Prepare with Cloudera : CCD-333 exam braindumps as your best preparation materials
Updated: Oct 18, 2026
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Cloudera CCD-333 Exam Overview:
| Certification Vendor: | Cloudera |
|---|---|
| Exam Name: | Cloudera Certified Developer for Apache Hadoop |
| Exam Number: | CCD-333 |
| Certificate Validity Period: | 2 years |
| Available Languages: | English |
| Real Exam Qty: | 50-60 |
| Exam Duration: | 90 minutes |
| Exam Format: | Multiple Choice, Scenario-based |
| Exam Price: | $295 USD |
| Related Certifications: | CCP-100 CCA-130 CCD-410 |
| Passing Score: | 70% |
| Recommended Training: | Cloudera Developer Training for Apache Hadoop |
| Exam Registration: | Cloudera Certification Portal |
| Sample Questions: | Cloudera CCD-333 Sample Questions |
| Exam Way: | Proctored online or at authorized testing centers; RETIRED since October 31, 2021 |
| Pre Condition: | Basic Java programming, Linux command line, and understanding of distributed systems |
| Official Syllabus URL: | https://www.cloudera.com/services-and-support/training/certification.html |
Cloudera CCD-333 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Hadoop Architecture and HDFS | 25% | - HDFS components and design - Data access, replication, and consistency - HDFS API usage |
| MapReduce Design and Development | 35% | - Job configuration and optimization - Input/output formats and data serialization - MapReduce workflow and execution - Mappers, reducers, combiners, partitioners |
| Best Practices and Optimization | 15% | - Debugging and error handling - Performance tuning - Scalability and fault tolerance |
| Hadoop Ecosystem Tools | 25% | - Apache Pig and data flow scripting - Sqoop and Flume for data ingestion - Apache Hive and data warehousing - Oozie workflow scheduling |
Cloudera Certified Developer for Apache Hadoop Sample Questions:
In the standard word count MapReduce algorithm, why might using a combiner reduce the overall Job running time?
- A. Because combiners perform local aggregation of word counts, thereby reducing the number of key-value pairs that need to be snuff let across the network to the reducers.
- B. Because combiners perform local aggregation of word counts, thereby allowing the mappers to process input data faster.
- C. Because combiners perform local aggregation of word counts, and then transfer that data to reducers without writing the intermediate data to disk.
- D. Because combiners perform local aggregation of word counts, thereby reducing the number of mappers that need to run.
Correct Answer: B 🗳️
Explanation: Only visible for BraindumpQuiz members. You can sign-up / login (it's free).
What is the standard configuration of slave nodes in a Hadoop cluster?
- A. Each slave node runs a JobTracker and a DataNode daemon.
- B. Each slave node runs a TaskTracker, but only a fraction of the slave nodes run DataNode daemons.
- C. Each slave node runs a TaskTracker and a DataNode daemon.
- D. Each slave node either runs a TaskTracker or a DataNode daemon, but not both.
- E. Each slave node runs a DataNode daemon, but only a fraction of the slave nodes run TaskTrackers.
Correct Answer: C 🗳️
Explanation: Only visible for BraindumpQuiz members. You can sign-up / login (it's free).
The NameNode uses RAM for the following purpose:
- A. To store the edits log that keeps track of changes in HDFS.
- B. To store the contents of files in HDFS.
- C. To manage distributed read and write locks on files in HDFS.
- D. To store filenames, list of blocks and other meta information.
Correct Answer: D 🗳️
Explanation: Only visible for BraindumpQuiz members. You can sign-up / login (it's free).
What types of algorithms are difficult to express MapReduce?
- A. Relational operations on large amounts of structured and semi structured data.
- B. Text analysis algorithms on large collections of unstructured text (e.g., Web crawls).
- C. Large-scale graph algorithms that require one-step link traversal.
- D. Algorithms that require applying the same mathematical function to large numbers of individual binary records.
- E. Algorithms that requite global, shared state.
Correct Answer: E 🗳️
Explanation: Only visible for BraindumpQuiz members. You can sign-up / login (it's free).
You have an employee who is a Date Analyst and is very comfortable with SQL. He would like to run ad-hoc analysis on data in your HDFS duster. Which of the following is a data warehousing software built on top of Apache Hadoop that defines a simple SQL-like query language well-suited for this kind of user?
- A. Hue
- B. Oozie
- C. Hadoop Streaming
- D. Pig
- E. Sqoop
- F. Hive
- G. Flume
Correct Answer: F 🗳️
Explanation: Only visible for BraindumpQuiz members. You can sign-up / login (it's free).
Viewing page 1 out of 12 pages.
