By the end of this course, you would have a clear idea about Hadoop development, MapReduce concepts, using MapReduce with Hive and Pig, and know the Hadoop ecosystem, all the concepts related to the Hadoop, that should be sufficient to help you start off with Administering the Hadoop Cluster as well as Developing MapReduce Applications for Hadoop Cluster.
Pre-Requisites to Learn Hadoop:
- A familiarity of programming in Java
- Pretty basics of SQL & Linux Commands
Who Should Join this Course:
- This course has been designed for people aspiring to learn and work in Big Data world using Hadoop Framework and become a Hadoop Developer. IT Freshers, Graduates/Post Graduates from other domains with knowledge on pre requisites, Software Professionals, Analytics Professionals, and ETL developers are the key beneficiaries of this course.
Topics - Understanding Big Data, Challenges in processing Big Data, 3V Characteristics (Volume, Variety and Velocity), Brief history of Hadoop, How Hadoop addresses Big Data?, Core Hadoop Daemons, Hadoop echo system, Hadoop Clusters.
Topics - HDFS Overview and Architecture, HDFS Keywords like Name Node, Data Node, Heart Beat etc, Configuring HDFS, Data Flows (Read and Write), HDFS Permissions and Security, HDFS commands, HDFS from Admin stand point, Rack Awareness
Topics - Basics of Map Reduce, Map Reduce Data Flow, Word count Example solving, Developing a Map Reduce Application, Configuring Map Reduce, 2 ways executing Map Reduce program, Input and Output file formats, Driver, Mapper and Reducer Code walk thru, Hadoop Integration with Eclipse in Linux, Partitioners, Map Reduce Web UI, Joins, Distributed cache, Compression techniques in mapreduce
Topics - Classic Map Reduce (Map Reduce I), YARN (Map Reduce II), Shuffle and Sort, Job Chaining, Input formats – Input splits & custom file input formats, Output formats – text output, custom file output formats, Hands-on
Topics - Overview of PIG, PIG Latin, Why PIG?, Loading and storing data, 21 Transformations of PIG, Local and HDFS modes of PIG, Grunt Shell, Script and Embedded modes of processing using PIG, Understanding Complex data types of PIG, Word Count using PIG, Hands-on
Topics - Overview of HIVE, PIG vs HIVE, HiveQL, Managed and External Tables, LOAD vs INSERT, Views, CTAS, Partitioning, Bucketing, Dynamic partitioning vs Bucketing, OVERWRITE key word, Collection Data types in HIVE, Date type in HIVE, ORC File Format and other File Formats, Understanding SerDe, Types of Hive JOINS, Tuning Hive JOINS, Vectorization, Exploring HIVE User Defined Functions, HIVE Unions, Hands-on
Topics - Overview of HBASE, NoSQL vs RDBMS, HBASE vs HDFS, HBASE Shell, CRUD with JAVA API, Hands-on
Topics - Overview, Data Ingestion mechanisms, Getting granted from MySQL, SQOOPING from MySQL, SQOOPING to MYSQL, Incremental append, working with Sqoop jobs
Topics - Assignments, POC's, Mock Interview, Horton Works Certification covered
Completed hadoop online training for more than 10 batches and gave 2 corporate training's as well. am a specialist in dealing fast track batches with excellent quality in the subject delivery.