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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 need to perform statistical analysis in your MapReduce job and would like to call methods in the Apache Commons Math library, which is distributed as a 1.3 megabyte Java archive (JAR) file. Which is the best way to make this library available to your MapReducer job at runtime?

A) Package your code and the Apache Commands Math library into a zip file named JobJar.zip
B) Have your system administrator place the JAR file on a Web server accessible to all cluster nodes and then set the HTTP_JAR_URL environment variable to its location.
C) When submitting the job on the command line, specify the -libjars option followed by the JAR file path.
D) Have your system administrator copy the JAR to all nodes in the cluster and set its location in the HADOOP_CLASSPATH environment variable before you submit your job.

2. Which one of the following statements is true regarding a MapReduce job?

A) The job's Partitioner shuffles and sorts all (key.value) pairs and sends the output to all reducers
B) The reduce method is invoked once for each unique value
C) The default Hash Partitioner sends key value pairs with the same key to the same Reducer
D) The Mapper must sort its output of (key.value) pairs in descending order based on value

3. Which one of the following statements is true about a Hive-managed table?

A) When the table is dropped, the underlying folder in HDFS is deleted.
B) Records can only be added to the table using the Hive INSERT command.
C) Hive dynamically defines the schema of the table based on the format of the underlying data.
D) Hive dynamically defines the schema of the table based on the FROM clause of a SELECT query.

4. Which project gives you a distributed, Scalable, data store that allows you random, realtime read/write access to hundreds of terabytes of data?

A) Oozie
B) Hue
C) Pig
D) Flume
E) Hive
F) Sqoop
G) HBase

5. 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) No, MapReduce cannot perform relational operations.
C) Yes, but only if one of the tables fits into memory
D) No, but it can be done with either Pig or Hive.
E) Yes, so long as both tables fit into memory.

Solutions: