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Hortonworks HADOOP-PR000007 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Hadoop Fundamentals & HDFS | 20% | - Hadoop 2.0 architecture & YARN - HDFS file operations, permissions, and data management |
| Topic 2: Data Ingestion & Ecosystem Integration | 5% | - Workflow orchestration with Oozie - Sqoop and Flume usage basics |
| Topic 3: Apache Pig Development | 40% | - User-defined functions (UDFs) and optimization - Integration with HCatalog and Hive - Pig Latin syntax, data loading, and storage - Data transformation, filtering, grouping, and joining |
| Topic 4: Apache Hive Development | 35% | - HiveQL queries, joins, aggregations, and partitioning - Hive architecture, metastore, and table management - Data types, serialization, and file formats - Performance tuning and indexing |
Hortonworks-Certified-Apache-Hadoop-2.0-Developer(Pig and Hive Developer) Sample Questions:
1. When is the earliest point at which the reduce method of a given Reducer can be called?
A) As soon as a mapper has emitted at least one record.
B) Not until all mappers have finished processing all records.
C) As soon as at least one mapper has finished processing its input split.
D) It depends on the InputFormat used for the job.
2. A client application creates an HDFS file named foo.txt with a replication factor of 3. Identify which best
describes the file access rules in HDFS if the file has a single block that is stored on data nodes A, B and
C?
A) The file can be accessed if at least one of the data nodes storing the file is available.
B) The file will be marked as corrupted if data node B fails during the creation of the file.
C) Each data node locks the local file to prohibit concurrent readers and writers of the file.
D) Each data node stores a copy of the file in the local file system with the same name as the HDFS file.
3. What is the term for the process of moving map outputs to the reducers?
A) Partitioning
B) Shuffling and sorting
C) Combining
D) Reducing
4. To process input key-value pairs, your mapper needs to lead a 512 MB data file in memory. What is the
best way to accomplish this?
A) Serialize the data file, insert in it the JobConf object, and read the data into memory in the configure
method of the mapper.
B) Place the data file in the DistributedCache and read the data into memory in the map method of the
mapper.
C) Place the data file in the DataCache and read the data into memory in the configure method of the
mapper.
D) Place the data file in the DistributedCache and read the data into memory in the configure method of
the mapper.
5. You want to run Hadoop jobs on your development workstation for testing before you submit them to your
production cluster. Which mode of operation in Hadoop allows you to most closely simulate a production
cluster while using a single machine?
A) Run the DataNode, TaskTracker, NameNode and JobTracker daemons on a single machine.
B) Run all the nodes in your production cluster as virtual machines on your development workstation.
C) Run the hadoop command with the -jt local and the -fs file:///options.
D) Run simldooop, the Apache open-source software for simulating Hadoop clusters.
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: A | Question # 3 Answer: B | Question # 4 Answer: C | Question # 5 Answer: A |








