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Hortonworks HADOOP-PR000007  Exam Questions & Answers
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Hortonworks HADOOP-PR000007 Exam Questions & Answers


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  • Vendor: Hortonworks

    Exam Code: HADOOP-PR000007

    Exam Name: Hortonworks Certified Apache Hadoop 2.0 Developer (Pig and Hive Developer)

    Certification Provider: Hortonworks

    Total Questions: 108 Q&A ( View Details)

    Updated on: Jun 08, 2025

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Related Exams

  • HADOOP-PR000007 Hortonworks Certified Apache Hadoop 2.0 Developer (Pig and Hive Developer)

Related Certifications

  • HCAHD
  • Hortonworks Certific...

HADOOP-PR000007 Online Practice Questions and Answers

Questions 1

Which HDFS command copies an HDFS file named foo to the local filesystem as localFoo?

A. hadoop fs -get foo LocalFoo

B. hadoop -cp foo LocalFoo

C. hadoop fs -Is foo

D. hadoop fs -put foo LocalFoo

Show Answer

Correct Answer: A

Questions 2

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. There is no difference in output between the two settings.

B. 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.

C. 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.

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.

Show Answer

Correct Answer: D

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 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.

Questions 3

You wrote a map function that throws a runtime exception when it encounters a control character in input data. The input supplied to your mapper contains twelve such characters totals, spread across five file splits. The first four file splits each have two control characters and the last split has four control characters.

Indentify the number of failed task attempts you can expect when you run the job with mapred.max.map.attempts set to 4:

A. You will have forty-eight failed task attempts

B. You will have seventeen failed task attempts

C. You will have five failed task attempts

D. You will have twelve failed task attempts

E. You will have twenty failed task attempts

Show Answer More Questions

Correct Answer: E

Explanation: There will be four failed task attempts for each of the five file splits.

Note:

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