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Big Data Internship Program - Data Processing - Hive and Pig
4.3 (33 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
753 students enrolled

Big Data Internship Program - Data Processing - Hive and Pig

Provide higher-level language to facilitate large-data processing.
4.3 (33 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
753 students enrolled
Created by Big Data Trunk
Last updated 1/2017
English
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Big Data Internship Program - Data Processing - Hive and Pig
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This course includes
  • 2 hours on-demand video
  • 8 articles
  • 18 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • Have excellent understanding of Apache Hive and Pig tool with hands-on experience .
  • Understand the working of a project in real-world scenario.
  • Work experience in end-to-end Project ( Data Masking) and can mention in Resume .
Course content
Expand all 34 lectures 02:13:53
+ – Data Processing Introduction in Big Data
2 lectures 07:27

In This video, we have explained the course structure of course, How our course is useful for Big data experts and beginners.

Introduction to the course
Preview 02:04

In This video, we have explained what is data processing, how data processing is done in big data environment, what is big data cycle. Why big data processing is important in different Areas.

Introduction to Data processing
05:23
+ – HIve
11 lectures 38:21

In this video, we have explained how Hadoop is applicable in the retail market, how hadoop can play important role in customer analysis.

Hadoop in Retail Industry
Preview 02:58

In this video, we have given a small introduction of the hive, why
Facebook uses hive, where the hive was developed, what are hive
features.

Hive Introduction
03:24
Hive Introduction
4 questions

In this video, we have explained what is hive Architecture, how the hive is integrated with other hive components, how hive executes hive query.

Hive Architecture
04:26
Hive Architecture
4 questions

In this video we have explained, what are the data type available in
HiveQL, what are primitive data type available, Collection data types
etc

DataTypes in Hive
03:07

In this video, we have explained what is an internal table, what is an
external table, How they are used, what is the feature of hive internal
table and external table.

Managed table and External table in Hive
01:51
Manage and external tables in hive
2 questions

In this video, we have explained what is an external table and internal
table, what is the benefit of an external table over an internal table.

Demonstrating difference between Internal and external table
08:00
Demonastrating diffrent between external and interrnal
3 questions
Hands on Lab Hive External Vs InternalTable
01:06

In this video we have explained partitioning in the hive, what is the meaning of partitioning table.

Partitions in Hive with demo
08:25
Hands on Lab Hive Partition
00:33
Partition in hive
5 questions

In this video we have explained Dynamic partition in hive, what is the usage of hive dynamic table, how to create dynamic table etc.

HIve Dynamic Partitioning
03:42
Hands on Lab HIve Dynamic Partitioning
00:48
Hive dynamic Partition
3 questions
+ – Pig
8 lectures 30:39
In this video, we have given a brief introduction of Pig, why it is used, and what are the characteristic of the pig.
What is Apache PIG?
Preview 04:37

In this video, we have shown Pig architecture, how Pig statement is executed in Pig grunt mode.

PIG Architecture
02:02

In this video, we have shown what are the different data types available in Pig, Type of data types, what are relations, bag, tuple etc.

Pig Data Types
03:18
Pig Data Types
3 questions
In this video, we have shown what is Pig Latin, what are various basic commands which are used in Pig Script, Pig latin Map Reduce, Use of Python with Pig
Pig Latin
06:07
Pig Latin
3 questions
In this video, we have described different running mode, and their usage, How pig script is executed in different modes
PIG Running Modes
03:40
PIG Running Modes
4 questions

In this video we have shown the different type of operators available in Pig Latin, like binary, ternary, flatter, how to load data using PigStorage(), Dump operator, store operator, limit and distinct, order by, grouping etc.

PIG Operators
07:03
PIG Operators
4 questions

In this video, we have shown how we can execute word count task in pig latin.

PIG Wordcount example
03:18
Pig Wordcount lab
00:34
+ – Data Processing in Recommendation Project
2 lectures 13:25

In this video we have explain how to execute our Book Recommendation Project by using hive, sqoop, mysql. How to upload data in system for processing.

BookRecommendationProject
05:13

In this video we have explained some attribute of table, how we can access them and how we can optimize query execution in hive, we have done some hands-on recommendation database, for analysis of tables and seen the results.

BookRecommendationProject-2
08:12
+ – Ad-on Project Data Masking
11 lectures 44:00

In this video, we have explained the data masking project, which components we are going to use, what is the use of data masking etc, what are project requirement, what is a flow of the project.

Data Masking Project Overview
Preview 03:42

In this video, we have explained data masking solution, how this project
is executed, what is the goal of the project, what Softwares/tools we
are going to use in execution.

Data Masking Project Solution Design
03:19

In this video we have explain the step-by-stpe flow of Data Masking project, and different stages of project.

Data Masking Project Solution Walkthrough
09:05
In this video we have explained how to create table in mysql, how to load data in mysql from file.
DataMaskingProject-step1(Create tables inMySql)
05:41
Hands on Lab DataMaskingProject-step1-Document
01:48

In this video, we have explained how to create an external table, and
how to load data in the external table, how to import data from external
table to hive table.

Step2:Creating and importing data in hive external tables
03:40
Hands on Lab DataMaskingProject-step2- Document
00:55
In this video we have explained, how to crreate UDFs, and how to jar for Data Masking Project
Step3:Creating UDFs in Java
06:36
Hands on Lab DataMaskingProject-step3(udf)- Document
02:20
In this video, we have shown you actual execution of data masking, by using MySQL, sqoop
Step4:Exporting data to MySql in masked database
05:34
Hands on Lab DataMaskingProjectStep4 - Document
01:19
Requirements
  • Should know the basics of BigData concepts like-HDFS,MapReduce and some knowledge of RDBMS.
  • Should take our Part-1 free course (Big data Internship Program - Foundation) to understand these concepts better. (Not mandatory but desirable).
  • Should take our Part-1 free course (Big data Internship Program - ingestion ) to understand sqoop and flume. ( For our Book Recommendation Project only).
Description

This course is part of “Big data Internship Program”  which is aligned to a typical Big data project life cycle stage.

  • Foundation
  • Ingestion
  • Storage
  • Processing
  • Visualization

This course is focused on Data Processing in Big data.This course is suitable for developers, data analysts and business analysts. Experience with SQL and scripting languages is recommended, but is not required. 

You will learn 

  • Understanding of Hive core concept and architecture.
  • How to create and manipulate tables using Hive.
  • Advanced features of Hive.
  • Hive Best Practices
  • Performing real-time, complex queries on datasets
  • Pig’s Architecture
  • Reading and Writing Data with Pig
  • Pig Best Practices

Project work -

  1. Provide Data in Hive and manipulate the data for Our Book Recommendation project. 
  2. One Ad-on project -- Data Masking with hive and sqoop
Who this course is for:
  • This course is for anyone who wants to learn about Hive and Pig in details with hand exprience.
  • Students who want to do internship.
  • Big Data Analytics Professional.
  • Developers who want to get clear concept .