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

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

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

2. Analyze each scenario below and indentify which best describes the behavior of the default partitioner?

A) The default partitioner implements a round-robin strategy, shuffling the key-value pairs to each reducer
in turn. This ensures an event partition of the key space.
B) The default partitioner assigns key-values pairs to reduces based on an internal random number
generator.
C) The default partitioner computes the hash of the key and divides that valule modulo the number of
reducers. The result determines the reducer assigned to process the key-value pair.
D) The default partitioner computes the hash of the key. Hash values between specific ranges are
associated with different buckets, and each bucket is assigned to a specific reducer.
E) The default partitioner computes the hash of the value and takes the mod of that value with the number
of reducers. The result determines the reducer assigned to process the key-value pair.

3. In a MapReduce job with 500 map tasks, how many map task attempts will there be?

A) Between 500 and 1000.
B) At least 500.
C) It depends on the number of reduces in the job.
D) At most 500.
E) Exactly 500.

4. In Hadoop 2.0, which TWO of the following processes work together to provide automatic failover of the
NameNode? Choose 2 answers

A) ZKFailoverController
B) JournalNode
C) ZooKeeper
D) QuorumManager

5. In a MapReduce job, the reducer receives all values associated with same key. Which statement best
describes the ordering of these values?

A) The values are arbitrarily ordered, and the ordering may vary from run to run of the same MapReduce
job.
B) The values are in sorted order.
C) Since the values come from mapper outputs, the reducers will receive contiguous sections of sorted
values.
D) The values are arbitrary ordered, but multiple runs of the same MapReduce job will always have the
same ordering.

Solutions: