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

1. Your cluster's HDFS block size in 64MB. You have directory containing 100 plain text files, each of which is 100MB in size. The InputFormat for your job is TextInputFormat. Determine how many Mappers will run?

A) 100
B) 640
C) 200
D) 64

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

3. To process input key-value pairs, your mapper needs to lead a 512 MB data file in memory. What is the best way to accomplish this?

A) Serialize the data file, insert in it the JobConf object, and read the data into memory in the configure method of the mapper.
B) Place the data file in the DataCache and read the data into memory in the configure method of the mapper.
C) Place the data file in the DistributedCache and read the data into memory in the map method of the mapper.
D) Place the data file in the DistributedCache and read the data into memory in the configure method of the mapper.

4. You are developing a combiner that takes as input Text keys, IntWritable values, and emits Text keys, IntWritable values. Which interface should your class implement?

A) Reducer <Text, Text, IntWritable, IntWritable>
B) Mapper <Text, IntWritable, Text, IntWritable>
C) Combiner <Text, Text, IntWritable, IntWritable>
D) Combiner <Text, IntWritable, Text, IntWritable>
E) Reducer <Text, IntWritable, Text, IntWritable>

5. MapReduce v2 (MRv2/YARN) splits which major functions of the JobTracker into separate
daemons? Select two.

A) MapReduce metric reporting
B) Managing file system metadata
C) Launching tasks
D) Managing tasks
E) Job coordination between the ResourceManager and NodeManager
F) Resource management
G) Heath states checks (heartbeats)
H) Job scheduling/monitoring

Solutions: