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Sijeesh Kunnotharamal

This training provides you with proficiency in all the steps required to operate and sustain a Cloudera Hadoop Cluster which includes Planning, Installation,Configuration ,Active Directory Integration , Securing Cluster using Kerberos ,HDFS Access Control List,High Availability ,Hadoop Eco system components in detail and Upgrading Cloudera Manager and CDH . This training will provide hands-on preparation for the real-world challenges faced by Hadoop Administrators. The course curriculum follows Cloudera Hadoop distribution.

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What's inside

Syllabus

Installation of Cloudera Manager and CDH
Deploying Virtual Machines on Amazon Web Service
Code and Documentation Repository
Configuring Prerequisites for Hadoop Installation
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Cloudera Data Platform is relatively new offering from Cloudera , that contains best tools from Hortonworks Data Platform ( HDP ) and Cloudera Enterprise Data Hub ( CDH ) .

CDP is making use of Cloudera Manager for deployment  and managing of Clusters.

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Provides hands-on experience with real-world challenges faced by Hadoop administrators, making it highly practical for those in the field
Covers Active Directory integration and Kerberos security, which are essential for securing Hadoop clusters in enterprise environments
Includes upgrading Cloudera Manager and CDH, which are critical tasks for maintaining a healthy and up-to-date Hadoop cluster
Explores High Availability configurations for NameNode and Resource Manager, which are crucial for ensuring continuous operation of Hadoop services
Focuses on Cloudera Data Platform (CDP), a relatively new offering, and its integration with tools from Hortonworks Data Platform (HDP)
Requires familiarity with Amazon Web Services and Azure Cloud, which may pose a barrier for learners without prior cloud experience

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Reviews summary

Comprehensive cloudera hadoop administration

Learners say this course offers comprehensive coverage of Cloudera Hadoop administration, including essential tasks, security (Kerberos, AD), and high availability. The hands-on labs are considered valuable for practical understanding, and recent updates, including CDP, keep the material relevant. However, some students note that setting up the lab environment can be tricky and time-consuming. It is also suggested the course assumes some prior knowledge and that certain topics or sections could benefit from more depth or a slower pace.
Some sections could use more detail or slower pace.
"Some parts felt a bit rushed, but overall solid."
"Decent overview but felt some topics lacked depth."
"Needed external resources [for depth]."
"Felt the pace was fast assuming some background."
Valuable practical exercises included.
"The labs were super helpful, though setting up the environment initially took some time."
"Labs reinforce concepts well."
"Fantastic practical training. ... Labs are key."
"Labs worked smoothly for me. Excellent course structure."
"The hands-on approach really solidified the concepts for me."
Wide range of admin tasks covered.
"Excellent course, covered all the essential admin tasks."
"Good content, particularly the Kerberos and HA sections."
"Best course I've taken on Cloudera administration. Comprehensive and practical."
"Active Directory integration was well-covered."
"Covered CDH and CDP migration aspects which is highly relevant now."
Course is updated with current technologies.
"The recent updates to CDP are a great addition."
"The new CDP modules are relevant."
"Updated content is much better! Kerberos part was clearly explained."
"Covered CDH and CDP migration aspects which is highly relevant now."
"Good to see the course includes Cloudera Data Platform."
May not be suitable for complete beginners.
"Not for beginners. Assumes prior knowledge."
"You should have some basic Linux and Hadoop concepts before starting."
"Might be challenging if you're completely new to the Hadoop ecosystem."
"Felt the pace was fast assuming some background."
Initial lab environment setup can be tricky.
"...though setting up the environment initially took some time."
"The labs were okay, but I struggled with environment setup a lot. Needed external resources."
"The labs were frustrating to get working, dependencies issues."
"Environment setup instructions could be clearer for newcomers."
"Getting the lab environment ready required significant effort."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Cloudera Hadoop Administration with these activities:
Review Linux System Administration Fundamentals
Solidify your understanding of Linux system administration concepts, as Hadoop administration relies heavily on Linux.
Show steps
  • Review basic Linux commands and utilities.
  • Practice user and group management.
  • Familiarize yourself with file system navigation and permissions.
Brush up on Networking Concepts
Reinforce your understanding of networking principles, as Hadoop clusters require a well-configured network.
Browse courses on Networking Concepts
Show steps
  • Review TCP/IP fundamentals and subnetting.
  • Understand DNS and DHCP configurations.
  • Familiarize yourself with basic network troubleshooting tools.
Follow Cloudera Manager Installation Tutorials
Practice installing Cloudera Manager in a virtualized environment to gain hands-on experience.
Show steps
  • Set up a virtual machine environment (e.g., VirtualBox, VMware).
  • Download and install Cloudera Manager following the official documentation.
  • Troubleshoot common installation issues.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice HDFS Commands
Reinforce your understanding of HDFS by practicing common commands for file management and data access.
Show steps
  • Create, move, copy, and delete files and directories in HDFS.
  • Set file permissions and ownership in HDFS.
  • View file contents and directory listings in HDFS.
Set up a small Hadoop Cluster
Build a small, multi-node Hadoop cluster in a virtualized environment to solidify your understanding of cluster configuration and management.
Show steps
  • Provision multiple virtual machines for the cluster nodes.
  • Install and configure Hadoop on each node.
  • Configure HDFS, YARN, and other Hadoop components.
  • Test the cluster by running a simple MapReduce job.
Document a Kerberos Integration Procedure
Create a detailed guide on integrating Hadoop with Kerberos for secure authentication, focusing on clarity and completeness.
Show steps
  • Research the Kerberos integration process for Hadoop.
  • Document each step of the configuration, including commands and configuration file changes.
  • Test the integration and document any troubleshooting steps.
Contribute to Hadoop Documentation
Improve your understanding of Hadoop by contributing to the official documentation, fixing errors, or adding new content.
Show steps
  • Identify areas in the Hadoop documentation that need improvement.
  • Submit a patch with your changes following the Hadoop contribution guidelines.

Career center

Learners who complete Cloudera Hadoop Administration will develop knowledge and skills that may be useful to these careers:
Hadoop Administrator
A Hadoop Administrator is responsible for the maintenance, configuration, and reliable operation of a Hadoop cluster. This course directly aligns with the responsibilities of a Hadoop Administrator, as it covers planning, installation, configuration, and upgrading Cloudera Manager and CDH. The hands-on experience provided by the course directly prepares you for real-world challenges in Hadoop administration. The course also addresses Active Directory integration and securing the cluster using Kerberos and HDFS Access Control List, all vital for a Hadoop Administrator.
Data Engineer
A Data Engineer builds and maintains the data infrastructure that enables data analysis and data science. This course helps build a foundation for a career as a Data Engineer, particularly in environments utilizing Cloudera Hadoop distributions. It emphasizes the practical aspects of managing a Cloudera Hadoop cluster, including installation, configuration, and security. A Data Engineer benefits greatly from the course's focus on integrating Hadoop with Active Directory, ensuring secure and efficient data access. For a Data Engineer working with large datasets, understanding Hadoop administration is essential.
Big Data Architect
A Big Data Architect designs and implements the overall architecture of big data systems. This course may assist a Big Data Architect expand on their understanding of the Cloudera Hadoop distribution. High availability, Kerberos security, and the integration of various Hadoop ecosystem components like Hive, HBase, and Kafka are all crucial areas covered in the course. The Big Data Architect needs to understand the practical considerations of managing a Cloudera Hadoop environment and this course may provide value.
Cloud Engineer
A Cloud Engineer is responsible for implementing, managing, and maintaining cloud infrastructure. This course may be helpful to the Cloud Engineer who works with big data solutions, especially those involving Hadoop clusters. The course covers deploying virtual machines on Amazon Web Services and Azure, which are essential skills for a Cloud Engineer working with cloud-based Hadoop deployments. Furthermore, the focus on Active Directory integration and security aspects is helpful for ensuring secure and compliant cloud environments. A Cloud Engineer should take this course to get familiar with Hadoop administration in the cloud.
Systems Administrator
A Systems Administrator is responsible for the upkeep, configuration, and reliable operation of computer systems. This course may be useful for Systems Administrators working with Hadoop clusters, especially those using the Cloudera distribution. It dives deep into the practical aspects of Hadoop cluster management. Key areas include configuring prerequisites for Hadoop installation, installing and configuring MySQL databases for Cloudera Manager, and integrating Linux hosts with Active Directory for centralized authentication. The Systems Administrator can increase their knowledge with this course.
Database Administrator
A Database Administrator manages and maintains database systems, ensuring their availability and performance. This course may be helpful for Database Administrators who are integrating traditional databases with Hadoop ecosystems. The course covers installing and configuring MySQL databases for Cloudera Manager, a critical skill for managing the metadata and configuration information of the Hadoop cluster. Understanding how to integrate database systems with Hadoop can enable the Database Administrator to build scalable and efficient data solutions.
Security Engineer
A Security Engineer is responsible for designing, implementing, and maintaining security measures to protect computer systems and networks. This course may assist a Security Engineer working with Hadoop clusters secure those systems. It covers securing the cluster using Kerberos and HDFS Access Control Lists, essential for protecting sensitive data within the Hadoop environment. The course's focus on Active Directory integration ensures that security policies are consistently applied across the entire infrastructure. The Security Engineer would benefit through stronger understanding of Hadoop security.
Solutions Architect
A Solutions Architect designs and implements technology solutions to address business problems. This course may provide value to a Solutions Architect working with big data projects involving Hadoop. The course covers installation and configuration of various Hadoop ecosystem components, such as Hive, HBase, and Kafka, which are commonly used in data processing pipelines. Understanding how to deploy and manage these components can help the Solutions Architect design scalable and efficient data solutions. In short, it could potentially increase the architect's depth of knowledge.
Data Analyst
A Data Analyst examines data to draw conclusions about that information. Learning about Hadoop Administration may allow a Data Analyst to better manipulate data. In particular, this course may be valuable to Data Analysts who work with large datasets stored in Hadoop clusters as it introduces Hadoop ecosystem components such as Hive. The course helps the Data Analyst understand how the data infrastructure is managed, enabling them to better collaborate with data engineers and administrators to access and analyze data.
Business Intelligence Analyst
A Business Intelligence Analyst analyzes data to identify trends and insights that can improve business decision-making. This course may be useful for Business Intelligence Analysts who need to access and analyze data stored in Hadoop clusters. The course introduces Hadoop ecosystem components like Hive and Impala, which are often used to query and analyze large datasets. By understanding how these components are installed and configured, the Business Intelligence Analyst can better leverage Hadoop for data analysis.
Machine Learning Engineer
A Machine Learning Engineer designs, develops, and deploys machine learning models and systems. This course may be useful for Machine Learning Engineers who work with large datasets stored in Hadoop clusters. The course introduces Hadoop ecosystem components, facilitating data access, processing, and feature engineering. Understanding Hadoop administration practices can help Machine Learning Engineers optimize their models, leading to more accurate and efficient results.
Software Developer
A Software Developer designs, codes, and tests software applications. This course may be useful for Software Developers working on applications that interact with Hadoop clusters. Knowing how to install, configure, and manage Hadoop environments can help Software Developers build more robust and scalable applications. Additionally, the course's focus on integrating Hadoop with Active Directory and securing the cluster can ensure that applications adhere to security best practices.
Technical Support Engineer
A Technical Support Engineer provides technical assistance to customers, resolving hardware and software issues. This course may be useful for Technical Support Engineers who support Hadoop environments. Understanding the installation, configuration, and maintenance of Hadoop clusters enables them to troubleshoot issues more effectively. The course's focus on Active Directory integration and security aspects helps them address security-related problems in Hadoop environments.
Project Manager
A Project Manager plans, executes, and closes projects, ensuring they are completed on time and within budget. This course may be helpful for Project Managers who oversee big data projects involving Hadoop. Understanding the technical aspects of Hadoop administration enables them to better manage project resources and timelines. The course can help project managers gain insights into the challenges and complexities of managing a Hadoop cluster, allowing them to make informed decisions.
Technical Consultant
A Technical Consultant provides expert advice and guidance to clients on technology-related matters. This course can enhance the Technical Consultant's understanding of Hadoop administration. The course covers planning, installation, configuration, Active Directory integration, securing clusters, and upgrading Cloudera Manager and CDH. This comprehensive knowledge will allow the Technical Consultant to offer more informed and practical recommendations to clients implementing or managing Hadoop solutions.

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Cloudera Hadoop Administration.
Provides a comprehensive overview of HBase for big data. It covers everything from the basics of HBase to advanced topics such as data management and security. It great resource for anyone who wants to use HBase for big data applications.
Provides a deep dive into the internals of Apache Kafka, including its architecture, data structures, and algorithms. It's a great resource for anyone who wants to understand how Kafka works under the hood.
Provides a comprehensive overview of Apache Kafka, covering everything from its architecture and data model to its APIs and internals. It's a must-read for anyone who wants to understand Kafka in depth.
Is widely considered the essential guide for anyone starting with Hadoop and HDFS. It provides a comprehensive overview of the Hadoop ecosystem, with detailed explanations of HDFS, MapReduce, and other key components. It's an excellent resource for gaining a broad understanding and is often used as a textbook.
Focuses specifically on the offensive side of Active Directory security, detailing exploitation techniques used by attackers. It's highly relevant for those interested in Active Directory pentesting and red teaming, as indicated by several course names. Understanding attack methods is crucial for building effective defenses.
Considered a comprehensive guide for IT professionals, this book delves into the architecture, design, deployment, and management of Active Directory. The third edition is updated to cover Windows Server 2022 and hybrid identity with Azure AD, making it relevant for current practices. It's suitable for those looking to deepen their understanding and gain expertise in complex AD environments.
Group Policy critical component of Active Directory for managing user and computer configurations. provides a deep dive into Group Policy, covering its fundamentals, security implications, and advanced management techniques. It's essential reading for anyone responsible for configuring and securing Windows environments using AD.
This cookbook provides practical, scenario-based solutions for common Active Directory administration tasks. It's a valuable reference for administrators at all levels, offering step-by-step instructions for a wide range of challenges. It includes recipes for managing users, groups, and computers, working with Group Policy, and integrating with Azure AD, making it highly relevant for contemporary AD environments.
Provides a concise yet comprehensive introduction to Apache Hive, covering the Hive workflow, data modeling, and integration with other Hadoop tools. It is an excellent resource for beginners and intermediate users seeking to quickly grasp the core concepts and practical applications of Hive. The book includes practical examples to solidify understanding and can serve as a quick reference.
Provides a practical guide to implementing and managing Kerberos. It covers all aspects of Kerberos, from installation and configuration to troubleshooting and security.
Automating tasks with PowerShell key skill for modern Active Directory administrators. focuses specifically on using PowerShell to manage and administer AD. It's valuable for improving efficiency and handling large-scale AD environments. This book is particularly relevant given the emphasis on automation in the course descriptions.
Focusing on the practical aspects of using Hive as a data warehouse system on Hadoop, this book guides readers through installation, configuration, HiveQL, and performance tuning. It includes real-world examples and case studies, making it highly relevant for professionals and students focused on applying Hive in practice. valuable resource for understanding how Hive functions in a production environment.
This widely recognized and comprehensive book on Active Directory, often referred to as a foundational text. While the 5th edition might cover slightly older Windows Server versions, the core concepts of AD architecture, design, and management remain highly relevant. It's a valuable resource for gaining a broad and deep understanding of AD.
Focused on the practical aspects of managing Hadoop clusters, this book is invaluable for those in administration roles. It dives into the intricacies of HDFS administration, covering configuration, security, and performance tuning. is more valuable as a reference for professionals and advanced users.
Similar to the newer administration cookbook, this edition provides a collection of recipes for performing various Active Directory tasks. It's a practical reference for administrators seeking solutions to specific problems. It covers a wide range of topics and provides different methods (GUI, command line, script) for accomplishing tasks.
Directly addresses the concept of using SQL interfaces, like HiveQL, on big data platforms. It delves into the technology, architecture, and innovations in this space. It is highly relevant for understanding the principles and challenges behind querying massive datasets using SQL, providing a broader context for Hive's role.
Focuses on engineering and building Active Directory environments for the future, addressing typical design flaws and emphasizing security and reliability. It's relevant for those involved in designing and implementing new AD infrastructures or modernizing existing ones.
Provides in-depth technical details of Active Directory, covering design, architecture, topology, and management. It's often cited as a comprehensive resource for serious AD professionals. While some editions may cover older Windows Server versions, the foundational concepts remain highly relevant for understanding the inner workings of AD.
Focuses on architectural patterns and considerations for building big data applications with Hadoop. It discusses how to effectively utilize HDFS and other components within a larger data architecture. It's a valuable resource for architects and senior developers.
Provides a deep understanding of the underlying principles of data systems, including distributed systems, data models, storage, and processing. This knowledge is invaluable for understanding how Hive and Hadoop work internally and for designing robust big data solutions. It highly recommended read for anyone working at a graduate level or as a professional in the big data space.
This cookbook offers a collection of recipes for common and advanced tasks in Apache Hive, covering data models, partitions, debugging, security, and integration with frameworks like Spark. It practical guide for users who want hands-on solutions to specific Hive problems. While useful for beginners, it is most valuable as a reference for those with some existing Hive knowledge.
Focuses on building data pipelines using key big data technologies, including HDFS, Kafka, and Spark. It provides practical guidance on integrating these components for data ingestion, storage, and processing. It's relevant for those interested in practical data engineering solutions involving HDFS.
Focuses on the practical aspects of designing, building, and deploying Active Directory infrastructures. It's a valuable resource for those involved in the initial setup and configuration of AD, covering key design considerations and deployment steps. (ISBN varies by edition).
A guide for enterprise architects and developers, this book focuses on building and deploying real-world Hadoop solutions. It covers integrating various Hadoop ecosystem components, including HDFS, and addresses topics like security and real-time processing. It's a useful reference for professionals designing Hadoop-based systems.
Delves into the details of Hadoop 3, including HDFS architecture and its role in big data processing. It's suitable for those looking to gain a deeper understanding of the latest version of Hadoop and its capabilities. It's geared towards intermediate to advanced users.
Dives deep into building authentication solutions using Azure Active Directory, focusing on modern protocols like OpenID Connect and OAuth. It's particularly relevant for developers and architects working on applications that integrate with Azure AD for identity and access management.
Focuses on the practical aspects of managing and operating Hadoop clusters, including topics such as security, performance tuning, and disaster recovery.
Provides a gentle introduction to Apache Kafka Streams, making it ideal for beginners. It covers the fundamentals of Kafka Streams, including its architecture, data model, and basic operations. It also includes hands-on examples that help you get started with Kafka Streams.
Provides practical tutorials on various components of the Hadoop ecosystem, including HDFS, Hive, HBase, and Spark. It focuses on how these tools work together as a cohesive platform. It's a hands-on guide for understanding the broader ecosystem around HDFS.
Is designed as a study guide for a Microsoft certification exam focused on identity with Windows Server 2016, which heavily features Active Directory. While the exam is retired, the content provides a structured approach to learning key AD concepts and tasks relevant to that era.
While focused on Apache Iceberg, this book is highly relevant to contemporary data architectures that often evolve from or coexist with Hive-based data warehouses. It provides insight into modern data lakehouse concepts, performance, and scalability, which are important considerations for professionals working with or migrating from Hive. adds depth by presenting a contemporary perspective on big data storage and querying.
While not solely focused on HDFS, this book provides deep insight into YARN, the resource manager for Hadoop 2 and later. Understanding YARN is crucial for comprehending how applications interact with HDFS in modern Hadoop deployments. It's a valuable resource for those wanting to understand the broader Hadoop architecture beyond just storage.
Apache Spark powerful processing engine that is often used with HDFS. provides a comprehensive guide to Spark, explaining how it can interact with HDFS for data storage. It's crucial for understanding modern big data processing workflows that leverage HDFS.
This cookbook provides practical recipes for solving real-world problems using Hadoop, including tasks involving HDFS. It's a hands-on resource for developers and administrators looking for tested solutions. It's valuable for its practical examples and code snippets.
Provides a comprehensive guide to big data analytics using Hadoop, covering topics such as data ingestion, data processing, and data visualization.
Hive data warehousing system built on top of HDFS. is essential for users who need to perform data analysis and querying on data stored in HDFS using SQL-like language. It demonstrates how Hive interacts with HDFS for data storage and retrieval.
This guide demystifies big data topics, including foundational Hadoop architecture and HDFS, and extends to real-time processing with Spark. It covers essential components and provides hands-on knowledge. It's a good resource for gaining a broad understanding of the modern big data landscape that includes HDFS.
While not exclusively about HDFS, this book provides a fundamental understanding of the principles behind data-intensive systems, which are highly relevant to HDFS. It covers topics like distributed systems, data models, and consistency. It's a valuable resource for gaining a deeper theoretical understanding.
Discusses principles of building scalable data systems, with concepts applicable to technologies like HDFS. While not solely about Hadoop, it provides valuable context on the challenges and patterns of big data architecture. It's more theoretical but highly relevant for understanding the 'why' behind HDFS design.
Focuses on the features and administration of Hadoop 3 and its ecosystem components, including Hive. It is relevant for understanding how Hive functions within a more recent version of the Hadoop framework. Useful for those managing or working with Hadoop 3 clusters where Hive is deployed.
A concise 'how-to' guide that quickly introduces the core functionalities of Apache Hive and HiveQL through step-by-step tutorials. is suitable for absolute beginners who want a rapid introduction to performing basic operations in Hive. Its brevity makes it more valuable as a quick-start guide than a comprehensive reference.
As the title suggests, this book is aimed at beginners and provides a gentle introduction to Hadoop and its ecosystem, including HDFS. It's a good starting point for those with little to no prior knowledge of big data or Hadoop. It helps build foundational knowledge.
This open-source book aims to make Hadoop concepts, including HDFS, accessible to a wider audience. It provides a gentle introduction to the big data problem and how Hadoop components address it. It's a good starting point for beginners who prefer a free resource.
This cookbook provides practical SQL solutions and techniques for a wide range of database tasks. While not Hive-specific, the patterns and examples are often transferable to HiveQL, helping users write more effective queries. It's a useful reference for those looking for practical SQL problem-solving approaches.
Sqoop tool used for transferring data between relational databases and Hadoop, including Hive. This cookbook provides practical recipes for using Sqoop, which is essential for understanding how data often gets into Hive for processing and analysis. Valuable for understanding the data ingestion side of working with Hive.
Provides a beginner-friendly introduction to Hadoop, covering its concepts and use cases in a simple and easy-to-understand manner.

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