Hortonworks Apache-Hadoop-Developer : Hadoop 2.0 Certification exam for Pig and Hive Developer

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Hortonworks Apache-Hadoop-Developer Exam Syllabus Topics:

Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer Sample Questions:

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, 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.
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) 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.

2. Which TWO of the following statements are true regarding Hive? Choose 2 answers

A) Offers real-time queries and row level updates
B) Allows you to define a structure for your unstructured Big Data
C) Is a relational database
D) Useful for data analysts familiar with SQL who need to do ad-hoc queries

3. Workflows expressed in Oozie can contain:

A) Sequences of MapReduce job only; on Pig on Hive tasks or jobs. These MapReduce sequences can be combined with forks and path joins.
B) Sequences of MapReduce and Pig. These sequences can be combined with other actions including forks, decision points, and path joins.
C) Sequences of MapReduce and Pig jobs. These are limited to linear sequences of actions with exception handlers but no forks.
D) Iterntive repetition of MapReduce jobs until a desired answer or state is reached.

4. The Hadoop framework provides a mechanism for coping with machine issues such as faulty configuration or impending hardware failure. MapReduce detects that one or a number of machines are performing poorly and starts more copies of a map or reduce task. All the tasks run simultaneously and the task finish first are used. This is called:

A) Speculative Execution
B) IdentityReducer
C) Default Partitioner
D) Combine
E) IdentityMapper

5. Assuming default settings, which best describes the order of data provided to a reducer's reduce method:

A) Neither keys nor values are in any predictable order.
B) The keys given to a reducer aren't in a predictable order, but the values associated with those keys always are.
C) The keys given to a reducer are in sorted order but the values associated with each key are in no predictable order
D) Both the keys and values passed to a reducer always appear in sorted order.

Solutions: