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Big Data Hadoop Certification Training

Gain in-depth advanced knowledge from our most popular Big Data Hadoop Certification Course Online. This course Curriculum is Designed to Meet global Industry Standards. The learners will use Hadoop Latest and advanced technologies to take their career into next level.
  • Training Type
    Live Training
  • Category
    Data & Analytics
  • Duration
    35 Hours
  • Rating
    4.9/5
Big Data Hadoop Certification Training

Big Data Hadoop Training Certification Course Introduction

About Big Data Hadoop Training Certification Course

Simpliv’s Big Data Hadoop Training covers in-depth knowledge on Big Data and Hadoop Ecosystem tools such as HDFS, YARN, MapReduce, Hive, and Pig. 

Big Data Hadoop Training Certification Course Objective

Hadoop basics and Hadoop ecosystem

Managing, monitoring, scheduling and troubleshooting Hadoop clusters effectively

Working with Apache Spark, Scala and Storm for real-time data analytics

Working with Hive, Pig, HDFS, MapReduce, Sqoop, ZooKeeper and Flume

Testing of Hadoop clusters with MRUnit and other automation tools

Successfully integrating various ETL tools with Hive, Pig, and MapReduce

Who is the Big Data Hadoop Course Target Audience?

Software Developers

Project Managers

ETL and Data Warehousing Professionals

Software Architects

Data Analysts & Business Intelligence Professionals

DBAs

Mainframe professionals

Data Engineers

Senior IT Professionals

Testing professionals

Graduates interested in Big Data Field

What Basic Knowledge Required to Learn Big Data Hadoop Training?

There are no specific prerequisites to learn Hadoop. Prior knowledge of Java and SQL is beneficial.

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Big Data Hadoop Training Certification Course Curriculum
Total Duration : 35 Hours
Understanding Big Data and Hadoop
  • Introduction to Big Data & Big Data Challenges  
  • Limitations & Solutions of Big Data Architecture  
  • Hadoop & its Features  
  • Hadoop Ecosystem  
  • Hadoop 2.x Core Components  
  • Hadoop Storage: HDFS (Hadoop Distributed File System)  
  • Hadoop Processing: MapReduce Framework  
  • Different Hadoop Distributions  
Hadoop Architecture and HDFS
  • Hadoop 2.x Cluster Architecture Preview  
  • Federation and High Availability Architecture Preview  
  • Typical Production Hadoop Cluster  
  • Hadoop Cluster Modes  
  • Common Hadoop Shell Commands Preview  
  • Hadoop 2.x Configuration Files  
  • Single Node Cluster & Multi-Node Cluster set up  
  • Basic Hadoop Administration  
Hadoop MapReduce Framework
  • Traditional way vs MapReduce way  
  • Why MapReduce  
  • YARN Components  
  • YARN Architecture  
  • YARN MapReduce Application Execution Flow  
  • YARN Workflow  
  • Anatomy of MapReduce Program  
  • Input Splits, Relation between Input Splits and HDFS Blocks  
  • MapReduce: Combiner & Partitioner  
Advanced Hadoop MapReduce
  • Counters  
  • Distributed Cache  
  • MRunit  
  • Reduce Join  
  • Custom Input Format  
  • Sequence Input Format  
  • XML file Parsing using MapReduce  
Apache Pig
  • Introduction to Apache Pig  
  • MapReduce vs Pig  
  • Pig Components & Pig Execution  
  • Pig Data Types & Data Models in Pig  
  • Pig Latin Programs  
  • Shell and Utility Commands  
  • Pig UDF & Pig Streaming  
  • Testing Pig scripts with Punit  
  • Aviation use-case in PIG  
Apache Hive
  • Introduction to Apache Hive  
  • Hive vs Pig  
  • Hive Architecture and Components  
  • Hive Metastore  
  • Comparison with Traditional Database  
  • Hive Data Types and Data Models  
  • Hive Partition  
  • Hive Bucketing  
  • Hive Tables (Managed Tables and External Tables)  
  • Importing Data  
  • Querying Data & Managing Outputs  
  • Hive Script & Hive UDF  
  • Retail use case in Hive  
Advanced Apache Hive and HBase
  • Hive QL: Joining Tables, Dynamic Partitioning  
  • Custom MapReduce Scripts  
  • Hive Indexes and views  
  • Hive Query Optimizers  
  • Hive Thrift Server  
  • Hive UDF  
  • Apache HBase: Introduction to NoSQL Databases and HBase  
  • HBase v/s RDBMS  
  • HBase Components  
  • HBase Architecture  
  • HBase Run Modes  
  • HBase Configuration  
  • HBase Cluster Deployment  
Advanced Apache HBase
  • HBase Data Model  
  • HBase Shell  
  • HBase Client API  
  • Hive Data Loading Techniques  
  • Apache Zookeeper Introduction  
  • ZooKeeper Data Model  
  • Zookeeper Service  
  • HBase Bulk Loading  
  • Getting and Inserting Data  
  • HBase Filters  
Processing Distributed Data with Apache Spark
  • What is Spark  
  • Spark Ecosystem  
  • Spark Components  
  • What is Scala  
  • Why Scala  
  • SparkContext  
  • Spark RDD  
Oozie
  • Oozie  
  • Oozie Components  
  • Oozie Workflow  
  • Scheduling Jobs with Oozie Scheduler  
  • Demo of Oozie Workflow  
  • Oozie Coordinator  
  • Oozie Commands  
  • Oozie Web Console  
  • Oozie for MapReduce  
  • Combining flow of MapReduce Jobs  
  • Hive in Oozie  
  • Hadoop Talend Integration