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Cloudera CCD-333 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Hadoop Ecosystem and Architecture | - YARN Resource Management
|
| Topic 2: Data Ingestion and Integration | - Sqoop
|
| Topic 3: Data Processing with MapReduce | - MapReduce programming model
|
| Topic 4: Data Processing Tools | - Pig
|
| Topic 5: Workflow and Scheduling | - Oozie
|
| Topic 6: Data Formats and Storage | - Serialization formats
|
Cloudera Certified Developer for Apache Hadoop Sample Questions:
1. Which two of the following are valid statements? (Choose two)
A) HDFS is a distributed file system that replaces ext3 or ext4 on Linux nodes in a Hadoop cluster.
B) HDFS is optimized for storing a large number of files smaller than the HDFS block size.
C) 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.
D) HDFS has the Characteristic of supporting a "write once, read many" data access model.
2. You are running a job that will process a single InputSplit on a cluster which has no other jobs currently running. Each node has an equal number of open Map slots. On which node will Hadoop first attempt to run the Map task?
A) The node with the most free local disk space
B) The node with the most memory
C) The node on which this InputSplit is stored
D) The node with the lowest system load
3. Combiners Increase the efficiency of a MapReduce program because:
A) They aggregate intermediate map output horn a small number of nearby (i.e., rack-local) machines and therefore reduce the amount of data that needs to be shuffled across the network to the reducers.
B) They aggregate intermediate map output locally on each individual machine and therefore reduce the amount of data that needs to be shuffled across the network to the reducers.
C) They provide an optimization and reduce the total number of computations that are needed to execute an algorithm by a factor of n, where is the number of reducer.
D) They provide a mechanism for different mappers to communicate with each Other, thereby reducing synchronization overhead.
4. When is the reduce method first called in a MapReduce job?
A) Reducers start copying intermediate key value pairs from each Mapper as soon as it has completed. The reduce method is called as soon as the intermediate key-value pairs start to arrive.
B) Reducers start copying intermediate key-value pairs from each Mapper as soon as it has completed. The programmer can configure in the job what percentage of the intermediate data should arrive before the reduce method begins.
C) Reducers start copying intermediate key-value pairs from each Mapper as soon as it has completed. The reduce method is called only after all intermediate data has been copied and sorted.
D) Reduce methods and map methods all start at the beginning of a job, in order to provide optimal performance for map-only or reduce-only jobs.
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) Three
B) Five
C) Six
D) Four
E) One
F) Two
Solutions:
| Question # 1 Answer: C,D | Question # 2 Answer: C | Question # 3 Answer: B | Question # 4 Answer: C | Question # 5 Answer: C |




