This Big Data and Hadoop Training Course in usa, india focus on how to manage voluminous data by making the best use of Big data and Hadoop concepts together. The course also provides you with the big data analytics, testing training program and the complete apache Hadoop tutorial. The meticulously designed Big Data and Hadoop course in intended to clear all your concepts of the topic and teaches you how to implement them in real life - industry use This Big Data and Hadoop Training and certification Course focus on how to manage voluminous data by making the best use of Big data and Hadoop concepts together. The course also provides you with the big data analytics and hadoop testing, training program and the complete apache Hadoop tutorial. The meticulously designed Big Data and Hadoop course in intended to clear all your concepts of the topic and teaches you how to implement them in real life - industry use
Knowledge of JAVA is essential for this course.
Introduction to Big Data and Hadoop. Its facts, evolution, market trends. Types of data, need for Big Data. Big data its sources, characteristics and the technology. Handling limitations of Big Data. Introduction to Hadoop. Its history, milestones, and usage in the industry.
Learn the Hadoop architecture, its key terms, and objectives. Understand its clusters, configuration and core services and components.
HDFS its key features, characteristics, feature, operation process. Replication methods and topologies. Representing the data in a business scenario.
Hadoop deployment, Ubuntu Server introduction and installing. Hadoop multi-node installation, cluster and cloning.
What is YARN? YARNReal infrastructure, real life connect. Resource manager its components and the HA mode. YARN startup and running. Map reduce, its concepts, uses in real life. Map reduce Input/output formats. Joins in Map reduce, Reduce join, replicate join, composite join.
Introduction to Pig, its real life, the related components, the working, its data models, the modes, Pig vs SQL. The related libraries and its overall working with Hadoop.
Hive, its components, characteristics, metastore, data types, query language, model tables, sterilizing and desterilizing. Learn to program and run the program in Hive. Built-in functions, map reduce scripts. Data analytics and word counts.
HBase, concepts and models, comparison with other RDBMS. Learn how to install it and how to use its commands.
Cloudera introduction, downloading, installing, starting and working with the Cloudera. Understanding the platform and running the Pivotal. Sqoop, Flume, Zookeeper, understand these concepts, and learn to work with them in detail.
Ecosystem, related various components, the work flow, Mahout, and its integration with Hadoop.
After completing this course the student will learn to handle big volume data and can seek a job as Big data developer. The demand for Big data and Hadoop is high.
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