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Exam Number : Hadoop-PR000007
Exam Name : Hortonworks Certified Apache Hadoop 2.0 Developer (Pig and Hive Developer)
Vendor Name : Hortonworks
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Hadoop-PR000007 Exam Format | Hadoop-PR000007 Course Contents | Hadoop-PR000007 Course Outline | Hadoop-PR000007 Exam Syllabus | Hadoop-PR000007 Exam Objectives


Exam Details for Hadoop-PR000007 Hortonworks Certified Apache Hadoop 2.0 Developer (Pig and Hive Developer):

Number of Questions: The Hadoop-PR000007 exam typically consists of 50-60 multiple-choice questions.

Time Limit: The exam has a time limit of 2 hours (120 minutes).

Course Outline:
The Hadoop-PR000007 certification exam focuses on assessing the knowledge and skills required to develop and work with Apache Hadoop 2.0, specifically focusing on Pig and Hive for data processing and analytics. The course outline covers the following key topics:

1. Introduction to Apache Hadoop:
- Overview of Hadoop ecosystem and its components
- Hadoop architecture and distributed file system (HDFS)
- MapReduce and YARN frameworks
- Hadoop cluster setup and configuration

2. Apache Pig:
- Introduction to Pig and Pig Latin scripting language
- Loading and storing data using Pig
- Transforming and manipulating data using Pig Latin operations
- User-defined functions (UDFs) in Pig
- Pig optimization techniques and performance tuning

3. Apache Hive:
- Introduction to Hive and HiveQL query language
- Creating and managing tables in Hive
- Data manipulation and querying with HiveQL
- Partitioning and bucketing in Hive
- Hive optimization techniques and performance tuning

4. Data Processing with Pig and Hive:
- Integrating Pig and Hive with Hadoop ecosystem components
- Using Pig and Hive for data transformations and analytics
- Joining and aggregating data in Pig and Hive
- Handling complex data types and nested structures
- Debugging and troubleshooting Pig and Hive scripts

Exam Objectives:
The Hadoop-PR000007 exam aims to assess the following objectives:

1. Understanding of Apache Hadoop architecture and its key components.
2. Proficiency in using Pig for data loading, transformation, and analysis.
3. Knowledge of Hive and its capabilities for data querying and management.
4. Competence in integrating Pig and Hive with other Hadoop ecosystem components.
5. Familiarity with performance optimization and debugging techniques in Pig and Hive.

Exam Syllabus:
The Hadoop-PR000007 exam covers the following syllabus:

1. Introduction to Apache Hadoop
- Overview of Hadoop ecosystem and its components
- Hadoop architecture and distributed file system (HDFS)
- MapReduce and YARN frameworks
- Hadoop cluster setup and configuration

2. Apache Pig
- Introduction to Pig and Pig Latin scripting language
- Loading and storing data using Pig
- Transforming and manipulating data using Pig Latin operations
- User-defined functions (UDFs) in Pig
- Pig optimization techniques and performance tuning

3. Apache Hive
- Introduction to Hive and HiveQL query language
- Creating and managing tables in Hive
- Data manipulation and querying with HiveQL
- Partitioning and bucketing in Hive
- Hive optimization techniques and performance tuning

4. Data Processing with Pig and Hive
- Integrating Pig and Hive with Hadoop ecosystem components
- Using Pig and Hive for data transformations and analytics
- Joining and aggregating data in Pig and Hive
- Handling complex data types and nested structures
- Debugging and troubleshooting Pig and Hive scripts



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