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Hortonworks HADOOP-PR000007 Exam Syllabus Topics:

SectionWeightObjectives
Hadoop Fundamentals & HDFS20%- Hadoop 2.0 architecture & YARN
- HDFS file operations, permissions, and data management
Apache Pig Development40%- Data transformation, filtering, grouping, and joining
- Integration with HCatalog and Hive
- Pig Latin syntax, data loading, and storage
- User-defined functions (UDFs) and optimization
Data Ingestion & Ecosystem Integration5%- Workflow orchestration with Oozie
- Sqoop and Flume usage basics
Apache Hive Development35%- Performance tuning and indexing
- HiveQL queries, joins, aggregations, and partitioning
- Hive architecture, metastore, and table management
- Data types, serialization, and file formats

Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer) Sample Questions:

1. Which process describes the lifecycle of a Mapper?

A) The JobTracker calls the TaskTracker's configure () method, then its map () method and finally its close () method.
B) The TaskTracker spawns a new Mapper to process each key-value pair.
C) The JobTracker spawns a new Mapper to process all records in a single file.
D) The TaskTracker spawns a new Mapper to process all records in a single input split.


2. What are the TWO main components of the YARN ResourceManager process? Choose 2 answers

A) Scheduler
B) Job Tracker
C) Task Tracker
D) Applications Manager


3. In a large MapReduce job with m mappers and n reducers, how many distinct copy operations will there
be in the sort/shuffle phase?

A) m+n (i.e., m plus n)
B) mn (i.e., m to the power of n)
C) n
D) mXn (i.e., m multiplied by n)
E) m


4. Which one of the following statements is true about a Hive-managed table?

A) Records can only be added to the table using the Hive INSERT command.
B) When the table is dropped, the underlying folder in HDFS is deleted.
C) Hive dynamically defines the schema of the table based on the format of the underlying data.
D) Hive dynamically defines the schema of the table based on the FROM clause of a SELECT query.


5. What types of algorithms are difficult to express in MapReduce v1 (MRv1)?

A) Algorithms that require global, sharing states.
B) Large-scale graph algorithms that require one-step link traversal.
C) Algorithms that require applying the same mathematical function to large numbers of individual binary
records.
D) Text analysis algorithms on large collections of unstructured text (e.g, Web crawls).
E) Relational operations on large amounts of structured and semi-structured data.


Solutions:

Question # 1
Answer: D
Question # 2
Answer: A,D
Question # 3
Answer: D
Question # 4
Answer: B
Question # 5
Answer: A

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