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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:
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
Correct Answer: A 🗳️
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.
Correct Answer: A 🗳️
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.
Correct Answer: A 🗳️
You want to Ingest log files Into HDFS, which tool would you use?
- A. Sqoop
- B. Flume
- C. HCatalog
- D. Ambari
Correct Answer: B 🗳️
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
Correct Answer: C 🗳️
