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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. Which two of the following statements are true about Pig's approach toward data? Choose 2 answers

A) Accepts any data: structured or unstructured
B) Accepts only data that has a key/value pair structure
C) Accepts tab-delimited text data only
D) Accepts data whether it has metadata or not
E) Accepts only data that is defined by metadata tables stored in a database

2. A combiner reduces:

A) The number of output files a reducer must produce.
B) The number of values across different keys in the iterator supplied to a single reduce method call.
C) The number of input files a mapper must process.
D) The amount of intermediate data that must be transferred between the mapper and reducer.

3. Review the following 'data' file and Pig code.

Which one of the following statements is true?

A) The Output Of the DUMP D command IS (M,{(M,62.95102),(M,38,95111)})
B) The code does not execute successfully because D is not a valid relation
C) The output of the dump d command is (M, {(38,95in),(62,95i02)})
D) The code executes successfully but there is not output because the D relation is empty

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

5. Identify the tool best suited to import a portion of a relational database every day as files into HDFS, and generate Java classes to interact with that imported data?

A) Oozie
B) Sqoop
C) fuse-dfs
D) Pig
E) Flume
F) Hive
G) Hue

Solutions: