2: Best Practices and Optimization | 15% | - Debugging and error handling - Scalability and fault tolerance - Performance tuning |
| Topic 3: Hadoop Architecture and HDFS | 25% | - Data access, replication, and consistency - HDFS API usage - HDFS components and design |
| Topic 4: Hadoop Ecosystem Tools | 25% | - Apache Pig and data flow scripting - Apache Hive and data warehousing - Sqoop and Flume for data ingestion - Oozie workflow scheduling |
Cloudera Certified Developer for Apache Hadoop Sample Questions:
Question 1
You write a MapReduce job to process 100 files in HDFS. Your MapReduce algorithm uses TextInputFormat and the IdentityReducer: the mapper applies a regular expression over input values and emits key-value pairs with the key consisting of the matching text, and the value containing the filename and byte offset. Determine the difference between setting the number of reducers to zero.
A. With zero reducers, all instances of matching patterns are gathered together in one file on HDFS. With one reducer, instances of matching patterns stored in multiple files on HDFS.
B. With zero reducers, no reducer runs and the job throws an exception. With one reducer, instances of matching patterns are stored in a single file on HDFS.
C. There is no difference in output between the two settings.
D. With zero reducers, instances of matching patterns are stored in multiple files on HDFS. With one reducer, all instances of matching patterns are gathered together in one file on HDFS.
Question 2
Your cluster has 10 DataNodes, each with a single 1 TB hard drive. You utilize all your disk capacity for HDFS, reserving none for MapReduce. You implement default replication settings. What is the storage capacity of your Hadoop cluster (assuming no compression)?
A. about 11 TB
B. about 5 TB
C. about 3 TB
D. about 10 TB
Question 3
Which happens if the NameNode crashes?
A. HDFS becomes temporarily unavailable until an administrator starts redirecting client requests to the Secondary NameNode.
B. HDFS becomes unavailable until the NameNode is restored.
C. The Secondary NameNode seamlessly takes over and there is no service interruption.
D. HDFS becomes unavailable to new MapReduce jobs, but running jobs will continue until completion.
Question 4
Which of the following best describes the map method input and output?
A. It accepts a single key-value pair as input and emits a single key and list of corresponding values as output
B. It accepts a single key-value pair as input and can emit any number of key-value pairs as output, including zero.
C. It accepts a list of key-value pairs as input hut run emit only one key value pair as output.
D. It accepts a single key-value pair as input and can emit only one key-value pair as output.
Question 5
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. Five
B. Two
C. Four
D. Three
E. One
F. Six
Solutions:
| Question 1 Answer: D | Question 2 Answer: C | Question 3 Answer: B | Question 4 Answer: B | Question 5 Answer: F |





