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    Mastering Sqoop: Rdbms To Hadoop Integration Mastery

    Posted By: ELK1nG
    Mastering Sqoop: Rdbms To Hadoop Integration Mastery

    Mastering Sqoop: Rdbms To Hadoop Integration Mastery
    Published 7/2024
    MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
    Language: English | Size: 4.56 GB | Duration: 8h 12m

    Master data integration learning Sqoop essentials and advanced techniques for seamless RDBMS to Hadoop integration.

    What you'll learn

    Understanding the basics of Sqoop and its role in data integration between RDBMS and Hadoop.

    Configuring Sqoop options for various data transfer scenarios.

    Implementing Sqoop commands to import data from MySQL to HDFS.

    Utilizing incremental imports and append features in Sqoop for efficient data synchronization.

    Handling complex data import tasks using Sqoop commands and jobs.

    Integrating Sqoop with Hive for data analytics and processing.

    Managing NULL values, data formats, and compression techniques in Sqoop.

    Implementing real-world projects like HR data analytics using Sqoop.

    Using Sqoop in conjunction with other Hadoop ecosystem tools like Hive, Pig, and MapReduce.

    Troubleshooting common issues and optimizing Sqoop performance for large-scale data transfers.

    Requirements

    Basic understanding of SQL and relational databases.

    Familiarity with Hadoop ecosystem components, such as HDFS and MapReduce.

    Proficiency in Linux command line interface.

    Knowledge of basic programming concepts, preferably in Java.

    Understanding of data formats like CSV, JSON, and XML.

    Access to a computer with Hadoop installed (preferably a Hadoop distribution like Cloudera or Hortonworks) for hands-on exercises.

    Description

    Course Introduction:Welcome to the comprehensive course on Sqoop and Hadoop data integration! This course is designed to equip you with the essential skills and knowledge needed to proficiently transfer data between Hadoop and relational databases using Sqoop. Whether you're new to data integration or seeking to deepen your understanding, this course will guide you through Sqoop's functionalities, from basic imports to advanced project applications. You will gain hands-on experience with Sqoop commands, learn best practices for efficient data transfers, and explore real-world projects to solidify your learning.Section 1: Sqoop - BeginnersThis section provides a foundational understanding of Sqoop, a vital tool in the Hadoop ecosystem for efficiently transferring data between Hadoop and relational databases. It covers essential concepts such as Sqoop options, table imports without primary keys, and target directory configurations.By mastering the basics presented in this section, learners will gain proficiency in using Sqoop for straightforward data transfers and understand its fundamental options and configurations, setting a solid groundwork for more advanced data integration tasks.Section 2: Sqoop - IntermediateBuilding on the fundamentals from the previous section, this intermediate level delves deeper into Sqoop's capabilities. It explores advanced topics like incremental data imports, integration with MySQL, and executing Sqoop commands for specific use cases such as data appending and testing.Through the exploration of Sqoop's intermediate functionalities, students will enhance their ability to manage more complex data transfer scenarios between Hadoop and external data sources. They will learn techniques for efficient data handling and gain practical insights into integrating Sqoop with other components of the Hadoop ecosystem.Section 3: Sqoop Project - HR Data AnalyticsFocused on practical application, this section guides learners through a comprehensive HR data analytics project using Sqoop. It covers setting up data environments, handling sensitive parameters, and executing Sqoop commands to import, analyze, and join HR data subsets for insights into salary trends and employee attrition.By completing this section, students will have applied Sqoop to real-world HR analytics scenarios, mastering skills in data manipulation, job automation, and complex SQL operations within the Hadoop framework. They will be well-prepared to tackle similar data integration challenges in professional settings.Section 4: Project on Hadoop - Social Media Analysis using HIVE/PIG/MapReduce/SqoopThis advanced section focuses on leveraging multiple Hadoop ecosystem tools—Sqoop, Hive, Pig, and MapReduce—for in-depth social media analysis. It covers importing data from relational databases using Sqoop, processing XML files with MapReduce and Pig, and performing complex analytics to understand user behavior and book performance.Through hands-on projects and case studies in social media analysis, students will gain proficiency in integrating various Hadoop components for comprehensive data processing and analytics. They will develop practical skills in big data handling and be equipped to apply these techniques to analyze diverse datasets in real-world scenarios.Course Conclusion:Congratulations on completing the Sqoop and Hadoop data integration course! Throughout this journey, you've acquired the foundational and advanced skills necessary to effectively manage data transfers between Hadoop and relational databases using Sqoop. From understanding Sqoop's command options to applying them in practical projects like HR analytics and social media analysis, you've gained invaluable insights into the power of Hadoop ecosystem tools. Armed with this knowledge, you are now prepared to tackle complex data integration challenges and leverage Sqoop's capabilities to drive insights and innovation in your data-driven projects.

    Overview

    Section 1: Sqoop - Beginners

    Lecture 1 Introduction to Scoop

    Lecture 2 Scoop Overview with Diagram

    Lecture 3 Sqoop Option Basics

    Lecture 4 Option Explanation

    Lecture 5 Sqoop Table Sub Option-M

    Lecture 6 Sqoop Table With no Primary Key

    Lecture 7 Sqoop Target DIR

    Lecture 8 Sqoop where Option

    Lecture 9 Sqoop Column Option With Full Overview

    Lecture 10 Installation

    Lecture 11 Installation Continue

    Section 2: Sqoop - Intermediate

    Lecture 12 Intro to Sqoop

    Lecture 13 MYSQL Connectivity

    Lecture 14 MYSQL to HDFS

    Lecture 15 MYSQL to HDFS Default Path

    Lecture 16 MySQL Data to Target Directory

    Lecture 17 Where Clause

    Lecture 18 Incremental Append Sqoop

    Lecture 19 Incremental Append Sqoop Continue

    Lecture 20 Test Cases

    Lecture 21 Sqoop Hive Import Test Case

    Lecture 22 Sqoop Hive Import Test Case Continue

    Lecture 23 Sqoop Export Test Case

    Lecture 24 Sqoop Export Test Case Continue

    Section 3: Sqoop Project - HR Data Analytics

    Lecture 25 Introduction to Project

    Lecture 26 Data Set Up

    Lecture 27 Password File Parameter

    Lecture 28 Basic Sqoop Cammand Part 1

    Lecture 29 Basic Sqoop Cammand Part 2

    Lecture 30 Basic Sqoop Cammand Part 3

    Lecture 31 Basic Sqoop Cammand Part 4

    Lecture 32 Salary Analysis Subset Import

    Lecture 33 Salary Analysis Subset Import Continue

    Lecture 34 Attrition Analysis Complex JOIN

    Lecture 35 Sqoop Jobs

    Lecture 36 Sqoop Jobs Continue

    Lecture 37 NULL Value Handling

    Lecture 38 Data Formats and Compression

    Section 4: Project on Hadoop - Social Media Analysis using HIVE/PIG/MapReduce/Sqoop

    Lecture 39 Introduction to Social Media Industry

    Lecture 40 Book Marking Website

    Lecture 41 Book Marking Website Continues

    Lecture 42 Understanding Sqoop

    Lecture 43 Get Data from RDMS to HDFS

    Lecture 44 Execute Map Reduce Program in order to Process XML File

    Lecture 45 Analyze Book Performance By Reviews Using Code

    Lecture 46 Analyze Book Performance By Reviews Using Code Continues

    Lecture 47 Analyse Book By Location

    Lecture 48 Example of Analyse Book By Location

    Lecture 49 Analyse Book Reader Against Author

    Lecture 50 How to process XML File in PIG

    Lecture 51 How to process XML File in PIG Continues

    Lecture 52 Analyze Book Performance in XML File in PIG

    Lecture 53 More on Analyze Book Performance in XML File in PIG

    Lecture 54 Pig XML File Output Using Book

    Lecture 55 Pig XML File Output Using Location

    Lecture 56 Pig XML File Output Using Location Continues

    Lecture 57 Understanding Complex Data Set Using Hive

    Lecture 58 Understanding Complex Data Set Using Hive Continues

    Lecture 59 Create Array in Map Reduce Using Hive

    Lecture 60 Book Marking Type Data Set Using Complex Type

    Lecture 61 Output of Book Marking Type Data Set

    Data Engineers: Who need to transfer data between Hadoop and relational databases efficiently.,Big Data Professionals: Looking to enhance their skills in data ingestion and integration.,Database Administrators: Interested in learning tools for large-scale data transfer and integration.,Data Analysts: Seeking to expand their capabilities in handling big data pipelines.,Software Developers: Who want to integrate Hadoop's capabilities into their applications using Sqoop.,IT Professionals: Working with Hadoop ecosystems and needing to manage data transfers effectively.