Viewing questions 1-5 out of 60 questions.
Cloudera CCD-333 Exam Overview:
| Certification Vendor: | Cloudera |
|---|---|
| Exam Name: | Cloudera Certified Developer for Apache Hadoop |
| Exam Number: | CCD-333 |
| Certificate Validity Period: | 2 years |
| Available Languages: | English |
| Real Exam Qty: | 50-60 |
| Exam Duration: | 90 minutes |
| Exam Format: | Multiple Choice, Scenario-based |
| Exam Price: | $295 USD |
| Related Certifications: | CCP-100 CCA-130 CCD-410 |
| Passing Score: | 70% |
| Recommended Training: | Cloudera Developer Training for Apache Hadoop |
| Exam Registration: | Cloudera Certification Portal |
| Sample Questions: | Cloudera CCD-333 Sample Questions |
| Exam Way: | Proctored online or at authorized testing centers; RETIRED since October 31, 2021 |
| Pre Condition: | Basic Java programming, Linux command line, and understanding of distributed systems |
| Official Syllabus URL: | https://www.cloudera.com/services-and-support/training/certification.html |
Cloudera CCD-333 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Hadoop Architecture and HDFS | 25% | - HDFS components and design - Data access, replication, and consistency - HDFS API usage |
| MapReduce Design and Development | 35% | - Job configuration and optimization - Input/output formats and data serialization - MapReduce workflow and execution - Mappers, reducers, combiners, partitioners |
| Best Practices and Optimization | 15% | - Debugging and error handling - Performance tuning - Scalability and fault tolerance |
| Hadoop Ecosystem Tools | 25% | - Apache Pig and data flow scripting - Sqoop and Flume for data ingestion - Apache Hive and data warehousing - Oozie workflow scheduling |
Cloudera Certified Developer for Apache Hadoop Sample Questions:
In the standard word count MapReduce algorithm, why might using a combiner reduce the overall Job running time?
- A. Because combiners perform local aggregation of word counts, thereby reducing the number of key-value pairs that need to be snuff let across the network to the reducers.
- B. Because combiners perform local aggregation of word counts, thereby allowing the mappers to process input data faster.
- C. Because combiners perform local aggregation of word counts, and then transfer that data to reducers without writing the intermediate data to disk.
- D. Because combiners perform local aggregation of word counts, thereby reducing the number of mappers that need to run.
Correct Answer: B 🗳️
Explanation: Only visible for BraindumpQuiz members. You can sign-up / login (it's free).
What is the standard configuration of slave nodes in a Hadoop cluster?
- A. Each slave node runs a JobTracker and a DataNode daemon.
- B. Each slave node runs a TaskTracker, but only a fraction of the slave nodes run DataNode daemons.
- C. Each slave node runs a TaskTracker and a DataNode daemon.
- D. Each slave node either runs a TaskTracker or a DataNode daemon, but not both.
- E. Each slave node runs a DataNode daemon, but only a fraction of the slave nodes run TaskTrackers.
Correct Answer: C 🗳️
Explanation: Only visible for BraindumpQuiz members. You can sign-up / login (it's free).
The NameNode uses RAM for the following purpose:
- A. To store the edits log that keeps track of changes in HDFS.
- B. To store the contents of files in HDFS.
- C. To manage distributed read and write locks on files in HDFS.
- D. To store filenames, list of blocks and other meta information.
Correct Answer: D 🗳️
Explanation: Only visible for BraindumpQuiz members. You can sign-up / login (it's free).
What types of algorithms are difficult to express MapReduce?
- A. Relational operations on large amounts of structured and semi structured data.
- B. Text analysis algorithms on large collections of unstructured text (e.g., Web crawls).
- C. Large-scale graph algorithms that require one-step link traversal.
- D. Algorithms that require applying the same mathematical function to large numbers of individual binary records.
- E. Algorithms that requite global, shared state.
Correct Answer: E 🗳️
Explanation: Only visible for BraindumpQuiz members. You can sign-up / login (it's free).
You have an employee who is a Date Analyst and is very comfortable with SQL. He would like to run ad-hoc analysis on data in your HDFS duster. Which of the following is a data warehousing software built on top of Apache Hadoop that defines a simple SQL-like query language well-suited for this kind of user?
- A. Hue
- B. Oozie
- C. Hadoop Streaming
- D. Pig
- E. Sqoop
- F. Hive
- G. Flume
Correct Answer: F 🗳️
Explanation: Only visible for BraindumpQuiz members. You can sign-up / login (it's free).
Viewing page 1 out of 12 pages.
Viewing questions 1-5 out of 60 questions.
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