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Hortonworks HADOOP-PR000007 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Data Processing with Pig | - Pig Latin fundamentals
|
| Hadoop Ecosystem Integration | - Data ingestion and ETL workflows - HDFS interaction - MapReduce basics |
| Data Warehousing with Hive | - HiveQL fundamentals
|
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) JournalNode
B) ZKFailoverController
C) QuorumManager
D) ZooKeeper
2. You write MapReduce job to process 100 files in HDFS. Your MapReduce algorithm uses
TextInputFormat: the mapper applies a regular expression over input values and emits key-values pairs
with the key consisting of the matching text, and the value containing the filename and byte offset.
Determine the difference between setting the number of reduces to one and settings the number of
reducers to zero.
A) With zero reducers, all instances of matching patterns are gathered together in one file on HDFS. With
one reducer, instances of matching patterns are stored in multiple files on HDFS.
B) With zero reducers, instances of matching patterns are stored in multiple files on HDFS. With one
reducer, all instances of matching patterns are gathered together in one file on HDFS.
C) There is no difference in output between the two settings.
D) With zero reducers, no reducer runs and the job throws an exception. With one reducer, instances of
matching patterns are stored in a single file on HDFS.
3. Which two of the following statements are true about Pig's approach toward data? Choose 2 answers
A) Accepts only data that has a key/value pair structure
B) Accepts only data that is defined by metadata tables stored in a database
C) Accepts data whether it has metadata or not
D) Accepts tab-delimited text data only
E) Accepts any data: structured or unstructured
4. Which describes how a client reads a file from HDFS?
A) The client queries all DataNodes in parallel. The DataNode that contains the requested data responds
directly to the client. The client reads the data directly off the DataNode.
B) The client contacts the NameNode for the block location(s). The NameNode contacts the DataNode
that holds the requested data block. Data is transferred from the DataNode to the NameNode, and then
from the NameNode to the client.
C) The client contacts the NameNode for the block location(s). The NameNode then queries the
DataNodes for block locations. The DataNodes respond to the NameNode, and the NameNode redirects
the client to the DataNode that holds the requested data block(s). The client then reads the data directly
off the DataNode.
D) The client queries the NameNode for the block location(s). The NameNode returns the block location(s)
to the client. The client reads the data directory off the DataNode(s).
5. For each input key-value pair, mappers can emit:
A) One intermediate key-value pair, of a different type.
B) As many intermediate key-value pairs as designed, but they cannot be of the same type as the input
key-value pair.
C) One intermediate key-value pair, but of the same type.
D) As many intermediate key-value pairs as designed. There are no restrictions on the types of those
key-value pairs (i.e., they can be heterogeneous).
E) As many intermediate key-value pairs as designed, as long as all the keys have the same types and all
the values have the same type.
Solutions:
| Question # 1 Answer: A,B | Question # 2 Answer: B | Question # 3 Answer: C,E | Question # 4 Answer: D | Question # 5 Answer: E |
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