Learn how to Analyse Hadoop Data using Apache Pig

A Comprehensive Course on Apache Pig for Everyone! Learn How to Analyse Big Data Stored in Hadoop using Pig Tool.
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  • Lectures 60
  • Length 14 hours
  • Skill Level All Levels
  • Languages English
  • Includes Lifetime access
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    Available on iOS and Android
    Certificate of Completion
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About This Course

Published 12/2015 English

Course Description

In this Apache Pig course, you will learn about Pig platform and how to use it to process a large volume of data sets in a parallel way. This includes an overview of Big Data and Hadoop, what data looks like before, during and after a dataflow, what data is supported, and the different forms it can take; how Pig can transform data, and advanced topics on debugging flows, flow optimization and some enterprise-level features of Apache Pig. This course on Apache Pig shows how Pig platform provides an abstraction over the MapReduce model to make the programming easier.

What are the requirements?

  • Prior experience with SQL is not required
  • Familiarity with Basic Linux commands
  • We are assuming, you should have basic knowledge of Java will be helpful but is not essential
  • Basic Hadoop knowledge is helpful but not required. If you don’t have, we will be providing links, blogs, installation files and tutorial videos in the LMS

What am I going to get from this course?

  • 1. The fundamentals concepts of Big Data and Hadoop
  • 2. What is Apache PIG and its Use Cases
  • 3. How to set up PIG in Local and MapReduce mode
  • 4. What is PIG Latin Language
  • 5. Working and implementation of PIG Latin Statements
  • 6. How to create a directory and different ways of inserting the Data
  • 7. PIG Latin operators and the supported data types
  • 8. Concepts of PIG Streaming
  • 9. How to write and execute PIG Scripts
  • 10.Built-in Functions and User Defined Functions
  • 11.The structuring of PIG scripts and how they are executed
  • 12.How to write PIG Macros and perform Parameter substitution
  • 13.The use of PIG's Shell and Utility Commands to run your programs
  • 14.How to compress files(input/output/intermediate results)
  • 15.Testing and Diagnostics tools to examine and/or debug your programs

What is the target audience?

  • Database Administrators
  • Data Scientists
  • Software developers who need to understand and develop applications for Hadoop
  • Students should have some structured programming experience
  • Lastly the passionate learners who wants to learn Apache Pig

What you get with this course?

Not for you? No problem.
30 day money back guarantee.

Forever yours.
Lifetime access.

Learn on the go.
Desktop, iOS and Android.

Get rewarded.
Certificate of completion.

Curriculum

Section 1: Module-0: Introduction to Course
0.1 Introduction
Preview
03:44
0.2 Prerequisites for Apache PIG
Preview
01:12
0.3 Use Cases of Apache PIG
Preview
04:54
Section 2: Module-1: Getting started with Apache PIG
1.1 What is Big Data
Preview
03:14
1.2 Apache Hadoop
03:10
1.3 HDFS in Hadoop
10:23
1.4 Hadoop MapReduce
Preview
05:34
1.5 What is Apache PIG?
Preview
02:44
1.6 PIG vs. MapReduce
02:24
1.7 Where to use PIG, where not!!
Preview
04:24
1.8 PIG’s History
01:37
Section 3: Module-2: Pig Latin language and its statement
2.1 PIG Latin Language
04:42
2.2 Running PIG in Different Modes
04:21
2.3 PIG Architecture
01:06
2.4 PIG Latin Statements
15:11
Section 4: Module-3: PIG Model and Operators
3.1 PIG’s Data Model part-I
17:52
3.1 PIG’s Data Model part-II
10:41
3.2 Arithmetic and Boolean Operators
17:51
3.3 Cast and Comparison Operators part-I
16:42
3.3 Cast and Comparison Operators part-II
09:28
3.4 Relational Operators part-A
19:51
3.4 Relational Operators part-B (I)
18:35
3.4 Relational Operators part-B (II)
13:06
3.4 Relational Operators part-C (I)
19:04
3.4 Relational Operators part-C (II)
07:33
3.5 PIG Streaming
12:51
Section 5: Module-4: PIG's Built in Functions
4.1 Eval Functions part-A (I)
14:48
4.1 Eval Functions part-A (II)
16:06
4.1 Eval Functions part-A (III)
09:52
4.1 Eval Functions part-B (I)
16:39
4.1 Eval Functions part-B (II)
11:53
4.2 Load and Store Functions part-I
18:29
4.2 Load and Store Functions part-II
07:43
4.3 Tuple and Bag Functions
06:41
Section 6: Module-5: PIG Scripts and UDF’s
5.1 Create and Run PIG Scripts
17:25
5.2 Writing JAVA UDF’s part-I
04:32
5.2 Writing JAVA UDF’s part-II
16:27
Section 7: Module-6: Control Structures
6.1 Embedded PIG in JAVA
13:10
6.2 PIG Macros part-I
12:55
6.2 PIG Macros part-II
12:16
6.3 Parameter Substitution
19:07
Section 8: Module-7: Shell and Utility Commands
7.1 Shell Commands
11:48
7.2 Utility Commands part-I
18:22
7.2 Utility Commands part-II
16:33
Section 9: Module-8: Compression with PIG
8.1 Compressed Files part-I
12:25
8.1 Compressed Files part-II
09:39
8.2 Compress the Results of Intermediate Jobs
08:54
Section 10: Module-9: Testing and Diagnostics
9.1 Diagnostic Operators
13:29
9.2 PIGUnit Testing part-I
11:39
9.2 PIGUnit Testing part-II
08:53
Section 11: Module-10: Quizzes
Quiz-1
4 pages
Quiz-2
4 pages
Quiz-3
5 pages
Quiz-4
4 pages
Quiz-5
4 pages
Quiz-6
4 pages
Quiz-7
4 pages
Quiz-8
5 pages
Quiz-9
4 pages
Section 12: Programs and Datasets
Programs and Datasets
Article

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