Process Big Data using Apache PIG

Process Big Data using Apache PIG, available at $19.99, has an average rating of 2.9, with 49 lectures, based on 29 reviews, and has 182 subscribers.

You will learn about Overview of Big Data and Hadoop Framework Anatomy of a MapReduce Framework Basics of Apache Pig tool and Where we should use it or not Run Pig in different Modes Use Pig Latin Queries Different types of PIG Operators for analysing the data Understand the architecture of PIG tool Work with PIG data model Different kinds of built-in functions Advanced PIG concepts such as PIG Streaming, PIG scripts and User Defined Functions(UDFs) Compress the input files, final output files and intermediate output files Pig Unit Testing, PIG Macros and Parameter Substitution How to embed PIG in Java This course is ideal for individuals who are Students having interest in Big Data and Hadoop Field or Database Developers and Administrator or Software developers want to build their career in Big Data field or Data Analysts or Data Scientists and Resesarcher It is particularly useful for Students having interest in Big Data and Hadoop Field or Database Developers and Administrator or Software developers want to build their career in Big Data field or Data Analysts or Data Scientists and Resesarcher.

Enroll now: Process Big Data using Apache PIG

Summary

Title: Process Big Data using Apache PIG

Price: $19.99

Average Rating: 2.9

Number of Lectures: 49

Number of Published Lectures: 49

Number of Curriculum Items: 49

Number of Published Curriculum Objects: 49

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Overview of Big Data and Hadoop Framework
Anatomy of a MapReduce Framework
Basics of Apache Pig tool and Where we should use it or not
Run Pig in different Modes
Use Pig Latin Queries
Different types of PIG Operators for analysing the data
Understand the architecture of PIG tool
Work with PIG data model
Different kinds of built-in functions
Advanced PIG concepts such as PIG Streaming, PIG scripts and User Defined Functions(UDFs)
Compress the input files, final output files and intermediate output files
Pig Unit Testing, PIG Macros and Parameter Substitution
How to embed PIG in Java

Who Should Attend

Students having interest in Big Data and Hadoop Field
Database Developers and Administrator
Software developers want to build their career in Big Data field
Data Analysts
Data Scientists and Resesarcher

Target Audiences

Students having interest in Big Data and Hadoop Field
Database Developers and Administrator
Software developers want to build their career in Big Data field
Data Analysts
Data Scientists and Resesarcher

Pig is a high-level platform for creating MapReduce programs used with Hadoop. The language for this platform is called Pig Latin. In this course we will go through the PIG data flow platform and the language used by PIG tool. The concepts which are covered in this course are:

Writing complex MapReduce transformations using a simple scripting language.

Basics of Big Data, Hadoop and MapReduce Framework.

PIG Data Model and Different type of operators to operate on datasets.

Built-in Functions as well as User Defined Functions for performing a specific task.

Running PIG Script, Unit Testing and Compression.

Many more advance topics such as Embedding PIG in Java, PIG Macros etc.

All the books and PDFs are included, allowing you to follow along with the author throughout the modules in this course.

Course Curriculum

Chapter 1: Module-0 Introduction to the Course

Lecture 1: 0.1 Introduction to Apache PIG

Lecture 2: 0.2 Prerequisites for Apache PIG

Lecture 3: 0.3 Exploring Use Cases of PIG

Lecture 4: 0.4 History of Apache PIG

Chapter 2: Module-1 Basics of Big Data, Hadoop and Pig

Lecture 1: 1.1 Big Data Overview

Lecture 2: 1.2 Apache Hadoop Framework

Lecture 3: 1.3 Hadoop Distributed File System

Lecture 4: 1.4 Hadoop MapReduce

Lecture 5: 1.5 Introduction to Apache Pig

Lecture 6: 1.6 Importance of Apache PIG

Lecture 7: 1.7 Why PIG Over MapReduce

Lecture 8: 1.8 Where PIG is Best Suited

Lecture 9: 1.9 Where to Avoid PIG

Chapter 3: Module-2 PIG Latin Language, Architecture and Modes of Pig

Lecture 1: 2.1 PIG Latin Language

Lecture 2: 2.2 Running PIG in Different Modes

Lecture 3: 2.3 PIG Architecture

Lecture 4: 2.4 GRUNT Shell

Lecture 5: 2.5 PIG Latin Statements

Chapter 4: Module-3 Data Model, Operators and Streaming in PIG

Lecture 1: 3.1 PIG Data Model- Scalar Datatype

Lecture 2: 3.2 PIG Data Model – Complex DataType

Lecture 3: 3.3 Arithmetic Operators

Lecture 4: 3.4 Comparison Operators

Lecture 5: 3.5 Cast Operators

Lecture 6: 3.6 Type Construction Operator

Lecture 7: 3.7 Relational Operators

Lecture 8: 3.8 Loading and Storing Operators

Lecture 9: 3.9 Filtering Operators

Lecture 10: 3.10 Filtering Operators-Pig Streaming with Python

Lecture 11: 3.11 Grouping and Joining Operators- PART-1

Lecture 12: 3.12 Grouping and Joining Operators- PART-2

Lecture 13: 3.13 Sorting Operator

Lecture 14: 3.14 Combining and Splitting Operators

Lecture 15: 3.15 Diagnostic Operators

Chapter 5: Module-4 Different Kinds of Built-In Functions in PIG

Lecture 1: 4.1 Eval Functions PART-1

Lecture 2: 4.2 Eval Functions PART-2

Lecture 3: 4.3 Eval Functions PART-3

Lecture 4: 4.4 Load and Store Functions

Lecture 5: 4.5 Tuple and Bag Functions

Lecture 6: 4.6 String Functions

Lecture 7: 4.7 Math Function

Chapter 6: Module-5 Advanced Pig Latin with Pig Scripts,UDF's,Utility Commands

Lecture 1: 5.1 Running Pig Scripts

Lecture 2: 5.3 Utility Commands

Chapter 7: Module-6 File Compression

Lecture 1: 6.1 File Compression in pig

Lecture 2: 6.2 Intermediate Compression

Lecture 3: 6.3 Pig Unit Testing

Chapter 8: Module-7 Advanced Pig Latin

Lecture 1: 7.1 Embedded Pig in JAVA

Lecture 2: 7.2 Pig Macros

Lecture 3: 7.3 Import Macros

Lecture 4: 7.4 Parameter Substitution

Instructors

Insculpt Technologies
Engraving Intelligence

Rating Distribution

1 stars: 3 votes
2 stars: 3 votes
3 stars: 5 votes
4 stars: 9 votes
5 stars: 9 votes

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