Hadoop and Spark for Administrators Training in Astana, Kazakhstan

This training program is designed for system administrators and DevOps professionals who want to set up, manage, and optimize Hadoop and Spark clusters. It focuses on core administration skills, including deployment, configuration, monitoring, and troubleshooting for Hadoop Distributed File System (HDFS), YARN, and Apache Spark. The course provides hands-on labs to build practical expertise in managing large-scale big data infrastructure.

INTRODUCTION TO HADOOP ARCHITECTURE AND SETUP

  Overview of Hadoop ecosystem and architecture

  Deep dive into HDFS and YARN components

  Setting up a multi-node Hadoop cluster

  Hadoop configuration files and environment variables

  Working with HDFS: commands, replication, data placement

  Resource management using YARN: containers, queues, and node managers

ADVANCED HADOOP ADMINISTRATION AND MONITORING

  Managing cluster health and logs

  Troubleshooting common Hadoop errors

  Hadoop file system permissions, quotas, and ACLs

  Hadoop security basics: Kerberos introduction, user roles

  Backups, snapshots, and data recovery strategies

  Capacity planning and cluster sizing fundamentals

SPARK DEPLOYMENT, CONFIGURATION, AND CLUSTER INTEGRATION

  Introduction to Apache Spark and its execution model

  Spark vs MapReduce for administrators

  Spark cluster deployment: Standalone mode, YARN integration

  Spark configuration tuning: memory, executors, caching

  Managing Spark jobs using CLI and Web UI

  Monitoring Spark jobs and handling job failures

  Debugging Spark logs and understanding DAGs

Hands-on Exercises