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Hortonworks Apache-Hadoop-Developer Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Apache Pig | - Pig execution model
|
| Topic 2: Hadoop Ecosystem Fundamentals | - HDFS Architecture and Data Storage Concepts
|
| Topic 3: Apache Hive | - Hive architecture
|
| Topic 4: Data Processing and Integration | - Hadoop data formats
|
Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer Sample Questions:
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. Place the data file in the DataCache and read the data into memory in the configure method of the mapper.
- B. Serialize the data file, insert in it the JobConf object, 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.
Correct Answer: A 🗳️
For each intermediate key, each reducer task can emit:
- A. One final key-value pair per value associated with the key; no restrictions on the type.
- B. As many final key-value pairs as desired. There are no restrictions on the types of those key-value pairs (i.e., they can be heterogeneous).
- C. One final key-value pair per key; no restrictions on the type.
- D. As many final key-value pairs as desired, but they must have the same type as the intermediate key-value pairs.
- E. As many final key-value pairs as desired, as long as all the keys have the same type and all the values have the same type.
Correct Answer: E 🗳️
Explanation: Only visible for PassReview members. You can sign-up / login (it's free).
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 arbitrary ordered, but multiple runs of the same MapReduce job will always have the same ordering.
- B. The values are in sorted order.
- C. The values are arbitrarily ordered, and the ordering may vary from run to run of the same MapReduce job.
- D. Since the values come from mapper outputs, the reducers will receive contiguous sections of sorted values.
Correct Answer: C 🗳️
Explanation: Only visible for PassReview members. You can sign-up / login (it's free).
Consider the following two relations, A and B.
What is the output of the following Pig commands?
X = GROUP A BY S1; DUMP X;
- A. Option B
- B. Option D
- C. Option C
- D. Option A
Correct Answer: B 🗳️
You have user profile records in your OLPT database, that you want to join with web logs you have already ingested into the Hadoop file system. How will you obtain these user records?
- A. Ingest with Hadoop Streaming
- B. Ingest with Flume agents
- C. Hive LOAD DATA command
- D. HDFS command
- E. Pig LOAD command
- F. Sqoop import
Correct Answer: F 🗳️
Explanation: Only visible for PassReview members. You can sign-up / login (it's free).
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