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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.
3.0 (18 ratings)
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163 students enrolled
Last updated 1/2016
English
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Includes:
  • 9 hours on-demand video
  • 1 Article
  • 48 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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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.

Who 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
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What Will I Learn?
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
View Curriculum
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
Curriculum For This Course
Expand All 60 Lectures Collapse All 60 Lectures 13:58:00
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Module-1: Getting started with Apache PIG
8 Lectures 33:30

1.2 Apache Hadoop
03:10

1.3 HDFS in Hadoop
10:23



1.6 PIG vs. MapReduce
02:24


1.8 PIG’s History
01:37
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Module-2: Pig Latin language and its statement
4 Lectures 25:20
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
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Module-3: PIG Model and Operators
11 Lectures 02:43:34
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
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Module-4: PIG's Built in Functions
8 Lectures 01:42:11
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
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Module-5: PIG Scripts and UDF’s
3 Lectures 38:24
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
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Module-6: Control Structures
4 Lectures 57:28
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
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Module-7: Shell and Utility Commands
3 Lectures 46:43
7.1 Shell Commands
11:48

7.2 Utility Commands part-I
18:22

7.2 Utility Commands part-II
16:33
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Module-8: Compression with PIG
3 Lectures 30:58
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
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Module-9: Testing and Diagnostics
3 Lectures 34:01
9.1 Diagnostic Operators
13:29

9.2 PIGUnit Testing part-I
11:39

9.2 PIGUnit Testing part-II
08:53
2 More Sections
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