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Cloudera CCD-333 Exam Syllabus Topics:

Cloudera Certified Developer for Apache Hadoop Sample Questions:

Question 1

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. Place the data file in theDistributedCacheand read the data into memory in the map method of the mapper.
B. Serialize the data file, insert it in the Jobconf object, and read the data into memory in the configure 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.

Question 2

Custom programmer-defined counters in MapReduce are:

A. 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.
B. Lightweight devices for bookkeeping within MapReduce programs.
C. Lightweight devices for synchronization within MapReduce programs. You can use counters to coordinate execution between a mapper and a reducer.

Question 3

You write a MapReduce job to process 100 files in HDFS. Your MapReduce algorithm uses TextInputFormat and the IdentityReducer: the mapper applies a regular expression over input values and emits key-value pairs with the key consisting of the matching text, and the value containing the filename and byte offset. Determine the difference between setting the number of reducers to zero.

A. With zero reducers, no reducer runs and the job throws an exception. With one reducer, instances of matching patterns are stored in a single file on HDFS.
B. With zero reducers, all instances of matching patterns are gathered together in one file on HDFS. With one reducer, instances of matching patterns stored in multiple files on HDFS.
C. There is no difference in output between the two settings.
D. With zero reducers, instances of matching patterns are stored in multiple files on HDFS. With one reducer, all instances of matching patterns are gathered together in one file on HDFS.

Question 4

Given a Mapper, Reducer, and Driver class packaged into a jar, which is the correct way of submitting the job to the cluster?

A. hadoop jar class MyJar.jar MyDriverClass inputdir outputdir
B. hadoop jar MyJar.jar MyDriverClass inputdir outputdir
C. jar MyJar.jar MyDriverClass inputdir outputdir
D. jar MyJar.jar

Question 5

You've written a MapReduce job that will process 500 million input records and generate 500 million key-value pairs. The data is not uniformly distributed. Your MapReduce job will create a significant amount of intermediate data that it needs to transfer between mappers and reducers which is a potential bottleneck. A custom implementation of which of the following interfaces is most likely to reduce the amount of intermediate data transferred across the network?

A. Combiner
B. Partitioner
C. OutputFormat
D. InputFormat
E. Writable
F. WritableComparable

Solutions: