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Hortonworks HADOOP-PR000007 Exam Syllabus Topics:
Section
Weight
Objectives
Hadoop Fundamentals & HDFS
20%
- Hadoop 2.0 architecture & YARN
- HDFS file operations, permissions, and data management
Apache Pig Development
40%
- Pig Latin syntax, data loading, and storage
- User-defined functions (UDFs) and optimization
- Data transformation, filtering, grouping, and joining
- Integration with HCatalog and Hive
Data Ingestion & Ecosystem Integration
5%
- Sqoop and Flume usage basics
- Workflow orchestration with Oozie
Apache Hive Development
35%
- Performance tuning and indexing
- Data types, serialization, and file formats
- Hive architecture, metastore, and table management
- HiveQL queries, joins, aggregations, and partitioning
Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer) Sample Questions:
Which of the following tool was designed to import data from a relational database into HDFS?
A. HCatalog
B. Flume
C. Ambari
D. Sqoop
Answer: D
MapReduce v2 (MRv2/YARN) splits which major functions of the JobTracker into separate daemons? Select two.
A. Managing file system metadata
B. Heath states checks (heartbeats)
C. Launching tasks
D. Resource management
E. Job coordination between the ResourceManager and NodeManager
F. MapReduce metric reporting
G. Job scheduling/monitoring
H. Managing tasks
Answer: D,G
Which one of the following statements describes the relationship between the ResourceManager and the ApplicationMaster?
A. The ApplicationMaster starts an instance of the ResourceManager within each Container
B. The ApplicationMaster requests resources from the ResourceManager
C. The ApplicationMaster starts a single instance of the ResourceManager
D. The ResourceManager monitors and restarts any failed Containers of the ApplicationMaster
Answer: B
Which one of the following Hive commands uses an HCatalog table named x?
A. SELECT * FROM x;
B. Hive commands cannot reference an HCatalog table
C. SELECT * FROM org.apache.hcatalog.hive.HCatLoader('x');
D. SELECT x.-FROM org.apache.hcatalog.hive.HCatLoader('x');
Answer: C
In a MapReduce job, the reducer receives all values associated with same key. Which statement best describes the ordering of these values?
A. Since the values come from mapper outputs, the reducers will receive contiguous sections of sorted values.
B. The values are in sorted order.
C. The values are arbitrary ordered, but multiple runs of the same MapReduce job will always have the same ordering.
D. The values are arbitrarily ordered, and the ordering may vary from run to run of the same MapReduce job.
Answer: D
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