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Exam Code: CCD-410
Exam Name: Cloudera (Cloudera Certified Developer for Apache Hadoop (CCDH))
One year free update, No help, Full refund!
Total Q&A: 60 Questions and Answers
Last Update: 2013-10-31

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NO.1 You need to move a file titled “weblogs” into HDFS. When you try to copy the file, you can’t.
You
know you have ample space on your DataNodes. Which action should you take to relieve this
situation and store more files in HDFS?
A. Increase the block size on all current files in HDFS.
B. Increase the block size on your remaining files.
C. Decrease the block size on your remaining files.
D. Increase the amount of memory for the NameNode.
E. Increase the number of disks (or size) for the NameNode.
F. Decrease the block size on all current files in HDFS.
Answer: C

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10. Indentify which best defines a SequenceFile?
A. A SequenceFile contains a binary encoding of an arbitrary number of homogeneous Writable
objects
B. A SequenceFile contains a binary encoding of an arbitrary number of heterogeneous Writable
objects
C. A SequenceFile contains a binary encoding of an arbitrary number of WritableComparable
objects, in sorted order.
D. A SequenceFile contains a binary encoding of an arbitrary number key-value pairs. Each key
must be the same type. Each value must be the same type.
Answer: D

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NO.2 For each intermediate key, each reducer task can emit:
A. As many final key-value pairs as desired. There are no restrictions on the types of those keyvalue
pairs (i.e., they can be heterogeneous).
B. As many final key-value pairs as desired, but they must have the same type as the intermediate
key-value pairs.
C. 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.
D. One final key-value pair per value associated with the key; no restrictions on the type.
E. One final key-value pair per key; no restrictions on the type.
Answer: E

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NO.3 In a large MapReduce job with m mappers and n reducers, how many distinct copy operations
will
there be in the sort/shuffle phase?
A. mXn (i.e., m multiplied by n)
B. n
C. m
D. m+n (i.e., m plus n)
E. E.mn(i.e., m to the power of n)
Answer: A

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NO.4 In a MapReduce job with 500 map tasks, how many map task attempts will there be?
A. It depends on the number of reduces in the job.
B. Between 500 and 1000.
C. At most 500.
D. At least 500.
E. Exactly 500.
Answer: D

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NO.5 Your cluster’s HDFS block size in 64MB. You have directory containing 100 plain text files, each
of
which is 100MB in size. The InputFormat for your job is TextInputFormat. Determine how many
Mappers will run?
A. 64
B. 100
C. 200
D. 640
Answer: C

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NO.6 When is the earliest point at which the reduce method of a given Reducer can be called?
A. As soon as at least one mapper has finished processing its input split.
B. As soon as a mapper has emitted at least one record.
C. Not until all mappers have finished processing all records.
D. It depends on the InputFormat used for the job.
Answer: C

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NO.7 Which process describes the lifecycle of a Mapper?
A. The JobTracker calls the TaskTracker’s configure () method, then its map () method and finally
its close () method.
B. The TaskTracker spawns a new Mapper to process all records in a single input split.
C. The TaskTracker spawns a new Mapper to process each key-value pair.
D. The JobTracker spawns a new Mapper to process all records in a single file.
Answer: C

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NO.8 Can you use MapReduce to perform a relational join on two large tables sharing a key?
Assume
that the two tables are formatted as comma-separated files in HDFS.
A. Yes.
B. Yes, but only if one of the tables fits into memory
C. Yes, so long as both tables fit into memory.
D. No, MapReduce cannot perform relational operations.
E. No, but it can be done with either Pig or Hive.
Answer: A

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NO.9 MapReduce v2 (MRv2 /YARN) splits which major functions of the JobTracker into separate
daemons? Select two.
A. Heath states checks (heartbeats)
B. Resource management
C. Job scheduling/monitoring
D. Job coordination between the ResourceManager and NodeManager
E. Launching tasks
F. Managing file system metadata
G. MapReduce metric reporting
H. Managing tasks
Answer: B,D

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