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
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.