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Cloudera CCD-333 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Hadoop Fundamentals | - HDFS architecture and data storage concepts - MapReduce programming model |
| Data Ingestion and Workflow | - Flume data ingestion concepts - Sqoop data import/export |
| Data Processing with Hadoop Ecosystem | - Hive query language and data warehousing - Pig Latin scripting basics |
| Data Analysis and Optimization | - Query optimization in Hive - Performance tuning in MapReduce jobs |
| Hadoop Cluster Operations | - Cluster configuration and management basics - Resource management with YARN |
Cloudera Certified Developer for Apache Hadoop Sample Questions:
Custom programmer-defined counters in MapReduce are:
- A. Lightweight devices for synchronization within MapReduce programs. You can use counters to coordinate execution between a mapper and a reducer.
- B. Lightweight devices for bookkeeping within MapReduce programs.
- C. Lightweight devices for ensuring the correctness of a MapReduce program. Mappers Increment counters, and reducers decrement counters. If at the end of the program the counters read zero, then you are sure that the job completed correctly.
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Which two of the following are valid statements? (Choose two)
- A. HDFS is optimized for storing a large number of files smaller than the HDFS block size.
- B. HDFS is a distributed file system that replaces ext3 or ext4 on Linux nodes in a Hadoop cluster.
- C. HDFS has the Characteristic of supporting a "write once, read many" data access model.
- D. HDFS is a distributed file system that runs on top of native OS filesystems and is well suited to storage of very large data sets.
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Workflows expressed in Oozie can contain:
- A. Sequences of MapReduce and Pig jobs. These are limited to linear sequences of actions with exception handlers but no forks.
- B. Sequences of MapReduce and Pig. These sequences can be combined with other actions including forks, decision points, and path joins.
- C. Sequences of MapReduce jobs only; no Pig or Hive tasks or jobs. These MapReduce sequences can be combined with forks and path joins.
- D. Iterative repetition of MapReduce jobs until a desired answer or state is reached.
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Given a Mapper, Reducer, and Driver class packaged into a jar, which is the correct way of submitting the job to the cluster?
- A. jar MyJar.jar
- B. hadoop jar MyJar.jar MyDriverClass inputdir outputdir
- C. jar MyJar.jar MyDriverClass inputdir outputdir
- D. hadoop jar class MyJar.jar MyDriverClass inputdir outputdir
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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. One
- B. Two
- C. Five
- D. Six
- E. Four
- F. Three
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Mona 
Augus 
Clark 
Modesty 
Susanna 
Jennifer 
Harry 
Sigrid 
Cornelia 
Hugh 
Mandel 
Valerie 
Priscilla 
Joyce 
Adela 
Maxwell 
