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Cloudera CCD-333 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Hadoop Architecture and HDFS | 25% | - HDFS API usage - HDFS components and design - Data access, replication, and consistency |
| Best Practices and Optimization | 15% | - Debugging and error handling - Scalability and fault tolerance - Performance tuning |
| Hadoop Ecosystem Tools | 25% | - Apache Pig and data flow scripting - Oozie workflow scheduling - Sqoop and Flume for data ingestion - Apache Hive and data warehousing |
| MapReduce Design and Development | 35% | - Input/output formats and data serialization - Job configuration and optimization - MapReduce workflow and execution - Mappers, reducers, combiners, partitioners |
Cloudera Certified Developer for Apache Hadoop Sample Questions:
1. MapReduce is well-suited for all of the following applications EXCEPT? (Choose one):
A) Online transaction processing (OLTP) for an e-commerce Website.
B) Analysis of large amounts of Web logs (queries, clicks, etc.).
C) Graph mining on a large social network (e.g., Facebook friends network).
D) Text mining on a large collections of unstructured documents.
2. Which happens if the NameNode crashes?
A) HDFS becomes unavailable until the NameNode is restored.
B) HDFS becomes temporarily unavailable until an administrator starts redirecting client requests to the Secondary NameNode.
C) HDFS becomes unavailable to new MapReduce jobs, but running jobs will continue until completion.
D) The Secondary NameNode seamlessly takes over and there is no service interruption.
3. The Hadoop framework provides a mechanism for coping with machine issues such as faulty configuration or impending hardware failure. MapReduce detects that one or a number of machines are performing poorly and starts more copies of a map or reduce task. All the tasks run simultaneously and the task that finish first are used. This is called:
A) IdentityMapper
B) Default Partitioner
C) Speculative Execution
D) Combiner
E) IdentityReducer
4. During the standard sort and shuffle phase of MapReduce, keys and values are passed to reducers. Which of the following is true?
A) Keys are presented to a reducer in random order; values for a given key are sorted in ascending order.
B) Keys are presented to a reducer in sorted order; values for a given key are not sorted.
C) Keys are presented to a reducer in soiled order; values for a given key are sorted in ascending order.
D) Keys are presented to a reducer in random order; values for a given key are not sorted.
5. Which MapReduce daemon runs on each slave node and participates in job execution?
A) Secondary NameNode
B) NameNode
C) TaskTracker
D) JobTracker
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: A | Question # 3 Answer: C | Question # 4 Answer: A | Question # 5 Answer: C |


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