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Hortonworks Apache-Hadoop-Developer Questions & Answers - in .pdf

Apache-Hadoop-Developer pdf
  • Total Q&A: 110
  • Update: Jun 03, 2026
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  • Vendor: Hortonworks
  • Exam Code: Apache-Hadoop-Developer
  • Exam Name: Hadoop 2.0 Certification exam for Pig and Hive Developer
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Hortonworks Apache-Hadoop-Developer Q&A - Testing Engine

Apache-Hadoop-Developer Study Guide
  • Total Q&A: 110
  • Update: Jun 03, 2026
  • Price: $49.99
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  • Vendor: Hortonworks
  • Exam Code: Apache-Hadoop-Developer
  • Exam Name: Hadoop 2.0 Certification exam for Pig and Hive Developer
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Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer Sample Questions:

1. Table metadata in Hive is:

A) Stored in ZooKeeper.
B) Stored in the Metastore.
C) Stored as metadata on the NameNode.
D) Stored along with the data in HDFS.


2. Can you use MapReduce to perform a relational join on two large tables sharing a key? Assume that the two tables are formatted as comma-separated files in HDFS.

A) No, but it can be done with either Pig or Hive.
B) Yes, so long as both tables fit into memory.
C) Yes.
D) No, MapReduce cannot perform relational operations.
E) Yes, but only if one of the tables fits into memory


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

A) 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.
B) 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.
C) 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.
D) The default partitioner assigns key-values pairs to reduces based on an internal random number generator.
E) 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.


4. MapReduce v2 (MRv2/YARN) is designed to address which two issues?

A) Standardize on a single MapReduce API.
B) Reduce complexity of the MapReduce APIs.
C) HDFS latency.
D) Single point of failure in the NameNode.
E) Ability to run frameworks other than MapReduce, such as MPI.
F) Resource pressure on the JobTracker.


5. You need to perform statistical analysis in your MapReduce job and would like to call methods in the Apache Commons Math library, which is distributed as a 1.3 megabyte Java archive (JAR) file. Which is the best way to make this library available to your MapReducer job at runtime?

A) When submitting the job on the command line, specify the -libjars option followed by the JAR file path.
B) Package your code and the Apache Commands Math library into a zip file named JobJar.zip
C) Have your system administrator place the JAR file on a Web server accessible to all cluster nodes and then set the HTTP_JAR_URL environment variable to its location.
D) Have your system administrator copy the JAR to all nodes in the cluster and set its location in the HADOOP_CLASSPATH environment variable before you submit your job.


Solutions:

Question # 1
Answer: B
Question # 2
Answer: C
Question # 3
Answer: B
Question # 4
Answer: D,F
Question # 5
Answer: A

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