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Hortonworks HADOOP-PR000007 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Data Processing with Pig | - Pig Latin fundamentals
|
| Hadoop Ecosystem Integration | - MapReduce basics - HDFS interaction - Data ingestion and ETL workflows |
| Data Warehousing with Hive | - HiveQL fundamentals
|
Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer) Sample Questions:
1. Which HDFS command copies an HDFS file named foo to the local filesystem as localFoo?
A) hadoop fs -get foo LocalFoo
B) hadoop -cp foo LocalFoo
C) hadoop fs -Is foo
D) hadoop fs -put foo LocalFoo
2. 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) Runs on the same machine and shares the memory of the active NameNode.
C) Processes all client requests and block reports from the appropriate DataNodes.
D) Communicates directly with the active NameNode to maintain the state of the active NameNode.
3. You have just executed a MapReduce job. Where is intermediate data written to after being emitted from
the Mapper's map method?
A) Into in-memory buffers that spill over to the local file system of the TaskTracker node running the
Mapper.
B) Into in-memory buffers on the TaskTracker node running the Mapper that spill over and are written into
HDFS.
C) Into in-memory buffers that spill over to the local file system (outside HDFS) of the TaskTracker node
running the Reducer
D) Intermediate data in streamed across the network from Mapper to the Reduce and is never written to
disk.
E) Into in-memory buffers on the TaskTracker node running the Reducer that spill over and are written into
HDFS.
4. You want to Ingest log files Into HDFS, which tool would you use?
A) Sqoop
B) Flume
C) HCatalog
D) Ambari
5. The Hadoop framework provides a mechanism for coping with machine issues such as faulty
configuration or impending hardware failure. MapReduce detects that one or a number of machines are
performing poorly and starts more copies of a map or reduce task. All the tasks run simultaneously and
the task finish first are used. This is called:
A) Default Partitioner
B) IdentityReducer
C) Speculative Execution
D) Combine
E) IdentityMapper
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: A | Question # 3 Answer: A | Question # 4 Answer: B | Question # 5 Answer: C |
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