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Hortonworks HADOOP-PR000007 Exam Syllabus Topics:

Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer) Sample Questions:

1. 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.

2. Which one of the following Hive commands uses an HCatalog table named x?

A) SELECT * FROM org.apache.hcatalog.hive.HCatLoader('x');
B) SELECT x.-FROM org.apache.hcatalog.hive.HCatLoader('x');
C) SELECT * FROM x;
D) Hive commands cannot reference an HCatalog table

3. For each intermediate key, each reducer task can emit:

A) One final key-value pair per value associated with the key; no restrictions on the type.
B) As many final key-value pairs as desired. There are no restrictions on the types of those key-value
pairs (i.e., they can be heterogeneous).
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) As many final key-value pairs as desired, but they must have the same type as the intermediate
key-value pairs.
E) One final key-value pair per key; no restrictions on the type.

4. Which one of the following statements is FALSE regarding the communication between DataNodes and a
federation of NameNodes in Hadoop 2.0?

A) DataNodes send periodic heartbeats to all the NameNodes.
B) DataNodes send periodic block reports to all the NameNodes.
C) Each DataNode receives commands from one designated master NameNode.
D) Each DataNode registers with all the NameNodes.

5. You have just executed a MapReduce job. Where is intermediate data written to after being emitted from
the Mapper's map method?

A) Into in-memory buffers that spill over to the local file system of the TaskTracker node running the
Mapper.
B) Into in-memory buffers that spill over to the local file system (outside HDFS) of the TaskTracker node
running the Reducer
C) Into in-memory buffers on the TaskTracker node running the Reducer that spill over and are written into
HDFS.
D) Intermediate data in streamed across the network from Mapper to the Reduce and is never written to
disk.
E) Into in-memory buffers on the TaskTracker node running the Mapper that spill over and are written into
HDFS.

Solutions: