Hadoop Administration Online Training
MAP R offers a trusted enterprise grade platform that base a broad set of mission critical and real time production uses with the help of Hadoop. Map R technologies provide distribution facility to Hadoop and offers Hadoop with unique features like cost effective, performance, trustworthiness, easy to use and real time production.
Hadoop Administration Online Training
Course Overview
The Hadoop Administration course is designed for professionals looking to manage and maintain Hadoop clusters effectively. It covers installation, configuration, monitoring, troubleshooting, and optimization of Hadoop environments. Gain the expertise to manage enterprise-level Big Data infrastructure confidently.
Prerequisites for Hadoop Administration Training Online
- Basic knowledge of Linux commands and shell scripting.
- Understanding of networking concepts (IP, DNS, ports).
- System administration or IT infrastructure experience.
- Basic Java or programming familiarity.
- Interest in Big Data technologies — no prior Hadoop experience required.
Why Choose Us for Hadoop Administration Training
- Expert Trainers: Industry professionals with real-world Hadoop experience.
- Practical Learning: Hands-on labs and live projects.
- Updated Curriculum: Includes Hadoop 3.3.x and latest ecosystem tools.
- Flexible Learning: Self-paced, instructor-led, or corporate batches.
- Comprehensive Resources: Lifetime access to materials and recordings.
- Dedicated Support: Continuous technical and career guidance.
- Certification Assistance: Resume workshops and placement help.
Course Content
Module 1: Introduction to Hadoop Administration
- Overview of Big Data and Hadoop
- Role of a Hadoop Administrator
- Core Components: HDFS, YARN, MapReduce
- Hadoop Ecosystem: Hive, Sqoop, Pig, Oozie, HBase, Spark
- Differences between Developer and Administrator roles
Module 2: Hadoop Architecture and Cluster Planning
- Cluster architecture: Master and Slave nodes
- NameNode, DataNode, ResourceManager, NodeManager roles
- Planning and sizing Hadoop clusters
- Rack awareness, block placement, and networking considerations
Module 3: Hadoop Installation and Configuration
- Installing Hadoop on Linux and setting up Java environment
- Single, pseudo-distributed, and fully distributed modes
- Configuration files: core-site.xml, hdfs-site.xml, yarn-site.xml, mapred-site.xml
- Environment variables and version compatibility (2.x vs 3.x)
Module 4: HDFS Management
- HDFS architecture, replication, and HA configuration
- NameNode federation and backup strategies
- Balancing clusters and recovery management
Module 5: YARN Resource Management
- YARN architecture and configuration
- Capacity vs Fair Scheduler
- Resource tuning and monitoring applications
Module 6: Cluster Monitoring and Maintenance
- Monitoring tools: Ambari, Cloudera Manager, Ganglia, Nagios
- Configuring logs, alerts, and performance health checks
- Troubleshooting common issues
Module 7: Hadoop Security
- Kerberos authentication setup
- User and group permissions
- Data encryption, SSL configuration, and secure transfers
Module 8: Ecosystem Administration
- Hive: Metastore management, optimization, and configuration
- Sqoop: Managing data transfers between RDBMS and Hadoop
- Oozie: Workflow scheduling and troubleshooting
- HBase: Cluster setup and performance monitoring
Module 9: Cluster Optimization
- Tuning cluster performance and JVM optimization
- HDFS and YARN performance enhancement
- Scaling best practices and job optimization
Module 10: Backup, Recovery, and Upgrades
- Backup and disaster recovery strategies
- Rolling upgrades and migrations
Module 11: Hands-On Projects
- Setting up multi-node clusters and configuring HA
- Monitoring with Ambari/Cloudera Manager
- Securing Hadoop with Kerberos
Module 12: Industry Use Cases
- Large-scale cluster management
- Hadoop on Cloud: AWS, Azure, GCP
Comprehensive Overview of Hadoop Administration Course
This course combines foundational concepts with advanced techniques for administering Hadoop in production. You’ll learn to manage, secure, and optimize clusters, handle real-world scenarios, and prepare for enterprise deployments.
Key Learning Areas
- Understand the Hadoop ecosystem and architecture.
- Install, configure, and manage single-node and multi-node clusters.
- Master HDFS and YARN resource management.
- Administer Hive, Sqoop, Oozie, and HBase.
- Implement security and performance best practices.
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