Cloudera CCD-333 Questions & Answers - in .pdf
- Total Q&A: 60
- Update: Jun 04, 2026
- Price: $59.99
- Vendor: Cloudera
- Exam Code: CCD-333
- Exam Name: Cloudera Certified Developer for Apache Hadoop
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Cloudera CCD-333 Q&A - Testing Engine
- Total Q&A: 60
- Update: Jun 04, 2026
- Price: $59.99
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- Exam Code: CCD-333
- Exam Name: Cloudera Certified Developer for Apache Hadoop
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.Cloudera Certified Developer for Apache Hadoop Sample Questions:
1. For each intermediate key, each reducer task can emit:
A) As many final key-value pairs as desired, as long as all the keys have the same type and all the values have the same type.
B) As many final key value pairs as desired. There are no restrictions on the types of those key-value pairs (i.e., they can be heterogeneous)
C) One final key-value pair per value associated with the key; no restrictions on the type.
D) One final key value pair per key; no restrictions on the type.
E) As many final key-value pairs as desired, but they must have the same type as the intermediate key-value pairs.
2. To process input key-value pairs, your mapper needs to load a 512 MB data file in memory. What is the best way to accomplish this?
A) Serialize the data file, insert it in the Jobconf object, and read the data into memory in the configure method of the mapper.
B) Place the data file in theDistributedCacheand read the data into memory in the map method of the mapper.
C) Place the data file in theDistributedCacheand read the data into memory in the configure method of the mapper.
D) Place the datafile in the DataCache and read the data into memory in the configure method ofthe mapper.
3. Which of the Following best describes the lifecycle of a Mapper?
A) The JobTracker spawns a new Mapper to process all records in a single file.
B) The TaskTracker spawns a new Mapper to process each key-value pair.
C) The JobTracker calls the FastTracker's configure () method, then its map () method and finally its closer ()
D) The TaskTracker spawns a new Mapper to process all records in a single input split.
4. Does the MapReduce programming model provide a way for reducers to communicate with each other?
A) No, each reducer runs independently and in isolation.
B) Yes, all reducers can communicate with each other by passing information through the jobconf object.
C) Yes, reducers can communicate with each other by dispatching intermediate key value pairs that get shuffled to another reduce
D) Yes, reducers running on the same machine can communicate with each other through shared memory, but not reducers on different machines.
5. MapReduce is well-suited for all of the following applications EXCEPT? (Choose one):
A) Text mining on a large collections of unstructured documents.
B) Online transaction processing (OLTP) for an e-commerce Website.
C) Analysis of large amounts of Web logs (queries, clicks, etc.).
D) Graph mining on a large social network (e.g., Facebook friends network).
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: B | Question # 3 Answer: B | Question # 4 Answer: A | Question # 5 Answer: B |
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