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Exam Code: HDPCDExam Name: Hortonworks Data Platform Certified Developer
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NO.1 You write MapReduce job to process 100 files in HDFS. Your MapReduce algorithm uses
TextInputFormat: the mapper applies a regular expression over input values and emits key-values
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 reduces to one and settings the
number of reducers to zero.
A. 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.
B. With zero reducers, all instances of matching patterns are gathered together in one file on HDFS.
With one reducer, instances of matching patterns are stored in multiple files on HDFS.
C. 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.
D. There is no difference in output between the two settings.
Answer: A
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Explanation:
* It is legal to set the number of reduce-tasks to zero if no reduction is desired.
In this case the outputs of the map-tasks go directly to the FileSystem, into the output path set by
setOutputPath(Path). The framework does not sort the map-outputs before writing them out to the
FileSystem.
* Often, you may want to process input data using a map function only. To do this, simply set
mapreduce.job.reduces to zero. The MapReduce framework will not create any reducer tasks.
Rather, the outputs of the mapper tasks will be the final output of the job.
Note:
Reduce
In this phase the reduce(WritableComparable, Iterator, OutputCollector, Reporter) method
is called for each <key, (list of values)> pair in the grouped inputs.
The output of the reduce task is typically written to the FileSystem via
OutputCollector.collect(WritableComparable, Writable).
Applications can use the Reporter to report progress, set application-level status messages
and update Counters, or just indicate that they are alive.
The output of the Reducer is not sorted.
NO.2 Which best describes how TextInputFormat processes input files and line breaks?
A. The input file is split exactly at the line breaks, so each RecordReader will read a series of complete
lines.
B. Input file splits may cross line breaks. A line that crosses file splits is read by the RecordReader of
the split that contains the beginning of the broken line.
C. Input file splits may cross line breaks. A line that crosses file splits is read by the RecordReader of
the split that contains the end of the broken line.
D. Input file splits may cross line breaks. A line that crosses file splits is read by the RecordReaders of
both splits containing the broken line.
E. Input file splits may cross line breaks. A line that crosses file splits is ignored.
Answer: B
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Reference: How Map and Reduce operations are actually carried out