Hadoop Admin Training
Leotrainings Hadoop Big Data online training program helps you master Big Data Hadoop and Spark to get ready for the Cloudera Hadoop Developer and exam as well as master Hadoop Administration with 10+ real-time industry experts and live projects.
- Fundamentals of Hadoop and YARN and write applications using them
- park, Spark SQL, Streaming, Data Frame, RDD, Graph and MLlib writing Spark applications
- HDFS, MapReduce, Hive, Pig, Sqoop, Flume, and Zookeeper
- Be equipped to clear Big Data Hadoop Certification
- Working with Avro data formats
- Practicing real-life projects using Hadoop and Apache Spark
What is Hadoop and Big Data?
Hadoop is an open-source software framework for storing data and running applications on clusters of commodity hardware. It provides massive storage for any kind of data, enormous processing power, and the ability to handle virtually limitless concurrent tasks or jobs. Hadoop is an open-source, Java-based framework used for storing and processing big data. The data is stored on inexpensive commodity servers that run as clusters. Its distributed file system enables concurrent processing and fault tolerance.
Hadoop does not require much coding. All you have to do is enrol in a Hadoop certification course and learn Pig and Hive, both of which require only the basic understanding of SQL Financial services companies use analytics to assess risk, build investment models, and create trading algorithms, Hadoop has been used to help build and run those applications. Retailers use it to help analyse structured and unstructured data to better understand and serve their customers. In this Big Data course, you will master MapReduce, Hive, Pig, Sqoop, Oozie and Flume and work with Amazon EC2 for cluster setup, Spark framework and RDD, Scala and Spark SQL, Machine Learning using Spark, Spark Streaming, etc.
Who can learn workday Integration?
- Mainframe Professionals, Architects and Testing Professionals
- Programming Developers and System Administrators
- Graduates and undergraduates eager to learn Big Data
- Experienced working professionals and Project Managers
- Big Data Hadoop Developers eager to learn other verticals like testing, analytics and administration
- Business Intelligence, Data Warehousing and Analytics Professional
What are the prerequisites for Big Data Hadoop?
There are no more prerequisites to take up this Big Data/Hadoop course only basics of SQL, Java, and UNIX would be good to learn Hadoop Big Data. we provide complimentary Linux and Java course with our Big Data certification training to brush up the required skills. So that you are good to go in the big data online learning path.
HADOOP BIG DATA ONLINE COURSE – UPCOMING COURSE
|JUN 05th||SAT & SUN (6 WEEKS) Weekend Batch||Timings – 07:00 AM to 10:00 AM (IST)|
|JUN 06th||SAT & SUN (6 WEEKS) Weekend Batch||Timings – 07:00 AM to 10:00 AM (IST)|
|JUN 07th||SAT & SUN (6 WEEKS) Weekend Batch||Timings – 07:00 AM to 10:00 AM (IST)|
|JUN 08th||SAT & SUN (6 WEEKS) Weekend Batch||Timings – 07:00 AM to 10:00 AM (IST)|
Big Data Hadoop Certification
This Big Data course is designed to help you clear the Cloudera Spark and Hadoop Developer Certification (CCA175) exams. The entire training course content is in line with these certification programs and helps you clear these certification exams with ease and get the best jobs in the top MNCs.
Hadoop Admin Training Demo
Hadoop Admin Online Training Content
- Introduction to big data
- Limitations of existing solutions
- Common Big Data domain scenarios
- Hadoop Architecture
- Hadoop Components and Ecosystem
- Data loading & Reading from HDFS
- Replication Rules
- Rack Awareness theory
- Hadoop cluster Administrator: Roles and Responsibilities.
- Working of HDFS and its internals
- Hadoop Server roles and their usage
- Hadoop Installation and Initial configuration
- Different Modes of Hadoop Cluster.
- Deploying Hadoop in a Pseudo-distributed mode
- Deploying a Multi-node Hadoop cluster
- Installing Hadoop Clients
- Understanding the working of HDFS and resolving simulated problems.
- Hadoop 1 and its Core Components.
- Hadoop 2 and its Core Components.
- Properties of NameNode, DataNode and Secondary Namenode
- OS Tuning for Hadoop Performance
- Understanding Secondary Namenode
- Log Files in Hadoop
- Working with Hadoop distributed cluster
- Decommissioning or commissioning of nodes
- Different Processing Frameworks
- Understanding MapReduce
- Spark and its Features
- Application Workflow in YARN
- YARN Metrics
- YARN Capacity Scheduler and Fair Scheduler
- Understanding Schedulers and enabling them.
- Namenode Federation in Hadoop
- HDFS Balancer
- High Availability in Hadoop
- Enabling Trash Functionality
- Checkpointing in Hadoop
- DistCP and Disk Balancer.
- Key Admin commands like DFSADMIN
- Importing Check Point
- MetaSave command
- Data backup and recovery
- Backup vs Disaster recovery
- Namespace count quota or space quota
- Manual failover or metadata recovery.
- Planning a Hadoop 2.0 cluster
- Cluster sizing
- Network and Software considerations
- Popular Hadoop distributions
- Workload and usage patterns
- Industry recommendations.
- Monitoring Hadoop Clusters
- Authentication & Authorization
- Nagios and Ganglia
- Hadoop Security System Concepts
- Securing a Hadoop Cluster With Kerberos
- Common Misconfigurations
- Overview on Kerberos
- Checking log files to understand Hadoop clusters for troubleshooting.
- Configuring Hadoop 2 with high availability
- Upgrading to Hadoop 2
- Working with Sqoop
- Understanding Oozie
- Working with Hive.
- Working with Pig.
- Cloudera Manager and cluster setup
- Hive administration
- HBase architecture
- HBase setup
- Hadoop/Hive/Hbase performance optimization.
- Pig setup and working with a grunt.