Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer) Sample Questions:
1. In Hadoop 2.0, which TWO of the following processes work together to provide automatic failover of the
NameNode? Choose 2 answers
A) ZooKeeper
B) JournalNode
C) QuorumManager
D) ZKFailoverController
2. Determine which best describes when the reduce method is first called in a MapReduce job?
A) Reduce methods and map methods all start at the beginning of a job, in order to provide optimal
performance for map-only or reduce-only jobs.
B) Reducers start copying intermediate key-value pairs from each Mapper as soon as it has completed.
The reduce method is called as soon as the intermediate key-value pairs start to arrive.
C) Reducers start copying intermediate key-value pairs from each Mapper as soon as it has completed.
The reduce method is called only after all intermediate data has been copied and sorted.
D) Reducers start copying intermediate key-value pairs from each Mapper as soon as it has completed.
The programmer can configure in the job what percentage of the intermediate data should arrive before
the reduce method begins.
3. You need to move a file titled "weblogs" into HDFS. When you try to copy the file, you can't. You know you
have ample space on your DataNodes. Which action should you take to relieve this situation and store
more files in HDFS?
A) Decrease the block size on all current files in HDFS.
B) Decrease the block size on your remaining files.
C) Increase the amount of memory for the NameNode.
D) Increase the block size on all current files in HDFS.
E) Increase the block size on your remaining files.
F) Increase the number of disks (or size) for the NameNode.
4. In Hadoop 2.0, which one of the following statements is true about a standby NameNode?
The Standby NameNode:
A) Receives the same block reports as the active NameNode.
B) Processes all client requests and block reports from the appropriate DataNodes.
C) Communicates directly with the active NameNode to maintain the state of the active NameNode.
D) Runs on the same machine and shares the memory of the active NameNode.
5. You want to count the number of occurrences for each unique word in the supplied input data. You've
decided to implement this by having your mapper tokenize each word and emit a literal value 1, and then
have your reducer increment a counter for each literal 1 it receives. After successful implementing this, it
occurs to you that you could optimize this by specifying a combiner. Will you be able to reuse your
existing Reduces as your combiner in this case and why or why not?
A) Yes, because Java is a polymorphic object-oriented language and thus reducer code can be reused as
a combiner.
B) No, because the sum operation in the reducer is incompatible with the operation of a Combiner.
C) No, because the Combiner is incompatible with a mapper which doesn't use the same data type for
both the key and value.
D) Yes, because the sum operation is both associative and commutative and the input and output types to
the reduce method match.
E) No, because the Reducer and Combiner are separate interfaces.
Solutions:
| Question # 1 Answer: B,D | Question # 2 Answer: C | Question # 3 Answer: B | Question # 4 Answer: A | Question # 5 Answer: D |
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